- Adding support for Microsoft Azure monitoring use cases with native Microsoft Azure console integration
- Enabling additional scalability and flexibility of data ingest architectures with the beta release of Fleet Server
- Accelerating root-cause analysis and lowering mean-time-to-resolution (MTTR) with time comparison and enhanced APM service instance views
Elastic Public Relations
Elastic (NYSE: ESTC) (“Elastic”), the company behind Elasticsearch and the Elastic Stack, announces new features and updates across the Elastic Observability solution in its 7.13 release to streamline workflows in Microsoft Azure, simplify data integrations, and accelerate root cause analysis. Expanded capabilities include native integration in the Microsoft Azure console, the beta release of Fleet Server, and new troubleshooting views in Elastic APM.
Elastic is announcing an enhanced partnership with Microsoft, enabling 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 onboard logs and metrics from their Azure services. This includes both compute services, such as virtual machines and containers, and non-compute services, such as Azure SQL Database and Azure Data Factory. Users can easily configure their setups with tag-based filters to limit data collection to only specific resources.
Elastic also announces the beta release of Fleet Server, a new app in 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 either centrally or close to Elastic Agents. Together, the Azure console integration and Fleet Server significantly lower total cost of ownership and time to value for users of Elastic Observability.
New enhancements to the Elastic APM Service Overview page are now available with time comparison and enhanced APM service instance views, enabling users to further accelerate root cause analysis and lower mean-time-to-resolution (MTTR). The time comparison view allows users to quickly and directly compare current and historical behavior, while the scatterplot view displays instances by latency and load distribution to reveal instances that are behaving differently under load. An enhanced instance panel breaks down services by instance, providing per-instance metrics and trends to quickly identify which instances might be contributing to service issues.
For more information read the Elastic blog about what’s new in Elastic Observability 7.13.
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