Operations | Monitoring | ITSM | DevOps | Cloud

Writing code is moving from the good old IDE into the realm of autonomous AI agents. One example of this is OpenAI, which has been developing internally with 0 lines of manually written code. You can read about their workflow in their engineering blog: Harness engineering: leveraging Codex in an agent-first world. For me, the main takeaway of OpenAI’s article is how AI has rewritten the constraints equation.

At VictoriaMetrics, we built vlagent as a high-performance log collector for VictoriaLogs. To validate its performance and correctness under a real production-like load, we developed a benchmark suite and ran it against 8 popular log collectors. This post covers the methodology, throughput results, resource usage, and delivery correctness. Collectors under the test: We’ve made all benchmark configurations and source code public, so you can reproduce and verify the results independently.