Building Microsoft Sentinel Connectors in Minutes with the Sentinel Connector Builder Agent
Overview We previously announced the public preview of the Microsoft Sentinel connector builder agent via VS code extension, that helps developers build Microsoft Sentinel codeless connectors faster with low-code and AI-assisted prompts. This post walks through a hands-on lab using a mock Network Log API to demonstrate how the Sentinel connector builder agent simplifies building Codeless Connector Framework (CCF) pull connectors. Instead of manually creating ingestion infrastructure and configuration files, you’ll use a guided, conversational workflow in VS Code to generate connector artifacts, test them against a live API, and deploy them into Microsoft Sentinel. The lab focuses on the end-to-end experience ranging from API setup to validated connector deployment so you can see how quickly a working integration can be produced. For additional guidance beyond this lab, refer to our MS Learn documentation. The Lab Environment This lab is built around a mock Network Log API hosted as an Azure Function App. The purpose of the lab environment is to give us a live API that we can use to build, validate, and test the Sentinel CCF connector builder agent against end to end. The API exposes 50 synthetic network activity records that look and behave like a real product data source, including web traffic, DNS requests, blocked remote access attempts, malware command-and-control blocks, VPN activity, and other common network events. That makes it a useful stand-in for the type of telemetry many teams want to onboard into Microsoft Sentinel. The API is intentionally shaped like the kind of source a customer might expose for telemetry retrieval. It uses API key authentication through the X-API-Key header, returns paginated results through a nextLink model, and provides a predictable response structure that the builder agent can map into a pull connector configuration. The repo contains everything needed for the walkthrough. There is an ARM template to deploy the Function App, reference documentation for the API, and a sample connector package showing the generated polling config, table schema, DCR, and connector definition. The end goal of the lab is straightforward: use the builder agent to generate a CCF pull connector that ingests this API into the custom NetworkLogAPIGetNetworkLogs_CL table in Sentinel. Prerequisites Before starting, make sure you have the following: Azure subscription -- with Contributor access on a resource group (for deploying the Function App) and Microsoft Sentinel Contributor access on a Sentinel-enabled workspace (for deploying the connector) Microsoft Sentinel workspace -- an existing Log Analytics workspace with Sentinel enabled. See Onboard Microsoft Sentinel to a Log Analytics workspace for more information. Azure CLI -- See How to install the Azure CLI for more information. VS Code with the Microsoft Sentinel for Visual Studio Code extension installed. GitHub Copilot -- with access to premium models. The connector builder agent requires Claude Sonnet 4.5 or 4.6, which uses Copilot premium model credits. Lab Repository -- Once the aforementioned prerequisites are met, you can access the lab repository here: Azure-Sentinel/Tools/CCF-Connector-Builder-Agent-Accelerator at master · Azure/Azure-Sentinel Deploying the Mock API The full CLI commands for this section are available in the repo. For a simpler option, you can use GitHub Copilot to handle the deployment. Enter this prompt: Follow the deployment instructions in Sentinel-CCF-Pull-Connector-Builder-Agent-Accelerator/agent-instructions.md. Let’s deploy the Network Log API and build a CCF pull connector. At a high level, the setup is four steps: clone the repo, create a resource group, ensure you have a Sentinel-enabled workspace, and deploy the Function App using the included ARM template. The template takes two parameters: an ApiKey of your choice (the secret the CCF connector will use to authenticate) and your Log Analytics workspace resource ID for Application Insights. Deployment takes about two to three minutes and outputs the FunctionAppName and endpoint URLs you will need later. Once deployed, verify the API is live: curl -s -H "X-API-Key: <your-api-key>" \ "https://<functionappname>.azurewebsites.net/api/GetNetworkLogs?page=1&pageSize=3" </functionappname></your-api-key> You should see a response like this: The API also exposes an /api/RefreshData endpoint that regenerates the 50 sample records with fresh timestamps. This is useful later in the walkthrough when you want to produce new events and trigger an immediate ingestion cycle without waiting for the next polling interval: curl -s -X POST -H "X-API-Key: <your-api-key>" \ "https://<functionappname>.azurewebsites.net/api/RefreshData" </functionappname></your-api-key> Building the Connector with the Sentinel Connector Builder Agent With the Microsoft Sentinel extension installed and GitHub Copilot running in agent mode, open a Copilot chat and enter a single prompt pointing at the API documentation file: That is the entire invocation. The agent takes it from there. It works through a structured seven-step sequence: preparation, polling config, table schema, DCR, connector definition, package validation, and summary. The agent produces four files in a sentinel-connectors/NetworkLogAPI_CCF/ output folder: NetworkLogAPI_PollingConfig.json – This is the API poller configuration. The agent reads the documentation and correctly identifies the GET /api/GetNetworkLogs endpoint, configures API Key authentication via the X-API-Key header, sets up NextPageUrl pagination using $.metadata.nextLink with a $.metadata.hasNextPage stop condition, and wires up the since query parameter for incremental delta pulls using the timestamp field. The RefreshData endpoint is correctly excluded, which the agent recognizes as a maintenance operation, not a security data stream. NetworkLogAPI_Table.json – This is the custom Log Analytics table schema for NetworkLogAPIGetNetworkLogs_CL . All 20 fields from the API response are mapped to the correct column types, with timestamp promoted to TimeGenerated as the standard Sentinel time column. NetworkLogAPI_DCR.json – This is the Data Collection Rule. This defines the stream declaration, the workspace destination, and the KQL transform that maps the raw snake_case API fields ( sourceIp , destinationIp , threatIndicator , etc.) to their PascalCase table columns. NetworkLogAPI_ConnectorDefinition.json – This is the connector UI configuration. This drives what the connector page looks like in Microsoft Sentinel: the title, description, prerequisite instructions, the BaseUrl and ApiKey input fields, sample KQL queries, and the connectivity status logic. The only point where the agent paused for input was to propose a connector description and ask for confirmation before writing it to the file. Everything else such as endpoint selection, auth type, pagination pattern, schema mapping, KQL transform, cross-file consistency was selected autonomously. To put that in perspective: without the agent, a developer building this connector from scratch would need to manually author four JSON files, understand the CCF schema for polling configs, DCRs, and connector definitions, write the KQL transform by hand, and validate that every cross-file reference lines up correctly. The agent compresses that work, typically hours of reading documentation, trial-and-error, and portal debugging, into a single prompt. Testing the Connector Before deploying anything to a Sentinel workspace, the Microsoft Sentinel connector builder agent lets you validate the generated polling config against the live API directly from your editor. Right-click the sentinel-connectors/NetworkLogAPI_CCF folder, select Microsoft Sentinel → Test Connector (Preview), and a Configuration Variables panel opens asking for the two template variables from the polling config: BaseUrl and apiKey . For other API patterns, there may be additional and different inputs. For example, apiKey input could be swapped with clientID and secret if the API supports OAUTH. Enter the Function App base URL and your API key, and the test runner connects immediately. The panel shows a live polling session. Poll #1 returns HTTP 200 with 50 events, and a countdown timer shows when the next poll will fire. Switching to the Events tab displays the ingested records in a tabular view with columns for timestamp , severity , action , bytesIn , bytesOut , category , and the rest of the mapped fields fresh from the API. Additionally, there are tabs for Headers, Payload, and Response, which can be useful for verifying that your pollerconfig.json configuration provides the expected request to your api with a working response. Data Extracted: The Test Connector feature can be used to visualize the response data in a table format to verify that data will land in a Sentinel table based on your configuration. Request from Poller: The Test Connector feature can be used to validate the request and response headers that will go out to the API based on the generated poller configuration. Request Response: The Test Connector feature shows you the live response from the API with respect to the request going to the API based on the poller configuration. This is a meaningful pre-flight check. It confirms that auth is working, the $.data events path resolves correctly, pagination is functional, and the polling interval fires as configured all before a single file is deployed to Azure. The most common connector configuration issues (wrong base URL, incorrect header name, mismatched JSON path) surface here in seconds rather than after a failed deployment and a 20-minute wait for Sentinel to attempt its first ingestion cycle. It is also the fastest way to troubleshoot if something goes wrong after deployment, far quicker than pushing changes to Azure and waiting for the connector to poll again. Deploying and Enabling the Connector With the connector tested and passing, deployment is the same right-click menu: right-click the sentinel-connectors/NetworkLogAPI_CCF folder, select Microsoft Sentinel → Deploy Connector (Preview). If you are not already signed in to Azure, the extension will prompt you to authenticate. The agent will also provide a clickbox in the chat window to invoke a connector deployment. Right Click Deploy Connector: UI Prompt Based Deploy Method: Once signed in, a workspace picker lists all available Log Analytics workspaces across your subscriptions. Select the one with Sentinel enabled and click Deploy. The extension deploys all four files to the workspace in the correct order: table schema first, then DCR, polling config, and connector definition. Once deployed, navigate to your Sentinel workspace via https://security.microsoft.com, go to Data Connectors, and find the Network Log API connector. The connector page shows the description, prerequisite notes, and the two credential fields generated by the agent: API Base URL and API Key. Enter your Function App base URL and API key and click Connect. The status updates to show the connector is connected and the deployment succeeded. Note: Data will appear in the workspace within 5 to 30 minutes depending on the polling interval. Run this query in Log Analytics to confirm ingestion. Note that the agent derives the table name from the vendor name and endpoint, so yours may differ slightly from the example below. Check the agent's summary output or the NetworkLogAPI_Table.json file for the exact name: NetworkLogAPIGetNetworkLogs_CL | sort by TimeGenerated desc | take 10 If you want to generate a fresh batch of events immediately rather than waiting for the next polling cycle, use the RefreshData endpoint to reset the sample records with new timestamps: curl -s -X POST -H "X-API-Key: " \ "https://.azurewebsites.net/api/RefreshData" Next Steps If you want to go further: Try it with your own API. The lab repo includes documentation on adapting the polling config, schema, and KQL transform to a real data source. Review the CCF connector schema documentation to understand the full range of supported configurations: pagination patterns, auth types, incremental pull strategies, and delta filter expressions. Explore the Microsoft Sentinel content hub to see how published connectors are structured and what the certification requirements look like for production submissions. Conclusion Following these steps, you saw how a working Sentinel connector can be generated, tested, and deployed in minutes rather than requiring days of manual configuration and infrastructure setup. If you are an ISV building a Sentinel integration and want hands-on support, Microsoft’s App Assure program is available to help. We partner with ISVs on connector development, validation, and deployment and provide guidance through implementation, testing, and readiness for production. You can get started by reaching out through our intake form. See our other Sentinel connector feature’s hands-on labs Building a CCF Nested API Pull Connector: A Technical Lab WalkthroughTransform your security operation with a unified experience in Defender
Co-authored with Lizet Pena, Caroline Mutua, Alvin Kua and Marco Sudahl Security operations teams today are being asked to do more than ever: respond faster, manage increasing data volumes, reduce operational complexity, stay ahead of evolving threats, and balance cost and efficiency. That’s why Microsoft is bringing Microsoft Sentinel into Microsoft Defender: to bring together SIEM, XDR, threat intelligence, AI, and automation into a single experience. By March 31, 2027, all Microsoft Sentinel customers will be automatically transitioned to Defender. But this transition is about far more than a new interface. It’s an opportunity to modernize the SOC, streamline operations, and unlock capabilities designed for the AI-first era of security operations. This blog kicks off a six-part series to help you confidently navigate the transition ahead of time, understand what changes (and what doesn’t), and maximize value along the way. Why this post, and why now This is the first of a six-part helping customers transition their Sentinel experience from the Azure portal to Defender: Part 1 – Beyond a portal move (You are here) ○ Part 2 – Anatomy of the change: Incidents, alerts, correlation, and data ○ Part 3 – Detection and automation, reimagined ○ Part 4 – The Governance Shift: RBAC, URBAC, Sentinel data lake, and MSSP ○ Part 5 – Your readiness playbook: Adoption helper, costs, APIs, and checklist ○ Part 6 – The AI-First SOC: Copilot, UEBA, threat intelligence, and SOC optimization The strategic shift in one paragraph Defender represents the convergence of Microsoft’s security capabilities into a single operational experience. Instead of switching between disconnected tools and workflows, security teams can work from one integrated environment spanning SIEM, XDR, threat intelligence, AI-powered investigation and response, cross-domain correlation, and SOC automation. Defender helps analysts investigate incidents faster, enables better collaboration across teams, and reduces operational friction across the security lifecycle. Most importantly, it creates a foundation for the future of AI-assisted and agentic security operations. Why migrate early? While the transition becomes mandatory in 2027, organizations that start earlier can begin realizing value immediately. Moving to Defender today helps organizations: Streamline analyst workflows with a unified incident queue Reduce investigation time through advanced cross-product correlation Take advantage of Security Copilot experiences integrated into Defender Simplify operations across Sentinel and Defender products Modernize governance and access management models Prepare their SOC for AI-driven investigation and response Take advantage of the latest innovations. Rather than treating migration as a compliance deadline, many customers are approaching it as a strategic modernization initiative for their SOC. What changes, and what stays the same One of the most important things to understand is that this is not a “rip and replace” migration. The foundational elements of Microsoft Sentinel remain intact while the operational experience evolves. Area What changes What stays Management plane Defender becomes the primary experience The Sentinel portal in Azure remains usable until March 31, 2027 Incident model Unified incident queue across Sentinel + Defender, XDR correlation, attack story view Log analytics remains the core storage layer Access control Unified RBAC (URBAC) preferred for cross-product, fine-grained access Azure RBAC continues to work until role migration to URBAC; service principals