AIOps
Release gates that hold up under incident pressure
Turn reliability policy into a release decision with fresh evidence, limited exceptions, and a clear path to resuming normal changes.
Search articles
Search titles and article text.
AIOps
Evaluate AIOps tools with the work your responders actually do
Compare detection, correlation, investigation, and automation using your incidents, review costs, and failure paths.
AIOps
What AIOps changes in the SRE workflow
Understand where detection, correlation, forecasting, and language models can help, and the operational work each introduces.
AIOps
Variational autoencoders: the model and its anomaly-detection limits
Understand the encoder, latent distribution, training objective, and why reconstruction error is evidence to evaluate rather than a diagnosis.
AIOps
Generative adversarial networks: realism is not operational validity
Understand how GANs train and why synthetic data needs checks for coverage, constraints, privacy, and downstream usefulness.
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
Splunk agent observability: follow the work, then the bill
Splunk’s September release connects agent evaluation and cost monitoring. The useful test is whether a responder can trace spending back to an outcome.
Technology Overviews
Supervising coding agents with Herdr
Check agent status, terminal persistence, and recovery before adopting Herdr.
AIOps
When agents can change production
Define the action, contain its scope, and verify what changed at the destination.
AIOps
The operational cost of AI tokens
Account for context limits, retries, latency, and the work behind a useful result.
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.