# Product Description Record (PRD) - k8s-maestro
**Version**: 1.0
**Status**: Active
**Last Updated**: 2026-03-19
## Executive Summary
k8s-maestro is a high-performance, type-safe Rust library for orchestrating complex workflows on Kubernetes. It provides a fluent builder API that abstracts away Kubernetes complexity while maintaining full control over execution. Built with test-driven development principles, k8s-maestro enables developers to define multi-step workflows with dependencies, conditional execution, networking capabilities, and robust error handling.
The library targets developers and DevOps engineers who need to:
- Orchestrate complex data pipelines on Kubernetes
- Implement multi-step job workflows with dependencies
- Expose services and configure ingress for workflow steps
- Manage sidecar containers and advanced networking patterns
- Execute workflows with checkpointing and recovery capabilities
## Vision and Product Goals
### Vision
To be the de facto standard for Kubernetes workflow orchestration in Rust, providing an intuitive, type-safe, and powerful API that simplifies complex workflow management while maintaining Kubernetes native capabilities.
### Product Goals
1. **Developer Experience**: Provide an intuitive, fluent API that abstracts Kubernetes complexity without losing control
2. **Type Safety**: Leverage Rust's type system to catch configuration errors at compile time
3. **Performance**: Support high-throughput workflow execution with minimal overhead
4. **Extensibility**: Enable custom step types, plugins, and integration patterns
5. **Observability**: Provide comprehensive logging, monitoring, and debugging capabilities
6. **Reliability**: Ensure robust error handling, checkpointing, and recovery mechanisms
## Target Audience
### Primary Users
- **Backend Developers**: Building data pipelines, batch processing jobs, and workflow-driven applications on Kubernetes
- **DevOps Engineers**: Orchestrating complex deployment and maintenance workflows
- **Data Engineers**: Managing ETL/ELT pipelines with multi-stage processing
- **Platform Engineers**: Building internal platforms that require workflow orchestration capabilities
### Secondary Users
- **Site Reliability Engineers**: Automating operational tasks and disaster recovery workflows
- **ML Engineers**: Orchestrating ML model training and inference pipelines
- **Security Engineers**: Managing security compliance workflows and audit trails
### User Skill Level
- Intermediate to advanced Rust developers
- Familiarity with Kubernetes concepts (pods, jobs, services, ingress)
- Understanding of container orchestration patterns
- Experience with workflow and pipeline orchestration (Airflow, Argo, etc.)
## Core Features
### Current Features (v1.0.1)
#### Workflow Management
- **Multi-step Workflows**: Define complex workflows with multiple steps and execution order
- **Dependency System**: DAG-based dependency management with conditional execution
- **Workflow Builder**: Fluent API for constructing workflows with validation
- **Parallel Execution**: Configurable parallelism for independent workflow steps
- **Execution Tracking**: Real-time status monitoring and result collection
#### Kubernetes Integration
- **Job Management**: Full Kubernetes Job lifecycle management
- **Pod Management**: Direct Pod execution for custom use cases
- **Service Exposure**: Automatic service creation for workflow steps
- **Ingress Configuration**: Built-in ingress support for external access
- **Resource Management**: CPU, memory, and ephemeral storage limits
#### Step Types
- **KubeJobStep**: Execute Kubernetes Jobs with full configuration
- **KubePodStep**: Execute Kubernetes Pods for custom use cases
- **Sidecar Containers**: Add auxiliary containers to workflow steps
- **File Observer**: Monitor file changes and trigger workflows
#### Networking
- **Service Builder**: Create ClusterIP, NodePort, LoadBalancer, and Headless services
- **Ingress Builder**: Configure ingress with path routing, TLS, and annotations
- **DNS Utilities**: Helper functions for DNS name resolution
