Customers running mission-critical Oracle workloads on Azure want more than database infrastructure in an Azure datacenter. They want their Oracle environments to fit naturally into the way their teams already build, govern, monitor, and purchase services on Azure.
Today, Oracle AI Database@Azure takes another step in that direction with a native Azure experience for Oracle GoldenGate. Customers can provision and manage GoldenGate resources through the Azure portal and APIs, configure connections across databases, clouds, streaming platforms, and Microsoft Fabric, and bring GoldenGate metrics and operational logs into Azure Monitor and Azure Log Analytics.
Together, these capabilities reduce the boundaries between Oracle data replication and the Azure applications, analytics services, operational tools, and governance processes that surround it.
Oracle GoldenGate as a native Azure experience
Oracle GoldenGate helps enterprises keep operational systems, analytics platforms, and AI workloads synchronized through real-time data replication. The native Azure experience brings GoldenGate provisioning, resource management, connectivity, automation, governance, and observability into the Oracle AI Database@Azure environment.
Customers can create, list, pair, manage, and delete GoldenGate deployments and connections through the Azure portal and incorporate the same lifecycle operations into automated workflows through APIs. Resources are discoverable from the Oracle AI Database@Azure overview and through Microsoft Marketplace search. Because these objects participate in the Azure control plane, teams can apply familiar Azure capabilities such as role-based access control, tags, sizing choices, and Activity Log auditing across the GoldenGate lifecycle.
Provisioning is handled through the Azure experience, while administrators can open the GoldenGate console for detailed replication configuration after deployment. This approach keeps resource deployment, ownership, automation, governance, and auditability in Azure while preserving the specialized GoldenGate experience for configuring replication processes.
Connect Oracle data to the platforms where teams use it
The native Azure experience also reflects the breadth of systems that GoldenGate can connect. Customers can configure connections for Oracle Database, Oracle Exadata, OCI Autonomous Database, and Amazon RDS for Oracle, along with Exadata and Autonomous Database services running across Azure, Google Cloud, and AWS.
For streaming scenarios, supported connection options include Azure Event Hubs, Apache Kafka, Confluent Kafka, Microsoft Fabric Eventstream, and OCI Streaming. GoldenGate can also synchronize Oracle data with Microsoft Fabric destinations including Fabric Lakehouse and Fabric Mirror expediting your ongoing journey of AI solutioning to build Data agents in Fabric more seamlessly.
These connection options make GoldenGate a practical bridge between operational Oracle data and the analytics, streaming, and AI services that depend on continuously updated information.
Observe GoldenGate with Azure Monitor and Log Analytics
Provisioning GoldenGate in Azure is only part of the operational experience. As replication environments grow, teams also need a consistent way to monitor service health, identify lag, and investigate operational changes alongside the rest of their Azure estate.
Oracle GoldenGate deployment metrics and operational logs are now generally available in Azure Monitor and Azure Log Analytics for Oracle AI Database@Azure customers. Teams can monitor replication health, create alerts, analyze lifecycle events, and correlate GoldenGate telemetry with Azure applications and infrastructure using the Azure tools they already rely on.
Metrics for health, resource use, lag, and process status
Azure Monitor provides 18 GoldenGate metrics organized around three operational needs. Deployment health and resource metrics cover CPU, memory, OCPU consumption, file system usage, temporary space, swap space, and overall deployment health.
Replication-lag metrics provide visibility across the deployment and its components, including inbound and outbound deployment lag, Extract and Replicat lag, distribution and receiver path lag, and heartbeat lag. Status metrics show the state of Extract, Replicat, distribution paths, and receiver paths.
Teams can use these signals in Azure alerts, dashboards, workbooks, and queries, helping them spot replication delays or unavailable processes before those issues affect downstream applications and data consumers.
Operational events in Azure Log Analytics
GoldenGate lifecycle and operational events can also be sent to an Azure Log Analytics workspace through diagnostic settings. The release includes event categories for deployment updates, deletions, restore workflows, maintenance activity, critical service conditions, and informational state transitions.
Bringing both metrics and operational events into Azure gives operations teams a more complete view. They can see when behavior changed, review the lifecycle or maintenance activity around that change, and correlate the result with signals from Azure applications and infrastructure.
A more connected Oracle and Azure experience
The native GoldenGate experience brings provisioning, API-driven lifecycle management, connectivity, governance, metrics, and operational logs together as part of Oracle AI Database@Azure. Customers can manage replication resources through Azure, connect Oracle data to the services and platforms where teams use it, and incorporate GoldenGate telemetry into day-to-day Azure operations.
The result is less operational friction for customers building applications, data platforms, analytics, and AI solutions around Oracle databases on Azure. Oracle AI Database@Azure continues to evolve as an experience that is managed, governed, automated, and observed through the Azure tools customers already use.
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Microsoft