18 AI tools for DevOps
Expert in backup retention policies, data lifecycle management, and disaster recovery. Optimizes storage and ensures compliance.
AI skill for writing production deployment guides - Kubernetes manifests, CI/CD scripts, rollback, and monitoring configs.
A Redis Cluster expert skill for production configuration, HA topology, performance tuning, and troubleshooting across multiple nodes.
Python skill for building container-based hosted agents in Azure AI Foundry via ImageBasedHostedAgentDefinition and the Projects SDK.
Python SDK for Azure API Center - register APIs, versions, environments, deployments, and governance metadata.
ARM SDK for managing Application Insights components, API keys, web tests, and workbooks in .NET.
.NET management SDK for provisioning Azure Bot Service resources and configuring channels like Teams, DirectLine, and Slack.
Production-ready incident runbook templates: severity levels, service-outage and database-incident playbooks, escalation, and communication scripts.
Designs stress test scenarios across volume, load, memory, CPU, I/O, concurrency and resource depletion, with runnable examples per category.
Manage Apache Ambari Hadoop clusters via natural language - service control, configs, host/alert monitoring, and AMS metrics through MCP tools.
MCP server connecting AI assistants to a Kubernetes cluster - kubectl operations, Helm charts, and node management via natural language.
MCP server exposing Dataverse tools for user/security admin, data operations, metadata exploration, and troubleshooting.
MCP server integrating the LLDB debugger with Claude - start sessions, set breakpoints, inspect memory, and debug crashes.
mcp-containerd manages Containerd via CRI: pods, containers, and images, through 14 tools built on RMCP in Rust.
An MCP server that generates and controls development containers directly from devcontainer.json configuration files.
kill-process-mcp lets AI assistants list and kill OS processes by name, user, CPU, or memory usage via natural language.
