Alert with SQL in Cloud Monitoring Observability Analytics
Traditional alerting systems often force a compromise: you can either alert immediately on simple, noisy log events, or monitor rigid, pre-configured metrics that fail when faced with data with many unique answers like user sessions or IP addresses. But the most critical system issues — like a 20% spike in error rates for a specific customer or a latency anomaly correlated with database timeouts — are hidden in the aggregates and relationships between these signals.
Recently, we announced that you can now use SQL to query logs and traces in Observability Analytics (formerly Log Analytics). But the story gets better. You can also use SQL to create alertsin Observability Analytics. By bringing SQL directly to your alerting engine, you can write complex analytical queries over logs and traces and turn them into alerts. Whether you need to calculate error percentages, analyze high-cardinality dimensions, or JOIN logs and traces, SQL...
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