})
+
+[Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/overview) is a fully managed platform that provides access to advanced generative AI models from OpenAI, such as GPT, Codex, and Embeddings, within Azure’s secure, enterprise-grade environment. It integrates seamlessly with Azure services like Cognitive Search, Machine Learning, and Logic Apps, as well as with external applications and data sources, enabling powerful capabilities in natural language processing, code generation, and reasoning. The platform also supports monitoring of key performance metrics, including request volume, token usage, response latency, and error rates, to ensure efficient model utilization and reliable AI-driven application performance.
+
+## Log and metric types
+
+For Azure OpenAI, you can collect the following logs and metrics:
+
+* **Resource logs**. To learn more about the different resource log category types and schemas collected for Azure OpenAI, refer to [Azure documentation](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/monitor-openai-reference#resource-logs).
+
+* **Platform Metrics for Azure OpenAI**. These metrics are available in the namespaces below:
+ * [Microsoft.CognitiveServices/accounts](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/monitor-openai-reference#supported-metrics-for-microsoftcognitiveservicesaccounts)
+
+For more information on supported metrics, refer to [Azure documentation](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/monitor-openai-reference#metrics).
+
+## Setup
+
+Azure services send monitoring data to Azure Monitor, which can then [stream data to Event Hub](https://learn.microsoft.com/en-us/azure/azure-monitor/essentials/stream-monitoring-data-event-hubs). Sumo Logic supports:
+
+* Logs collection from [Azure Monitor](https://docs.microsoft.com/en-us/azure/monitoring-and-diagnostics/monitoring-get-started) using our [Azure Event Hubs source](/docs/send-data/collect-from-other-data-sources/azure-monitoring/ms-azure-event-hubs-source/).
+* Metrics collection using our [Azure Metrics Source](/docs/send-data/hosted-collectors/microsoft-source/azure-metrics-source).
+
+You must explicitly enable diagnostic settings for each OpenAI resource you want to monitor. You can forward logs to the same Event Hub, provided they satisfy the limitations and permissions as described [here](https://learn.microsoft.com/en-us/azure/azure-monitor/essentials/diagnostic-settings?tabs=portal#destination-limitations).
+
+When you configure the event hubs source or HTTP source, plan your source category to ease the querying process. A hierarchical approach allows you to make use of wildcards. For example: `Azure/OpenAI/Logs`, `Azure/OpenAI/Metrics`.
+
+### Configure collector
+
+Create a hosted collector if not already configured and tag the `tenant_name` field. You can get the tenant name using the instructions [here](https://learn.microsoft.com/en-us/azure/active-directory-b2c/tenant-management-read-tenant-name#get-your-tenant-name). Make sure you create the required sources in this collector. })
+
+### Configure metrics collection
+
+import MetricsSource from '../../reuse/metrics-source.md';
+
+})
+1. Tag the location field in the source with the right location value. })
+
+#### Activity logs (optional)
+
+import ActivityLogs from '../../reuse/apps/azure-activity-logs.md';
+
+})
+
+### Models
+
+The **Azure OpenAI - Models** dashboard enables a deep dive into individual model performance, usage, and health. Tracks model availability, request rates, operations, latency, throughput (tokens per second), and usage split by deployment, model name, and resources
+})
+
+### Performance and Latency
+
+The **Azure OpenAI - Performance and Latency** dashboard focuses on the responsiveness of Azure OpenAI APIs and models. It tracks time-to-first-byte (TTFB), time-to-response, time-between-tokens for streaming performance, tokens-per-second speed, and time-to-last-byte. Use this dashboard to identify latency bottlenecks across models, deployments and to compare streaming vs non-streaming performance trends.
+})
+
+### Reliability and Availability
+
+The **Azure OpenAI - Reliability and Availability** dashboard provides visibility into the operational health of Azure OpenAI across deployments and models. It highlights metrics that track overall API availability, request success vs client/server errors, and throttled calls (429). Use this dashboard to quickly identify availability degradation, error spikes, or throttling events that may affect your applications.
+})
+
+### Usage and Token Consumption
+
+The **Azure OpenAI - Usage and Token Consumption** dashboard provides details on model utilization and token consumption across deployments. The dashboard surfaces prompt tokens (input), generated tokens (output), total tokens processed, and cache match rates. Use this dashboard for cost optimization and understanding workload trends across different models and regions.
+})
+
+### Content Safety
+
+The **Azure OpenAI - Content Safety** dashboard provides metrics on responsible AI policies and content safety enforcement. It monitors harmful content detected, requests blocked by filters, abusive user identification, and system safety events. Use this dashboard for compliance, RAI monitoring, and auditing risky behaviors across workloads.
+})
+
+### Administrative Operations
+
+The **Azure OpenAI - Administrative Operations** dashboard provides details on the operational activities and status of your Azure OpenAI resources.
+
+Use this dashboard to:
+* Monitor the distribution of operation types and their success rates to ensure proper functioning of your OpenAI.
+* Identify potential issues by analyzing the top operations causing errors and correlating them with specific users or applications.
+* Track recent write and delete operations to maintain an audit trail of changes made to your OpenAI.
+
+})
+
+### Policy and Recommendations
+
+The **Azure OpenAI - Policy and Recommendations** dashboard provides details on policy events and recommendations for your Azure OpenAI resources.
+
+Use this dashboard to:
+* Monitor the success and failure rates of policy events to ensure proper configuration and compliance.
+* Track and analyze recent recommendations to improve the performance and security of your OpenAI setup.
+* Identify trends in policy events and recommendations over time to proactively address potential issues.
+
+})
+
+## Create monitors for Azure OpenAI
+
+import CreateMonitors from '../../reuse/apps/create-monitors.md';
+
+A guide to the Sumo Logic integration for Azure IP Addresses.
+})
diff --git a/docs/integrations/product-list/product-list-a-l.md b/docs/integrations/product-list/product-list-a-l.md
index 27b7b5320d..a1d903b174 100644
--- a/docs/integrations/product-list/product-list-a-l.md
+++ b/docs/integrations/product-list/product-list-a-l.md
@@ -119,7 +119,7 @@ For descriptions of the different types of integrations Sumo Logic offers, see [
| }){kind=logo}
| [AWS Simple Notification Service](https://aws.amazon.com/sns/) | Automation integration: [AWS Simple Notification Service](/docs/platform-services/automation-service/app-central/integrations/aws-simple-notification-service/) |
| })
| [AWS WAF](https://aws.amazon.com/waf/) | Apps: })
| [Axonius](https://www.axonius.com/) | Automation integration: [Axonius](/docs/platform-services/automation-service/app-central/integrations/axonius/) |
-| }){kind=logo}
| [Azure](https://azure.microsoft.com/en-us) | Apps: | [Azure](https://azure.microsoft.com/en-us) | Apps: