# mlops-devops-04-26/kubernetes-ai-log-analysis-rca-slack-bot architecture

> Architecture diagram of the GitHub repository mlops-devops-04-26/kubernetes-ai-log-analysis-rca-slack-bot, generated by GitDiagram from its file tree, README and a sample of source files (last updated 2026-06-27). It is an AI-made overview: check details against the source.

- Interactive diagram: https://gitdiagram.com/mlops-devops-04-26/kubernetes-ai-log-analysis-rca-slack-bot
- Repository: https://github.com/mlops-devops-04-26/kubernetes-ai-log-analysis-rca-slack-bot

## Overview

1. **Repository purpose**
   - This is a Kubernetes-based demo system for AIOps: a Python Slack bot analyzes cluster logs/telemetry with an LLM, while a sample microservice and load generator create behavior to observe.
   - The repo is organized around three runtime domains: **aiops-bot**, **microservices**, and **monitoring**.

2. **Top-level deployment model**
   - Everything is designed to run inside a **local KIND cluster**.
   - The `kind-config.yaml` and README show several **NodePort mappings** so the cluster can be accessed from the host for Grafana, Prometheus, Alertmanager, and the sample service.
   - The `setup.sh` and `update-deployments.sh` scripts indicate the repo expects repeatable local environment setup and image reference updates.

3. **AIOps bot subsystem**
   - `aiops-bot/` contains a Python service packaged as a Docker image and deployed to Kubernetes with its own `deployment.yaml` and `rbac.yaml`.
   - Its boundary is important: it is not a general app server, but an operator-facing bot that needs Kubernetes read permissions and secret access.
   - It depends on external integrations configured via environment variables/secrets: **Slack Bot Token**, **Slack App Token**, **Slack webhook/channel**, and **HuggingFace API/model**.

4. **Bot data flow**
   - The bot receives Slack commands/events, queries cluster information/logs/metrics, sends prompts to the HuggingFace model API, and returns analysis/RCA back to Slack.
   - The repo structure implies this is the “intelligence” layer that sits between Kubernetes telemetry and Slack notifications.
   - RBAC is a key boundary here: the bot can only do what `rbac.yaml` grants.

5. **Sample workload / microservice subsystem**
   - `microservices/service1/` is the target application workload.
   - It has its own Dockerfile, Python app, requirements, and Kubernetes deployment manifest, meaning it is meant to be deployed independently as a simple observable service.
   - This service provides the system under test for metrics, errors, and log patterns that the bot and monitoring stack can react to.

6. **Load generation subsystem**
   - `load-generator/` is a separate Python containerized workload that likely creates traffic or failure pressure against the sample service.
   - Its role is to stimulate the microservice so the monitoring and RCA pipeline has events to detect.
   - Architecturally it is an upstream producer of load, not a user-facing service.

7. **Observability stack**
   - `monitoring/` contains the Prometheus, Grafana, Alertmanager, and alert-rule configuration.
   - The repository uses a mix of **Helm values** (`prometheus-values.yaml`, `grafana-values.yaml`, `loki-values.yaml`) and raw Kubernetes manifests (`grafana-deployment.yaml`, `prometheus-service.yaml`, `alertmanager-config.yaml`, `ingress.yaml`, etc.).
   - This stack is the telemetry backend that collects metrics, evaluates rules, and visualizes system state.

8. **Alerting and dashboard path**
   - `monitoring/prometheus-rules.yaml` and `monitoring/microservices-alerts.yaml` define the alerting conditions for the system.
   - Prometheus evaluates these rules, Alertmanager receives firing alerts, and Grafana provides visualization/dashboard access.
   - The repo also includes a Grafana dashboard manifest, implying a prebuilt view into the service and cluster behavior.

9. **Logging/metrics boundary**
   - The presence of `loki-values.yaml` indicates logs may also be centralized through Loki in addition to Prometheus metrics.
   - This matters because the RCA bot is described as a log-analysis bot; the architecture likely combines **metrics from Prometheus** with **logs from Loki or Kubernetes logs** for diagnosis.
   - The monitoring layer is therefore the evidence source for the bot’s analysis pipeline.

10. **Infrastructure and runtime assumptions**
   - All application components are Python-based and containerized with Docker.
   - Kubernetes is the runtime, with namespaces separating concerns: `aiops-bot`, `microservices`, and `monitoring`.
   - External services are limited but important: **Slack** for interaction and **HuggingFace Router/API** for LLM inference.

11. **Operational workflow**
   - The README shows a workflow of: build images, push to Docker Hub, patch deployment image references, create a KIND cluster, install monitoring, deploy workloads, then deploy the bot.
   - That means the repo is designed for a **local reproducible demo environment**, not just a single application.
   - The `update-deployments.sh` script is the main coupling point between image publishing and Kubernetes manifests.

