Over 160 production-ready skill documents (SKILL.md) for LLM coding agents like Claude Code, Cursor, and Codex.Each skill contains expert-level configs, CLI commands, troubleshooting guides, and ready-to-run scripts spanning six domains: DevOps (CI/CD, Kubernetes, observability), Security (vulnerability scanning, secrets, hardening), Infrastructure (AWS/Azure/GCP, networking, databases, local inference stacks), LLM engineering (agent evals, RAG infrastructure, inference scaling), Compliance (SOC2, HIPAA, GDPR, ISO 27001), and IT operations. Skills install in under a minute via the `npx skills add` CLI or a simple git clone, and the agent discovers, matches, and activates them on demand.
- Ships with notable niche skills absent from other repos: MCP server security, eBPF kernel-level observability, OpenTofu migration, agent-eval CI/CD gates, and multi-tenant LLM hosting with KEDA autoscaling.
- Ships with notable niche skills absent from other repos: MCP server security, eBPF kernel-level observability, OpenTofu migration, agent-eval CI/CD gates, and multi-tenant LLM hosting with KEDA autoscaling.
The article explores a real-world architectural shift where specialized data tools—Redis for caching/pub-sub, Elasticsearch for search, and Kafka for event streaming—were consolidated into a single database engine: PostgreSQL. The primary motivation was to reduce operational complexity, simplify the infrastructure stack, and minimize the cognitive load on developers by managing one unified system instead of several distributed ones.
Summary points:
- Consolidating specialized tools into PostgreSQL reduces overhead in deployment, monitoring, and data synchronization.
- Modern Postgres features like GIN indexes and Full Text Search can effectively substitute for Elasticsearch in many use cases.
- Utilizing Postgres's LISTEN/NOTIFY or simple table structures can replace lightweight pub-sub needs previously handled by Redis or Kafka.
Summary points:
- Consolidating specialized tools into PostgreSQL reduces overhead in deployment, monitoring, and data synchronization.
- Modern Postgres features like GIN indexes and Full Text Search can effectively substitute for Elasticsearch in many use cases.
- Utilizing Postgres's LISTEN/NOTIFY or simple table structures can replace lightweight pub-sub needs previously handled by Redis or Kafka.
At GrafanaCON 2026, Grafana Labs announced significant updates including the launch of Grafana 13 and a major architectural overhaul for Loki. The new Loki design moves away from replication-at-ingestion toward using Kafka as a durability layer to reduce data duplication and improve query performance. Additionally, the company introduced GCX, a new CLI tool in public preview designed to integrate observability data directly into agentic development environments like Claude Code and Cursor, allowing engineers to resolve production issues without leaving their coding tools.
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- Loki rearchitected with Kafka to reduce storage overhead and improve query speed.
- Introduction of GCX CLI for seamless observability integration within AI coding agents.
- Launch of Grafana 13 featuring dynamic dashboards and expanded data source support.
- New AI Observability product in public preview for monitoring LLM applications.
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- Loki rearchitected with Kafka to reduce storage overhead and improve query speed.
- Introduction of GCX CLI for seamless observability integration within AI coding agents.
- Launch of Grafana 13 featuring dynamic dashboards and expanded data source support.
- New AI Observability product in public preview for monitoring LLM applications.
This article examines the development of Microsoft’s Azure SRE Agent, designed to mitigate operational toil in mission-critical environments. By utilizing an "agentic workflow" of specialized AI agents, Microsoft has integrated automation across the entire software development lifecycle. This human-AI partnership has autonomously resolved over 35,000 incidents and saved more than 50,000 developer hours, accelerating root cause analysis and mitigation while maintaining rigorous governance and human oversight.
This article details how HPE is addressing operational fatigue and burnout in IT teams through the introduction of agentic AI operations. HPE's new system utilizes skills-based AI agents that work alongside human operators to reduce alert noise, improve response times, and cut root cause analysis time by at least half, according to early adopters.
The focus is on augmenting human capabilities rather than replacing them, with a strong emphasis on auditability, transparency, and human oversight in AI-driven actions. The system aims to break down data silos and provide proactive insights to prevent issues before they escalate.
The focus is on augmenting human capabilities rather than replacing them, with a strong emphasis on auditability, transparency, and human oversight in AI-driven actions. The system aims to break down data silos and provide proactive insights to prevent issues before they escalate.
