Every deployment is a win or lose

Being able to detect negative change is imperative to gain confidence during rapid releases.

What are your containers, services and nodes normally doing?

Understand how your environment is behaving before you introduce change.

What will the effect be of that change?

Spot anomalies and problems within seconds after a deploy by inspecting log based anomalies.

How do you learn from past problems and failures?

Tag the data that explains bugs, problems and concerns and track them over time.

MONITOR VIRTUALLY ANY SOFTWARE ENTITY, INCLUDING:

Even the most coordinated teams could use more insight

When your environment is successfully serving users and requests

You will want to see the patterns and events that make everything tick, down to every event, on every dependency.

Then when a deployment causes a production issue

Identify which new errors and tracebacks where produced, when and where. Act before it becomes worse.

You may find that a memory allocation issue started it all.

After a failure, go back in time and review how the anomalies happened across multiple dependencies over time.

Don’t forget to document your fix.

Tie the learnings from incidents, postmortems etc to the data by adding knowns and tags to the data.

Finally, if the problem reoccurs, alert the right person.

Notify on anomalies in Slack, add tickets to JIRA or build custom event driven automations by tying javascript based actions to events.

Be responsive to changes that results in production issues and outages

More confidence to deploy

Know that if your change causes more change you will notice and understand it

Less technical debt

Use anomaly detection to weed out latent root causes that will bite you later.

Faster resolutions

One shared view of anomalies and knowns across development and ops.

Ready to get started?

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