Operations | Monitoring | ITSM | DevOps | Cloud

How do you measure engineering excellence in the age of AI? In this ShipTalk episode, Dewan Ahmed talks with Adeeb Valiulla, leader of Developer Productivity & Efficiency at Harness, about redefining productivity beyond dashboards and vanity metrics.

This video demonstrates how you can use ModelScan step in Harness STO to scan you AI/ML models.

This video details about the base image approval mechanism in Harness STO.

This video explains how to configure base image identification for your container image scans, so that vulnerabilities originating from the base image are detected and labeled appropriately.

In this video, we explore how to set up the Harness MCP server in VS Code. Harness MCP server exposes 160+ tools across DevOps, Testing, Security, and FinOps.

Nothing drains developer productivity like codebase maintenance. The endless cycle of dependency upgrades, bug fixes, refactoring, and paying down technical debt is tedious, error-prone work that pulls engineers away from building new features. Harness Autonomous Code Maintenance (ACM) turns these manual chores into automated, intent-driven workflows. Developers can now state their intent in plain English, with prompts like, "Upgrade the front end from React 15.6 to 16.4". From there, the Harness AI agent drives the workflow.

Many software engineers are experts in application code but not in the nuances of creating a production-ready delivery pipeline. Architect Mode acts as a seasoned DevOps expert, engaging the user in a conversation to design a pipeline that incorporates organizational best practices for security, quality, and compliance from the very beginning. It’s like having a personal DevOps architect as a partner.

We're making Internal Developer Platforms (IDPs) more accessible with a natural language assistant. Developers can ask questions like, "What are the failing checks for my service's scorecard?" or "Who is the owner of a service?" to find metadata instantly. The agent also bridges the gap to action by suggesting and executing self-service workflows, like creating a new repo or onboarding a new engineer. It can even assist in generating new workflows, turning complex processes into simple conversational tasks.

Our first AI/ML capability, Continuous Verification, made Harness the first Continuous Delivery tool to understand observability telemetry and trigger rollbacks when deployments caused trouble. We knew we could do more to eliminate the friction involved in its setup. Deploying with confidence shouldn't require a coordination meeting between DevOps, SREs, and developers just to configure the right health checks. That’s why we’re introducing the next generation: AI Verification and Rollback.