12. **CI/CD and automation**
   - The `.github/workflows/main.yml` file indicates at least one GitHub Actions pipeline exists for automated checks/builds/deployment-related tasks.
   - Even without its exact contents, it is part of the repo’s delivery path and likely validates or packages the containerized components.

13. **How to draw the architecture**
   - A good diagram should show:
     - Host machine running Docker, kubectl, Helm, and KIND.
     - Three Kubernetes namespaces or logical zones.
     - The sample service and load generator interacting inside `microservices`.
     - Monitoring components collecting cluster/app telemetry.
     - The bot consuming telemetry/cluster data, calling HuggingFace, and returning results to Slack.
   - The main directional flow is: **load generator → service1 → telemetry/alerts/logs → bot analysis → Slack response**.

Main entry points: [`monitoring/prometheus-values.yaml`](https://github.com/mlops-devops-04-26/kubernetes-ai-log-analysis-rca-slack-bot/blob/main/monitoring/prometheus-values.yaml) (Prometheus), [`aiops-bot/app.py`](https://github.com/mlops-devops-04-26/kubernetes-ai-log-analysis-rca-slack-bot/blob/main/aiops-bot/app.py) (Bot app), [`monitoring`](https://github.com/mlops-devops-04-26/kubernetes-ai-log-analysis-rca-slack-bot/tree/main/monitoring) (Monitoring), [`microservices/service1/app.py`](https://github.com/mlops-devops-04-26/kubernetes-ai-log-analysis-rca-slack-bot/blob/main/microservices/service1/app.py) (Service 1)

