Pastries with SREs: No compromises on cost-effective observability or donuts.
In this episode of Pastries and SREs, we dig into how vendor lock-in and sky-high observability costs are forcing teams to choose between coverage and budget, AND why you shouldn’t have to settle.
With donuts in hand, we explore how to take back control of your observability strategy by making it cost-effective, comprehensive, and flexible.
We explore:
⦁ Real-world stories of surprise observability charges and blown budgets
⦁ Why partial instrumentation creates critical blind spots in your environment
⦁ How to manage observability costs without sacrificing data fidelity
⦁ The importance of object storage, data lakes, and full-fidelity retention
⦁ Strategies to avoid vendor lock-in and future-proof your stack
⦁ What it takes to build a platform that scales flexibly with your needs, not against them
⦁ Observability should empower your teams, not drain your budget or limit your visibility.
00:00 – Donuts & vendor lock-in: the real cost of switching tools
00:33 – Data retention struggles and breaking out of silos
01:09 – Cutting logs to save costs: why it backfires later
01:44 – Hidden productivity losses from chasing short-term savings
02:11 – Balancing flexibility, value, and budget in observability
02:48 – Case study: financial services storing 100% of traces
03:13 – Cost-efficient data storage and future-proofing your stack
03:35 – Why sampling data breaks ML accuracy (and donuts)
04:01 – Full-fidelity data for anomaly detection and customer insights
04:25 – Predictive observability: stopping problems before they happen
Additional Resources:
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About Elastic
Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale. Elastic’s solutions for search, observability, and security are built on the Elastic Search AI Platform — the development platform used by thousands of companies, including more than 50% of the Fortune 500.
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