Autopilot for Deployment Verification
To verify a deployment in production it takes a village. Typically a 5 person Ops team spends at least an hour per deployment to verify the performance of a new release using various monitoring tools that cover a wide spectrum of application and infrastructure stack.With Autopilot teams can easily integrate all their monitoring and logging tools to rapidly verify the performance and quality of a change in just minutes.
Continuous Verification of Deployments
Integrate Autopilot with your CD pipeline to automatically verify new deployments, enabling automated rollback or roll forward of versions in seconds using Autopilot’s intelligent feedback.
Risk Assessment of Performance
Autopilot finds performance regressions and flags anomalies in new releases by comparing them with the normal behavior of your systems, using unsupervised ML to continuously analyze performance, service level, and infrastructure metric data.
Risk Assessment of Logs
Verify a new release is reliable by analysing events, exceptions, and errors during deployment. Autopilot tokenizes event data and applies unsupervised machine learning to understand the frequency and genuineness of each event.
Visibility and Insights
Use an intuitive UI with a graphical representation of success and failure of previous releases to increase visibility and collaboration among dev, ops and infrastructure teams.
Vendor Agnostic
Autopilot comes “out-of-the-box”with direct integrations for many CI/CD tools, log analyzers, and APM tools, requiring only a few mins to configure, fetch and analyze metrics from your logs and data sources.
Key Benefits
Elevate Ops Productivity
Autopilot reduces by 90% the time DevOps team spend manually investigating deployments with real-time performance and quality analyses of new deployments.
Zero Production Downtime
With risk analysis of new deployments at their fingertips, DevOps teams can quickly rollback applications to the previous version should performance degradation occur.
Gain Confidence
Automated monitoring of logs in near real-time gives DevOps teams increased confidence about the status, risks, and quality of release candidates via intuitive dashboards.
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