are not supported in URBAC Data Data lake for long-term retention and advanced analytics No workspace migration required Cost Data lake can materially reduce overall cost by shifting high-volume logs out of the analytics tier, also allowing longer term retention at a lower cost (up to 12 years) No change in the business model after moving over to Defender The key takeaway: customers are not rebuilding their environments from scratch. Existing investments continue to work while the operational layer becomes more integrated and intelligent. What Defender unlocks The transition to Defender is designed to unlock capabilities that are difficult to achieve in siloed environments. Security Copilot: Defender enables deeper integration with Security Copilot, including: AI-assisted incident triage Natural-language investigation workflows Guided response recommendations Natural language to KQL experiences Copilot capabilities help reduce analyst fatigue and accelerate investigation workflows. Unified correlation: With a single engine across all your alerts you can create richer, more contextual incidents spanning identities, endpoints, email, cloud apps, and data sources. This means you spend less time stitching alerts together manually and more time focused on high-confidence incidents. Data lake: Sentinel data lake introduces new flexibility for long-term retention, large-scale analytics, and cross-workspace investigation scenarios. For many customers, this creates opportunities to balance visibility, compliance, and cost more effectively. Case management: Collaborate across teams to respond to incidents. Playbook generator: Create custom workflow automations using natural language. Sentinel graph: Visualize relationships across users, devices, and activities to investigate attack paths, blast radius, and root cause. Sentinel MCP server: Let AI agents and Copilot query Sentinel in natural language through a unified, identity-secured Model Context Protocol interface Triage agent: Autonomous Security Copilot agent that triages high-volume alerts (phishing, identity, cloud) with AI reasoning and a transparent rationale. What this means for you Different roles feel this transition differently. Use this as a quick orientation as later posts go deep on each. Role What to pay attention to Security analyst New incident queue, attack story view, and Copilot-assisted triage – your day-to-day surface changes most. Detection engineer Custom detections become the forward direction; analytics rules continue to work but the model is evolving from SIEM to XDR detection. SOC manager URBAC governance, data lake blast-radius, and incident-centric automation reshape how you run the SOC. MSSP and Partner Multi-tenant view (up to 100 tenants), planning to support up to 1k tenants, unified incident queue, dual RBAC model – Lighthouse is still needed for Azure resources. Clearing up common misconceptions “The transition is optional.” No. Customers must migrate their experience by March 31, 2027. “We need to migrate our workspaces.” You do not need to migrate log analytics workspaces simply to use Microsoft Sentinel in Defender. “This is only a UI change.” Defender introduces meaningful operational and architectural improvements across investigation, correlation, governance, automation, and AI-assisted workflows. “The transition itself increases costs.” There is no additional licensing charge simply for using Sentinel in Defender. Optional capabilities—such as Security Copilot or Sentinel data lake usage—may introduce additional costs depending on adoption and usage patterns. How to get started Align your stakeholders: Brief your SOC leadership and detection engineering leads on the March 31, 2027 deadline and the platform shift narrative. Form a readiness team: Identify a small working group (analyst + engineer + SOC manager + identity owner) to own the readiness effort. Explore Defender: Start familiarizing yourself with Defender and workflows. Assess your data strategy: Review how leveraging the data lake may fit into your future strategy. Follow Tech Community: Get more information in this series Additional resources Further reading: The Microsoft Security Community post Migrate Sentinel to Defender – Why it is a security architecture decision, not just a portal change frames the same thesis from an architectural lens. For the official transition guidance, start with the Microsoft Learn article Connect Microsoft Sentinel to the Microsoft Defender portal. Continue the series This is the first of six parts. The remaining posts will be published over the coming days. Each one stands alone, so you can read them in order as they go live or jump to the angle that matters most to you once it's out: Part 2 – Anatomy of the change: Incidents, alerts, correlation, and data If you want component-level mechanics: how the XDR correlation engine replaces Fusion, why incidents are no longer alert-centric, and what changes (and doesn’t) in your data architecture. Part 3 – Detection and automation, reimagined If you write detections or run automation: the shift from analytics rules to custom detections, the move from alert-driven to incident-driven SOAR, and how hunting evolves. Part 4 – The governance shift: RBAC, URBAC, Sentinel data lake, and MSSP If you own identity, access, or multi-tenant operations: the move from Azure RBAC to URBAC, Sentinel data lake, better blast-radius identification, and the MSSP model. Part 5 – Your readiness playbook: Adoption helper, costs, APIs, and the checklist If you need a practical plan: a walk-through of the Defender adoption helper, cost reality, API strategy, and the migration checklist. Part 6 – The AI-first SOC: Copilot, UEBA, Threat intelligence, and SOC optimization If you want to see the destination: how Security Copilot, UEBA, threat intelligence, and SOC optimization combine into a fundamentally different operating model.Microsoft Sentinel data lake FAQ
Microsoft Sentinel data lake (generally available) is a purpose‑built, cloud‑native security data lake. It centralizes all security data in an open format, serving as the foundation for agentic defense, enhanced security insights, and graph-based enrichment. It offers cost‑effective ingestion, long‑term retention, and advanced analytics. In this blog we offer answers to many of the questions we’ve heard from our customers and partners. General questions What is the Microsoft Sentinel data lake? Microsoft has expanded its industry-leading SIEM solution, Microsoft Sentinel, to include a unified, security data lake, designed to help optimize costs, simplify data management, and accelerate the adoption of AI in security operations. This modern data lake serves as the foundation for the Microsoft Sentinel platform. It has a cloud-native architecture and is purpose-built for security—bringing together all security data for greater visibility, deeper security analysis, contextual awareness and agentic defense. It provides affordable, long-term retention, allowing organizations to maintain robust security while effectively managing budgetary requirements. What are the benefits of Sentinel data lake? Microsoft Sentinel data lake is purpose built for security offering flexible analytics, cost management, and deeper security insights. Sentinel data lake: Centralizes security data delta parquet and open format for easy access. This unified data foundation accelerates threat detection, investigation, and response across hybrid and multi-cloud environments. Enables data federation by allowing customers to access data in external sources like Microsoft Fabric, ADLS and Databricks from the data lake. Federated data appears alongside native Sentinel data, enabling correlated hunting, investigation, and custom graph analysis across a broader digital estate. Offers a disaggregated storage and compute pricing model, allowing customers to store massive volumes of security data at a fraction of the cost compared to traditional SIEM solutions. Allows multiple analytics engines like Kusto, Spark, and ML to run on a single data copy, simplifying management, reducing costs, and supporting deeper security analysis. Integrates with GitHub Copilot and VS Code empowering SOC teams to automate enrichment, anomaly detection, and forensic analysis. Supports AI agents via the MCP server, allowing tools like GitHub Copilot to query and automate security tasks. The MCP Server layer brings intelligence to the data, offering Semantic Search, Query Tools, and Custom Analysis capabilities that make it easier to extract insights and automate workflows. Provides streamlined onboarding, intuitive table management, and scalable multi-tenant support, making it ideal for MSSPs and large enterprises. The Sentinel data lake is designed for security workloads, ensuring that processes from ingestion to analytics meet evolving cybersecurity requirements. Is Microsoft Sentinel SIEM going away? No. Microsoft is expanding Sentinel into an AI powered end-to-end security platform that includes SIEM and new platform capabilities - Security data lake, graph-powered analytics and MCP Server. SIEM remains a core component and will be actively developed and supported. Getting started What are the prerequisites for Sentinel data lake? To get started: Connect your Sentinel workspace to Microsoft Defender prior to onboarding to Sentinel data lake. Once in the Defender experience see data lake onboarding documentation for next steps. Note: Sentinel is moving to the Microsoft Defender portal and the Sentinel Azure portal will be retired by March 31, 2027. I am a Sentinel-only customer, and not a Defender customer. Can I use the Sentinel data lake? Yes. You must connect Sentinel to the Defender experience before onboarding to the Sentinel data lake. Microsoft Sentinel is generally available in the Microsoft Defender portal, with or without Microsoft Defender XDR or an E5 license. If you have created a log analytics workspace, enabled it for Sentinel and have the right Microsoft Entra roles (e.g. Global Administrator + Subscription Owner, Security Administrator + Sentinel Contributor), you can enable Sentinel in the Defender portal. For more details on how to connect Sentinel to Defender review these sources: Microsoft Sentinel in the Microsoft Defender portal In what regions is Sentinel data lake available? For supported regions see: Geographical availability and data residency in Microsoft Sentinel | Azure Docs. Is there an expected release date for Microsoft Sentinel data lake in GCC, GCC-H, and DoD? While the exact date is not yet finalized, we plan to expand Sentinel data lake to the US Government environments. . How will URBAC and Entra RBAC work together to manage the data lake given there is no centralized model? Entra RBAC will provide broad access to the data lake (URBAC maps the right permissions to specific Entra role holders: GA/SA/SO/GR/SR). URBAC will become a centralized pane for configuring non-global delegated access to the data lake. For today, you will use this for the “default data lake” workspace. In the future, this will be enabled for non-default Sentinel workspaces as well – meaning all workspaces in the data lake can be managed here for data lake RBAC requirements. Azure RBAC on the Log Analytics (LA) workspace in the data lake is respected through URBAC as well today. If you already hold a built-in role like log analytics reader, you will be able to run interactive queries over the tables in that workspace. Or, if you hold log analytics contributor, you can read and manage table data. For more details see: Roles and permissions in the Microsoft Sentinel platform | Microsoft Learn Data ingestion and storage How do I ingest data into the Sentinel data lake? To ingest data into the Sentinel data lake, you can use existing Sentinel data connectors or custom connectors to bring data from Microsoft and third-party sources. Data can be ingested into the analytics tier or the data lake tier. Data ingested into the analytics tier is automatically mirrored to the lake (at no additional cost). Alternatively, data that is not needed in the analytics tier can be ingested directly into the data lake. Data retention is configured directly in table management, for both analytics retention and data lake storage. Note: Certain tables do not support data lake-only ingestion via either API or data connector UI. See here for more information: Custom log tables. What is Microsoft’s guidance on when to use analytics tier vs. the data lake tier? Sentinel data lake offers flexible, built-in data tiering (analytics and data lake tiers) to effectively meet diverse business use cases and achieve cost optimization goals. Analytics tier: Is ideal for high-performance, real-time, end-to-end detections, enrichments, investigation and interactive dashboards. Typically, high-fidelity data from EDRs, email gateways, identity, SaaS and cloud logs, threat intelligence (TI) should be ingested into the analytics tier. Data in the analytics tier is best monitored proactively with scheduled alerts and scheduled analytics to enable security detections Data in this tier is retained at no cost for up to 90 days by default, extendable to 2 years. A copy of the data in this tier is automatically available in the data lake tier at no extra cost, ensuring a unified copy of security data for both tiers. Data lake tier: Is designed for cost-effective, long-term storage. High-volume logs like NetFlow logs, TLS/SSL certificate logs, firewall logs and proxy logs are best suited for data lake tier. Customers can use these logs for historical analysis, compliance and auditing, incident response (IR), forensics over historical data, build tenant baselines, TI matching and then promote resulting insights into the analytics tier. Customers can run full Kusto queries, Spark Notebooks and scheduled jobs over a single copy of their data in the data lake. Customers can also search, enrich and promote data from the data lake tier to the analytics tier for full analytics. For more details see documentation. What does it mean that a copy of all new analytics tier data will be available in the data lake? When Sentinel data lake is enabled, a copy of all new data ingested into the analytics tier is automatically duplicated into the data lake tier. This means customers don’t need to manually configure or manage this process, every new log or telemetry added to the analytics tier becomes instantly available in the data lake. This allows security teams to run advanced analytics, historical investigations, and machine learning models on a single, unified copy of data in the lake, while still using the analytics tier for real-time SOC workflows. It’s a seamless way to support both operational and long-term use cases—without duplicating effort or cost. What is the guidance for customers using data federation capability in Sentinel data lake? Starting April 1, 2026, federate data from Microsoft Fabric, ADLS, and Azure Databricks into Sentinel data lake. Use data federation when data is exploratory, infrequently accessed, or must remain at source due to governance, compliance, sovereignty, or contractual requirements. Ingest data directly into Sentinel to unlock full SIEM capabilities, always-on detections, advanced automation, and AI‑driven defense at scale. This approach lets security teams start where their data already lives — preserving governance, then progressively ingest data into Sentinel for full security value. Is there any cost for retention in the analytics tier? Analytics ingestion includes 90 days of interactive retention, at no additional cost. Simply set analytics retention to 90 days or less. Analytics retention beyond 90 days will incur a retention cost. Data can be retained longer within the data lake by using the “total retention” setting. This allows you to extend retention within the data lake for up to 12 years. While data is retained within the analytics tier, there is no charge for the mirrored data within the lake. Retaining data in the lake beyond the analytics retention period incurs additional storage costs. See documentation for more details: Manage data tiers and retention in Microsoft Sentinel | Microsoft Learn What is the guidance for Microsoft Sentinel Basic and Auxiliary Logs customers? If you previously enabled Basic or Auxiliary Logs plan in Sentinel: You can view Basic Logs in the Defender portal but manage it from the Log Analytics workspace. To manage it in the Defender portal, you must change the plan from Basic to Analytics. Once the table is transitioned to the analytics tier, if desired, it can then be transitioned to the data lake. Existing Auxiliary Log tables will be available in the data lake tier for use once the Sentinel data lake is