GPU capacity depends on power and cooling
When inference slows without obvious application errors, test physical constraints alongside queueing, workload changes, and software regressions.
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When inference slows without obvious application errors, test physical constraints alongside queueing, workload changes, and software regressions.
The stable Kubernetes attributes processor helps connect AI-agent traces to their workloads. Check the metadata joins before upgrading.
Use AIOps to connect operational evidence, then test whether it improves investigation without hiding missing signals or unsupported conclusions.
Splunk’s September release connects agent evaluation and cost monitoring. The useful test is whether a responder can trace spending back to an outcome.
Use a curated notebook to compare runbooks and incident evidence, while keeping citations, freshness, and operational authority in view.
Test evidence retrieval, long-session consistency, tool boundaries, and cost before letting a model influence production changes.
Choose representative traffic, define promotion criteria, and verify rollback compatibility before expanding a release.
Use consistent onset and discovery timestamps, include customer-reported incidents, and interpret the average with its sample and uncertainty.
Counters, gauges, and distributions answer different questions. Build metrics that preserve scope, denominators, and the evidence behind an incident.
Understand spans, parent-child relationships, retries, and missing evidence so traces support a careful diagnosis.