## Diagram (Mermaid)

```mermaid
flowchart TD

subgraph group_host["Host machine"]
  node_scripts["Setup scripts<br/>automation<br/>[setup.sh]"]
  node_update_deployments["Image patcher<br/>automation"]
  node_kind_config["KIND config<br/>cluster config<br/>[kind-config.yaml]"]
  node_workflow["CI workflow<br/>github actions<br/>[main.yml]"]
end

subgraph group_cluster["KIND cluster"]
  node_aiops_bot_ns{{"AIOps bot<br/>k8s namespace"}}
  node_bot_app["Bot app<br/>python service<br/>[app.py]"]
  node_bot_rbac["Bot RBAC<br/>k8s access<br/>[rbac.yaml]"]
  node_micro_ns{{"Microservices<br/>k8s namespace"}}
  node_service1["Service 1<br/>python app<br/>[app.py]"]
  node_loadgen["Load generator<br/>python workload<br/>[app.py]"]
  node_monitoring_ns{{"Monitoring<br/>k8s namespace"}}
  node_prometheus[("Prometheus<br/>metrics backend")]
  node_alertmanager["Alertmanager<br/>alert router"]
  node_grafana["Grafana<br/>dashboard"]
  node_loki[("Loki<br/>logs backend<br/>[loki-values.yaml]")]
end

subgraph group_external["External services"]
  node_slack(("Slack<br/>chat platform"))
  node_huggingface(("HuggingFace API<br/>llm inference"))
end

node_scripts -->|"create cluster"| node_kind_config
node_scripts -->|"patch images"| node_update_deployments
node_workflow -.->|"automate"| node_scripts
node_aiops_bot_ns -->|"runs"| node_bot_app
node_aiops_bot_ns -->|"binds"| node_bot_rbac
node_bot_app -->|"commands/responses"| node_slack
node_bot_app -->|"prompts"| node_huggingface
node_bot_app -->|"queries metrics"| node_prometheus
node_bot_app -->|"reads logs"| node_loki
node_bot_rbac -.->|"permits access"| node_prometheus
node_micro_ns -->|"runs"| node_service1
node_micro_ns -->|"runs"| node_loadgen
node_loadgen -->|"triggers traffic"| node_service1
node_service1 -->|"exposes metrics"| node_prometheus
node_service1 -->|"emits logs"| node_loki
node_monitoring_ns -->|"hosts"| node_prometheus
node_monitoring_ns -->|"hosts"| node_alertmanager
node_monitoring_ns -->|"hosts"| node_grafana
node_monitoring_ns -->|"hosts"| node_loki
node_prometheus -->|"fires alerts"| node_alertmanager
node_prometheus -.->|"visualizes"| node_grafana
node_grafana -.->|"operator view"| node_slack

click node_scripts "https://github.com/mlops-devops-04-26/kubernetes-ai-log-analysis-rca-slack-bot/blob/main/setup.sh"
click node_update_deployments "https://github.com/mlops-devops-04-26/kubernetes-ai-log-analysis-rca-slack-bot/blob/main/update-deployments.sh"
click node_kind_config "https://github.com/mlops-devops-04-26/kubernetes-ai-log-analysis-rca-slack-bot/blob/main/kind-config.yaml"
click node_workflow "https://github.com/mlops-devops-04-26/kubernetes-ai-log-analysis-rca-slack-bot/blob/main/.github/workflows/main.yml"
click node_aiops_bot_ns "https://github.com/mlops-devops-04-26/kubernetes-ai-log-analysis-rca-slack-bot/tree/main/aiops-bot"
click node_bot_app "https://github.com/mlops-devops-04-26/kubernetes-ai-log-analysis-rca-slack-bot/blob/main/aiops-bot/app.py"
click node_bot_rbac "https://github.com/mlops-devops-04-26/kubernetes-ai-log-analysis-rca-slack-bot/blob/main/aiops-bot/rbac.yaml"
click node_micro_ns "https://github.com/mlops-devops-04-26/kubernetes-ai-log-analysis-rca-slack-bot/tree/main/microservices"
click node_service1 "https://github.com/mlops-devops-04-26/kubernetes-ai-log-analysis-rca-slack-bot/blob/main/microservices/service1/app.py"
click node_loadgen "https://github.com/mlops-devops-04-26/kubernetes-ai-log-analysis-rca-slack-bot/blob/main/load-generator/app.py"
click node_monitoring_ns "https://github.com/mlops-devops-04-26/kubernetes-ai-log-analysis-rca-slack-bot/tree/main/monitoring"
click node_prometheus "https://github.com/mlops-devops-04-26/kubernetes-ai-log-analysis-rca-slack-bot/blob/main/monitoring/prometheus-values.yaml"
click node_alertmanager "https://github.com/mlops-devops-04-26/kubernetes-ai-log-analysis-rca-slack-bot/blob/main/monitoring/alertmanager-config.yaml"
click node_grafana "https://github.com/mlops-devops-04-26/kubernetes-ai-log-analysis-rca-slack-bot/blob/main/monitoring/grafana-deployment.yaml"
click node_loki "https://github.com/mlops-devops-04-26/kubernetes-ai-log-analysis-rca-slack-bot/blob/main/monitoring/loki-values.yaml"

classDef toneNeutral fill:#f8fafc,stroke:#334155,stroke-width:1.5px,color:#0f172a
classDef toneBlue fill:#dbeafe,stroke:#2563eb,stroke-width:1.5px,color:#172554
classDef toneAmber fill:#fef3c7,stroke:#d97706,stroke-width:1.5px,color:#78350f
classDef toneMint fill:#dcfce7,stroke:#16a34a,stroke-width:1.5px,color:#14532d
classDef toneRose fill:#ffe4e6,stroke:#e11d48,stroke-width:1.5px,color:#881337
classDef toneIndigo fill:#e0e7ff,stroke:#4f46e5,stroke-width:1.5px,color:#312e81
classDef toneTeal fill:#ccfbf1,stroke:#0f766e,stroke-width:1.5px,color:#134e4a
class node_scripts,node_update_deployments,node_kind_config,node_workflow toneBlue
class node_aiops_bot_ns,node_bot_app,node_bot_rbac,node_micro_ns,node_service1,node_loadgen,node_monitoring_ns,node_prometheus,node_alertmanager,node_grafana,node_loki toneAmber
class node_slack,node_huggingface toneMint
```

## Components

### Host machine

Local development machine running the demo tooling and cluster lifecycle scripts

- [Setup scripts](https://github.com/mlops-devops-04-26/kubernetes-ai-log-analysis-rca-slack-bot/blob/main/setup.sh): automation · Build, push, and patch deployment references for repeatable local setup · `setup.sh`
- [Image patcher](https://github.com/mlops-devops-04-26/kubernetes-ai-log-analysis-rca-slack-bot/blob/main/update-deployments.sh): automation · Updates Kubernetes manifests with published image tags · `update-deployments.sh`
- [KIND config](https://github.com/mlops-devops-04-26/kubernetes-ai-log-analysis-rca-slack-bot/blob/main/kind-config.yaml): cluster config · Local cluster topology and NodePort exposure settings · `kind-config.yaml`
- [CI workflow](https://github.com/mlops-devops-04-26/kubernetes-ai-log-analysis-rca-slack-bot/blob/main/.github/workflows/main.yml): github actions · Repository automation for validation/build/deploy tasks · `.github/workflows/main.yml`

