Elastic Observability 8.8: Efficient operations with GitOps-based synthetics monitoring and direct AWS Firehose ingest
Elastic Observability 8.8 delivers the general availability release of synthetic monitoring, the ability to ingest data directly to Elastic Cloud from Amazon Kinesis Firehose, and new capabilities for managing service level objectives.
An overview of the AIOps capabilities within the Elastic Observability full-stack solution! From noise reduction to anomaly detection and root cause analysis, AIOps helps teams troubleshoot and respond more quickly to application performance issues.
Common use cases and scenarios for a successful AIOps deployment within observability. From monitoring to anomaly detection and root cause analysis, understand how you can improve your AIOps deployment and see success.
Elastic Observability 8.6: Maximizing operational efficiencies with improved application analysis and workflow integrations
Elastic Observability 8.6 introduces new host observability and application dependency operations views, providing key insights into complex, distributed environments. In addition, the connector for OpsGenie is now generally available.
Elastic Observability allows users to automatically create and close alerts within Opsgenie when triggered in Elastic. By providing granular control over alert content, users gain greater flexibility to target audiences and resolve issues quickly.
AIOps has become an increasingly important consideration for operations teams. With the rapidly increasing volume of metrics, logs, and traces, operations teams are increasingly relying on machine learning driven AI to analyze data and reduce noise.
APM correlations in Elastic Observability: Automatically identifying probable causes of slow or failed transactions
An overview on how Elastic Observability and APM correlations can help diagnose and troubleshoot application issues. We will cover a real-life application issue and review some other common scenarios where APM is commonly used by developers and SREs.