How-To
How to evaluate incident-response agents
Build repeatable cases and check recovery independently, with a runnable Python grader.
Search articles
Search titles and article text.
News
New AI energy alliance puts workload flexibility on the SRE agenda
Google, NVIDIA and Emerald AI are backing flexible data centers. Operators will need to define which AI work can yield power, and how it recovers.
News
Claude adds on-demand compaction for long-running agents
The Messages API can now summarize conversation history when an application chooses. SRE teams should test which operational constraints survive.
News
Claude’s Chrome transcripts enter the enterprise audit trail
Anthropic has added Chrome-session transcripts to its Compliance API beta. Responders gain another evidence source, with important gaps to understand.
News
Kubernetes Memory QoS: what AI inference teams should test
Memory QoS reaches beta in Kubernetes 1.37. For AI inference teams, the rollout question is how host-memory policy affects serving latency and neighboring workers.
Technology Overviews
Supervising coding agents with Herdr
Check agent status, terminal persistence, and recovery before adopting Herdr.
AIOps
What MTTD misses
Separate detection from response and find delays that an improving average can conceal.
AIOps
When agents can change production
Define the action, contain its scope, and verify what changed at the destination.
AIOps
NotebookLM for SRE: build a source-backed incident dossier
Use a curated notebook to compare runbooks and incident evidence, while keeping citations, freshness, and operational authority in view.
AIOps
Evaluate Claude Opus 4.6 for operational work
Test evidence retrieval, long-session consistency, tool boundaries, and cost before letting a model influence production changes.
AIOps
Agent skills for SRE: write the execution contract
Define inputs, permissions, idempotency, verification, and stop conditions for one operational capability before expanding its authority.
AIOps
What AIOps alert correlation can hide
Evaluate AIOps grouping by detection coverage, investigation effort, and recoverable mistakes, not alert reduction alone.