- **Network Policies**: Security rules for pod-to-pod communication
#### Security
- **RBAC Builders**: ServiceAccount, Role, RoleBinding, ClusterRole, ClusterRoleBinding
- **Security Contexts**: Pod and container-level security configuration
- **Resource Quotas**: Namespace-level resource limits
- **Network Policies**: Preset security rules (deny_all, allow_all, allow_within_namespace)
#### Storage
- **Volume Builders**: PVC, ConfigMap, Secret, EmptyDir, HostPath volumes
- **Volume Mounts**: Configure container volume mounting
- **Persistent Storage**: Integration with Kubernetes PVCs
#### Workflow Orchestration
- **Workflow Execution Orchestrator**: DAG-based execution with dependency resolution
- **Checkpointing System**: SQLite-based state persistence with configurable frequency
- **Failure Strategies**: Configurable failure handling (stop or continue)
- **Cycle Detection**: Automatic detection of dependency cycles
- **Condition Evaluation**: Conditional execution based on step results
#### Development Tools
- **MaestroClient**: Centralized client with builder pattern configuration
- **Dry Run Mode**: Test workflows without actual execution
- **Comprehensive Logging**: Structured logging with configurable levels
- **Error Handling**: Rich error types with context
### Planned Features
#### v1.1.0
- **CronJob Support**: Scheduled periodic workflows
- **Workflow Reusability**: Workflow templates and composition
- **Event Triggers**: Trigger workflows from Kubernetes events
- **Advanced Retry Logic**: Exponential backoff, custom retry policies
#### v1.2.0
- **Workflow UI**: Web-based workflow visualization and monitoring
- **Metrics Integration**: Prometheus metrics export
- **Custom Resource Definitions**: K8s-maestro custom resources
- **Multi-cluster Support**: Execute workflows across multiple clusters
#### v2.0.0
- **Distributed Execution**: Cross-cluster workflow coordination
- **Event Sourcing**: Complete audit trail of workflow executions
- **Plugin System**: Extensible plugin architecture
- **Multi-language Steps**: Native support for Python, WASM, and other runtimes
## Technical Requirements
### Performance Requirements
- **Startup Time**: < 500ms for client initialization
- **Workflow Creation**: < 50ms for typical workflow (5-10 steps)
- **Execution Latency**: < 100ms overhead per workflow step
- **Throughput**: Support 1000+ concurrent workflow executions
- **Memory Footprint**: < 100MB idle, linear scaling with active workflows
### Scalability Requirements
- **Horizontal Scaling**: Support multiple MaestroClient instances
- **Vertical Scaling**: Efficient resource utilization (CPU, memory)
- **Cluster Size**: Support clusters with 1000+ nodes
- **Namespace Isolation**: Efficient multi-tenant resource management
### Reliability Requirements
- **Uptime**: 99.9% availability for client library
- **Error Recovery**: Automatic retry with exponential backoff
- **Checkpoint Durability**: 99.99% checkpoint recovery success rate
- **Data Consistency**: Strong consistency guarantees for workflow state
### Compatibility Requirements
- **Kubernetes**: v1.28 through v1.32 (with feature flags)
- **Rust**: 2021 edition, stable channel
- **Operating Systems**: Linux, macOS, Windows (via WSL)
- **Architectures**: x86_64, ARM64
### Security Requirements
- **Authentication**: Support for multiple K8s auth methods (kubeconfig, token, cert)
- **Authorization**: RBAC integration with least privilege principles
- **Secrets Management**: Secure handling of Kubernetes secrets
- **Network Security**: Network policies and ingress TLS support
- **Audit Logging**: Complete audit trail of workflow operations
### Testing Requirements
- **Unit Tests**: > 80% code coverage
- **Integration Tests**: All K8s operations tested with Kind clusters
- **E2E Tests**: End-to-end workflow execution scenarios
- **Performance Tests**: Benchmark execution for critical paths
- **Security Tests**: Automated vulnerability scanning
## Quality Standards
### Code Quality
- **Code Style**: Follow Rust naming conventions and formatting
- **Documentation**: All public APIs documented with rustdoc
