How-To
Alert trust: decide which signals earn an interruption
Decide which alerts earn an interruption using urgency, reachable authority, coverage evidence, and a practical alert acceptance record.
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AIOps
What AIOps alert correlation can hide
Evaluate AIOps grouping by detection coverage, investigation effort, and recoverable mistakes, not alert reduction alone.
AIOps
What MTTD misses
Separate detection from response and find delays that an improving average can conceal.
How-To
How to evaluate incident-response agents
Build repeatable cases and check recovery independently, with a runnable Python grader.
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.
How-To
Design an on-call rotation people can actually support
Define coverage, escalation, training, and recovery time before assigning the calendar. Review workload as well as shift counts.
Leadership & Culture
On-call overload: respond to the workload before it becomes normal
Use interruption patterns and responder feedback to change paging, coverage, and recovery expectations when on-call work becomes unsustainable.
AIOps
AIOps anomaly detection: unusual does not always mean actionable
Choose a baseline, evaluate false positives and missed incidents, and connect anomalies to an operational decision before paging on them.
SRE
SRE feedback loops: check whether the signal still means the same thing
Connect telemetry, customer reports, decisions, and verification so improvements in a dashboard reflect improvements in the service.
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
OpenTelemetry’s Kubernetes milestone matters for AI agent tracing
The stable Kubernetes attributes processor helps connect AI-agent traces to their workloads. Check the metadata joins before upgrading.
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.