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How do you ingest and store petabytes of telemetry every day in a cost effective and high performing way? How can you do this in a way which gives engineers the operational data they need to keep services running? How has this challenge be tackled in the past and what's been the evolution?
This week I'm joined by Observe co-founder Jacob Leverich to go deep into this topic. We discuss...
💾 A deep-dive into the evolution of telemetry storage and where it's going
💽 The advent of generic storage that handles metrics, logs, and traces well
🫶 Having empathy for people who need great observability but struggle to obtain it
🤲 Not holding telemetry data hostage
✍️ Lessons from 8 years of running a start-up
...and much more.
You can find Jacob on...
LinkedIn: https://www.linkedin.com/in/jacob-leverich/
And find out more about Observe here:
In the episode Jacob referred to Google's Dremel analysis platform: https://research.google/pubs/dremel-interactive-analysis-of-web-scale-datasets-2/
And Apache Iceberg: https://iceberg.apache.org/
You can buy Slight Reliability merch here (Note: you cannot order the mugs outside of New Zealand):
https://slightreliability.digitees.co.nz/
You can find Stephen on:
LinkedIn: https://www.linkedin.com/in/stephentownshend/
Bluesky: https://bsky.app/profile/slightreliability.bsky.social
YouTube: https://www.youtube.com/c/SlightReliability
Instagram: https://www.instagram.com/slight_reliability/
TikTok: https://www.tiktok.com/@the_kiwi_sre