- **Error Handling**: Comprehensive error types with helpful messages
- **Type Safety**: Leverage Rust type system for configuration validation
### Documentation Quality
- **API Docs**: Complete rustdoc on crates.io
- **User Guide**: Getting started, concepts, and guides in site-docs/
- **Reference Documentation**: ADRs and FDRs in docs/
- **Examples**: Comprehensive examples for all major features
- **Migration Guides**: Detailed guides for major version upgrades
### Testing Standards
- **TDD Approach**: Write tests before implementation
- **Test Categories**: Unit, integration, and E2E tests
- **Test Isolation**: Each test is independent and reproducible
- **Test Speed**: Unit tests < 10s, integration tests < 5min
- **Coverage**: Minimum 80% code coverage for core modules
### Release Process
- **Semantic Versioning**: Follow SemVer 2.0.0
- **Release Notes**: Automated CHANGELOG.md generation
- **Beta Releases**: Pre-release testing for major versions
- **Breaking Changes**: Documented with migration guides
- **Backward Compatibility**: Maintain stable APIs within major versions
## Roadmap
### v1.1.0 - Enhanced Workflow Capabilities (Q2 2026)
**Goals**
- Add scheduled workflow execution
- Improve workflow reusability and composition
- Enhance retry and error handling
**Features**
- [FDR-0001] CronJob Support
- [FDR-0002] Workflow Templates
- [FDR-0003] Event Triggers
- [FDR-0004] Advanced Retry Logic
**Technical Improvements**
- Optimized dependency resolution algorithm
- Enhanced checkpoint compression
- Improved error context and debugging
### v1.2.0 - Observability and CRDs (Q3 2026)
**Goals**
- Provide comprehensive workflow observability
- Introduce Kubernetes-native workflow resources
- Improve multi-cluster support
**Features**
- [FDR-0005] Workflow UI Dashboard
- [FDR-0006] Metrics Integration (Prometheus)
- [FDR-0007] K8s-maestro CRDs
- [FDR-0008] Multi-cluster Execution
**Technical Improvements**
- Custom Controller for CRD management
- Webhook-based validation
- Cluster federation support
### v2.0.0 - Distributed Execution (Q4 2026)
**Goals**
- Enable distributed workflow execution
- Introduce plugin architecture
- Support multiple language runtimes
**Features**
- [FDR-0009] Distributed Execution Engine
- [FDR-0010] Event Sourcing Architecture
- [FDR-0011] Plugin System
- [FDR-0012] Multi-language Steps
**Breaking Changes**
- Updated client API for distributed execution
- New checkpoint format for event sourcing
- Plugin system replaces current extension mechanisms
## Version History
**Note**: Version 0.4.0 was planned but never released. The development work intended for 0.4.0 was instead released as 1.0.0-beta, followed by 1.0.0 and 1.0.1. This was a strategic decision to establish k8s-maestro as a stable, production-ready library with the initial major release.
### Released Versions
- **1.0.1** (2026-03-18) - Bug fixes and quality improvements
- **1.0.0** (2026-03-18) - Initial stable release
- **1.0.0-beta** (2026-03-17) - Beta release for production testing
- **0.3.0** - Previous release (pre-workflow-centric API)
### Unreleased Versions
- **0.4.0** - Never released (features integrated into 1.0.0)
## Appendix
### Terminology
- **Workflow**: A collection of steps with defined execution order and dependencies
- **Step**: A unit of work (Kubernetes Job, Pod, or custom execution)
- **Dependency Chain**: Directed acyclic graph (DAG) of step dependencies
- **Checkpoint**: Serialized workflow state for recovery after failures
- **Dry Run**: Execution mode that validates workflows without actual execution
- **Sidecar**: Auxiliary container that supports the main container in a workflow step
### References
- [GitHub Repository](https://github.com/andreclaudino/k8s-maestro)
- [Crates.io Package](https://crates.io/crates/k8s-maestro)
- [API Documentation](https://docs.rs/k8s-maestro)
- [AGENTS.md](../../AGENTS.md) - Development guidelines
- [CHANGELOG.md](../../CHANGELOG.md) - Version history
### Contributing
See [Contributing Guidelines](../../README.md#contributing) in the main README.
### License
This project is dual-licensed under MIT and Apache-2.0. See LICENSE files for details.