Late last year, startup Platform Engineering Labs made waves in the world of Infrastructure as Code (IaC) by introducing a new IaC platform, called Formae, available initially on Amazon Web Services. This week, Platform Engineering Labs‘ platform gets (beta) support from additional cloud platforms, including Google Cloud Platform, Microsoft Azure, Oracle Cloud Infrastructure, and OVHcloud. The company has also released new AI-enhanced software for managing infrastructure tooling, called the Platform for Infrastructure Builders.
>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.
Plural is bringing AI into the DevOps lifecycle with a new release that leverages a unified GitOps platform as a RAG engine. This provides AI-powered troubleshooting, natural language infrastructure querying, autonomous upgrade assistance, and agentic workflows for infrastructure modification, all with enterprise-grade guardrails.
TraceRoot accelerates the debugging process with AI-powered insights. It integrates seamlessly into your development workflow, providing real-time trace and log analysis, code context understanding, and intelligent assistance. It offers both a cloud and self-hosted version, with SDKs available for Python and JavaScript/TypeScript.
The Azure MCP Server implements the MCP specification to create a seamless connection between AI agents and Azure services. It allows agents to interact with various Azure services like AI Search, App Configuration, Cosmos DB, and more.
The article discusses how agentic LLMs can help users overcome the learning curve of the command line interface (CLI) by automating tasks and providing guidance. It explores tools like ShellGPT and Auto-GPT that leverage LLMs to interpret natural language instructions and execute corresponding CLI commands. The author argues that this approach can make the CLI more accessible and powerful, even for those unfamiliar with its intricacies.
This GitHub repository contains a collection of example files demonstrating various use cases and configurations for the llamafiles tools, including examples:
* **System Administration:** Scripts and configurations for Ubuntu, Raspberry Pi 5, and macOS.
* **LLM Interaction:** Examples of prompts and interactions with LLMs like Mixtral and Dolphin.
* **Text Processing:** Scripts for summarizing text, extracting information, and formatting output.
* **Development Tools:** Examples related to Git, Emacs, and other development tools.
* **Hardware Monitoring:** Scripts for monitoring GPU and NVMe drive status.
* **System Administration:** Scripts and configurations for Ubuntu, Raspberry Pi 5, and macOS.
* **LLM Interaction:** Examples of prompts and interactions with LLMs like Mixtral and Dolphin.
* **Text Processing:** Scripts for summarizing text, extracting information, and formatting output.
* **Development Tools:** Examples related to Git, Emacs, and other development tools.
* **Hardware Monitoring:** Scripts for monitoring GPU and NVMe drive status.
"A fully autonomous, AI-powered DevOps platform for managing cloud infrastructure across multiple providers, with AWS and GitHub integration, powered by OpenAI's Agents SDK."
