Operations | Monitoring | ITSM | DevOps | Cloud

Seer fixes Seer: How Seer pointed us toward a bug and helped fix an outage

Seer is our AI agent that takes bugs and uses all of the context Sentry has to find the root cause and suggest a fix. We use it all the time to help us improve Sentry. Seer fixes Sentry. More recently, Seer has been helping us fix itself — Seer fixing Seer. An upstream outage triggered a bit of an avalanche, revealing a bug that had been hiding away for months. When it came time to fix it, Seer pointed us exactly where we needed to look.

Harness AI for Argo CD

Managing GitOps at scale shouldn’t feel like an endless game of "Whac-A-Mole." In this 3-minute demo, we show how Harness AI moves beyond simple syncs to provide agentic troubleshooting and automated orchestration for your entire GitOps estate. Watch as we use the Harness DevOps Agent to: Identify Common Failure Patterns: Instead of clicking through individual clusters, we ask the AI to analyze 4 out-of-sync applications simultaneously.

FinOps Leaders Who Will Win The AI Era Are Already Experimenting

Engineering teams are shipping faster than ever. AI coding tools like Claude Code and OpenAI’s Codex have quietly removed some of the biggest friction points in the development cycle — and the result is that FinOps teams are being asked to keep up with a pace most practitioners haven’t fully reckoned with yet. That acceleration has a cost consequence. More shipping means more services, more experiments, more infrastructure spun up without review cycles.

Architecting MCP for AI Agents: Lessons from Our Redesign | Harness Blog

-- Key Takeaways: The Harness MCP server is an MCP-compatible interface that lets AI agents discover, query, and act on Harness resources across CI/CD, GitOps, Feature Flags, Cloud Cost Management, Security Testing, Resilience Testing, Internal Developer Portal, and more. -- The first wave of MCP servers followed a natural pattern: take every API endpoint, wrap it in a tool definition, and expose it to the LLM.

Claude Code + Lightrun MCP: Your AI Agent Now Has Live Runtime Vision

Claude Code, Anthropic’s coding agent, now integrates with Lightrun through MCP. AI code assistants have been flying blind. Google Dora’ 2025 report found it is causing, an almost 10% increase in code instability. Even with up to 1M tokens of context available in Claude, this powerful agenti cannot see how the code it writes actually behaves inside a live system under real traffic, real dependencies, and under a load of 10,000 requests per second.

AI Assistant for Calico: Troubleshooting at the Speed of Thought

Despite the wealth of data available, distilling a coherent narrative from a Kubernetes cluster remains a challenge for modern infrastructure teams. Even with powerful visualization tools like the Policy Board, Service Graph, and specialized dashboards, users often find themselves spending significant time piecing together context across different screens.