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sec-design.md

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Okay, let's create a design document for the Airflow Helm Chart project.

BUSINESS POSTURE

Business Priorities and Goals:

  • Provide a simplified and standardized way to deploy and manage Apache Airflow on Kubernetes.
  • Enable scalability and high availability for Airflow deployments.
  • Reduce the operational overhead of managing Airflow infrastructure.
  • Provide a customizable and configurable deployment solution to meet diverse user needs.
  • Foster community contributions and maintain an up-to-date, reliable Helm chart.
  • Support different Airflow versions and Kubernetes versions.

Most Important Business Risks:

  • Deployment failures or misconfigurations leading to Airflow downtime and disruption of data pipelines.
  • Security vulnerabilities in the Helm chart or its dependencies exposing sensitive data or allowing unauthorized access.
  • Lack of compatibility with specific Kubernetes distributions or versions, limiting adoption.
  • Inadequate documentation or support, hindering user adoption and troubleshooting.
  • Failure to keep up with updates in Airflow or Kubernetes, leading to outdated and potentially vulnerable deployments.
  • Inability to scale Airflow resources to meet growing data processing demands.

SECURITY POSTURE

Existing Security Controls:

  • security control: Use of Helm, a package manager for Kubernetes, which allows for versioned releases and controlled deployments. (Described in Helm documentation and chart's Chart.yaml)
  • security control: Templating of Kubernetes resources, enabling parameterization and customization of security settings (e.g., resource limits, network policies). (Described in chart's templates directory)
  • security control: Support for configuring resource requests and limits for Airflow components, preventing resource exhaustion attacks. (Described in chart's values.yaml)
  • security control: Ability to configure network policies to restrict traffic flow between Airflow components and external services. (Described in chart's values.yaml)
  • security control: Option to enable TLS encryption for communication between Airflow components and the web interface. (Described in chart's values.yaml)
  • security control: Support for using existing secrets or creating new secrets for sensitive information (e.g., database passwords, API keys). (Described in chart's values.yaml)
  • security control: Ability to define Pod Security Context and Security Context Constraints (SCCs) for enhanced pod security. (Described in chart's values.yaml)
  • security control: Regular updates and releases to address security vulnerabilities in dependencies. (Tracked in GitHub repository and release notes)
  • security control: Community contributions and reviews, providing additional scrutiny and security improvements. (Visible in GitHub pull requests and issues)

Accepted Risks:

  • accepted risk: Reliance on third-party container images (e.g., apache/airflow, database images). Vulnerabilities in these images could impact the security of the deployment.
  • accepted risk: Default configurations may not be suitable for all environments and require customization for optimal security.
  • accepted risk: The complexity of Airflow and Kubernetes introduces a potential for misconfiguration, leading to security weaknesses.
  • accepted risk: Users are responsible for managing their own secrets and ensuring their confidentiality.

Recommended Security Controls:

  • security control: Implement a robust vulnerability scanning process for container images used in the chart.
  • security control: Integrate security linters and static analysis tools into the chart's CI/CD pipeline.
  • security control: Provide detailed security documentation and best practices for deploying the chart securely.
  • security control: Implement Role-Based Access Control (RBAC) within the Airflow deployment to limit user permissions.
  • security control: Enable audit logging for Kubernetes and Airflow to track security-relevant events.
  • security control: Regularly review and update network policies to ensure least privilege access.
  • security control: Provide examples and guidance for integrating with external authentication providers (e.g., LDAP, OAuth).

Security Requirements:

  • Authentication:
    • The chart should support secure authentication mechanisms for accessing the Airflow web interface and API.
    • Integration with external identity providers (e.g., LDAP, OAuth) should be possible.
    • Support for strong password policies and multi-factor authentication is desirable.
  • Authorization:
    • The chart should support role-based access control (RBAC) to restrict user permissions within Airflow.
    • Fine-grained access control to specific DAGs and resources should be possible.
  • Input Validation:
    • The chart itself does not handle user input directly, as it's a deployment tool. However, Airflow itself, once deployed, should implement proper input validation for DAG definitions and user-provided parameters to prevent code injection vulnerabilities.
  • Cryptography:
    • The chart should support TLS encryption for all communication channels (web interface, API, inter-component communication).
    • Sensitive data (e.g., passwords, API keys) should be stored securely using Kubernetes secrets.
    • Support for encrypting data at rest (e.g., database encryption) should be configurable.

