Making Azure the Best Place to Observe Your Apps with OpenTelemetry
Our goal is to make Azure the most observable cloud. To that end, we are refactoring Azure’s native observability platform to be based on OpenTelemetry, an industry standard for instrumenting applications and transmitting telemetry.Running natural language queries against Log analytics using Semantic function
Unlocking the Power of Log Analytics: Run Natural Language Queries with Semantic Functions! In this blog, we will walk through the process of creating a semantic function-based solution that can accept a string like "please share all sign-in locations?" and generate a KQL (Kusto Query Language) query. This query will be used to retrieve log analytics data from the signin table.Announcing the Public Preview of Code Optimizations
Code Optimizations: A New AI-Based Service for .NET Performance Optimization We are thrilled to announce that Code Optimizations (previously known as Optimization Insights) is now available in public preview! This new AI-based service can identify performance issues and offer recommendations specifically tailored for .NET applications and cloud services. What is Code Optimizations? Code Optimizations is a service within Application Insights that continuously analyzes profiler traces from your application or cloud service and provides insights and recommendations on how to improve its performance. Code Optimizations can help you identify and solve a wide range of performance issues, ranging from incorrect API usages and unnecessary allocations all the way to issues relating to exceptions and concurrency. It can also detect anomalies whenever your application or cloud service exhibits abnormal CPU or Memory behavior. Why should I use Code Optimizations? Code Optimizations can help you optimize the performance of your .NET applications and cloud services by: Saving you time and effort: Instead of manually sifting through gigabytes of profiler data or relying on trial-and-error methods, you can use Code Optimizations to automatically uncover complex performance bugs and get guidance on how to solve them. Improving your user experience: By improving the speed and reliability of your application or cloud service, you can enhance your user satisfaction and retention rates. This can also help you gain a competitive edge over other apps or services in your market. Saving you money: By fixing performance issues early and efficiently, you can reduce the need for scaling out cloud resources or paying for unnecessary compute power. This can help you avoid problems such as cloud sprawling or overspending on your Azure bill. How does Code Optimizations work? Code Optimizations relies on an AI model trained on thousands of traces collected from Microsoft-owned services around the globe. By learning from these traces, the model can glean patterns corresponding to various performance issues seen in .NET applications and learn from the expertise of performance engineers at Microsoft. This enables our AI model to pinpoint with accuracy a wide range of performance issues in your app and provide you with actionable recommendations on how to fix them. Code Optimizations runs at no additional cost to you and is completely offline to the app. It has no impact on your app’s performance. How can I use Code Optimizations? If you are interested in trying out this new service for free during its public preview period, you can access it using the following steps: Sign up for Application Insights if you haven't already. Application Insights is a powerful application performance monitoring (APM) tool that helps you monitor, diagnose, and troubleshoot your apps. Enable profiling for your .NET app or cloud service. Profiling collects detailed information about how your app executes at runtime. Navigate to the Application Insights Performance blade from the left navigation pane under Investigate and select Code Optimizations from the top menu. Click here for the documentation. Click here for information on troubleshooting. Click here for videos on how to set up and use Code Optimizations. Fill out this quick survey if you have any additional issues or questions.How to leverage Azure Monitor to meet functional and non-functional requirements - No.1 overview
Azure Monitor can be used for centralized monitoring and analysis of log data by using Kusto query, thus Azure Monitor allows you to effectively monitor and visualize Azure resources. Azure Arc also empowers Azure Monitor to expand its capability to on-premise and other public clouds. You can monitor every resources across environments, Azure, AWS, GCP, OCI, on-premise and others, with Azure Monitor and Azure Arc, then Azure Monitor minimize your effort to manage all the resources regardless locations or environments. Azure Monitor is a very powerful solution, but customers and partners sometimes have a challenge to map Azure Monitor features to their functional and non-functional requirements. These series articles describe how to use various Azure Monitor features in terms of functional and non-functional requirements. This article answers how to meet the requirements by using Azure Monitor.Identify and solve performance issues faster with App Insights Code Optimizations
The integration of Code Optimizations with Microsoft Copilot for Azure and GitHub Copilot enables seamless integration between operations teams identifying performance bottlenecks in running .NET applications on Azure, and developers remediating them faster on code level in Visual Studio Code.Application Insights Java Profiler April 2023 - Public Preview Update
In October 2022, Microsoft announced the Public Preview feature of the Java Profiler feature. This Java Profiler feature allows Java developers and service owners to gather JDK Flight Recorder (JFR) recordings. A JFR recording is created and stored by Application Insights when the application breaches a user-defined SLA. The recording is then ready for end users to download and inspect using tools like JDK Mission Control. Since the Public Preview launch of the Java Profiler feature, we have added some additional functionality to enhance the end-user experience. Java Profiling feature is enabled by default within the agent. New profiling triggers based on Open Telemetry Spans. Improvements to the discoverability of JFR recordings.
Announcing the Public Preview of Azure Monitor health models
Troubleshooting modern cloud-native workloads has become increasingly complex. As applications scale across distributed services and regions, pinpointing the root cause of performance degradation or outages often requires navigating a maze of disconnected signals, metrics, and alerts. This fragmented experience slows down troubleshooting and burdens engineering teams with manual correlation work. We address these challenges by introducing a unified, intelligent concept of workload health that’s enriched with application context. Health models streamline how you monitor, assess, and respond to issues affecting your workloads. Built on Azure service groups, they provide an out-of-the-box model tailored to your environment, consolidate signals to reduce alert noise, and surface actionable insights — all designed to accelerate detection, diagnosis, and resolution across your Azure landscape. Overview Azure Monitor health models enable customers to monitor the health of their applications with ease and confidence. These models use the Azure-wide workload concept of service groups to infer the scope of workloads and provide out-of-the-box health criteria based on platform metrics for Azure resources. Key Capabilities Out-of-the-Box Health Model Customers often struggle with defining and monitoring the health of their workloads due to the variability of metrics across different Azure resources. Azure Monitor health models provide a simplified out-of-the-box health experience built using Azure service group membership. Customers can define the scope of their workload using service groups and receive default health criteria based on platform metrics. This includes recommended alert rules for various Azure resources, ensuring comprehensive monitoring coverage. Improved Detection of Workload Issues Isolating the root cause of workload issues can be time-consuming and challenging, especially when dealing with multiple signals from various resources. The health model aggregates health signals across the model to generate a single health notification, helping customers isolate the type of signal that became unhealthy. This enables quick identification of whether the issue is related to backend services or user-centric signals. Quick Impact Assessment Assessing the impact of workload issues across different regions and resources can be complex and slow, leading to delayed responses and prolonged downtime. The health model provides insights into which Azure resources or components have become unhealthy, which regions are affected, and the duration of the impact based on health history. This allows customers to quickly assess the scope and severity of issues within the workload. Localize the Issue Identifying the specific signals and resources that triggered a health state change can be difficult, leading to inefficient troubleshooting and resolution processes. Health models inform customers which signals triggered the health state change, and which service group members were affected. This enables quick isolation of the trouble source and notifies the relevant team, streamlining the troubleshooting process. Customizable Health Criteria for Bespoke Workloads Many organizations operate complex, bespoke workloads that require their own specific health definitions. Relying solely on default platform metrics can lead to blind spots or false positives, making it difficult to accurately assess the true health of these custom applications. Azure Monitor health models allow customers to tailor health assessments by adding custom health signals. These signals can be sourced from Azure Monitor data such as Application Insights, Managed Prometheus, and Log Analytics. This flexibility empowers teams to tune the health model to reflect the unique characteristics and performance indicators of their workloads, ensuring more precise and actionable health insights. Getting Started Ready to simplify and accelerate how you monitor the health of your workloads? Getting started with Azure Monitor health models is easy — and during the public preview, it’s completely free to use. Pricing details will be shared ahead of general availability (GA), so you can plan with confidence. Start Monitoring in Minutes Define Your Service Group Create your service group and add the relevant resources as members to the service group. If you don’t yet have access to service groups, you can join here. Create Your Health Model In the Azure Portal navigate to Health Models and create your first model. You’ll get out-of-the-box health criteria automatically applied. Customize to Fit Your Needs In many cases the default health signals may suit your needs, but we support customization as well. Investigate and Act Use the health timeline and our alerting integration to quickly assess impact, isolate issues, and take action — all from a single pane of glass. You can access health models today in the Azure portal! For more details on how to get started with health models, please refer to our documentation. We Want to Hear From You Azure Monitor health models are built with our customers in mind — and your feedback is essential to shaping the future of this experience. Whether you're using the out-of-the-box health model or customizing it to fit your unique workloads, we want to know what’s working well and where we can improve. Share Your Feedback Use the “Give Feedback” feature directly within the Azure Monitor health models experience to send us your thoughts in context. Post your ideas in the Azure Monitor community. Prefer email? Reach out to us at azmonhealthmodels@service.microsoft.com — we’re listening. Your insights help us prioritize features, improve usability, and ensure Azure Monitor continues to meet the evolving needs of modern cloud-native operations.
