AIOps
Build an AIOps business case around one operational bottleneck
Connect an AIOps investment to a measurable workflow, its full operating cost, and the evidence needed to expand or stop the trial.
Search articles
Search titles and article text.
News
NVIDIA’s confidential inference results need a workload boundary
NVIDIA reports low confidential-computing overhead on an eight-GPU test. Separate that measured performance result from your own security and recovery claims.
News
GPT-6 Sol and Luna change the agent cost calculation
Lower model prices and new caching controls make agent pilots cheaper to run. Measure accepted work before expanding the workload.
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
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.
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.
AIOps
What MTTD misses
Separate detection from response and find delays that an improving average can conceal.
How-To
The SRE and platform handoff
Clarify ownership across shared platforms, service reliability, and incident response.
How-To
What did the postmortem fix prove?
Separate a completed task from evidence that the underlying risk was reduced.
AIOps
The operational cost of AI tokens
Account for context limits, retries, latency, and the work behind a useful result.
How-To
Use the 5 Whys without forcing an incident into one cause
Follow evidence through technical failure and incident response, then test whether the proposed correction changes the mechanism.
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.