enabled. Billing for these tables will automatically switch to the Sentinel data lake meters. Microsoft Sentinel customers are recommended to start planning their data management strategy with the data lake. While Basic and Auxiliary Logs are still available, they are not being enhanced further. Sentinel data lake offers more capabilities at a lower price point. Please plan on onboarding your security data to the Sentinel data lake. Azure Monitor customers can continue to use Basic and Auxiliary Logs for observability scenarios. What happens to customers that already have Archive logs enabled? If a customer has already configured tables for Archive retention, existing retention settings will not change and will be automatically inherited by the Sentinel data lake. All data, including existing data in archive retention will be billed using the data lake storage meter, benefiting from 6x data compression. However, the data itself will not move. Existing data in archive will continue to be accessible through Sentinel search and restore experiences: o Data will not be backfilled into the data lake. o Data will be billed using the data lake storage meter. New data ingested after enabling the data lake: o Will be automatically mirrored to the data lake and accessible through data lake explorer. o Data will be billed using the data lake storage meter. Example: If a customer has 12 months of total retention enabled on a table, 2 months after enabling ingestion into the Sentinel data lake, the customer will still have access to 10 months of archived data (through Sentinel search and restore experiences), but access to only 2 months of data in the data lake (since the data lake was enabled). Key considerations for customers that currently have Archive logs enabled: The existing archive will remain, with new data ingested into the data lake going forward; previously stored archive data will not be backfilled into the lake. Archive logs will continue to be accessible via the Search and Restore tab under Sentinel. If analytics and data lake mode are enabled on table, which is the default setting for analytics tables when Sentinel data lake is enabled, all new data will be ingested into the Sentinel data lake. There will only be one storage meter (which is data lake storage) going forward. Archive will continue to be accessible via Search and Restore. If Sentinel data lake-only mode is enabled on table, new data will be ingested only into the data lake; any data that’s not already in the Sentinel data lake won’t be migrated/backfilled. Only data that was previously ingested under the archive plan will be accessible via Search and Restore. What is the guidance for customers using Azure Data Explorer (ADX) alongside Microsoft Sentinel? Some customers might have set up ADX cluster for their DIY lake setup. Customers can choose to continue using that setup and gradually migrate to Sentinel data lake for new data that they want to manage. The lake explorer will support federation with ADX to enable the customers to migrate gradually and simplify their deployment. What happens to the Defender XDR data after enabling Sentinel data lake? By default, Defender XDR tables are available for querying in advanced hunting, with 30 days of analytics tier retention included with the XDR license. To retain data beyond this period, an explicit change to the retention setting is required, either by extending the analytics tier retention or the total retention period. You can extend the retention period of supported Defender XDR tables beyond 30 days and ingest the data into the analytics tier. For more information see Manage XDR data in Microsoft Sentinel. You can also ingest XDR data directly into the data lake tier. See here for more information. A list of XDR advanced hunting tables supported by Sentinel are documented here: Connect Microsoft Defender XDR data to Microsoft Sentinel | Microsoft Learn. KQL queries and jobs Is KQL and Notebook supported over the Sentinel data lake? Yes, via the data lake KQL query experience along with a fully managed Notebook experience which enables spark-based big data analytics over a single copy of all your security data. Customers can run queries across any time range of data in their Sentinel data lake. In the future, this will be extended to enable SQL query over lake as well. Note: Triggering a KQL job directly via an API or Logic App is not yet supported but is on the roadmap. Why are there two different places to run KQL queries in Sentinel experience? Advanced hunting queries both XDR and analytics tables, with compute cost included. Data lake explorer only queries data in the lake and incurs a separate compute cost. Consolidating advanced hunting and KQL explorer user interfaces is on the roadmap. This will provide security analysts a unified query experience across both analytics and data lake tiers. Where is the output from KQL jobs stored? KQL jobs are written into existing or new custom tables in the analytics tier. Is it possible to run KQL queries on multiple data lake tables? Yes, you can run KQL interactive queries and jobs using operators like join or union. Can KQL queries (either interactive or via KQL jobs) join data across multiple workspaces? Security teams can run multi-workspace KQL queries for broader threat correlation Pricing and billing How does a customer pay for Sentinel data lake? Billing is automatically enabled at the time of onboarding based on Azure Subscription and Resource Group selections. Customers are then charged based on the volume of data ingested, retained, and analyzed (e.g. KQL Queries and Jobs). See Sentinel pricing page for more details. 2. What are the pricing components for Sentinel data lake? Sentinel data lake offers a flexible pricing model designed to optimize security coverage and costs. At a high level, pricing is based on the volume of data ingested/processed, the volume of data retained, and the volume of data processed. For specific meter definitions, see documentation. 3. How does the business model for Sentinel SIEM change with the introduction of the data lake? There is no change to existing Sentinel analytics tier ingestion business model. Sentinel data lake has separate meters for ingestion, storage and analytics. 4. What happens to the existing Sentinel SIEM and related Azure Monitor billing meters when a customer onboards to Sentinel data lake? When a customer onboards to the Sentinel data lake, nothing changes with analytic ingestion or retention. Customers using data archive and Auxiliary Logs will automatically transition to the new data lake meters. How does data lake storage affect cost efficiency for high volume data retention? Sentinel data lake offers cost-effective, long-term storage with uniform data compression of 6:1 across all data sources, applicable only to data lake storage. Example: For 600GB of data stored, you are only billed for 100GB compressed data. This approach allows organizations to retain greater volumes of security data over extended periods cost-effectively, thereby reducing security risks without compromising their overall security posture. here How “Data Processing” billed? To support the ingestion and standardization of diverse data sources, the Data Processing feature applies a $0.10 per GB (US East) charge for all data ingested into the data lake. This feature enables a broad array of transformations like redaction, splitting, filtering and normalization. The data processing charge is applied per GB of uncompressed data Note: For regional pricing, please refer to the “Data processing” meter within the Microsoft Sentinel Pricing official documentation. Does “Data processing” meter apply to analytics tier data mirrored in the data lake? No. Data processing charge will not be applied to mirrored data. Data mirrored from the analytic tier is not subject to either data ingestion or processing charges. How is retention billed for tables that use data lake-only ingestion & retention? Sentinel data lake decouples ingestion, storage, and analytics meters. Customers have the flexibility to pay based on how data is retained and used. For tables that use data lake‑only ingestion, there is no included free retention—unlike the analytics tier, which includes 90 days of analytics retention. Retention charges begin immediately once data is stored in the data lake. Data lake storage billing is based on compressed data size rather than raw ingested volume, which significantly reduces storage costs and delivers lower overall retention spend for customers. Does data federation incur charges? Data federation does not generate any ingestion or storage fees in Sentinel data lake. Customers are billed only when they run analytics or queries on federated data, with charges based on Sentinel data lake compute and analytics meters. This means customers pay solely for actual data usage, not mere connectivity. How do I understand Sentinel data lake costs? Sentinel data lake costs driven by three primary factors: how much data is ingested, how long that data is retained, and how the data is used. Customers can flexibly choose to ingest data into the analytics tier or data lake tier, and these architectural choices directly impact cost. For example, data can be ingested into the analytics tier—where commitment tiers help optimize costs for high data volumes—or ingested data directly into the Sentinel data lake for lower‑cost ingestion, storage, and on‑demand analysis. Customers are encouraged to work with their Microsoft account team to obtain an accurate cost estimate tailored to their environment. See Sentinel pricing page to understand Sentinel pricing. How do I manage Sentinel data lake costs? Built-in cost management experiences help customers with cost predictability, billing transparency, and operational efficiency. Reports provide customers with insights into usage trends over time, enabling them to identify cost drivers and optimize data retention and processing strategies. Set usage-based alerts on specific meters to monitor and control costs. For example, receive alerts when query or notebook usage passes set limits, helping avoid unexpected expenses and manage budgets. See our Sentinel cost management documentation to learn more. If I’m an Auxiliary Logs customer, how will onboarding to the Sentinel data lake affect my billing? Once a workspace is onboarded to Sentinel data lake, all Auxiliary Logs meters will be replaced by new data lake meters. Do we charge for data lake ingestion and storage for graph experiences? Microsoft Sentinel graph-based experiences are included as part of the existing Defender and Purview licenses. However, Sentinel graph requires Sentinel data lake and specific data sources to build the underlying graph. Enabling these data sources will incur ingestion and data lake storage costs. Note: For Sentinel SIEM customers, most required data sources are free for analytics ingestion. Non-entitled sources such as Microsoft Entra ID logs will incur ingestion and data lake storage costs. How is Entra asset data and ARG data billed? Data lake ingestion charges of $0.05 per GB (US EAST) will apply to Entra asset data and ARG data. Note: This was previously not billed during public preview and is billed since data lake GA. To learn more, see: https://learn.microsoft.com/azure/sentinel/datalake/enable-data-connectors When a customer activates Sentinel data lake, what happens to tables with archive logs enabled? To simplify billing, once the data lake is enabled, all archive data will be billed using the data lake storage meter. This provides consistent long-term retention billing and includes automatic 6x data compression. For most customers, this change results in lower long‑term retention costs. However, customers who previously had discounted archive retention pricing will not automatically receive the same discounts on the new data lake storage meters. In these cases, customers should engage their Microsoft account team to review pricing implications before enabling the Sentinel data lake. Thank you Thank you to our customers and partners for your continued trust and collaboration. Your feedback drives our innovation, and we’re excited to keep evolving Microsoft Sentinel to meet your security needs. If you have any questions, please don’t hesitate to reach out—we’re here to support you every step of the way. Learn more: Get started with Sentinel data lake today: https://aka.ms/Get_started/Sentinel_datalake Microsoft Sentinel AI-ready platform: https://aka.ms/Microsoft_Sentinel Sentinel data lake videos: https://aka.ms/Sentineldatalake_videos Latest innovations and updates on Sentinel: https://aka.ms/msftsentinelblog Sentinel pricing page: https://aka.ms/MicrosoftSentinel_PricingWhat’s new in Microsoft Sentinel: May 2026
Welcome to the May edition of What's new in Microsoft Sentinel. This month’s updates focus on unified role-based access control (RBAC), ecosystem breadth, AI-agent security, and high-assurance identity. RBAC and row-level scoping are now generally available, giving security teams a single, granular permissions model across Sentinel and the Microsoft Defender portal and enabling multi-team SOC collaboration. The Sentinel connector catalog has passed 400 connectors, expanding coverage across Microsoft and third-party data sources and helping customers and partners onboard new data faster with the Codeless Connector Framework (CCF). The Agent 365 connector, now in public preview, brings AI agent telemetry into Sentinel data lake as first-class standardized signals so you can monitor agent behavior alongside identity, endpoint, and cloud activity. Finally, Entra Verified ID partner integrations in Microsoft Security Store are now generally available, delivering high‑assurance identity verification that makes account recovery after compromise far safer and significantly reduces the risk of re‑compromise. Read on for the full list of updates across Sentinel in May. Sentinel innovations: Sentinel SIEM Sentinel data lake Microsoft Security Store Sentinel SIEM Unified role-based access controls and row level scoping [Generally available] Sentinel now delivers general availability of two powerful access management capabilities: Unified RBAC and row-level data scoping. Together, these innovations provide a consistent, end-to-end model for controlling who can access data and what actions they can take — extending unified permissions management across the Defender portal while enabling granular, row-level visibility within a single Sentinel workspace. With Unified RBAC, organizations can simplify and centralize permissions across security workloads, reducing operational overhead, while row-level scoping enables secure collaboration across multiple teams by ensuring users only see data aligned to their role or scope. This milestone unlocks more scalable, multi-team SOC operations without the need for workspace segmentation, helping us to advance toward fully unified, granular access control across Microsoft Security. Tenant groups [Public preview] Managing security across multiple tenants just got simpler. Tenant Groups in the Microsoft Defender multi-tenant portal (MTO) give managed security service providers (MSSPs), cloud service partners (CSPs), and multi-tenant security teams a flexible way to organize tenants into logical groupings such as customer segment, geography, or operational priority, and instantly switch views with a single click. This streamlined experience reduces noise, improves investigation focus, and aligns to how teams actually work, all while respecting existing permissions and access controls. Learn more. Out-of-the-box integrations for Sentinel automation [Public preview] Out-of-the-box (OOTB) integrations for Sentinel automation brings a centralized catalog to easily discover, configure, and manage both Microsoft and third-party integrations. With simple, authentication-based setup, users can quickly add integrations and seamlessly incorporate them into playbooks. The experience places OOTB and custom integrations side by side, with enhanced with smart search, recommendations, and duplicate prevention to streamline automation workflows end to end. Learn more. UEBA enhancements [Public preview] Microsoft Sentinel UEBA continues to evolve with improvements that simplify management and expand detection coverage. A dedicated UEBA tab view in the Sentinel settings page consolidates UEBA and behaviors settings, making configuration easier to find and manage. Learn more. UEBA insights and anomalies now support the OktaV2_CL table alongside the existing Okta_CL table, extending anomalous activity and anomalous MFA failures detections to customers using the newer Okta connector format, without requiring