Sparki API System Requirements Specification

:::info readme This document outlines the System Requirements Specification (SRS) for the Sparki API, the core backend service that powers framework detection, pipeline management, deployment orchestration, and CI/CD automation for the Sparki platform. It defines the functional and non-functional requirements necessary to meet developer needs and business objectives. As the primary interface between CLI clients, terminal UI, and backend services, the Sparki API is designed to be ultra-high performance, intelligent, and developer-friendly. This SRS serves as a foundational reference for architects, developers, and quality assurance personnel involved in the design, implementation, and maintenance of the API. ::: :::success takeaways Key takeaways of this document include:

Understanding core API functionalities for framework detection and pipeline management
Comprehending the system architecture and Go Fiber-based technology stack
Identifying functional requirements for CI/CD operations and deployment automation
Recognizing non-functional requirements for performance, scalability, and reliability
Establishing traceability between business requirements and API specifications
Facilitating communication among cross-functional teams

::: Version: 1.0
Date: December 3, 2025
Repository: sparki-api
Service Type: Core Backend API (Go Fiber)
Framework: Fiber v2 with high-performance async runtime

1. Introduction

1.1 Purpose

This document communicates the user needs and technical requirements of the Sparki API to all stakeholders, providing a comprehensive overview of expected system functions and capabilities. It identifies functional requirements, constraints, assumptions, and enables development of user stories and use cases.

1.2 Concepts

The operational concepts and support strategies in this document are based on:

Developer expected use of the system (from CLI, TUI, and external integrations)
Functionality and performance for normal operation with 1M+ concurrent developers
Robustness requirements for production workload support
Operational boundaries and practical deployment constraints
Technical architecture decisions and performance targets

1.3 Scope

The Sparki API is a Fiber-based RESTful service with WebSocket support that provides:

Project framework autodetection and analysis
CI/CD pipeline generation and management
Pipeline execution orchestration
Build, test, and lint automation
Deployment workflow management
Real-time pipeline status and logs
User workspace and team management
Third-party cloud platform integration
Metrics, telemetry, and observability

1.4 Definitions

Property	Value
Project	Git repository with detected framework/language
Workspace	Team’s organizational container
Pipeline	CI/CD workflow (build, test, deploy steps)
Build	Single pipeline execution instance
Framework	Detected development framework (Django, Next.js)
Adapter	Framework-specific handler plugin
Deployment	Release of code to cloud platform
WebSocket Session	Real-time connection for streaming logs/status

1.5 Document Conventions

SHALL: Mandatory requirement
SHOULD: Recommended requirement
MAY: Optional requirement
WILL: External dependency or future intention

2. System Overview

2.1 System Context

The Sparki API serves as the orchestration layer between CLI/TUI clients and backend services, implementing intelligent CI/CD automation with framework-aware pipeline generation and deployment management. It coordinates:

Project Analysis: Framework detection with AST analysis and dependency scanning
Pipeline Generation: Intelligent CI/CD pipeline synthesis for detected frameworks
Build Orchestration: Container-based build execution with real-time streaming
Test Automation: Framework-agnostic test discovery and execution
Deployment Management: Multi-stage deployment orchestration via Loco engine
Real-Time Communication: WebSocket streaming of logs, status, and metrics
User Management: Workspace, team, and permission management
Cloud Integration: Railway, Render, Fly.io, Vercel native API integration
Observability: Structured logging, Prometheus metrics, distributed tracing
Security: JWT token validation, RBAC, audit logging

2.2 System Objectives

Sub-50ms API Response Times: 95th percentile response <50ms through Fiber optimization and caching
Instant Framework Detection: <2 seconds project analysis with high accuracy (>99%)
Universal Framework Support: Support 50+ languages/frameworks with intelligent detection
Massive Scalability: Support 1M+ developers with 100K+ concurrent pipeline executions
Real-Time Observability: <100ms log streaming and status updates via WebSocket
Zero Configuration: Generate working pipelines without user input for 95%+ of projects
Intelligent Adaptability: Learn from framework patterns and customize pipelines
High Availability: 99.95% uptime SLA with graceful degradation
Developer Experience: Intuitive REST API matching developer expectations
Extensibility: Plugin system for custom framework adapters and build strategies