DESIGN

C4 CONTEXT

graph LR
    subgraph "Airflow Ecosystem"
      direction LR
      airflow["Apache Airflow (Helm Chart)"]
    end

    users["Users/Administrators"] --> airflow
    dags["DAGs & Plugins"] --> airflow
    external_systems["External Systems (Data Sources/Sinks)"] <..> airflow
    monitoring_tools["Monitoring Tools"] --> airflow
    k8s["Kubernetes Cluster"] <..> airflow

    classDef default fill:#fff,stroke:#000,stroke-width:1px;
    class airflow default
    class users,dags,external_systems,monitoring_tools,k8s default
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Element Descriptions:

  • Element:
    • Name: Users/Administrators
    • Type: Person
    • Description: Individuals who interact with Airflow to create, manage, and monitor data pipelines.
    • Responsibilities: Define DAGs, configure Airflow settings, monitor pipeline execution, troubleshoot issues.
    • Security controls: Authentication, Authorization (RBAC).
  • Element:
    • Name: DAGs & Plugins
    • Type: Software System
    • Description: User-defined data pipelines and custom plugins that extend Airflow's functionality.
    • Responsibilities: Define the workflow of data processing tasks, interact with external systems.
    • Security controls: Code review, static analysis, input validation (within DAG code).
  • Element:
    • Name: External Systems (Data Sources/Sinks)
    • Type: Software System
    • Description: External systems that Airflow interacts with, such as databases, cloud storage, message queues, etc.
    • Responsibilities: Provide data to Airflow or receive data from Airflow.
    • Security controls: Authentication, authorization, encryption in transit, encryption at rest (managed by the external system).
  • Element:
    • Name: Monitoring Tools
    • Type: Software System
    • Description: Tools used to monitor the health and performance of Airflow and its components.
    • Responsibilities: Collect metrics, logs, and alerts.
    • Security controls: Authentication, authorization (managed by the monitoring tool).
  • Element:
    • Name: Kubernetes Cluster
    • Type: Infrastructure
    • Description: The Kubernetes cluster where Airflow is deployed.
    • Responsibilities: Provide the compute, storage, and networking resources for Airflow.
    • Security controls: Kubernetes security best practices (RBAC, network policies, pod security policies, etc.).
  • Element:
    • Name: Apache Airflow (Helm Chart)
    • Type: Software System
    • Description: The Helm chart that deploys and manages Airflow on Kubernetes.
    • Responsibilities: Deploy Airflow components, configure settings, manage upgrades.
    • Security controls: Helm security features, templating, resource limits, network policies, TLS encryption, secret management.

C4 CONTAINER

graph LR
    subgraph "Apache Airflow (Helm Chart)"
      direction TB
      webserver["Webserver"]
      scheduler["Scheduler"]
      worker["Worker(s)"]
      database["Database"]
      redis["Redis (Optional)"]
      flower["Flower (Optional)"]

      webserver <..> scheduler
      scheduler <..> worker
      worker <..> database
      scheduler <..> database
      webserver <..> database
      worker --> external_systems["External Systems"]
      scheduler --> external_systems
      flower <..> worker
      redis <..> scheduler
      redis <..> worker

      dags["DAGs & Plugins"] --> worker
      dags --> scheduler
      users["Users/Administrators"] --> webserver
      users --> flower
      monitoring_tools["Monitoring Tools"] --> webserver
      monitoring_tools --> scheduler
      monitoring_tools --> worker
      monitoring_tools --> database
      monitoring_tools --> redis
      monitoring_tools --> flower
    end

    classDef default fill:#fff,stroke:#000,stroke-width:1px;
    class webserver,scheduler,worker,database,redis,flower,dags,users,external_systems,monitoring_tools default
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Element Descriptions:

