Our IT operations are reactive - something breaks, we get alerted, we scramble to fix it. I want to implement AIOps to move to predictive operations where AI detects degradation before users notice, correlates incidents automatically, and eventually enables self-healing for common issues. But I need a realistic plan for a mid-size IT team, not an enterprise playbook that requires 50 SREs.
Plan for: Implement AIOps - Predictive IT Operations, Incident Prevention, and Self-Healing Infrastructure
Team distrusts AI correlation and fears missing critical alerts if they are grouped incorrectly.
Start by running correlation in 'shadow mode' or non-production environments first, and emphasize Step 4 (human-in-the-loop tuning).
Self-healing scripts execute incorrectly and cause unintended system outages.
Implement automations as 'diagnostic only' at first (e.g., fetching logs). When moving to remediation, require a human 'approve' button click before full automation is trusted.
Anomaly detection generates too many false positives due to seasonal traffic spikes.
Ensure the anomaly detection algorithms are set to account for seasonality (e.g., using Datadog's Agile or Robust algorithms with weekly seasonality).
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