3. Functional Requirements

3.1 Project Detection & Analysis

REQ-API-DETECT-001: Framework Auto-Detection

Property	Value
ID	`REQ-API-DETECT-001`
Requirement	The API SHALL support automatic framework detection via `POST /api/v1/projects/analyze` endpoint analyzing git repository and generating framework report.
Rationale	Zero-configuration onboarding requires accurate framework detection without user input. Enables core Sparki value proposition.
Inputs	`{git_url, branch, commit_hash}` or local path
Outputs	Framework detection report with confidence scores and recommended pipeline template
Verify Method	Test
Acceptance Criteria:	Detect 50+ frameworks with >99% accuracy Analysis completes in <2 seconds Return confidence scores for detected frameworks Identify primary language Report dependency tree and versions Suggest 3+ pipeline templates

Implementation Details:

Analysis Pipeline:
Clone/fetch repository (max 100MB)
Scan directory structure and file signatures
Parse dependency files (package.json, go.mod, requirements.txt, etc.)
AST analysis for language-specific patterns
Heuristic detection for framework markers
Return ranked framework candidates with confidence

Supported Frameworks by Language:

Python: Django, FastAPI, Flask, Pyramid, Tornado
Node.js: Express, Next.js, Remix, Nuxt, NestJS, Svelte
Go: Gin, Echo, Fiber, GORM, Beego
Rust: Axum, Actix-Web, Rocket, Yew
Java: Spring Boot, Quarkus, Micronaut, Dropwizard
.NET: ASP.NET Core, Minimal APIs, Entity Framework
Ruby: Rails, Sinatra, Hanami, Roda
PHP: Laravel, Symfony, Slim, Zend

REQ-API-DETECT-002: Dependency Analysis

Property	Value
ID	`REQ-API-DETECT-002`
Requirement	The API SHALL parse and analyze project dependencies, versions, and transitive dependencies for security and compatibility verification.
Rationale	Understand project dependencies enables intelligent build strategy selection and vulnerability scanning recommendations.
Inputs	Project path, dependency files (package.json, go.mod, requirements.txt, pom.xml, Cargo.toml)
Outputs	Dependency graph with versions, security alerts, and compatibility warnings
Verify Method	Test
Acceptance Criteria:	Parse all major dependency manifests Build transitive dependency graph Identify security vulnerabilities Report version conflicts Suggest dependency updates

REQ-API-DETECT-003: Build System Detection

Property	Value
ID	`REQ-API-DETECT-003`
Requirement	The API SHALL auto-detect project build systems and provide appropriate build commands for pipeline generation.
Rationale	Intelligent build orchestration requires understanding project build tooling to generate correct build steps.
Inputs	Project root directory and framework context
Outputs	Detected build system with recommended build commands and configuration
Verify Method	Test
Acceptance Criteria:	Detect all major build systems (npm, yarn, cargo, go build, maven, etc.) Identify build config files Suggest build commands Report build parallelization options

3.2 Pipeline Management

REQ-API-PIPELINE-001: Intelligent Pipeline Generation

Property	Value
ID	`REQ-API-PIPELINE-001`
Requirement	The API SHALL generate production-grade CI/CD pipelines via `POST /api/v1/pipelines` based on framework detection with zero user configuration.
Rationale	Automatic pipeline generation is core Sparki value proposition—eliminates YAML configuration complexity.
Inputs	Project ID, framework context from detection analysis
Outputs	Complete CI/CD pipeline with build, test, lint, and deployment stages
Verify Method	Test + Demonstration
Acceptance Criteria:	Generate complete pipeline for 95%+ of detected projects Pipeline should pass build tests without modification Include linting, testing, security checks Support multi-stage builds Enable parallel job execution

Default Pipeline Stages:

1. Build
   - Install dependencies
   - Compile/build artifacts
   - Cache layer optimization

2. Test
   - Run unit tests
   - Run integration tests
   - Generate coverage reports

3. Lint & Security
   - Code linting (ESLint, Pylint, etc.)
   - Security scanning (SAST)
   - Dependency vulnerability scan

