8 min read
KQL for SQL People: The Query Language Azure Already Runs On
Why KQL is a baseline Azure skill, how its pipe model differs from SQL, and the operators, join defaults and has-vs-contains traps that matter most.
Azure Monitor
9 articles
8 min read
LLM Observability: The Few Signals That Actually Matter
Which LLM signals deserve a dashboard or a page: tokens by feature, latency split by phase, throttling, and sampled quality, using OpenTelemetry on Azure.
1 min read
Monitoring AI Applications: Observability Patterns for LLM Systems
LLM systems have unique characteristics: non-deterministic outputs, variable latency, complex cost models, and quality metrics that require semantic…
1 min read
Monitoring AI Applications with Azure Monitor and Application Insights
Configure alerts for latency spikes, error rate increases, and token usage anomalies to catch issues before they impact users.
1 min read
AI Observability with Azure Monitor and Application Insights
Monitor these essential AI metrics: latency (p50, p95, p99), token consumption per request, error rates by model and endpoint, cache hit rates for…
1 min read
Observability for LLM Applications: Tracing, Metrics, and Debugging
Log prompts and responses for failed interactions to a secure store for debugging. Implement sampling for successful calls to control storage costs while…
2 min read
Deep Dive into Azure Monitor for Containers
Azure Monitor for Containers (the Container Insights feature) is the native Azure observability solution for AKS that doesn't require running your own…
2 min read
Comprehensive AKS Monitoring with Container Insights
Container Insights is the Azure Monitor feature that closes the observability gap for AKS clusters—without it, you have Kubernetes metrics available in the…
7 min read
Azure Monitor Workbooks as an Incident Triage Tool, Not a Wallboard
Design an Azure Monitor workbook for incident triage on workspace-based Application Insights, with sampling-safe KQL, drill-down and ARM deployment.