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Checkly SRE Bot: Intelligent Incident Response System

Project Vision

An intelligent, real-time incident management system that transforms raw alerts into actionable insights by automatically aggregating and analyzing contextual data from relevant sources, reducing human effort and accelerating response.

Core Value Proposition

  • Reduce MTTR through automated, proactive context gathering and analysis
  • Eliminate initial context gathering during incidents with real-time data integration
  • Provide intelligent, AI-powered insights that guide response actions effectively

Key Features

  1. Proactive Context Collection
    • Automatically gathers pertinent incident data as soon as an alert is triggered.
    • Integrates data from multiple systems (e.g., GitHub, logs, traces) in real time.
  2. Intelligent Analysis
    • Employs AI-driven analysis to assess context, prioritize critical data, and provide probable root cause insights.
    • Integrates a follow-up assistant to handle user queries, refining and extending initial insights.
  3. Seamless Integration
    • Modular plugin-based architecture allowing easy extensibility with additional tools.
    • Native integrations with Checkly and options for expanding to other DevOps tools like Grafana or Datadog.
    • Multi-channel support, with initial Slack integration for real-time incident collaboration.

System Structure

  1. Input Layer
    • Alert Ingestion: Triggers from Checkly and other sources to initiate incident response.
    • Authentication: Ensures secure data flow and plugin access.
    • Initial Processing: Standardizes incoming data for streamlined handling by downstream layers.
  2. Intelligence Layer
    • Context Aggregation: Aggregates and organizes data from plugins via a key-value-based Context Store.
    • AI Analysis: Utilizes LLMs to analyze, filter, and summarize context into actionable insights.
    • AI Chatbot: Manages follow-up questions and user interactions, refining the context and retrieving relevant data on demand.
  3. Communication Layer
    • Channel Adapter: Integrates with communication tools (initially Slack) for incident updates and user responses.
    • User Interactions: Supports threading, allowing users to query for additional insights directly in incident threads.

Target Outcomes

  1. Operational
    • Faster incident response and MTTR reduction
    • More accurate root cause identification
    • Lower manual investigation load on responders
  2. Strategic
    • Improved system reliability through faster and more accurate incident resolution
    • Optimized resource allocation by reducing on-call demands
    • Enhanced team collaboration by centralizing incident communications
  3. Technical
    • Scalable architecture that supports horizontal expansion
    • Easily extensible platform for additional plugins and data sources
    • Maintainable and modular codebase enabling continuous improvement and community contributions

Success Metrics

  • MTTR Reduction: Percentage decrease in time to incident resolution.
  • Insight Accuracy: Rate of correct root cause identification by the AI.
  • User Engagement: Frequency of follow-up interactions with AI insights and recommendations.
  • System Adoption Rate: Team usage and reliance on the bot during incident management.
  • Integration Effectiveness: Efficiency and relevance of data from integrated tools.

System Context

---
config:
  layout: elk
  elk:
    mergeEdges: true
    nodePlacementStrategy: LINEAR_SEGMENTS
---

graph LR
    subgraph "External"
        Trigger[Webhook Trigger]
        Checkly[Checkly]
        Grafana[Grafana]
        GitHub[GitHub]
    end

    subgraph "Channels"
        Slack[Slack]
        WhatsApp[WhatsApp]
        MSTeams[Microsoft Teams]
    end

    Trigger -- triggers event --> ChecklySREBot[Checkly SRE Bot]

    ChecklySREBot -- retrieves data from --> Grafana
    ChecklySREBot -- retrieves data from --> GitHub
    ChecklySREBot -- retrieves data from --> Checkly

    ChecklySREBot -- sends incident info --> Slack
    ChecklySREBot -- sends incident info --> WhatsApp
    ChecklySREBot -- sends incident info --> MSTeams

    Channels --> User[User]

    style ChecklySREBot fill:#0075FF,stroke:#333
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Checkly SRE Bot

