Splunk Blogs

Master RAG observability with this end-to-end guide on tracing execution paths, implementing retrieval evaluators, and building incident playbooks to ensure production reliability.

How on-premises AI observability works — what agent telemetry contains, why evaluation is the hard part to keep behind the firewall, and how the deployment models compare.

Unlock the key to AI agent testing with our guide. Discover metrics, best practices, and innovative techniques to evaluate your AI agents.

Learn the benefits of multi-agent systems and when to implement them to improve application performance and reliability.

Review the eight critical RAG failure modes and learn how to build a robust evaluation

Learn to diagnose the six primary hallucination patterns and implement a robust pipeline of retrieval, reranking, and guardrail enforcement to ensure reliability.

Splunk's new add-ons let teams track who used AI tools, what changed, and whether API keys were created or misused across ChatGPT, Claude, and other providers.

These .conf26 sessions will guide practitioners through building ML-based detections, understanding AI agent risks, and applying these techniques to real attack scenarios.

Learn the eval-to-guardrail lifecycle to transform offline evaluation criteria into runtime policies that intercept and block agent failures in production.