new anomaly types. Learn more. UEBA extends GCP Audit Logs coverage with five anomaly detections for login activity, privileged actions, resource deployments, secret/KMS key access, and infrastructure usage. Learn more. Together, these updates make UEBA easier to operate while extending its visibility into identity and behavior signals from additional cloud and identity providers. Read the latest blog from the Microsoft Defender Research Team to learn more about Microsoft Sentinel UEBA and binary feature stacking, which uses clear binary signals to help establish behavioral context and inform investigation and detection decisions. Threat Intelligence – TAXII Export connector [Generally available] Sentinel supports threat intelligence export through the built-in Threat Intelligence – Trusted Automated Exchange of Intelligence Information (TAXII) Export connector, giving customers a standards-based way to share curated Structured Threat Information Expression (STIX) objects with supported TAXII 2.1 platforms. Configured from the Defender portal, the connector handles destination setup and intelligence delivery to external platforms. The capability supports cross-organization intelligence sharing for collective defense and centralized management in multi-tenant environments, with use cases across government, critical infrastructure, and large distributed organizations. Additional enhancements are planned, including more export options and expanded destination support. Learn more. Decision-stage resources for SIEM migration to Sentinel The AI-powered SIEM migration experience helps teams analyze detections, identify required data sources and connectors, and plan a phased move to Sentinel. But, customers still need help turning that analysis into a clear decision. To support that step, we’re introducing two new customer-facing resources: the Sentinel SIEM Migration Decision and Planning Guide, which explains the migration journey, outputs, and decision checkpoints before execution, and the Decision-Stage Customer FAQ, which answers common questions around disruption, cost, dual running, detection coverage, and delivery support. Together, these resources help make migration conversations more concrete and move teams more quickly from evaluation to a clearer, lower-risk next step. Learn more: Read the blog: AI-powered SIEM migration experience announcement Download the guide: Decision and planning guide Download the FAQ: Decision-stage customer FAQ Learn more: SIEM migration experience documentation Register for live AMA (Jun 23 at 9am PT): Live Microsoft Tech Community AMA on SIEM migration Sentinel data lake 400+ Sentinel data connectors The Sentinel connector catalog now includes 400+ connectors, providing broad, ready-to-deploy coverage across Microsoft and third-party data sources. Customers can flexibly ingest security data into Microsoft Sentinel analytics tier or the data lake tier. The Codeless Connector Framework (CCF) and VS code-based connector builder agent enables partners and customers to onboard new data sources faster and scale the catalog. Discover connectors in the Sentinel Content hub within the Defender portal or build custom connectors when needed. Learn more. Agent 365 connector [Public preview] Agent 365 connector streams AI agent telemetry from Agent 365 into Sentinel data lake, giving SOC teams visibility into agent behavior alongside identity, endpoint, and cloud signals. With the Agent 365 connector in place, Sentinel data lake becomes the system of record for agent security, turning activity such as data exposure or access drift into first-class security signals that analysts can correlate, hunt across, and investigate. Telemetry is normalized and to mapped to standard Advanced Security Information Model (ASIM) schemas, ready for analytics and detections, and end-to-end investigations can run through KQL, graph, and MCP-powered workflows. Install the connector with a single click from Sentinel Content Hub in the Defender portal. Learn more. CCF support for Azure Blob Storage [Public preview] Sentinel Codeless Connector Framework (CCF) supports Azure Blob Storage as a data source, providing an ingestion pattern designed for high-volume security data. Partners and customers can build CCF connectors that read from Blob Storage through a durable architecture that buffers spikes, handles backpressure, and reduces data loss risk during outages or throttling, making ingestion more reliable for variable or distributed pipelines. The pattern broadens compatibility with partners already streaming logs to Azure as part of their audit data delivery, with Cloudflare and Netskope as early adopters. App Assure further provides engineering-backed support for designing, validating, and remediating the Azure Blob Storage CCF connector integration. Learn more. Data filtering and splitting [Generally available] At RSAC, we announced built‑in filtering and splitting capabilities in Microsoft Sentinel, which is now generally available. As security teams ingest more data, it is important to optimize security data pipeline by controlling what data is ingested and in which tier. With filtering and splitting natively integrated into the Defender portal, security teams can shape data before it reaches Sentinel, without switching tools or managing custom JSON files. Using simple KQL‑based transformations directly in the UI, you can filter low‑value events and intelligently route data, making ingestion optimization faster, more intuitive, and easier to manage at scale. Filtering at ingest time allows you to remove low‑value or benign events to reduce noise, lower unnecessary processing, and ensure high‑signal data drives detections and investigations. Splitting enables intelligent routing of data between the analytics tier and the data lake tier based on relevance and usage. Together, these capabilities help you balance cost and performance while scaling data ingestion sustainably as your digital estate grows. Learn more. Transition your Sentinel connectors to the Codeless Connector Framework (CCF) [Action required] Azure has announced that the legacy Azure Data Collection API will be deprecated on September 14, 2026. Sentinel recommends customers review existing connectors and upgrade to the latest Codeless Connector Framework (CCF) versions to ensure continued access to the newest Sentinel capabilities. CCF delivers a fully managed SaaS experience with built-in health monitoring, centralized credential management, and improved performance. This enables partners and customers to onboard new data sources faster and at scale. Microsoft Security Store Entra Verified ID partner integrations via Security Store [Generally available] Security Store helps organizations secure one of the most critical steps in incident response: safe account recovery after compromise. Once a SOC team detects and contains a potential account takeover (ATO), restoring access requires high confidence that the user is legitimate. Through partner integrations with IDEMIA, AU10TIX, CLEAR, 1Kosmos, and WhoAmI, customers can extend Entra Verified ID with high-assurance identity verification (such as document and biometric checks) to validate users during recovery, onboarding, or helpdesk workflows. This helps replace weaker fallback methods that attackers often exploit, enabling SOC and IT teams to safely restore access while reducing risk of re-compromise. Learn more. Purview Data Security Triage Agent in Defender [Public preview] Security Store powers how customers discover and activate data security agents across Defender and Microsoft Purview, starting with the Data Security Triage Agent. This capability delivers AI-generated summaries and prioritization of Data Loss Prevention (DLP) alerts directly into Defender XDR, helping security teams reduce noise and focus on the incidents that matter most. By unifying discovery and activation through Security Store, customers can deploy data security agents in fewer steps and enable more integrated workflows across threat and data protection surfaces. Learn more. Additional resources Blogs and documentation: From idea to production: Building Security Store Advisor with an agentic SDLC Upcoming webinars: June 4: End-to-End Security in the Age of Agentic AI June 10: Deploy, optimize, and implement threat protection with Sentinel June 10: Security Foundations for AI Adoption June 24: Modern Security Made Simple: Stay Ahead of Threats with Sentinel Upcoming events: June 2–3: Microsoft Build, San Francisco (and free online) CEO Satya Nadella Day 1 keynote 90+ sessions, Microsoft Security experts onsite Register: build.microsoft.com Stay connected Check back each month for the latest innovations, updates, and events to ensure you’re getting the most out of Microsoft Sentinel. We’ll see you in the next edition!The Microsoft Copilot Data Connector for Microsoft Sentinel is Now in Public Preview
*Please note that this connector is now in GA status as of March, 2026* We are happy to announce a new data connector that is available to the public: the Microsoft Copilot data connector for Microsoft Sentinel. The new Microsoft Copilot data connector will allow for audit logs and activities generated by different offerings of Copilot to be ingested into Microsoft Sentinel and Microsoft Sentinel data lake. This allows for Copilot activities to be leveraged within Microsoft Sentinel features such as analytic rules/custom detections, Workbooks, automation, and more. This also allows for Copilot data to be sent to Sentinel data lake, which opens the possibilities for integrations with custom graphs, MCP server, and more while offering lower cost ingestion and longer retention as needed. Eligibility for the Connector The connector is available for all customers within Microsoft Sentinel, but will only ingest data for environments that have access to Copilot licenses and SCUs as the activities rely on Copilot being used. These logs are available via the Purview Unified Audit Log (UAL) feed, which is available and enabled for all users by default. A big value of this new connector is that it eliminates the need for users to go to the Purview Portal in order to see these activities, as they are proactively brought into the workspace, enabling SOCs to generate detections and proactively threat hunt on this information. Note: This data connector is a single-tenant connector, meaning that it will ingest the data for the entire tenant that it resides in. This connector is not designed to handle multi-tenant configurations. What’s Included in the Connector The following are record types from Office 365 Management API that will be supported as part of this connector: 261 CopilotInteraction 310 CreateCopilotPlugin 311 UpdateCopilotPlugin 312 DeleteCopilotPlugin 313 EnableCopilotPlugin 314 DisableCopilotPlugin 315 CreateCopilotWorkspace 316 UpdateCopilotWorkspace 317 DeleteCopilotWorkspace 318 EnableCopilotWorkspace 319 DisableCopilotWorkspace 320 CreateCopilotPromptBook 321 UpdateCopilotPromptBook 322 DeleteCopilotPromptBook 323 EnableCopilotPromptBook 324 DisableCopilotPromptBook 325 UpdateCopilotSettings 334 TeamCopilotInteraction 363 Microsoft365CopilotScheduledPrompt 371 OutlookCopilotAutomation 389 CopilotForSecurityTrigger 390 CopilotAgentManagement These are great options for monitoring users who have permission to make changes to Copilot across the environment. This data can assist with identifying if there are anomalous interactions taking place between users and Copilot, unauthorized attempts of access, or malicious prompt usage. How to Deploy the Connector The connector is available via the Microsoft Sentinel Content Hub and can be installed today. To find the connector: Within the Defender Portal, expand the Microsoft Sentinel navigation in the left menu. Expand Configuration and select Content Hub. Within the search bar, search for “Copilot”. Click on the solution that appears and click Install. Once the solution is installed, the connector can be configured by clicking on the connector within the solution and selecting Open Connector Page. To enable the connector, the user will need either Global Administrator or Security Administrator on the tenant. Once the connector is enabled, the data will be sent to the table named CopilotActivity. Note: Data ingestion costs apply when using this data connector. Pricing will be based on the settings for the Microsoft Sentinel workspace or at the Microsoft Sentinel data lake tier pricing. As this data connector is in Public Preview, users can start deploying this connector right now! As always, let us know what you think in the comments so that we may continue to build what is most valuable to you. We hope that this new data connector continues to assist your SOC with high valuable insights that best empowers your security. Resources: Office Management API Event Number List: https://learn.microsoft.com/en-us/office/office-365-management-api/office-365-management-activity-api-schema#auditlogrecordtype Purview Unified Audit Log Library: Audit log activities | Microsoft Learn Copilot Inclusion in the Microsoft E5 Subscription: Learn about Security Copilot inclusion in Microsoft 365 E5 subscription | Microsoft Learn Microsoft Sentinel: What is Microsoft Sentinel SIEM? | Microsoft Learn Microsoft Sentinel Platform: Microsoft Sentinel data lake overview - Microsoft Security | Microsoft Learn
Agent 365 connector: Monitor, hunt, and investigate AI agent activity in Microsoft Sentinel
As enterprises scale the use of AI agents, SOC teams need visibility into AI agent behavior. The Agent 365 connector, now in public preview, streams rich agent telemetry from Agent 365 into Microsoft Sentinel data lake. Agent activity, such as agent data exposure or access drift, is surfaced alongside other security data, giving SOC teams a unified view across digital environments. AI Agent actions are correlated with agent identity, endpoint, and cloud signals, enabling analysts to run end‑to‑end investigations using KQL, graph, and MCP-powered workflows. Why this matters for organizations By centralizing security and AI agent telemetry in Sentinel data lake, organizations establish a unified control plane for securing AI agents. This enables security teams to analyze agent activity in context with broader signals and investigate using familiar Sentinel tools. This unlocks the ability for SOCs to detect risky or anomalous agent behavior early, understand impact quickly, and respond with speed and confidence. As AI agents take on real operational responsibility, this level of visibility is critical to prevent blind spots, reduce risk, and ensure agents operate safely at enterprise scale. End‑to‑end visibility into AI agent behavior: A centralized view of AI agent behavior allows AI agents to be treated as first-class entities alongside users, identities, endpoints, and workloads. Advanced hunting with KQL: Hunt using KQL to proactively uncover unusual AI agent execution patterns, sensitive actions, or activity without clear human context. These hunts help surface potential risk early using the same workflows already used for other security data. Analyzing blast radius and impact with Sentinel graph: Security teams can correlate AI agent activity with identities, endpoints, and cloud resources to understand blast radius and potential impact during an investigation. By pivoting across related entities in Sentinel, analysts can assess how agent actions connect to the broader environment and support deeper, end‑to‑end investigations. Querying agent data through MCP: Use MCP to surface agent observability data through AI assistants, letting analysts pull agent telemetry into investigation workflows alongside other Sentinel data. Agent 365 connector key capabilities Install the Agent 365 connector with a single click using Sentinel Content Hub in the Defender portal. Once enabled, two capabilities come online automatically: Unified agent telemetry across Agent 365 agent experiences: Rich Agent 365 agent telemetry streams into Sentinel data lake, ready to analyze alongside identity, endpoint, and cloud signals using familiar SOC workflows. ASIM unified schema for AI agent observability: Agent 365 agent observability data is normalized into an ASIM-aligned schema so it is consistent, queryable, and ready for analytics and detections. With the connector in place, Sentinel data lake becomes the system of record and the control plane for Agent 365 agent security—turning agent behavior into first-class security signals across SecOps workflows like hunting, investigation, detection engineering, and response. Use cases Prevent sensitive data exposure from misconfigured agents When an AI agent is granted broader access than intended, a