Description
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
OpenObservability Talks episodes are released monthly, on the last Thursday of each month and are available for listening on your favorite podcast app and on YouTube.
We live-stream the episodes on Twitch and YouTube Live - tune in to see us live, and chime in with your comments and questions on the live chat.
https://www.twitch.tv/openobservability
https://www.youtube.com/channel/UCLKOtaBdQAJVRJqhJDuOlPg
Have you got an interesting topic you'd like to share in an episode? Reach out to us and submit your proposal at https://openobservability.io/
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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YouTube: https://www.youtube.com/channel/UCLKOtaBdQAJVRJqhJDuOlPg
Website: https://openobservability.io/
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