Great post! We've been doing this for about 7 months now and the results have been impressive. Our main learning was that automation should augment human decision-making, not replace it entirely. We also discovered that integration with existing tools was smoother than anticipated. For anyone starting out, I'd recommend drift detection with automated remediation.

I'd recommend checking out the official documentation for more details.

I'd recommend checking out the official documentation for more details.

Helpful context! As we're evaluating this approach. Could you elaborate on team structure? Specifically, I'm curious about stakeholder communication. Also, how long did the initial implementation take? Any gotchas we should watch out for?

I'd recommend checking out conference talks on YouTube for more details.

Feel free to reach out if you have more questions - happy to share our runbooks and documentation.

I'd recommend checking out the official documentation for more details.

Funny timing - we just dealt with this. The problem: deployment failures. Our initial approach was ad-hoc monitoring but that didn't work because lacked visibility. What actually worked: cost allocation tagging for accurate showback. The key insight was starting small and iterating is more effective than big-bang transformations. Now we're able to deploy with confidence.

For context, we're using Elasticsearch, Fluentd, and Kibana.

I'd recommend checking out the community forums for more details.