crafted prompt could override safeguards and expose confidential data. With agent telemetry, security teams can trace the full execution path—from prompt to tools to data access—to quickly identify the root cause and contain the exposure. Detect and control agent access drift over time As agents take on new tasks, their permissions can expand beyond the original scope, often without clear visibility. Agent telemetry enables continuous behavioral baselining, making it easier to spot abnormal access patterns early and prevent privilege misuse before it escalates. Uncover hidden lateral movement across agent workflows Agents often collaborate and delegate tasks across systems, creating complex chains of execution that are difficult to track. Agent telemetry provides visibility into these interactions, mapping delegation paths and helping teams understand and limit the potential blast radius. Defend against prompt injection and manipulation attacks Attackers can craft prompts to override agent instructions and manipulate behavior. By capturing prompts and reasoning flows, agent telemetry enables detection of these attacks and provides the context needed to investigate and remediate quickly. Accelerate SOC investigations with end-to-end visibility When an agent is involved in a security alert, understanding its actions can be challenging. Agent telemetry correlates prompts, identities, tools, and data access into a unified timeline, giving SOC teams the clarity needed to investigate faster and respond with confidence. Strengthen governance and compliance for AI agents Organizations need visibility into what agents exist and what data they can access. Agent telemetry provides a comprehensive audit trail of agent activity and access patterns, supporting compliance reporting and policy enforcement. Enable proactive threat hunting on agent behavior Security teams need to stay ahead of emerging risks as agent usage grows. Agent telemetry enables advanced hunting across agent activity, helping detect anomalies, uncover patterns, and identify threats before they impact the organization. Get started with Agent 365 connector Getting started is straightforward. In the Microsoft Defender portal, navigate to Microsoft Sentinel Open Content hub and search for Agent 365 Install the Agent 365 Connector (if not already installed) Open the connector page and select Connect to begin ingestion Once connected, AI agent telemetry starts flowing into Sentinel, ready for hunting, investigation, and response. Data ingestion and analytics are billed using existing Sentinel meters. Learn more Find the Agent 365 data connector | Microsoft Learn Discover and manage Sentinel out-of-the-box content | Microsoft Learn Connect data sources to Sentinel by using data connectors | Microsoft Learn Sample KQL queries for Sentinel data lake | Microsoft Learn Watch the Sentinel data lake video playlist | Microsoft Security Get started with Sentinel data lake | Microsoft LearnWhat’s new in Microsoft Sentinel: RSAC 2026
Security is entering a new era, one defined by explosive data growth, increasingly sophisticated threats, and the rise of AI-enabled operations. To keep pace, security teams need an AI-powered approach to collect, reason over, and act on security data at scale. At RSA Conference 2026 (RSAC), we’re unveiling the next wave of Sentinel innovations designed to help organizations move faster, see deeper, and defend smarter with AI-ready tools. These updates include AI-driven playbooks that accelerate SOC automation, Granular Delegated Admin Privileges (GDAP) and granular role-based access controls (RBAC) that let you scale your SOC, accelerated data onboarding through new connectors, and data federation that enables analysis in place without duplication. Together, they give teams greater clarity, control, and speed. Come see us at RSAC to view these innovations in action. Hear from Sentinel leaders during our exclusive Microsoft Pre-Day, then visit Microsoft booth #5744 for demos, theater sessions, and conversations with Sentinel experts. Read on to explore what’s new. See you at RSAC! Sentinel feature innovations: Sentinel SIEM Sentinel data lake Sentinel graph Sentinel MCP Threat Intelligence Microsoft Security Store Sentinel promotions Sentinel SIEM Playbook generator [Now in public preview] The Sentinel playbook generator delivers a new era of automation capabilities. You can vibe code complex automations, integrate with different tools to ensure timely and compliant workflows throughout your SOC and feel confident in the results with built in testing and documentation. Customers and partners are already seeing benefit from this innovation. “The playbook generator gives security engineers the flexibility and speed of AI-assisted coding while delivering the deterministic outcomes that enterprise security operations require. It's the best of both worlds, and it lives natively in Defender where the engineers already work.” – Jaime Guimera Coll | Security and AI Architect | BlueVoyant Learn more about playbook generator. SIEM migration experience [General availability now] The Sentinel SIEM migration experience helps you plan and execute SIEM migrations through a guided, in-product workflow. You can upload Splunk or QRadar exports to generate recommendations for best‑fit Sentinel analytics rules and required data connectors, then assess migration scope, validate detection coverage, and migrate from Splunk or QRadar to Sentinel in phases while tracking progress. “The tool helps turn a Splunk to Sentinel migration into a practical decision process. It gives clear visibility into which detections are relevant, how they align to real security use cases, and where it makes sense to enable or prioritize coverage—especially with cost and data sources in mind.” – Deniz Mutlu | Director | Swiss Post Cybersecurity Ltd Learn more about SIEM migration experience. GDAP, unified RBAC, and row-level RBAC for Sentinel [Public preview, April 1] As Sentinel environments grow for enterprises, MSSPs, hyperscalers, and partners operating across shared or multiple environments, the challenge becomes managing access control efficiently and consistently at scale. Sentinel’s expanded permissions and access capabilities are designed to meet these needs. Granular Delegated Admin Privileges (GDAP) lets you streamline management across multiple governed tenants using your primary account, based on existing GDAP relationships. Unified RBAC allows you to opt in to managing permissions for Sentinel workspaces through a single pane of glass, configuring and enforcing access across Sentinel experiences in the analytics tier and data lake in the Defender portal. This simplifies administration and improves operational efficiency by reducing the number of permission models you need to manage. Row-level RBAC scoping within tables enables precise, scoped access to data in the Sentinel data lake. Multiple SOC teams can operate independently within a shared Sentinel environment, querying only the data they are authorized to see, without separating workspaces or introducing complex data flow changes. Consistent, reusable scope definitions ensure permissions are applied uniformly across tables and experiences, while maintaining strong security boundaries. To learn more, read our technical deep dives on RBAC and GDAP. Sentinel data lake Sentinel data federation [Public preview, April 1] Sentinel data federation lets you analyze security data in place without copying or duplicating your data. Powered by Microsoft Fabric, you can now federate data from Fabric, Azure Data Lake Storage (ADLS), and Azure Databricks into Sentinel data lake. Federated data appears alongside native Sentinel data, so you can use familiar tools like KQL hunting, notebooks, and custom graphs to correlate signals and investigate across your entire digital estate, all while preserving governance and compliance. You can start analyzing data in place and progressively ingest data into Sentinel for deeper security insights, advanced automation, and AI-powered defense at scale. You are billed only when you run analytics on federated data using existing Sentinel data lake query and advanced insights meters. les for unified investigation and hunting Sentinel cost estimation tool [Public Preview, April 9] The new Sentinel cost estimation tool offers all Microsoft customers and partners a guided, meter-level cost estimation experience that makes pricing transparent and predictable. A built-in three-year cost projection lets you model data growth and ramp-up over time, anticipate spend, and avoid surprises. Get transparent estimates into spend as you scale your security operations. All other customers can continue to use the Azure calculator for Sentinel pricing estimates. See the Sentinel pricing page for more information. Sentinel data connectors A365 connector [Public preview, May 5] Bring AI agent telemetry into the Sentinel data lake to investigate agent behavior, tool usage, prompts, reasoning and execution using hunting, graph, and MCP workflows. GitHub audit log connector using API polling [General availability, March 6] Ingest GitHub enterprise audit logs into Sentinel to monitor user and administrator activity, detect risky changes, and investigate security events across your development environment. Google Kubernetes Engine (GKE) connector [General availability, March 6] Collect Google Kubernetes Engine (GKE) audit and workload logs in Sentinel to monitor cluster activity, analyze workload behavior, and detect security threats across Kubernetes environments. Microsoft Entra and Azure Resource Graph (ARG) connector enhancements [Public preview, April 15] Enable new Entra assets (EntraDevices, EntraOrgContacts) and ARG assets (ARGRoleDefinitions) in existing asset connectors, expanding inventory coverage and powering richer, built‑in graph experiences for greater visibility. With over 350 Sentinel data connectors, customers achieve broad visibility into complex digital environments and can expand their security operations effectively. “Microsoft Sentinel data lake forms the core of our agentic SOC. By unifying large volumes of Microsoft and third-party data, enabling graph-based analysis, and supporting MCP-driven workflows, it allows us to investigate faster, at lower cost, and with greater confidence.” – Øyvind Bergerud | Head of Security Operations | Storebrand Learn more about Sentinel data connectors. Sentinel connector builder agent using Sentinel Visual Studio Code extension [Public preview, March 31] Build Sentinel data connectors in minutes instead of weeks using the AI‑assisted Connector Builder agent in Visual Studio Code. This low‑code experience guides developers and ISVs end-to-end, automatically generating schemas, deployment assets, connector UI, secure secret handling, and polling logic. Built‑in validation surfaces issues early, so you can validate event logs before deployment and ingestion. Example prompt in GitHub Copilot Chat: @sentinel-connector-builder Create a new connector for OpenAI audit logs using https://api.openai.com/v1/organization/audit_logs Get started with custom connectors and learn more in our blog. Data filtering and splitting [Public preview, March 30] As security teams ingest more data, the challenge shifts from scale to relevance. With filtering and splitting now built into the Defender portal, teams can shape data before it lands in Sentinel, without switching tools or managing custom JSON files. Define simple KQL‑based transformations directly in the UI to filter low‑value events and intelligently route data, making ingestion optimization faster, more intuitive, and easier to manage at scale. Filtering at ingest time allows you to remove low-value or benign events to reduce noise, cut unnecessary processing, and ensure that high-signal data drives detections and investigations. Splitting enables intelligent routing of data between the analytics tier and the data lake tier based on relevance and usage. Together, these two capabilities help you balance cost and performance while scaling data ingestion sustainably as your digital estate grows. Create workbook reports directly from the data lake [Public preview, April 1] Sentinel workbooks can now directly run on the data lake using KQL, enabling you to visualize and monitor security data straight from the data lake. By selecting the data lake as the workbook data source, you can now create trend analysis and executive reporting. Sentinel graph Custom graphs [Public preview, April 1] Custom graphs let you build tailored security graphs tuned to your unique security scenarios using data from Sentinel data lake as well as non-Microsoft sources. With custom graph, powered by Fabric, you can build, query, and visualize connected data, uncover hidden patterns and attack paths, and help surface risks that are hard to detect when data is analyzed in isolation. These graphs provide the knowledge context that enables AI-powered agent experiences to work more effectively, speeding investigations, revealing blast radius, and helping you move from noisy, disconnected alerts to confident decisions at scale. In the words of our preview customers: “We ingested our Databricks management-plane telemetry into the Sentinel data lake and built a custom security graph. Without writing a single detection rule, the graph surfaced unusual patterns of activity and overprivileged access that we escalated for investigation. We didn't know what we were looking for, the graph surfaced the risk for us by revealing anomalous activity patterns and unusual access combinations driven by relationships, not alerts.” – SVP, Security Solutions | Financial Services organization Custom graph API usage for creating graph and querying graph will be billed starting April 1, 2026, according to the Sentinel graph meter. Creating custom graph Using the Sentinel VS Code extension, you can generate graphs to validate hunting hypotheses, such as understanding attack paths and blast radius of a phishing campaign, reconstructing multi‑step attack chains, and identifying structurally unusual or high‑risk behavior, making it accessible to your team and AI agents. Once persisted via a schedule job, you can access these custom graphs from the ready-to-use section in the graph experience in the Defender portal. Graphs experience in the Microsoft Defender portal After creating your custom graphs, you can access them in the graphs section of the Defender portal under Sentinel. From there, you’ll be able to perform interactive graph-based investigations, such as using a graph built for phishing analysis to help you quickly evaluate the impact of a recent incident, profile the attacker, and trace its paths across Microsoft telemetry and third-party data. The new graph experience lets you run Graph Query Language (GQL) queries, view the graph schema, visualize the graph, view graph results in tabular format, and interactively travers the graph to the next hop with a simple click. Sentinel MCP Sentinel MCP entity analyzer [General availability, April 1] Entity analyzer provides reasoned, out-of-the-box risk assessments that help you quickly understand whether a URL or user identity represents potential malicious activity. The capability analyzes data across modalities including threat intelligence, prevalence, and organizational context to generate clear, explainable verdicts you can trust. Entity analyzer integrates easily with your agents through Sentinel MCP server connections to first-party and third-party AI runtime platforms, or with your SOAR workflows through Logic Apps. The entity analyzer is also a trusted foundation for the Defender Triage Agent and delivers more accurate alert classifications and deeper investigative reasoning. This removes the need to manually engineer evaluation logic and creates trust for analysts and AI agents to act with higher accuracy and confidence. Learn more about entity analyzer and in our blog here. Entity analyzer will be billed starting April 1, 2026, based on Security Compute Units (SCU) consumption. Learn more about MCP billing. Sentinel MCP graph tool collection [Public preview, May 20] Graph tool collection helps you visualize and explore relationships between identities and device assets, threats and activities signals ingested by data connectors and alerted by analytic rules. The tool provides a clear graph view that highlights dependencies and configuration gaps, which makes it easier to understand how content interacts across your environment. This helps security teams assess coverage, optimize content deployment, and identify areas that may need tuning or additional data sources, all from a single, interactive workspace. Executing graph queries via the