### KIND cluster

Local Kubernetes cluster hosting the bot, workloads, and observability stack

- [AIOps bot](https://github.com/mlops-devops-04-26/kubernetes-ai-log-analysis-rca-slack-bot/tree/main/aiops-bot): k8s namespace · Operator-facing Slack bot that analyzes telemetry with an LLM · `aiops-bot`
- [Bot app](https://github.com/mlops-devops-04-26/kubernetes-ai-log-analysis-rca-slack-bot/blob/main/aiops-bot/app.py): python service · Receives Slack events, gathers cluster evidence, and produces RCA responses · `aiops-bot/app.py`
- [Bot RBAC](https://github.com/mlops-devops-04-26/kubernetes-ai-log-analysis-rca-slack-bot/blob/main/aiops-bot/rbac.yaml): k8s access · Kubernetes permissions boundary for reading cluster data and secrets · `aiops-bot/rbac.yaml`
- [Microservices](https://github.com/mlops-devops-04-26/kubernetes-ai-log-analysis-rca-slack-bot/tree/main/microservices): k8s namespace · Sample workload domain used to generate observable behavior · `microservices`
- [Service 1](https://github.com/mlops-devops-04-26/kubernetes-ai-log-analysis-rca-slack-bot/blob/main/microservices/service1/app.py): python app · Observable sample service targeted by load and monitored for failures · `microservices/service1/app.py`
- [Load generator](https://github.com/mlops-devops-04-26/kubernetes-ai-log-analysis-rca-slack-bot/blob/main/load-generator/app.py): python workload · Produces traffic or pressure against the sample service · `load-generator/app.py`
- [Monitoring](https://github.com/mlops-devops-04-26/kubernetes-ai-log-analysis-rca-slack-bot/tree/main/monitoring): k8s namespace · Telemetry and alerting stack for metrics, logs, and dashboards · `monitoring`
- [Prometheus](https://github.com/mlops-devops-04-26/kubernetes-ai-log-analysis-rca-slack-bot/blob/main/monitoring/prometheus-values.yaml): metrics backend · Scrapes metrics and evaluates alert rules · `monitoring/prometheus-values.yaml`
- [Alertmanager](https://github.com/mlops-devops-04-26/kubernetes-ai-log-analysis-rca-slack-bot/blob/main/monitoring/alertmanager-config.yaml): alert router · Receives firing alerts and routes notifications · `monitoring/alertmanager-config.yaml`
- [Grafana](https://github.com/mlops-devops-04-26/kubernetes-ai-log-analysis-rca-slack-bot/blob/main/monitoring/grafana-deployment.yaml): dashboard · Visualizes cluster and workload state through dashboards · `monitoring/grafana-deployment.yaml`
- [Loki](https://github.com/mlops-devops-04-26/kubernetes-ai-log-analysis-rca-slack-bot/blob/main/monitoring/loki-values.yaml): logs backend · Central log store used for log-driven diagnosis · `monitoring/loki-values.yaml`

### External services

Outside integrations used for chat and model inference

- **Slack**: chat platform · User-facing interface for bot commands and analysis responses
- **HuggingFace API**: llm inference · External model endpoint used for prompt-based analysis

## Connections

- Setup scripts → KIND config: create cluster · Uses the KIND config to stand up the local environment
- Setup scripts → Image patcher: patch images · Coordinates image reference updates before deployment
- CI workflow → Setup scripts: automate · Runs repository automation around build and deploy steps
- AIOps bot → Bot app: runs · Namespace hosts the bot container
- AIOps bot → Bot RBAC: binds · Attaches permissions required for cluster and secret access
- Bot app → Slack: commands/responses · Receives requests and posts analysis back to Slack
- Bot app → HuggingFace API: prompts · Sends evidence to the LLM for diagnosis and summarization
- Bot app → Prometheus: queries metrics · Reads cluster and workload telemetry for analysis
- Bot app → Loki: reads logs · Consumes logs when available for RCA context
- Bot RBAC → Prometheus: permits access · Allows the bot to read cluster resources and telemetry sources
- Microservices → Service 1: runs · Namespace hosts the sample application
- Microservices → Load generator: runs · Namespace hosts the traffic generator workload
- Load generator → Service 1: triggers traffic · Generates requests or pressure against the service
- Service 1 → Prometheus: exposes metrics · Service emits signals scraped by the monitoring stack
- Service 1 → Loki: emits logs · Application logs feed centralized log analysis
- Monitoring → Prometheus: hosts · Monitoring namespace contains the metrics backend
- Monitoring → Alertmanager: hosts · Monitoring namespace contains alert routing
- Monitoring → Grafana: hosts · Monitoring namespace contains dashboards
- Monitoring → Loki: hosts · Monitoring namespace contains log storage
- Prometheus → Alertmanager: fires alerts · Alert rules generate notifications when conditions match
- Prometheus → Grafana: visualizes · Grafana dashboards are typically backed by Prometheus data
- Grafana → Slack: operator view · Provides human visibility into system behavior