AIOps
Use AIOps to shorten the part of incident response that is slow
Locate the delay, choose a bounded intervention, and measure recovery quality alongside elapsed time.
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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.
AIOps
The operational cost of AI tokens
Account for context limits, retries, latency, and the work behind a useful result.
AIOps
GPU capacity depends on power and cooling
When inference slows without obvious application errors, test physical constraints alongside queueing, workload changes, and software regressions.
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.
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.
AIOps
Python logging for operations: record failure and preserve the exit status
Use Python logging to capture useful context without swallowing errors, duplicating exceptions, or exposing sensitive data.
AIOps
Observability With AIOps: A Practical Evaluation Guide
Use AIOps to connect operational evidence, then test whether it improves investigation without hiding missing signals or unsupported conclusions.
AIOps
Continuous monitoring needs a visible stale-data state
Design continuous monitoring around freshness, coverage, delivery, and response ownership before adding analysis or automation.
How-To
How to evaluate incident-response agents
Build repeatable cases and check recovery independently, with a runnable Python grader.
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.