MCP tools will trigger the graph meter. Claude MCP connector [Public preview, April 1] Anthropic Claude can connect to Sentinel through a custom MCP connector, giving you AI-assisted analysis across your Sentinel environment. Microsoft provides step-by-step guidance for configuring a custom connector in Claude that securely connects to a Sentinel MCP server. With this connection you can summarize incidents, investigate alerts, and reason over security signals while keeping data inside Microsoft's security boundary. Access to large language models (LLMs) is managed through Microsoft authentication and role-based controls, supporting faster triage and investigation workflows while maintaining compliance and visibility. Threat Intelligence CVEs of interest in the Threat Intelligence Briefing Agent [Public preview in April] The Threat Intelligence Briefing Agent delivers curated intelligence based on your organization’s configuration, preferences, and unique industry and geographic needs. CVEs of interest which highlights vulnerabilities actively discussed across the security landscape and assesses their potential impact on your environment, delivering more timely threat intelligence insights. The agent automatically incorporates internet exposure data powered by the Sentinel platform to surface threats targeting technologies exposed in your organization. Together, these enhancements help you focus faster on the threats that matter most, without manual investigation. Microsoft Security Store Security Store embedded in Entra [General availability, March 23] As identity environments grow more complex, teams need to move faster and extend Entra with trusted third‑party capabilities that address operational, compliance, and risk challenges. The Security Store embedded directly into Entra lets you discover and adopt Entra‑ready agents and solutions in your workflow. You can extend Entra with identity‑focused agents that surface privileged access risk, identity posture gaps, network access insights, and overall identity health, turning identity data into clear recommendations and reports teams can use immediately. You can also enhance Entra with Verified ID and External ID integrations that strengthen identity verification, streamline account recovery, and reduce fraud across workforce, consumer, and external identities. Security Store embedded in Microsoft Purview [General availability, March 31] Extending data security across the digital estate requires visibility and enforcement into new data sources and risk surfaces, often requiring a partnered approach. The Security Store embedded directly into Purview lets you discover and evaluate integrated solutions inside your data security workflows. Relevant partner capabilities surface alongside context, making it easier to strengthen data protection, address regulatory requirements, and respond to risk without disrupting existing processes. You can quickly assess which solutions align to data security scenarios, especially with respect to securing AI use, and how they can leverage established classifiers, policies, and investigation workflows in Purview. Keeping integration discovery in‑flow and purchases centralized through the Security Store means you move faster from evaluation to deployment, reducing friction and maintaining a secure, consistent transaction experience. Security Store Advisor [General availability, March 23] Security teams today face growing complexity and choice. Teams often know the security outcome they need, whether that's strengthening identity protection, improving ransomware resilience, or reducing insider risk, but lack a clear, efficient way to determine which solutions will help them get there. Security Store Advisor provides a guided, natural-language discovery experience that shifts security evaluation from product‑centric browsing to outcome‑driven decision‑making. You can describe your goal in plain language, and the Advisor surfaces the most relevant Microsoft and partner agents, solutions, and services available in the Security Store, without requiring deep product knowledge. This approach simplifies discovery, reduces time spent navigating catalogs and documentation, and helps you understand how individual capabilities fit together to deliver meaningful security outcomes. Sentinel promotions Extending signups for promotional 50 GB commitment tier [Through June 2026] The Sentinel promotional 50 GB commitment tier offers small and mid-sized organizations a cost-effective entry point into Sentinel. Sign up for the 50 GB commitment tier until June 30, 2026, and maintain the promotional rate until March 31, 2027. This promotion is available globally with regional variations in pricing and accessible through EA, CSP, and Direct channels. Visit the Sentinel pricing page for details and to get started. Sentinel RSAC 2026 sessions All week – Sentinel product demos, Microsoft Booth #5744 Mon Mar 23, 3:55 PM – RSAC 2026 main stage Keynote with CVP Vasu Jakkal [KEY-M10W] Ambient and autonomous security: Building trust in the agentic AI era Tue Mar 24, 10:30 AM – Live Q&A session, Microsoft booth #5744 and online Ask me anything with Microsoft Security SMEs and real practitioners Tue Mar 24, 11 AM – Sentinel data lake theater session, Microsoft booth #5744 From signals to insights: How Microsoft Sentinel data lake powers modern security operations Tue Mar 24, 2 PM – Sentinel SIEM theater session, Microsoft booth #5744 Vibe-coding SecOps automations with the Sentinel playbook generator Wed Mar 25, 12 PM – Executive event at Palace Hotel with Threat Protection GM Scott Woodgate The AI risk equation: Visibility, control, and threat acceleration Wed Mar 25, 1:30 PM – Sentinel graph theater session, Microsoft booth #5744 Bringing knowledge-driven context to security with Microsoft Sentinel graph Wed Mar 25, 5 PM – MISA theater session, Microsoft booth #5744 Cut SIEM costs without reducing protection: A Sentinel data lake case study Thu Mar 26, 1 PM – Security Store theater session, Microsoft booth #5744 What's next for Security Store: Expanding in portal and smarter discovery All week – 1:1 meetings with Microsoft security experts Meet with Microsoft Defender and Sentinel SIEM and Defender Security Operations Additional resources Sentinel data lake video playlist Explore the full capabilities of Sentinel data lake as a unified, AI-ready security platform that is deeply integrated into the Defender portal Sentinel data lake FAQ blog Get answers to many of the questions we’ve heard from our customers and partners on Sentinel data lake and billing AI‑powered SIEM migration experience ninja training Walk through the SIEM migration experience, see how it maps detections, surfaces connector requirements, and supports phased migration decisions SIEM migration experience documentation Learn how the SIEM migration experience analyzes your exports, maps detections and connectors, and recommends prioritized coverage Accenture collaborates with Microsoft to bring agentic security and business resilience to the front lines of cyber defense Stay connected Check back each month for the latest innovations, updates, and events to ensure you’re getting the most out of Sentinel. We’ll see you in the next edition!RSAC 2026: New Microsoft Sentinel Connectors Announcement
Microsoft Sentinel helps organizations detect, investigate, and respond to security threats across increasingly complex environments. With the rollout of the Microsoft Sentinel data lake in the fall, and the App Assure-backed Sentinel promise that supports it, customers now have access to long-term, cost-effective storage for security telemetry, creating a solid foundation for emerging Agentic AI experiences. Since our last announcement at Ignite 2025, the Microsoft Sentinel connector ecosystem has expanded rapidly, reflecting continued investment from software development partners building for our shared customers. These connectors bring diverse security signals together, enabling correlation at scale and delivering richer investigation context across the Sentinel platform. Below is a snapshot of Microsoft Sentinel connectors newly available or recently enhanced since our last announcement, highlighting the breadth of partner solutions contributing data into, and extending the value of, the Microsoft Sentinel ecosystem. New and notable integrations Acronis Cyber Protect Cloud Acronis Cyber Protect Cloud integrates with Microsoft Sentinel to bring data protection and security telemetry into a centralized SOC view. The connector streams alerts, events, and activity data - spanning backup, endpoint protection, and workload security - into Microsoft Sentinel for correlation with other signals. This integration helps security teams investigate ransomware and data-centric threats more effectively, leverage built-in hunting queries and detection rules, and improve visibility across managed environments without adding operational complexity. Anvilogic Anvilogic integrates with Microsoft Sentinel to help security teams operationalize detection engineering at scale. The connector streams Anvilogic alerts into Microsoft Sentinel, giving SOC analysts centralized visibility into high-fidelity detections and faster context for investigation and triage. By unifying detection workflows, reducing alert noise, and improving prioritization, this integration supports more efficient threat detection and response while helping teams extend coverage across evolving attack techniques. BigID BigID integrates with Microsoft Sentinel to extend data security posture management (DSPM) insights into security operations workflows. The solution brings visibility into sensitive, regulated, and critical data across cloud, SaaS, and on‑premises environments, helping security teams understand where high‑risk data resides and how it may be exposed. By incorporating data‑centric risk context into Sentinel, this integration supports more informed investigation and prioritization, enabling organizations to reduce data‑related risk and align security operations with data protection and compliance objectives. Commvault Cloud Commvault Cloud integrates with Microsoft Sentinel to bring data protection and cyber‑resilience telemetry into security operations workflows. The connector ingests security‑relevant signals from Commvault Cloud—such as backup anomalies, malware and ransomware indicators, and other threat‑related events—into Sentinel, enabling centralized detection, investigation, and automated response. By correlating backup intelligence with broader Sentinel telemetry, this integration helps security teams reduce blind spots, validate the scope of incidents, and improve coordination between security and recovery operations. CyberArk Audit CyberArk Audit integrates with Microsoft Sentinel to centralize visibility into privileged identity and access activity. By streaming detailed audit logs - covering system events, user actions, and administrative activity - into Microsoft Sentinel, security teams can correlate identity-driven risks with broader security telemetry. This integration supports faster investigations, improved monitoring of privileged access, and more effective incident response through automated workflows and enriched context for SOC analysts. Cyera Cyera integrates with Microsoft Sentinel to extend AI-native data security posture management into security operations. The connector brings Cyera’s data context and actionable intelligence across multi-cloud, on-premises, and SaaS environments into Microsoft Sentinel, helping teams understand where sensitive data resides and how it is accessed, exposed, and used. Built on Sentinel’s modern framework, the integration feeds context-rich data risk signals into the Sentinel data lake, enabling more informed threat hunting, automation, and decision-making around data, user, and AI-related risk. TacitRed CrowdStrike IOC Automation Data443 TacitRed CS IOC Automation integrates with Microsoft Sentinel to streamline the operationalization of compromised credential intelligence. The solution uses Sentinel playbooks to automatically push TacitRed indicators of compromise into CrowdStrike via Sentinel playbooks, helping security teams turn identity-based threat intelligence into action. By automating IOC handling and reducing manual effort, this integration supports faster response to credential exposure and strengthens protection against account-driven attacks across the environment. TacitRed SentinelOne IOC Automation Data443 TacitRed SentinelOne IOC Automation integrates with Microsoft Sentinel to help operationalize identity-focused threat intelligence at the endpoint layer. The solution uses Sentinel playbooks to automatically consume TacitRed indicators and push curated indicators into SentinelOne via Sentinel playbooks and API-based enforcement, enabling faster enforcement of high-risk IOCs without manual handling. By automating the flow of compromised credential intelligence from Sentinel into EDR, this integration supports quicker response to identity-driven attacks and improves coordination between threat intelligence and endpoint protection workflows. TacitRed Threat Intelligence Data443 TacitRed Threat Intelligence integrates with Microsoft Sentinel to provide enhanced visibility into identity-based risks, including compromised credentials and high-risk user exposure. The solution ingests curated TacitRed intelligence directly into Sentinel, enriching incidents with context that helps SOC teams identify credential-driven threats earlier in the attack lifecycle. With built-in analytics, workbooks, and hunting queries, this integration supports proactive identity threat detection, faster triage, and more informed response across the SOC. Cyren Threat Intelligence Cyren Threat Intelligence integrates with Microsoft Sentinel to enhance detection of network-based threats using curated IP reputation and malware URL intelligence. The connector ingests Cyren threat feeds into Sentinel using the Codeless Connector Framework (CCF), transforming raw indicators into actionable insights, dashboards, and enriched investigations. By adding context to suspicious traffic and phishing infrastructure, this integration helps SOC teams improve alert accuracy, accelerate triage, and make more confident response decisions across their environments. TacitRed Defender Threat Intelligence Data443 TacitRed Defender Threat Intelligence integrates with Microsoft Sentinel to surface early indicators of credential exposure and identity-driven risk. The solution automatically ingests compromised credential intelligence from TacitRed into Sentinel and can support synchronization of validated indicators with Microsoft Defender Threat Intelligence through Sentinel workflows, helping SOC teams detect account compromise before abuse occurs. By enriching Sentinel incidents with actionable identity context, this integration supports faster triage, proactive remediation, and stronger protection against credential-based attacks. Datawiza Access Proxy (DAP) Datawiza Access Proxy integrates with Microsoft Sentinel to provide centralized visibility into application access and authentication activity. By streaming access and MFA logs from Datawiza into Sentinel, security teams can correlate identity and session-level events with broader security telemetry. This integration supports detection of anomalous access patterns, faster investigation through session traceability, and more effective response using Sentinel automation, helping organizations strengthen Zero Trust controls and meet auditing and compliance requirements. Endace Endace integrates with Microsoft Sentinel to provide deep network visibility by providing always-on, packet-level evidence. The connector enables one-click pivoting from Sentinel alerts directly to recorded packet data captured by EndaceProbes. This helps SOC and NetOps teams reconstruct events and validate threats with confidence. By combining Sentinel’s AI-driven analytics with Endace’s always-on, full-packet capture across on-premises, hybrid, and cloud environments, this integration supports faster investigations, improved forensic accuracy, and more decisive incident response. Feedly Feedly integrates with Microsoft Sentinel to ingest curated threat intelligence directly into security operations workflows. The connector automatically imports Indicators of Compromise (IoCs) from Feedly Team Boards and folders into Sentinel, enriching detections and investigations with context from the original intelligence articles. By bringing analyst‑curated threat intelligence into Sentinel in a structured, automated way, this integration helps security teams stay current on emerging threats and reduce the manual effort required