Correlating Exceptions with Deployments

You’re called in. The system is misbehaving. It could be a key metric going crazy, or exceptions starting to fire. You’re troubleshooting, beating around the bush, just to realize that one of the team’s deployments was the one messing things up.

Sounds familiar? If you’re practicing continuous deployment, you probably experience that several times a week, if not more. Users report that 50% of their outages are due to infrastructure and code changes, namely deployments.

In modern systems, CI/CD events are a vital signal in the observability scheme. Correlating these ever-more-frequent deployments with the system’s telemetry will guide you to the right version to roll back for quick remediation., It will also guide you to the rogue code or configuration to resolve, with a shorter MTTR.

On the Logz.io Observability Platform, we aim to make your deployments easy to correlate with your other signals. Our Log Management product already has the machine-learning intelligence to aggregate and flag exceptions and errors inside Kibana Discover. It was only natural to let you correlate these exceptions with your deployments.

Imagine you see the exception trend plotted on a graph over time, and just before the graph starts spiking you see a marker denoting a new deployment. Imagine no more: with the new Deployments feature, now released in beta, you can see that on the Exceptions tab.

What does it take to have your deployments reported to Logz.io, you ask? It’s just a matter of adding a single RESTful API call to your CI/CD pipeline. You can add a human-readable description as well as additional information on the deployment such as the version, the cloud region or the deployer, to make root-cause analysis and remediation quicker. Check out the API docs for more information.

These deployment markers in the Log Management product join the deployment markers available on the Infrastructure Monitoring product.

Check out Deployments in your Exceptions now. See the user guide for more details, and provide your feedback on the beta release through our support in-app chat to help us make it the most usable.