Dev tools · September 24, 2024
Oodle – serverless, fully-managed, drop-in replacement for Prometheus
Hello HN! My co-founder, Vijay and I are excited to open up Oodle for everyone. We used to be observability geeks at Rubrik. Our metrics bills grew like 20x over 4 years. We tried to control spend by getting better visibility, blocking high cardinality labels like pod_id, cluster_id, and customer_id. But that made debugging issues complicated. App engineers hated blocking metrics, and blocking others' code reviews was not fun for platform engineers either! Migrations (and lock-ins) were very painful, the first migration from Influx to Signalfx took 6+ months and the second migration from…
In plain words
Oodle is a serverless, fully-managed metrics platform designed as a drop-in replacement for Prometheus. Built by former observability engineers at Rubrik, it addresses runaway metrics costs by storing data efficiently on S3 while maintaining query performance at scale. The platform eliminates the need to block high-cardinality labels like pod IDs or cluster IDs for cost control, allowing engineers to retain full debugging visibility without sacrificing performance or requiring lengthy migrations.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
Hello HN! My co-founder, Vijay and I are excited to open up Oodle for everyone. We used to be observability geeks at Rubrik. Our metrics bills grew like 20x over 4 years. We tried to control spend by getting better visibility, blocking high cardinality labels like pod_id, cluster_id, and customer_id. But that made debugging issues complicated. App engineers hated blocking metrics, and blocking others' code reviews was not fun for platform engineers either! Migrations (and lock-ins) were very painful, the first migration from Influx to Signalfx took 6+ months and the second migration from Splunk took over a year. Oodle is taking a new approach to building a cost-efficient serverless metrics observability platform. It delivers fast performance at high scale. We leverage custom storage format on S3, tuned for metrics data. Queries are serverless. The hard part is how to achieve fast performance while optimizing for costs (every cpu cycle, storage/memory byte counts!). We've written about the architecture in more detail on our blog: https://blog.oodle.ai/building-a-high-performance-low-cost-m... Try out our playground with 13M+ active time series/hr & 13B+ samples/day: https://play.oodle.ai Explore all features with live data via Quick Signup: https://us1.oodle.ai/signup - Instant exploration (<5min): Run one command to stream synthetic metrics to your account - Easy integration (<15min): Explore with your data from existing Prometheus or OTel setup. We’d love your feedback! cheers
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