to operationalize external intelligence. Gigamon Gigamon integrates with Microsoft Sentinel through a new connector that provides access to Gigamon Application Metadata Intelligence (AMI), delivering high-fidelity network-derived telemetry with rich application metadata from inspected traffic directly into Sentinel. This added context helps security teams detect suspicious activity, encrypted threats, and lateral movement faster and with greater precision. By enriching analytics without requiring full packet ingestion, organizations can reduce noise, manage SIEM costs, and extend visibility across hybrid cloud infrastructure. Halcyon Halcyon integrates with Microsoft Sentinel to provide purpose-built ransomware detection and automated containment across the Microsoft security ecosystem. The connector surfaces Halcyon ransomware alerts directly within Sentinel, enabling SOC teams to correlate ransomware behavior with Microsoft Defender and broader Microsoft telemetry. By supporting Sentinel analytics and automation workflows, this integration helps organizations detect ransomware earlier, investigate faster using native Sentinel tools, and isolate affected endpoints to prevent lateral spread and reinfection. Illumio The Illumio platform identifies and contains threats across hybrid multi-cloud environments. By integrating AI-driven insights with Microsoft Sentinel and Microsoft Graph, Illumio Insights enables SOC analysts to visualize attack paths, prioritize high-risk activity, and investigate threats with greater precision. Illumio Segmentation secures critical assets, workloads, and devices and then publishes segmentation policy back into Microsoft Sentinel to ensure compliance monitoring. Joe Sandbox Joe Sandbox integrates with Microsoft Sentinel to enrich incidents with dynamic malware and URL analysis. The connector ingests Joe Sandbox threat intelligence and automatically detonates suspicious files and URLs associated with Sentinel incidents, returning behavioral and contextual analysis results directly into investigation workflows. By adding sandbox-driven insights to indicators, alerts, and incident comments, this integration helps SOC teams validate threats faster, reduce false positives, and improve response decisions using deeper visibility into malicious behavior. Keeper Security The Keeper Security integration with Microsoft Sentinel brings advanced password and secrets management telemetry into your SIEM environment. By streaming audit logs and privileged access events from Keeper into Sentinel, security teams gain centralized visibility into credential usage and potential misuse. The connector supports custom queries and automated playbooks, helping organizations accelerate investigations, enforce Zero Trust principles, and strengthen identity security across hybrid environments. Lookout Mobile Threat Defense (MTD) Lookout Mobile Threat Defense integrates with Microsoft Sentinel to extend SOC visibility to mobile endpoints across Android, iOS, and Chrome OS. The connector streams device, threat, and audit telemetry from Lookout into Sentinel, enabling security teams to correlate mobile risk signals such as phishing, malicious apps, and device compromise, with broader enterprise security data. By incorporating mobile threat intelligence into Sentinel analytics, dashboards, and alerts, this integration helps organizations detect mobile driven attacks earlier and strengthen protection for an increasingly mobile workforce. Miro Miro integrates with Microsoft Sentinel to provide centralized visibility into collaboration activity across Miro workspaces. The connector ingests organization-wide audit logs and content activity logs into Sentinel, enabling security teams to monitor authentication events, administrative actions, and content changes alongside other enterprise signals. By bringing Miro collaboration telemetry into Sentinel analytics and dashboards, this integration helps organizations detect suspicious access patterns, support compliance and eDiscovery needs, and maintain stronger oversight of collaborative environments without disrupting productivity. Obsidian Activity Threat The Obsidian Threat and Activity Feed for Microsoft Sentinel delivers deep visibility into SaaS and AI applications, helping security teams detect account compromise and insider threats. By streaming user behavior and configuration data into Sentinel, organizations can correlate application risks with enterprise telemetry for faster investigations. Prebuilt analytics and dashboards enable proactive monitoring, while automated playbooks simplify response workflows, strengthening security posture across critical cloud apps. OneTrust for Purview DSPM OneTrust integrates with Microsoft Sentinel to bring privacy, compliance, and data governance signals into security operations workflows. The connector enriches Sentinel with privacy relevant events and risk indicators from OneTrust, helping organizations detect sensitive data exposure, oversharing, and compliance risks across cloud and non-Microsoft data sources. By unifying privacy intelligence with Sentinel analytics and automation, this integration enables security and privacy teams to respond more quickly to data risk events and support responsible data use and AI-ready governance. Pathlock Pathlock integrates with Microsoft Sentinel to bring SAP-specific threat detection and response signals into centralized security operations. The connector forwards security-relevant SAP events into Sentinel, enabling SOC teams to correlate SAP activity with broader enterprise telemetry and investigate threats using familiar SIEM workflows. By enriching Sentinel with SAP security context and focused detection logic, this integration helps organizations improve visibility into SAP landscapes, reduce noise, and accelerate detection and response for risks affecting critical business systems. Quokka Q-scout Quokka Q-scout integrates with Microsoft Sentinel to centralize mobile application risk intelligence across Microsoft Intune-managed devices. The connector automatically ingests app inventories from Intune, analyzes them using Quokka’s mobile app vetting engines, and streams security, privacy, and compliance risk findings into Sentinel. By surfacing app-level risks through Sentinel analytics and alerts, this integration helps security teams identify malicious or high-risk mobile apps, prioritize remediation, and strengthen mobile security posture without deploying agents or disrupting users. Semperis Lightning Semperis Lightning integrates with Microsoft Sentinel to deliver deep visibility into identity‑centric risk across Active Directory and Microsoft Entra environments. The connector ingests identity security telemetry such as indicators of exposure, Tier 0 assets, and attack path insights into Sentinel, enabling security teams to correlate identity risks with broader security signals. By bringing rich identity context into Sentinel analytics, hunting, and investigations, this integration helps organizations detect, prioritize, and respond to identity‑driven attacks more effectively across hybrid identity infrastructures. Synqly Synqly integrates with Microsoft Sentinel to simplify and scale security integrations through a unified API approach. The connector enables organizations and security vendors to establish a bi‑directional connection with Sentinel without relying on brittle, point‑to‑point integrations. By abstracting common integration challenges such as authentication handling, retries, and schema changes, Synqly helps teams orchestrate security data flows into and out of Sentinel more reliably, supporting faster onboarding of new data sources and more maintainable integrations at scale. Versasec vSEC:CMS Versasec vSEC:CMS integrates with Microsoft Sentinel to provide centralized visibility into credential lifecycle and system health events. The connector securely streams vSEC:CMS and vSEC:CLOUD alerts and status data into Sentinel using the Codeless Connector Framework (CCF), transforming credential management activity into correlation-ready security signals. By bringing smart card, token, and passkey management telemetry into Sentinel, this integration helps security teams monitor authentication infrastructure health, investigate credential-related incidents, and unify identity security operations within their SIEM workflows. VirtualMetric DataStream VirtualMetric DataStream integrates with Microsoft Sentinel to optimize how security telemetry is collected, normalized, and routed across the Microsoft security ecosystem. Acting as a high-performance telemetry pipeline, DataStream intelligently filters and enriches logs, sending high-value security data to Sentinel while routing less-critical data to Sentinel data lake or Azure Blob Storage for cost-effective retention. By reducing noise upstream and standardizing logs to Sentinel ready schemas, this integration helps organizations control ingestion costs, improve detection quality, and streamline threat hunting and compliance workflows. VMRay VMRay integrates with Microsoft Sentinel to enrich SIEM and SOAR workflows with automated sandbox analysis and high-fidelity, behavior-based threat intelligence. The connector enables suspicious files and phishing URLs to be submitted directly from Sentinel to VMRay for dynamic analysis, while validated, high-confidence indicators of compromise (IOCs) are streamed back into Sentinel’s Threat Intelligence repository for correlation and detection. By adding detailed attack-chain visibility and enriched incident context, this integration helps SOC teams reduce investigation time, improve detection accuracy, and strengthen automated response workflows across Sentinel environments. XBOW XBOW integrates with Microsoft Sentinel to bring autonomous penetration testing insights directly into security operations workflows. The connector ingests automated penetration test findings from the XBOW platform into Sentinel, enabling security teams to analyze validated exploit activity alongside alerts, incidents, and other security telemetry. By correlating offensive testing results with Sentinel detections, this integration helps organizations identify monitoring gaps, validate detection coverage, and strengthen defensive controls using real‑world, continuously generated attack evidence. Zero Networks Segment Audit Zero Networks Segment integrates with Microsoft Sentinel to provide visibility into micro-segmentation and access-control activity across the network. The connector can collect audit logs or activities from Zero Networks Segment, enabling security teams to monitor policy changes, administrative actions, and access events related to MFA-based network segmentation. By bringing segmentation audit telemetry into Sentinel, this integration supports compliance monitoring, investigation of suspicious changes, and faster detection of attempts to bypass lateral-movement controls within enterprise environments. Zscaler Internet Access (ZIA) Zscaler Internet Access integrates with Microsoft Sentinel to centralize cloud security telemetry from web and firewall traffic. The connector enables ZIA logs to be ingested into Sentinel, allowing security teams to correlate Zscaler Internet Access signals with other enterprise data for improved threat detection, investigation, and response. By bringing ZIA web, firewall, and security events into Sentinel analytics and hunting workflows, this integration helps organizations gain broader visibility into internet-based threats and strengthen Zero Trust security operations. In addition to these solutions from our third-party partners, we are also excited to announce the following connector published by the Microsoft Sentinel team: GitHub Enterprise Audit Logs Microsoft’s Sentinel Promise For Customers Every connector in the Microsoft Sentinel ecosystem is built to work out of the box. In the unlikely event a customer encounters any issue with a connector, the App Assure team stands ready to assist. For Software Developers Software partners in need of assistance in creating or updating a Sentinel solution can also leverage Microsoft’s Sentinel Promise to support our shared customers. For developers seeking to build agentic experiences utilizing Sentinel data lake, we are excited to announce the launch of our Sentinel Advisory Service to guide developers across their Sentinel journey. Customers and developers alike can reach out to us via our intake form. Learn More Microsoft Sentinel data lake Microsoft Sentinel data lake: Unify signals, cut costs, and power agentic AI Introducing Microsoft Sentinel data lake What is Microsoft Sentinel data lake Unlocking Developer Innovation with Microsoft Sentinel data lake Microsoft Sentinel Codeless Connector Framework (CCF) Create a codeless connector for Microsoft Sentinel Public Preview Announcement: Microsoft Sentinel CCF Push What’s New in Microsoft Sentinel Monthly Blog Microsoft App Assure App Assure home page App Assure services App Assure blog App Assure Request Assistance Form App Assure Sentinel Advisory Services announcement App Assure’s promise: Migrate to Sentinel with confidence App Assure’s Sentinel promise now extends to Microsoft Sentinel data lake Ignite 2025 new Microsoft Sentinel connectors announcement Microsoft Security Microsoft’s Secure Future Initiative Microsoft Unified SecOps Editor's Note - April 7th, 2026: This blog was updated to include connector descriptions for BigID, Commvault, Semperis, and XBOW.Agentic Use Cases for Developers on the Microsoft Sentinel Platform
Interested in building an agent with Sentinel platform solutions but not sure where to start? This blog will help you understand some common use cases for agent development that we’ve seen across our partner ecosystem. SOC teams don’t need more alerts - they need fast, repeatable investigation and response workflows. Security Copilot agents can help orchestrate the steps analysts perform by correlating across the Sentinel data lake, executing targeted KQL queries, fetching related entities, enriching with context, and producing an evidence-backed decision without forcing analysts to switch tools. Microsoft Sentinel platform is a strong foundation for agentic experiences because it exposes a normalized security data layer, an investigation surface based on incidents and entities, and extensive automation capabilities. An agent can use these primitives to correlate identity, endpoint, cloud, and network telemetry; traverse entity relationships; and recommend remediation actions. In this blog, I will break down common agentic use cases that developers can implement on Sentinel platform, framed in buildable and repeatable patterns: Identify the investigation scenario Understand the required Sentinel data connectors and KQL queries Build enrichment and correlation logic Summarize findings with supporting evidence and recommended remediation steps Use Case 1: Identity & Access Intelligence Investigation Scenario: Is this risky sign-in part of an attack path? Signals Correlated: Identity access telemetry: Source user, IPs, target resources, MFA logs Authentication outcomes and diversity: Success vs. failure, Geographic spread Identity risk posture: User risk level/state Post-auth endpoint execution: Suspicious LOLBins Correlation Logic: An analyst receives a risky sign-in signal for a user and needs to determine whether the activity reflects expected behavior - such as travel, remote access, or MFA friction - or if it signals the early stage of an identity compromise that could escalate into privileged access and downstream workload impact. Practical Example: Silverfort Identity Threat Triage Agent, which is built on a similar framework, takes the user’s UPN as input and builds a bounded, last-24-hour investigation across authentication activity, MFA logs, user risk posture, and post-authentication endpoint behavior. Outcome: By correlating identity risk signals, MFA logs, sign-in success and failure patterns, and suspicious execution activity following authentication, the agent connects the initial risky sign-in to endpoint behavior, enabling the analyst to quickly assess compromise likelihood, identify escalation indicators, and determine appropriate remediation actions. “Our collaboration with Microsoft Sentinel and Security Copilot underscores the central role identity plays across every stage of attack path triage. By integrating Silverfort’s identity risk signals with Microsoft Entra ID and Defender for Endpoint, and sharing rich telemetry across platforms, we enable Security Copilot Agent to distinguish isolated anomalies from true identity-driven intrusions - while dramatically reducing the manual effort traditionally required for incident