  • Element:
    • Name: Webserver
    • Type: Web Application
    • Description: Provides the user interface for interacting with Airflow.
    • Responsibilities: Serve the web UI, handle user authentication, display DAG status, allow triggering of DAG runs.
    • Security controls: Authentication, authorization, TLS encryption, session management.
  • Element:
    • Name: Scheduler
    • Type: Application
    • Description: Schedules and triggers DAG runs based on defined schedules and dependencies.
    • Responsibilities: Monitor DAG status, schedule tasks, trigger worker processes.
    • Security controls: Authentication (internal), authorization (internal), secure communication with workers and database.
  • Element:
    • Name: Worker(s)
    • Type: Application
    • Description: Execute the tasks defined in DAGs.
    • Responsibilities: Run tasks, interact with external systems, report task status.
    • Security controls: Authentication (internal), authorization (internal), secure communication with scheduler and database, input validation (within DAG code).
  • Element:
    • Name: Database
    • Type: Database
    • Description: Stores metadata about DAGs, tasks, and execution history.
    • Responsibilities: Persist Airflow metadata.
    • Security controls: Authentication, authorization, encryption at rest, encryption in transit, database security best practices.
  • Element:
    • Name: Redis (Optional)
    • Type: Cache/Message Queue
    • Description: Used as a message broker for CeleryExecutor and/or as a result backend.
    • Responsibilities: Facilitate communication between scheduler and workers, store task results.
    • Security controls: Authentication, TLS encryption, access control.
  • Element:
    • Name: Flower (Optional)
    • Type: Web Application
    • Description: Provides a web-based monitoring tool for Celery workers.
    • Responsibilities: Display worker status, task details, and logs.
    • Security controls: Authentication, authorization, TLS encryption.
  • Element:
    • Name: DAGs & Plugins
    • Type: Software System
    • Description: User-defined data pipelines and custom plugins that extend Airflow's functionality.
    • Responsibilities: Define the workflow of data processing tasks, interact with external systems.
    • Security controls: Code review, static analysis, input validation (within DAG code).
  • Element:
    • Name: Users/Administrators
    • Type: Person
    • Description: Individuals who interact with Airflow to create, manage, and monitor data pipelines.
    • Responsibilities: Define DAGs, configure Airflow settings, monitor pipeline execution, troubleshoot issues.
    • Security controls: Authentication, Authorization (RBAC).
  • Element:
    • Name: External Systems
    • Type: Software System
    • Description: External systems that Airflow interacts with, such as databases, cloud storage, message queues, etc.
    • Responsibilities: Provide data to Airflow or receive data from Airflow.
    • Security controls: Authentication, authorization, encryption in transit, encryption at rest (managed by the external system).
  • Element:
    • Name: Monitoring Tools
    • Type: Software System
    • Description: Tools used to monitor the health and performance of Airflow and its components.
    • Responsibilities: Collect metrics, logs, and alerts.
    • Security controls: Authentication, authorization (managed by the monitoring tool).

DEPLOYMENT

Possible Deployment Solutions:

  1. Standard Kubernetes Deployment: Deploying Airflow components as standard Kubernetes Deployments and Services.
  2. StatefulSet Deployment: Using StatefulSets for components that require persistent storage (e.g., database).
  3. Helm Operator: Using the Helm Operator to manage the Airflow deployment as a custom resource.

Chosen Solution (Standard Kubernetes Deployment):

graph LR
    subgraph "Kubernetes Cluster"
      direction TB
      subgraph "Namespace: airflow"
        direction TB
        webserver_deployment["Webserver Deployment"]
        webserver_service["Webserver Service"]
        scheduler_deployment["Scheduler Deployment"]
        scheduler_service["Scheduler Service"]
        worker_deployment["Worker Deployment(s)"]
        worker_service["Worker Service"]
        database_deployment["Database Deployment"]
        database_service["Database Service"]
        redis_deployment["Redis Deployment (Optional)"]
        redis_service["Redis Service (Optional)"]
        flower_deployment["Flower Deployment (Optional)"]
        flower_service["Flower Service (Optional)"]
        ingress["Ingress"]

        webserver_deployment -- Pods --> webserver_service
        scheduler_deployment -- Pods --> scheduler_service
        worker_deployment -- Pods --> worker_service
        database_deployment -- Pods --> database_service
        redis_deployment -- Pods --> redis_service
        flower_deployment -- Pods --> flower_service

        ingress --> webserver_service
        ingress --> flower_service

        pv["Persistent Volume(s)"]
        pvc_database["PersistentVolumeClaim (Database)"] --> database_deployment
        pvc_logs["PersistentVolumeClaim (Logs)"] --> worker_deployment
        pvc_logs --> scheduler_deployment
        pvc_logs --> webserver_deployment
        pvc_database --> pv
        pvc_logs --> pv

        secret["Secrets"]
        secret --> webserver_deployment
        secret --> scheduler_deployment
        secret --> worker_deployment
        secret --> database_deployment
        secret --> redis_deployment

      end
    end

    classDef default fill:#fff,stroke:#000,stroke-width:1px;
    class webserver_deployment,webserver_service,scheduler_deployment,scheduler_service,worker_deployment,worker_service,database_deployment,database_service,redis_deployment,redis_service,flower_deployment,flower_service,ingress,pv,pvc_database,pvc_logs,secret default
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Element Descriptions:

