ExplainerAI in production
How GANs generate synthetic telemetry
GANs learn to resemble training data. A cascading-timeout example explains what generated traces contribute to testing and what a controlled fixture supplies.
AIOps
AI in production: tools, operating patterns, costs, and failure modes.
GuideObservability
Python logging and exit status in a scheduled job
A complete Python example sends the result to stdout, records an exception once and returns the failure status its scheduler needs.
CommentaryEngineering leadership
Who puts an AIOps mistake right?
A misrouted support ticket shows how automated decisions affect customers and what a usable correction path requires from the people responsible.
GuideAI in production
Automating a worker restart from diagnosis to recovery
A worker restart shows how AIOps can select a repair, reconcile a lost response and check whether customer work recovers.
GuideObservability
Collecting and aggregating operational data with Python
A complete Python example combines request and error counts, while a failed regional collection explains why correct arithmetic can still produce an incomplete report.
The work behind an AIOps business case
Faster incident-update drafts can save time or move work into review. The business case depends on the cost of the accepted update.
GuideObservability
What an AIOps assistant adds to an investigation
A deployment and a simultaneous dependency outage illustrate how AI-assisted observability can locate useful evidence and distinguish competing explanations.
ExplainerAI in production
From an anomaly score to a useful service signal
Baselines, event-level precision and recall, and the cost of waiting determine whether an unusual pattern belongs in investigation or paging.
GuideAI in production
Routing support tickets with Python and NLP
An executable keyword router provides a baseline for NLP classification. An ambiguous login ticket shows how handoffs and human triage affect the result.
ExplainerObservability
Why a refreshing dashboard can still show stale data
Observation, collection and evaluation timestamps explain why the last zero-error result may no longer describe the service.