Splunk Blogs

.conf26 focused on driving real-world impact across the public sector.

Compare top agent frameworks like LangGraph and CrewAI based on operational resilience, durable execution, and production-grade observability.

Learn how to measure autonomous agent performance with this guide. Elite teams layer observability in to isolate workflow failures and improve production reliability.

Learn how digital steganography allows attackers to hide malicious data in plain sight. Discover how this technique bypasses security and how to detect it using behavioral analysis.

F1 score provides a more reliable performance metric than accuracy for imbalanced AI tasks, such as toxicity detection and safety classification.

Hallucinations in autonomous agents create business liability. Learn how teams can verify model outputs against certified source data, in a systematic way.

Measure LLM reliability and performance using seven key metrics to isolate system health from generation quality.

This field guide categorizes AI agents across seven levels of autonomy, providing a roadmap for mapping system architectures against common failure modes and production-ready requirements.

Measure and improve AI accuracy by distinguishing between classification metrics, generative faithfulness, and agentic trajectory completion.