Datadog plugins

Diagnose performance bottlenecks, implement distributed tracing, and manage incident response with Prometheus, Grafana, OpenTelemetry, and Datadog. Define SLIs/SLOs, run blameless postmortems, and build production-ready observability pipelines for microservices and infrastructure.

Run the full engineering lifecycle from a chat interface: review code, debug issues, design systems, document decisions, manage incidents, and generate standups. Connects to Linear, Jira, Slack, Notion, Datadog, PagerDuty, and Benchling for project management, monitoring, and incident response.

Manage and monitor Datadog resources (monitors, logs, APM traces, dashboards, security signals, SLOs) via CLI commands and specialized agents, enabling observability workflows for infrastructure, applications, and CI/CD pipelines.

Orchestrate the entire AI-assisted development lifecycle with enforced quality gates at every stage—from ticket creation and brainstorming through TDD implementation, parallel code review, PR management, and postmortem analysis.

Run structured product discovery workflows: brainstorm ideas from PM/designer/engineer perspectives, build opportunity solution trees, prioritize features/assumptions with ICE/RICE/risk matrices, design low-cost experiments, generate user interview scripts/summaries per Mom Test/JTBD, and spec metrics dashboards with Markdown outputs.

Generate Google-SRE-style blameless incident postmortems from a tracker URL. The agent gathers evidence from Slack, Datadog, and pull requests, builds a chronological timeline with evidence tags, and writes a markdown document with summary, impact, timeline, root cause, and action items.

Query Datadog logs, metrics, traces, dashboards, alerts, SLOs, and incidents through natural conversation in Claude Code, with setup and tool management skills for the Datadog MCP server.