ExplainerAI in production
How variational autoencoders learn telemetry patterns
The encoder, latent distribution and reconstruction objective explain why a VAE can flag a legitimate traffic change while overlooking a familiar failure.
Articles
Guides, news and explanations about AI and reliable systems.
GuidePlatform engineering
What a canary deployment actually tests
Traffic assignment determines which behavior reaches a canary. Promotion also depends on the baseline, service objectives and state left behind by rollback.
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.
ExplainerIncident response
Calculating mean time to detect from incident records
Worked incident records explain the MTTD formula, uncertain onset times and the effect of including failures first reported by customers.
CommentaryIncident response
Why blameless reviews investigate the conditions around a mistake
A mistaken target selection shows how an incident review can explain a responder’s choice and lead to a more useful interface improvement.
GuideIncident response
Writing a post-incident review the next responder can use
A delayed rollback connects the incident timeline to the information responders had, the compatibility question they faced and the follow-up that remains.
CommentaryPlatform engineering
What KISS means for service configuration
Feature flags and customer overrides show why a shorter configuration file can leave just as much behavior to investigate and support.
ExplainerObservability
What observability metrics keep and leave out
Counters, gauges and distributions preserve different information. A misleading latency trend shows why the counted requests matter as much as the chart.
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.