  • Element:
    • Name: Webserver Deployment
    • Type: Kubernetes Deployment
    • Description: Manages the Airflow webserver pods.
    • Responsibilities: Ensure the desired number of webserver pods are running, handle updates and rollbacks.
    • Security controls: Resource limits, pod security context.
  • Element:
    • Name: Webserver Service
    • Type: Kubernetes Service
    • Description: Provides a stable endpoint for accessing the webserver.
    • Responsibilities: Load balance traffic to webserver pods.
    • Security controls: Network policies.
  • Element:
    • Name: Scheduler Deployment
    • Type: Kubernetes Deployment
    • Description: Manages the Airflow scheduler pods.
    • Responsibilities: Ensure the desired number of scheduler pods are running, handle updates and rollbacks.
    • Security controls: Resource limits, pod security context.
  • Element:
    • Name: Scheduler Service
    • Type: Kubernetes Service
    • Description: Provides a stable endpoint for accessing the scheduler.
    • Responsibilities: Load balance traffic to scheduler pods (if multiple schedulers are deployed).
    • Security controls: Network policies.
  • Element:
    • Name: Worker Deployment(s)
    • Type: Kubernetes Deployment
    • Description: Manages the Airflow worker pods.
    • Responsibilities: Ensure the desired number of worker pods are running, handle updates and rollbacks.
    • Security controls: Resource limits, pod security context.
  • Element:
    • Name: Worker Service
    • Type: Kubernetes Service
    • Description: Provides a stable endpoint for accessing the workers.
    • Responsibilities: Load balance traffic to worker pods.
    • Security controls: Network policies.
  • Element:
    • Name: Database Deployment
    • Type: Kubernetes Deployment (or StatefulSet)
    • Description: Manages the database pods.
    • Responsibilities: Ensure the desired number of database pods are running, handle updates and rollbacks.
    • Security controls: Resource limits, pod security context, persistent volume claims.
  • Element:
    • Name: Database Service
    • Type: Kubernetes Service
    • Description: Provides a stable endpoint for accessing the database.
    • Responsibilities: Load balance traffic to database pods (if multiple database instances are deployed).
    • Security controls: Network policies.
  • Element:
    • Name: Redis Deployment (Optional)
    • Type: Kubernetes Deployment (or StatefulSet)
    • Description: Manages the Redis pods.
    • Responsibilities: Ensure the desired number of Redis pods are running, handle updates and rollbacks.
    • Security controls: Resource limits, pod security context, persistent volume claims (if persistence is enabled).
  • Element:
    • Name: Redis Service (Optional)
    • Type: Kubernetes Service
    • Description: Provides a stable endpoint for accessing Redis.
    • Responsibilities: Load balance traffic to Redis pods.
    • Security controls: Network policies.
  • Element:
    • Name: Flower Deployment (Optional)
    • Type: Kubernetes Deployment
    • Description: Manages the Flower pods.
    • Responsibilities: Ensure the desired number of Flower pods are running, handle updates and rollbacks.
    • Security controls: Resource limits, pod security context.
  • Element:
    • Name: Flower Service (Optional)
    • Type: Kubernetes Service
    • Description: Provides a stable endpoint for accessing Flower.
    • Responsibilities: Load balance traffic to Flower pods.
    • Security controls: Network policies.
  • Element:
    • Name: Ingress
    • Type: Kubernetes Ingress
    • Description: Exposes the webserver and Flower services to external traffic.
    • Responsibilities: Route external traffic to the appropriate services based on hostnames or paths.
    • Security controls: TLS termination, ingress controller security settings.
  • Element:
    • Name: Persistent Volume(s)
    • Type: Kubernetes Persistent Volume
    • Description: Provides persistent storage for the database and logs.
    • Responsibilities: Store data that needs to be persisted across pod restarts.
    • Security controls: Storage class security settings, access modes.
  • Element:
    • Name: PersistentVolumeClaim (Database)
    • Type: Kubernetes PersistentVolumeClaim
    • Description: Requests persistent storage for the database.
    • Responsibilities: Bind to a PersistentVolume.
    • Security controls: Access modes, storage class.
  • Element:
    • Name: PersistentVolumeClaim (Logs)
    • Type: Kubernetes PersistentVolumeClaim
    • Description: Requests persistent storage for Airflow logs.
    • Responsibilities: Bind to a PersistentVolume.
    • Security controls: Access modes, storage class.
  • Element:
    • Name: Secrets
    • Type: Kubernetes Secret
    • Description: Stores sensitive information (e.g., passwords, API keys).
    • Responsibilities: Provide secrets to pods.
    • Security controls: Kubernetes secret management best practices.