This article discusses how AI is changing infrastructure as code (IaC) and the challenges it presents. Spacelift's co-founder, Marcin Wyszynski, explains that while AI tools can democratize infrastructure provisioning, the lack of understanding of the generated code poses risks. He draws a parallel to learning a foreign language – AI can produce the code, but teams need to comprehend it to avoid potentially disastrous infrastructure changes.
Spacelift's solution, Intent, focuses on deterministic guardrails and integration with tools like Open Policy Agent to ensure safe and controlled AI-driven infrastructure management. The core challenge is balancing speed and control in a rapidly evolving landscape.
Spacelift's solution, Intent, focuses on deterministic guardrails and integration with tools like Open Policy Agent to ensure safe and controlled AI-driven infrastructure management. The core challenge is balancing speed and control in a rapidly evolving landscape.
>When deployed strategically, agents can empower SREs to offload low-risk, toilsome tasks so they can focus on the most critical matters.
Agents in practice include:
* **Contextual Information:** Providing SREs with details from previously resolved incidents involving the same service, including responder notes.
* **Root Cause Analysis:** Suggesting potential origins of an issue and identifying recent configuration changes that might be responsible.
* **Automated Remediation:** Handling low-risk, well-defined issues without human intervention, with SRE review of after-action reports.
* **Diagnostic Suggestions:** Nudging SREs towards running specific diagnostics for partially understood incidents and supplying them automatically.
* **Runbook Generation:** Automatically creating and updating runbooks based on successful remediation steps, preventing recurring issues.
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Agents in practice include:
* **Contextual Information:** Providing SREs with details from previously resolved incidents involving the same service, including responder notes.
* **Root Cause Analysis:** Suggesting potential origins of an issue and identifying recent configuration changes that might be responsible.
* **Automated Remediation:** Handling low-risk, well-defined issues without human intervention, with SRE review of after-action reports.
* **Diagnostic Suggestions:** Nudging SREs towards running specific diagnostics for partially understood incidents and supplying them automatically.
* **Runbook Generation:** Automatically creating and updating runbooks based on successful remediation steps, preventing recurring issues.
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Tap these Model Context Protocol servers to supercharge your AI-assisted coding tools with powerful devops automation capabilities.
* **GitHub MCP Server:** Enables interaction with repositories, issues, pull requests, and CI/CD via GitHub Actions.
* **Notion MCP Server:** Allows AI access to notes and documentation within Notion workspaces.
* **Atlassian Remote MCP Server:** Connects AI tools with Jira and Confluence for project management and collaboration. (Currently in beta)
* **Argo CD MCP Server:** Facilitates interaction with Argo CD for GitOps workflows.
* **Grafana MCP Server:** Provides access to observability data from Grafana dashboards.
* **Terraform MCP Server:** Enables AI-driven Terraform configuration generation and management. (Local use only currently)
* **GitLab MCP Server:** Allows AI to gather project information and perform operations within GitLab. (Currently in beta, Premium/Ultimate customers only)
* **Snyk MCP Server:** Integrates security scanning into AI-assisted DevOps workflows.
* **AWS MCP Servers:** A range of servers for interacting with various AWS services.
* **Pulumi MCP Server:** Enables AI interaction with Pulumi organizations and infrastructure.
* **GitHub MCP Server:** Enables interaction with repositories, issues, pull requests, and CI/CD via GitHub Actions.
* **Notion MCP Server:** Allows AI access to notes and documentation within Notion workspaces.
* **Atlassian Remote MCP Server:** Connects AI tools with Jira and Confluence for project management and collaboration. (Currently in beta)
* **Argo CD MCP Server:** Facilitates interaction with Argo CD for GitOps workflows.
* **Grafana MCP Server:** Provides access to observability data from Grafana dashboards.
* **Terraform MCP Server:** Enables AI-driven Terraform configuration generation and management. (Local use only currently)
* **GitLab MCP Server:** Allows AI to gather project information and perform operations within GitLab. (Currently in beta, Premium/Ultimate customers only)
* **Snyk MCP Server:** Integrates security scanning into AI-assisted DevOps workflows.
* **AWS MCP Servers:** A range of servers for interacting with various AWS services.
* **Pulumi MCP Server:** Enables AI interaction with Pulumi organizations and infrastructure.
Platform Engineering Labs has released formae, an open-source infrastructure-as-code platform designed to address limitations in existing tools, focusing on automatic discovery, codification of existing infrastructure, and a reconcile/patch workflow. It uses PKL instead of HCL and targets reducing drift and complexity.