response and threat hunting. AI-driven agents accelerate analysis, enrich investigative context, reduce dwell time, and speed detection. Instead of relying on complex queries or deep familiarity with underlying data structures, security teams can now perform seamless, identity-centric reasoning within a single interaction.” - Frank Gasparovic, Director of Solution Architecture, Technology Alliances, Silverfort Use Case 2: Cyber Resilience, Backup & Recovery Investigation Scenario: Are the threats detected on a backup indicative of production impact and recovery risk? Signals Correlated: Backup threat telemetry: Backup threat scan alerts, risk analysis events, affected host/workload, detection timestamps Cross-vendor security alerts: Endpoint, network, and cloud security alerts for the same host/workload in the same time window Correlation Logic: The agent correlates threat signals originating from the backup environment with security telemetry associated with same host/workload to validate whether there is corroborating evidence in the production environment and whether activity aligns in time. Practical Example: Commvault Security Investigation Agent, which is built on a similar framework, takes a hostname as input and builds an investigation across Commvault Threat Scan / Risk Analysis events and third-party security telemetry. By correlating backup-originating detections with production security activity for the same host, the agent determines whether the backup threat signal aligns with observable production impact. Outcome: By correlating backup threat detections with endpoint, network, and cloud security telemetry while validating timing alignment, event spikes, and data coverage, the agent connects a backup originating threat signal to production evidence, enabling the analyst to quickly assess impact likelihood and determine appropriate actions such as containment or recovery-point validation. Use Case 3: Network, Exposure & Connectivity Investigation Scenario: Is this activity indicative of legitimate remote access, or does it demonstrate suspicious connectivity and access attempts that increase risk to private applications and internal resources. Signals Correlated: User access telemetry: Source user, source IPs/geo, device/context, destinations Auth and enforcement outcomes: Success vs. failure, MFA allow/block Behavior drift: new/rare IPs/locations, unusual destination/app diversity. Suspicious activity indicators: Risky URLs/categories, known-bad indicators, automated/bot-like patterns, repeated denied private app access attempts Correlation Logic: An analyst receives an alert for a specific user and needs to determine whether the activity reflects expected behavior such as travel, remote work, or VPN usage, or whether it signals the early stages of a compromise that could later extend into private application access. Practical Example: Zscaler ZIA ZPA Correlation Agent starts with a username and builds a bounded, last-24-hour investigation across Zscaler Internet Access and Zscaler Private Access activity. By correlating user internet behavior, access context, and private application interactions, the agent connects the initial Zscaler alert to any downstream access attempts or authentication anomalies, enabling the analyst to quickly assess risk, identify suspicious patterns, and determine whether Zscaler policy adjustments are required. Outcome: Provides a last‑24‑hour verdict on whether the activity reflects expected access patterns or escalation toward private application access, and recommends next actions—such as closing as benign drift, escalating for containment, or tuning access policy—based on correlated evidence. Use Case 4: Endpoint & Runtime Intelligence Investigation Scenario: Is this process malicious or a legitimate admin action? Signals Correlated: Execution context: Process chain, full command line, signer, unusual path Account & logon: Initiating user, logon type (RDP/service), recent risky sign-ins Tooling & TTPs: LOLBins, credential access hints, lateral movement tooling Network behavior: Suspicious connections, repeated callbacks/beaconing Correlation Logic: A PowerShell alert triggers on a production server. The agent ties the process to its parent (e.g., spawned by a web worker vs. an admin shell), validates the command-line indicators, correlates outbound connections from the same PID to a first-seen destination, and checks for immediate follow-on persistence and any adjacent runtime alerts in the same time window. Outcome: Classifies the activity as malicious vs. admin and produces an evidence pack (process tree, key command indicators, destinations, persistence/tamper artifacts) as well as the recommended containment step (isolate host and revoke/reset initiating credentials). Use Case 5: Exposure & Exploitability Investigation Scenario: What is the likelihood of exploitation and blast radius? Signals Correlated: Asset exposure: Internet-facing status, exposed services/ports, and identity or network paths required to reach the workload Exploit activity: Defender alerts on the resource, IDS/WAF hits, IOC matches, and first seen exploit or probing attempts Risk amplification signals: Internet communication, high privilege access paths, and indicators that the workload processes PII or sensitive data Blast radius: Downstream reachability to crown jewel systems (e.g., databases, key vaults) and trust relationships that could enable escalation Correlation Logic: An analyst receives a Medium/High Microsoft Defender for Cloud alert on a workload and needs to determine whether it’s a standalone detection or an exploitable exposure that can quickly progress into privilege abuse and data impact. The agent correlates exposure evidence signals such as internet reachability, high-privilege paths, and indicators that workload handles sensitive data by analyzing suspicious network connections in the same bounded time window. Outcome: Produces a resource-specific risk analysis that explains why the Defender for Cloud alert is likely to be exploited, based on asset attack surface and effective privileges, plus any supporting activity in the same 24-hour window. Use Case 6: Threat Intelligence & Adversary Context Investigation Scenario: Is this activity aligned with known attacker behavior? Signals Correlated: Behavior sequence: ordered events identity → execution → network. Technique mapping: MITRE ATT&CK technique IDs, typical progression, and required prerequisites. Threat intel match: campaign/adversary, TTPs, IOCs Correlation Logic: A chain of identity compromise, PowerShell obfuscation, and periodic outbound HTTPS is observed. The agent maps the sequence to ATT&CK techniques and correlates it with threat intel that matches a known adversary campaign. Outcome: Surfaces adversary-aligned behavioral insights and TTP context to help analysts assess intrusion likelihood and guide the next investigation steps. Summary This blog is intended to help developers better understand the key use cases for building agents with Microsoft Sentinel platform along with practical patterns to apply when designing and implementing agent scenarios. Need help? If you have any issues as you work to develop your agent, the App Assure team is available to assist via our Sentinel Advisory Service. Reach out via our intake form. Resources Learn more: For a practical overview of how ISVs can move from Sentinel data lake onboarding to building agents, see the Accelerate Agent Development blog - https://aka.ms/AppAssure_AccelerateAgentDev. Get hands-on: Explore the end-to-end journey from Sentinel data lake onboarding to a working Security Copilot agent through the accompanying lab modules available on GitHub Repo: https://github.com/suchandanreddy/Microsoft-Sentinel-Labs.Extending App Assure’s Sentinel Promise through the Sentinel Advisory Service
At RSAC last year, we introduced the Microsoft Sentinel Promise with a straightforward commitment to our customers: that third-party data ingestion for Sentinel is reliable, predictable, and scalable without the need for complex custom coding and architecting. In other words, your connectors for Sentinel will just work. That promise has guided App Assure’s work ever since, enabling customers to bring data from across their various security solutions into Sentinel to drive clearer insights and stronger protection. Over the past year, that foundation has proven critical. As organizations move from legacy SIEM platforms to Sentinel, consistent access to high-quality third-party data remains essential, not only for detection and response, but increasingly for advanced analytics and AI-driven security experiences. With the introduction of Microsoft Sentinel data lake, customers and partners can now reason over security data cost-effectively and at greater scale. But as many teams are discovering, unlocking those outcomes requires more than simply getting data in the door. At App Assure, we’ve seen a clear pattern emerge. Software companies often revisit connector design and data modeling multiple times as they help our mutual customers move from ingestion to analytics, and then again as they begin building agentic AI solutions, whether through Security Copilot, MCP server integrations, or custom workflows. Each iteration brings new requirements and new questions, often upstream of where teams initially started. That’s why, as an extension of our Sentinel Promise, we’re excited to announce the Sentinel Advisory Service from App Assure. A Natural Evolution The Sentinel Advisory Service builds directly on the work we’ve been doing through the Sentinel Promise and our support for Sentinel data lake. Our commitment to helping customers bring third-party data into the platform remains unchanged. What this new service adds is an expert-guided approach focused on helping software companies design customer solutions and data strategies with downstream outcomes in mind. Rather than addressing ingestion challenges in isolation, the Sentinel Advisory Service is designed to help teams think end-to-end across the Sentinel platform: aligning connector design, data structure, and platform capabilities to support advanced scenarios such as AI agents, analytics jobs, and marketplace-ready solutions. The goal is fewer rebuild cycles, faster progress, and greater confidence as teams move from data ingestion to meaningful security outcomes. What Sentinel Advisory Service Offers The Sentinel Advisory Service is a no-cost program delivered by App Assure in close collaboration with Sentinel engineering to continually make it easier to build and maintain connectors that utilize data lake and facilitate building agentic AI solutions on top of it. Key areas of support include: Technical workshops covering best practices for Sentinel integrations, data lake usage, and agent development Advisory guidance on leveraging Sentinel platform features to support AI-driven security scenarios Code samples and design reviews to unblock development and improve solution quality Break/fix assistance and escalation paths to Microsoft engineers to assist with software development and provide product feedback Early Partner Momentum We’re already seeing strong momentum from software companies participating in early advisory engagements. Partners are working with App Assure to refine Sentinel integrations and explore new agentic AI scenarios built on a solid data foundation. Their work reflects a broader shift across the ecosystem: moving beyond connectivity alone, toward building differentiated, outcome-driven security solutions on Sentinel. Below are some of the partners we’ve already worked with and what they have to say about the experience: Srinivas Chakravarty, VP of Cloud & AI Ecosystem, Gigamon “Through active collaboration with Microsoft Security Engineering and the App Assure team, we quickly created and published our CCF-Push connector to deliver enriched network-derived telemetry from the Gigamon Deep Observability Pipeline into Sentinel data lake. In a parallel sprint, with the introduction of our initial Security Copilot Agent, security teams can apply AI to this network intelligence within Sentinel to uncover threats hidden in encrypted and lateral traffic that might otherwise go undetected.” Mario Espinoza, Chief Product Officer, Illumio "Illumio is proud to partner with Microsoft, proving together that cybersecurity can scale. Microsoft's product management teams collaborated closely with Illumio on several integrations, most recently Illumio Insights Agent for Security Copilot and Illumio for Microsoft Sentinel Data Lake Connector. Together, Illumio and Sentinel solutions empower customers to correlate joint security threat findings and ensure breaches don't become disasters." Duncan Barnes, Director Global Alliances, RSA "The partnership between RSA and Microsoft, exemplified by the RSA Advisor for Admin Threats agent, underscores the value of the Sentinel Advisory Service. It highlights how collaborative innovation drives differentiated, outcome-driven security solutions, ensuring customers can migrate with confidence and harness the full potential of agentic AI to find, prioritize, and resolve threats faster and more efficiently." Vlad Sushitsky, Research Engineer, Semperis “We developed a Security Copilot agent that correlates Tier-0 classifications, identity attack paths, and Indicators of Exposure for any given identity. The correlation is powered by Semperis Lightning telemetry, streamed into the Data Lake through our new data connector. What used to take analysts hours of manually pivoting across multiple tables to piece together an identity's risk profile now happens instantly in a single conversation. This gives our joint customers significantly better visibility into identity threats, faster investigations, and substantial cost savings. Developing the agent on Security Copilot was smooth and fast — thanks to great collaboration with the Microsoft team, we had it up and running in a matter of days.” Harman Kaur, SVP Technology Strategy and AI, Tanium "This partnership with Microsoft represents a new level of AI and security integration. Through the Microsoft Sentinel Advisory Service, Tanium integrated AI agents into Microsoft Security Copilot, including the recently launched Tanium Security Triage Agent with Identity Insights. By unifying Tanium’s real-time endpoint intelligence with identity information from the Microsoft Sentinel data lake and Entra ID, security analysts gain the speed, precision and confidence needed to stop threats before they escalate." Ariel Negrin, Worldwide Head of Partnerships and Alliances, Upwind "Through the Sentinel Advisory Service and the broader App Assure engineering teams, Microsoft has been side‑by‑side with us, from connector and data model design to advanced AI scenarios, helping us architect for high‑quality ingestion, graph‑aware context, and AI security use cases. That level of hands‑on guidance and roadmap alignment means our joint customers get faster time to value, fewer integration rebuilds, and a more intelligent security experience built on top of the Microsoft security stack they already trust." Matthew Payne, Field Engineer, XBOW "The team worked alongside us from the start, not just on ingestion, but on designing how XBOW's penetration testing data should flow into Sentinel to actually drive downstream outcomes. Their engineering guidance helped us build agents for Security Copilot and a Sentinel data connector that turns validated exploit paths into actionable security telemetry. The result is that joint customers can trigger a pentest, see real findings in Sentinel alongside their existing alerts, and investigate and remediate without leaving the Microsoft security console." Paul Lopez, Principal Solutions Architect, Zscaler "Organizations looking to improve visibility across internet and private access activities benefit from integrating these signals. Through collaboration with Microsoft’s App Assure team, Zscaler’s ZIA–ZPA Correlation Agent for Security Copilot leverages data from the Sentinel Data Lake to deliver a single, cohesive view, simplifying investigations and enabling faster response times." Getting Started The Sentinel Advisory Service is available today for developers building on Microsoft Sentinel and Sentinel data lake. If you’re enhancing an existing connector, designing an AI-driven security solution, or planning how to translate data into action on the Sentinel platform, App Assure is here to help. As always, our focus remains on customer confidence, ensuring that as Sentinel evolves, the ecosystem around it can evolve just as reliably. The Sentinel Advisory Service is the next step in delivering on that promise. Reach out to us here.