---
config:
  layout: elk
  elk:
    mergeEdges: true
    nodePlacementStrategy: LINEAR_SEGMENTS
---

graph TB
    %% External Systems
    subgraph External[External Systems]
        Checkly[Checkly]
        GitHub[GitHub]
        Grafana[Grafana]
    end

    %% Communication Channels
    subgraph Channels[Communication Channels]
        Slack[Slack]
        Teams[MS Teams]
        WhatsApp[WhatsApp]
    end

    %% Core System
    subgraph ChecklySREBot[Checkly SRE Bot]
        WebhookHandler[Webhook Handler]
        AuthService[Auth Service]
        AIAssistant[AI Assistant]
        ChannelManager[Channel Manager]
        ContextAggregator[Context Aggregator]
        ContextStore[(Context Store)]
    end

    %% Internal Relationships
    WebhookHandler -- Authenticates --> AuthService
    WebhookHandler -- Triggers context collection --> ContextAggregator
    ContextAggregator -- Uses --> ContextStore
    ContextAggregator -- sends context to --> AIAssistant
    AIAssistant <--> ChannelManager
    AIAssistant -- loads context --> ContextStore

    %% External Relationships
    Checkly -- Triggers --> WebhookHandler
    Checkly -- Checks & scripts --> ContextAggregator
    GitHub -- Commit history & PRs --> ContextAggregator
    Grafana -- Metrics & dashboards --> ContextAggregator

    %% Channel Communication
    ChannelManager <--> Slack
    ChannelManager <--> Teams
    ChannelManager <--> WhatsApp
    ChannelManager -- Authenticates --> AuthService

    %% User Communication
    Channels <-- interacts --> User[End User]

    style ChecklySREBot fill:#0075FF
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Context Aggregator & Retriever

---
config:
  layout: elk
  elk:
    mergeEdges: true
    nodePlacementStrategy: LINEAR_SEGMENTS
---

graph TB
    subgraph ContextAggregator[Context Aggregator]
        Collector[Collector]
        PluginManager[Plugin Manager]
        ChecklyPlugin[Checkly Plugin]
        GitHubPlugin[GitHub Plugin]
        GrafanaPlugin[Grafana Plugin]
    end

    subgraph ContextRetriever[Context Retriever]
        Retriever[Retriever]
        Filter[Filter]
    end

    style ContextRetriever fill:#0075FF

    %% Relationships
    Collector -- Uses --> PluginManager
    PluginManager --> ChecklyPlugin
    PluginManager --> GitHubPlugin
    PluginManager --> GrafanaPlugin
    Collector -- stores context --> ContextStore[(Context Store)]
    Retriever -- loads context --> ContextStore
    Retriever -- Uses --> Filter

    style ContextAggregator fill:#0075FF
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AI Assistant

---
config:
  layout: elk
  elk:
    mergeEdges: true
    nodePlacementStrategy: LINEAR_SEGMENTS
---
graph TB

    subgraph AIAssistant[AI Assistant]
        LLM[LLM Interface]
        ThreadManager[Thread Manager]
        PromptManager[Prompt Manager]
        Assistant[Assistant]

        subgraph Tools[Tools]
            AggregatorTool[Aggregator Tool]
            RetrieverTool[Retriever Tool]
            ChecklyTool[Checkly Tool]
        end

        subgraph Prompts[Prompts]
            BasePrompt[System Prompt]
            AnalysisPrompt[Analysis Prompt]
            SummaryPrompt[Summary Prompt]
        end

        subgraph Threads[Threads]
            MessageHistory[Message History]
            MemoryStore[Memory Store]
        end
    end

    %% Relationships
    LLM -- powers --> Assistant
    Assistant -- Uses --> ThreadManager
    Assistant -- Uses --> PromptManager
    Assistant -- Uses --> Tools
    PromptManager -- renders --> Prompts
    ThreadManager -- stores --> Threads


    style AIAssistant fill:#0075FF
    style Tools fill:#051734
    style Prompts fill:#051734
    style Threads fill:#051734
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