At Meta (Facebook, Instragram et al) everything is data, and data driven approach is the rule, from product to engineering, from HR to finance. This is also how the team at Meta treats observability. Let’s see how we treat observability as a data analytics problem, and what you can implement, even if you’re not a hyperscaler.

On this episode I’ll host David Ostrovsky from Meta. David is a software developer with over 20 years of industry experience, speaker, trainer, blogger and co-author of “Pro Couchbase Server”. He specializes in large-scale distributed system architecture.

The episode was live-streamed on 7 November 2022 and the video is available at https://youtu.be/1l0HKUDoX4Q

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Show Notes:

• Addressing business observability
• Machine learning and predictions in observability
• From the business inwards, using SLOs
• Accelerate engineering quality with developer observability
• Organizational and communications aspects of high scale observability
• Actionable observability
• How small-medium size orgs can achieve a similar effect
• OpenTelemetry demo is GA
• PromLens is open sourced and contributed to Prometheus

Resources:

• TEMPLE signals for observability: https://medium.com/@YuriShkuro/temple-six-pillars-of-observability-4ac3e3deb402
• PromLens open sourced: https://promlabs.com/blog/2022/10/25/promlabs-and-chronosphere-open-source-the-promlens-query-builder

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