Mackerel
Integrates Large Language Models (LLMs) with Mackerel for enhanced monitoring and management capabilities.
About
Mackerel facilitates seamless interaction between LLMs and the Mackerel monitoring platform. It acts as a local server, enabling LLMs to execute Mackerel-specific commands, retrieve crucial monitoring data, and even update configurations. This integration empowers users to leverage natural language queries and AI-driven automation for tasks such as fetching alert details, querying host and service metrics, managing dashboards, and analyzing traces, streamlining operational workflows and making monitoring data more accessible through conversational interfaces.
Key Features
- Retrieve Mackerel alerts and their logs programmatically
- Access and update Mackerel dashboards
- List hosts and fetch their associated metrics data
- List services and retrieve their metrics information
- Get monitor configurations and trace data for analysis
- 3 GitHub stars
Use Cases
- Querying monitoring data from Mackerel using AI-driven interfaces
- Automating Mackerel interactions using natural language commands via LLMs
- Updating Mackerel dashboard configurations through conversational AI
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