Operations | Monitoring | ITSM | DevOps | Cloud

Large language models are effective at security review for the same reason they are effective at many other tasks: they reason rather than pattern match. In plain terms, a traditional scanner checks code against a list of known bad patterns, the way a spell checker flags a misspelled word, regardless of what the sentence means. An LLM can instead follow the program's logic: trace a piece of attacker-controlled input through several layers of application code to determine whether it is reachable.

15 AWS cost optimization tactics across compute, storage, networking, and monitoring plus a quick-reference table by effort and savings potential.

New integration gives security teams continuous visibility and real-time threat detection across agent interactions on AWS Today, Harness announced a new integration with Amazon Bedrock AgentCore Gateway that helps enterprises discover and secure the AI agents, tools, and resources operating across their AWS environments. The integration brings Harness’ AI posture management and AI firewall to agent interactions flowing through AgentCore Gateway.

Learn why cloud cost optimization for engineers fails and how to fix it with developer-centric FinOps practices. See how Harness helps. Engineers often ignore cloud costs due to a lack of visibility, context, and ownership in their daily workflows. By shifting cost governance left and integrating real-time cost insights into CI/CD pipelines, teams build lasting cost accountability.

Auditable Agent Judgment: Jev's Decision Primitive at Harness Agents do more than generate - they continuously make judgments between reasoning and action. This article explores how typed, probabilistic decisions can become a first-class primitive for building agent loops that can be evaluated, governed, and trusted.

See how machine learning is changing secure SDLC practices, from AI-assisted code review and finding triage to new risks like model supply chain attacks.

94% of engineering leaders say their AI metrics are missing. Here's how platform engineering is changing to close that gap. Based on the InfoQ webinar "Platform Engineering in the Age of AI," featuring panelists from Harness, DKB, and Shine, August 18, 2026. 94% of engineering leaders say the AI metrics that matter most to them are missing.

Based on the LeadDev panel discussion "Governance Is the Platform Problem Worth Solving," hosted in partnership with Harness, August 5, 2026. AI agents are no longer waiting for a human to approve their next move. They open pull requests, adjust configurations, and act on behalf of the people who deployed them — often faster than any review cycle can keep up.