Elastic supports Microsoft Azure monitoring use cases with native Microsoft Azure console integration
Elastic announces new features and updates in the Elastic Observability solution in version 7.13 to streamline workflows in Microsoft Azure, simplify data integrations, and accelerate root cause analysis. Extended features include native integration into Microsoft Azure Console, Fleet Server beta, and new troubleshooting views in Elastic APM.
Elastic announces an enhanced partnership with Microsoft, allowing users to find and deploy Elastic directly from the Azure console and natively integrate observability and security data from Azure services.
In Elastic Observability, the new native Azure Console integration allows customers to easily integrate logs and metrics from their Azure services. This includes both compute services, such as virtual machines and containers, and non-IT services, such as Azure SQL Database and Azure Data Factory. Users can easily configure their configurations with tag-based filters to limit data collection to specific resources only.
Elastic is also announcing the beta of Fleet Server, a new application from Kibana that allows practitioners to centrally manage an entire fleet of Elastic agents. Fleet Server offers a distributed architecture for scalability and flexible deployment. It can be deployed centrally or near elastic agents. Together, the integration of Azure Console and Fleet Server dramatically reduces total cost of ownership and time to value for users of Elastic Observability.
New improvements to the Elastic APM service overview page are now available with time comparison and improved APM service instance views, allowing users to further speed up root cause analysis and reduce average time resolution (MTTR).
The time comparison view allows users to quickly and directly compare current and historical behavior, while the point cloud view displays instances by latency and load distribution to reveal which instances behave differently under load.
An enhanced instance panel breaks down services by instance, providing metrics and trends by instance to quickly identify instances that may be contributing to service issues.