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Blog posts
The Data Race That Wasn't a Bug (and the One That Was)
You turn on Go’s race detector and get a data race inside net/http that makes no sense at first. This post digs into how Go’s HTTP client really sends a request body, why it can keep reading your buffer after Client.Do has returned, why we decided that race is harmless in vmagent, and why the same behavior could corrupt data in vmauth, so we fixed it there.
How Linux readahead works, and the two ways to change it
The kernel reads your files before you ask for them, guessing from where your reads land. Here is how that guessing actually works (the window, the marker, the background fetch) and the two ways to influence it: read_ahead_kb on the device, and posix_fadvise from inside the program. Neither does quite what its name suggests.
The Life of a Metric
Follow a single metric through its whole life inside VictoriaMetrics: born as a counter in your process, exported over the wire, given an identity and an inverted-index entry, written through an LSM tree, compressed into columnar blocks on disk, read back by a rate() query, downsampled as it ages, and finally deleted when retention runs out.
How Go’s Built-in Map Works with Swiss Tables
Go 1.24 replaced the built-in map’s bucket-based runtime with Swiss Tables. This article explains groups, control bytes, H1 and H2, probing, table growth, directories, deletion, load factor, and the experimental split-group layout.
Understanding Go's sync.Map from API to Hash Trie
Go’s sync.Map now uses a hash trie. This article builds the implementation from a normal map, then explains lock-free reads, fine-grained writer locking, collisions, retries, deletion, Clear, Range, and the trade-offs against map plus RWMutex.
How VictoriaLogs Stores Your Logs in a Columnar Layout
A beginner-friendly tour of how VictoriaLogs stores your logs on disk: streams and daily partitions, immutable parts, blocks and columns, and the files inside a part (timestamps, values, bloom filters, column headers, and the two-level index) that let a query read only the bytes it needs.
How Airbnb Built a High-Volume Metrics Pipeline with OpenTelemetry and vmagent
Learn how Airbnb rebuilt its observability pipeline with OpenTelemetry and vmagent to handle over 100 million samples per second, reduce cost by 10x, and simplify high-scale metrics aggregation.
Not All Telemetry Requires Premium Pricing
Reduce observability costs with hybrid strategies: prioritize revenue-driving signals in SaaS, self-host high-volume telemetry. Cut bills 3-12x without losing visibility.
Observability Lessons From OpenAI
OpenAI applies observability to autonomous AI agents using the VictoriaMetrics Stack and OpenTelemetry. Learn to build your own local setup with metrics, logs, and traces that help LLMs test, benchmark, and iterate autonomously.