Top all-time · #6769
Last9
Company blog · last9.io/blogprogrammingsystems
Last9 is the company blog at last9.io, writing about programming and systems. Since 2023, 12 different Hacker News readers have linked it 20 times, most often “Taming High Cardinality by sharding a stream”. It is still writing: the last post was on 2026-10-28, and you can follow it by feed.
Too few sampled comments (2) to say how often HN recommends it.?
Why HN links it
Linked for posts on why observability is so expensive and on ingesting OpenTelemetry metrics into Prometheus. Commenters discuss telemetry storage and cost, with one disagreeing with the cost argument.
Summarised by Claude from a sample of 2 HN comments that link here. Each comment is marked recommending, critical or neutral (citing without judging); how this works.
Unified observability for developers, SREs, and AI agents. Metrics, logs, traces, and APM in one view, with full visibility and no cost explosion.
Most-linked posts?
- Taming High Cardinality by sharding a stream2 people · 2 mentions · first linked 2023-08-17
What Hacker News says?
I have a different take >Engineers have to pre-define and send all telemetry data they might need – since it’s so difficult to make changes after the fact – regardless of the percentage chance of the actual need. YES. Let them send all the data. The best place to solve for it is at Ingestion. There's typically 5 different stages to this process. Instrumentation -> Ingestion -> Storage -> Query (Dashboard) -> Query (…
Comment linking /data-tiering/
on “Why is observability so expensive?”Submitted Monitoring Node.js: Key Metrics You Should Track as a story · 45 points
HN discussionI did use stackdriver for quite a while before I moved to Mimir. TBH its great that you are still sticking to opentelemetry. Stackdriver as metric storage is not even a wise option in todays world give there are some really good TSDB providers SaaS or otherwise that would do a much better job. I moved away because of 2 primary reasons 1. The cost of stackdriver can add up with large-scale deployments or high-frequen…
Comment linking /blog/time-series-database-comparison/
on “Ingest OpenTelemetry metrics with Prometheus natively”Submitted Replit replaced thanos with this as a story · 6 points
HN discussionSubmitted Learnings from integrating JMX metrics from Java apps into time series databases as a story · 5 points
HN discussionSubmitted Golang Logging: A Comprehensive Guide for Developers as a story · 4 points
HN discussionSubmitted Managing high cardinality time series data using streaming aggregations as a story · 4 points
HN discussionSubmitted Taming High Cardinality by sharding a stream as a story · 3 points
HN discussionSubmitted Understanding Metrics, Events, Logs and Traces – Key Pillars of Observability as a story · 3 points
HN discussionSubmitted Everything in software monitoring is dead, apparently as a story · 2 points
HN discussionSubmitted Why high-cardinality workloads fail differently in Prometheus vs. ClickHouse as a story · 1 points
HN discussionSubmitted Why high-cardinality labels stress metrics databases as a story · 1 points
HN discussionSubmitted Fix Production Issues in Your Local Environment as a story · 1 points
HN discussionSubmitted What Is CDN? The Complete Guide for DevOps Engineers as a story · 1 points
HN discussionSubmitted We tame High Cardinality by Sharding a stream as a story · 1 points
HN discussionSubmitted Solving for High Cardinality at 500M requests/minute as a story · 1 points
HN discussionSubmitted Ingest OpenTelemetry metrics with Prometheus natively as a story · 1 points
HN discussionSubmitted Taming High Cardinality Data with Streaming Aggregation and Recording Rules as a story · 1 points
HN discussionSubmitted Using a Golang package in Python using Gopy as a story · 1 points
HN discussionSubmitted A practical guide to implementing SLO as a story · 1 points
HN discussion