BUILD

graph LR
    subgraph "Build Process"
    developer["Developer"] --> git_repo["Git Repository (GitHub)"]
    git_repo --> ci_cd["CI/CD Pipeline (GitHub Actions)"]
    ci_cd --> linting["Linting (yamale, helm lint)"]
    linting --> tests["Tests (Unit Tests)"]
    tests --> package["Package (helm package)"]
    package --> chart_repo["Chart Repository (GitHub Releases, Artifact Hub)"]
    end

    classDef default fill:#fff,stroke:#000,stroke-width:1px;
    class developer,git_repo,ci_cd,linting,tests,package,chart_repo default
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Build Process Description:

  1. Developers commit changes to the Helm chart source code in the GitHub repository.
  2. GitHub Actions (CI/CD pipeline) is triggered on push or pull request events.
  3. Linting: The pipeline runs linters (e.g., yamale for YAML validation, helm lint for Helm chart validation) to check for syntax errors and best practices.
  4. Tests: Unit tests are executed to verify the functionality of the chart templates and helper functions.
  5. Package: If linting and tests pass, the Helm chart is packaged using helm package.
  6. Chart Repository: The packaged chart is published to a chart repository (e.g., GitHub Releases, Artifact Hub).

Security Controls:

  • security control: Linting (yamale, helm lint) to enforce coding standards and prevent common errors.
  • security control: Unit tests to verify the functionality of the chart and prevent regressions.
  • security control: CI/CD pipeline (GitHub Actions) to automate the build and release process, ensuring consistency and reducing manual errors.
  • security control: Versioned releases of the Helm chart, allowing users to track changes and roll back to previous versions if necessary.
  • security control: Use of a well-defined release process (e.g., semantic versioning) to manage changes and communicate updates to users.

RISK ASSESSMENT

Critical Business Processes:

  • Data pipeline execution and management.
  • Data ingestion, transformation, and loading.
  • Workflow orchestration and scheduling.
  • Monitoring and alerting of data pipeline status.

Data Sensitivity:

  • Metadata about DAGs, tasks, and execution history (stored in the database): Potentially sensitive, depending on the nature of the data pipelines. Could include information about data sources, destinations, and transformations.
  • DAG code and plugins: May contain sensitive information such as API keys, credentials, or business logic.
  • Logs: May contain sensitive data depending on what is being logged by the DAGs.
  • Configuration files: May contain sensitive information such as database connection strings, passwords, and API keys.

QUESTIONS & ASSUMPTIONS

Questions:

  • What specific Kubernetes distributions and versions are targeted for support?
  • What are the expected resource requirements (CPU, memory, storage) for typical Airflow deployments?
  • Are there any specific security certifications or compliance requirements that need to be met?
  • What is the process for handling security vulnerabilities discovered in the chart or its dependencies?
  • What level of support and maintenance is provided for the chart?
  • What external authentication providers should be supported out of the box?
  • What are the requirements for audit logging?

Assumptions:

  • BUSINESS POSTURE: The primary goal is to provide a reliable and easy-to-use Helm chart for deploying Airflow on Kubernetes. Cost optimization is a secondary concern.
  • SECURITY POSTURE: Users are responsible for securing their Kubernetes cluster and external systems. The chart provides reasonable default security settings, but users may need to customize them based on their specific requirements.
  • DESIGN: The standard Kubernetes deployment model is sufficient for most use cases. The chart will support optional features like Redis and Flower. Users will manage their own DAGs and plugins.