4. Deploy (optional)
   - Pre-deployment validation
   - Staged deployment strategy
   - Health checks and monitoring

REQ-API-PIPELINE-002: Pipeline Customization & Override

Property	Value
ID	`REQ-API-PIPELINE-002`
Requirement	The API SHALL support pipeline customization via YAML configuration file (`.sparki.yml`) while maintaining zero-configuration default behavior.
Rationale	Teams need customization flexibility for complex workflows while maintaining Sparki’s zero-configuration promise.
Inputs	`.sparki.yml` configuration file in project root
Outputs	Merged pipeline combining auto-generated and custom configuration
Verify Method	Test
Acceptance Criteria:	Parse and validate YAML configuration Merge custom config with auto-generated pipeline Support stage overrides and additions Enable conditional steps based on branch/tag

Example .sparki.yml:

version: 1
pipelines:
    main:
        stages:
            build:
                commands:
                    - npm install
                    - npm run build:prod
            test:
                commands:
                    - npm test -- --coverage
            deploy:
                stages:
                    - staging
                    - production
                requires_approval: true

REQ-API-PIPELINE-003: Multi-Pipeline Management

Property	Value
ID	`REQ-API-PIPELINE-003`
Requirement	The API SHALL support multiple named pipelines per project via `POST /api/v1/pipelines/{name}/execute` for different workflows.
Rationale	Complex projects need separate pipelines for different branches, purposes (nightly builds, release builds, etc.).
Inputs	Pipeline name, trigger parameters
Outputs	Pipeline execution instance
Verify Method	Test
Acceptance Criteria:	Support naming multiple pipelines per project Enable branch-specific pipeline routing Support scheduled/manual triggers Manage pipeline versioning

3.3 Pipeline Execution & Orchestration

REQ-API-EXEC-001: Build Execution

Property	Value
ID	`REQ-API-EXEC-001`
Requirement	The API SHALL orchestrate build execution via `POST /api/v1/builds` with container isolation and real-time log streaming.
Rationale	Container-based builds provide isolation, repeatability, and security essential for production CI/CD.
Inputs	Pipeline definition, git commit reference, environment variables
Outputs	Build execution context with build ID and WebSocket log stream endpoint
Verify Method	Test + Demonstration
Acceptance Criteria:	Execute build in isolated container Stream logs in real-time via WebSocket Support parallel job execution Enable job-level timeout enforcement Cache layer optimization for dependencies

REQ-API-EXEC-002: Test Execution & Reporting

Property	Value
ID	`REQ-API-EXEC-002`
Requirement	The API SHALL auto-discover and execute tests via `POST /api/v1/builds/{id}/tests` with framework-agnostic test execution and result aggregation.
Rationale	Automatic test discovery and execution enables zero-configuration test orchestration across diverse frameworks.
Inputs	Project framework, test framework detection results
Outputs	Test results with pass/fail status, coverage reports, and performance metrics
Verify Method	Test
Acceptance Criteria:	Auto-detect test frameworks (pytest, jest, go test, cargo test, etc.) Discover test files and suites Execute tests in parallel Aggregate results across test runners Generate coverage reports

REQ-API-EXEC-003: Linting & Security Scanning

Property	Value
ID	`REQ-API-EXEC-003`
Requirement	The API SHALL execute linting and security scanning via `POST /api/v1/builds/{id}/lint` with framework-appropriate linters and SAST tools.
Rationale	Automated code quality and security scanning prevents defects and vulnerabilities from reaching production.
Inputs	Project code, framework context, linting configuration
Outputs	Linting results with violations, security findings, and quality metrics
Verify Method	Test
Acceptance Criteria:	Execute linters for detected language (ESLint, Pylint, golangci-lint, etc.) Run SAST security scanning Perform dependency vulnerability scan Aggregate results with severity classification

3.4 Build & Pipeline Status

REQ-API-STATUS-001: Real-Time Log Streaming

Property	Value
ID	`REQ-API-STATUS-001`
Requirement	The API SHALL stream build logs in real-time via WebSocket connection at `/api/v1/builds/{id}/logs` with structured JSON format.
Rationale	Real-time log streaming enables developers to monitor builds and debug failures instantly without polling.
Inputs	Build ID, WebSocket connection
Outputs	Continuous stream of log entries with timestamps and severity levels
Verify Method	Test + Demonstration
Acceptance Criteria:	Stream logs with <100ms latency Support log filtering and search Include severity levels (DEBUG, INFO, WARN, ERROR) Support connection recovery with backlog replay

Log Entry Format:

{
    "timestamp": "2025-12-03T10:30:45.123Z",
    "level": "INFO",
    "stage": "build",
    "job": "install-dependencies",
    "message": "Installing npm dependencies...",
    "metadata": {
        "duration_ms": 1234,
        "lines": 42
    }
}

REQ-API-STATUS-002: Build Status & Metrics

Property	Value
ID	`REQ-API-STATUS-002`
Requirement	The API SHALL provide build status and metrics via `GET /api/v1/builds/{id}` and `/api/v1/projects/{id}/status`.
Rationale	Developers need quick access to build status for awareness and decision-making.
Inputs	Build ID or Project ID
Outputs	Build/project status with metrics (duration, stage durations, resource usage)
Verify Method	Test
Acceptance Criteria:	Return current build status with stage progression Show historical build metrics (duration, success rate) Display resource usage (CPU, memory) Support querying multiple builds

3.5 Deployment Management

REQ-API-DEPLOY-001: Deployment Configuration

Property	Value
ID	`REQ-API-DEPLOY-001`
Requirement	The API SHALL support deployment configuration via `POST /api/v1/projects/{id}/deployments/configure` for cloud platform targets.
Rationale	Developers need to configure deployment targets (Railway, Render, Fly.io) with API credentials and deployment parameters.
Inputs	Deployment platform, credentials, deployment parameters
Outputs	Deployment configuration stored and validated
Verify Method	Test
Acceptance Criteria:	Support Railway, Render, Fly.io, Vercel configurations Validate platform credentials Store encrypted credentials securely Enable deployment strategy selection (blue-green, canary, rolling)

REQ-API-DEPLOY-002: Deployment Orchestration (via Loco)

Property	Value
ID	`REQ-API-DEPLOY-002`
Requirement	The API SHALL orchestrate deployments via Loco engine through `POST /api/v1/builds/{id}/deploy` with staged deployment support.
Rationale	Loco engine provides intelligent deployment orchestration with pre-deployment validation and rollback capability.
Inputs	Build ID, deployment target, deployment parameters
Outputs	Deployment execution instance with status tracking
Verify Method	Test + Demonstration
Acceptance Criteria:	Execute pre-deployment validation checks Support staged deployments (staging → production) Enable approval gates Provide instant rollback capability Stream deployment logs

REQ-API-DEPLOY-003: Rollback & Deployment History

Property	Value
ID	`REQ-API-DEPLOY-003`
Requirement	The API SHALL support instant rollback via `POST /api/v1/deployments/{id}/rollback` with complete deployment history tracking.
Rationale	Instant rollback capability critical for production incident response. History enables post-incident analysis and audit compliance.
Inputs	Deployment ID, optional target version
Outputs	Rollback execution with status and completion confirmation
Verify Method	Test + Demonstration
Acceptance Criteria:	Complete rollback in <30 seconds Maintain complete deployment history Support rollback to any previous deployment Log all rollback operations

3.6 User & Workspace Management

REQ-API-USER-001: User Account Management

Property	Value
ID	`REQ-API-USER-001`
Requirement	The API SHALL support user account operations via `/api/v1/users` endpoints (create, retrieve, update) with proper authentication.
Rationale	User account management essential for identity and access control across platform.
Inputs	User information (email, name, password, preferences)
Outputs	User object with generated user ID and authentication tokens
Verify Method	Test
Acceptance Criteria:	Support user registration, profile updates, password reset Enforce password complexity requirements Enable email verification

REQ-API-USER-002: Workspace Management

Property	Value
ID	`REQ-API-USER-002`
Requirement	The API SHALL support workspace operations via `/api/v1/workspaces` (create, list, manage members, configure settings).
Rationale	Workspaces provide organizational boundaries for teams and projects with distinct settings and permissions.
Inputs	Workspace name, members, configuration settings
Outputs	Workspace object with generated workspace ID
Verify Method	Test
Acceptance Criteria:	Create and manage workspaces Add/remove workspace members Configure workspace-level settings Support workspace invitations

REQ-API-USER-003: Role-Based Access Control (RBAC)

Property	Value
ID	`REQ-API-USER-003`
Requirement	The API SHALL enforce role-based access control via role definitions (owner, admin, developer, viewer) with fine-grained permissions.
Rationale	RBAC enables secure delegation of responsibilities while maintaining control over sensitive operations.
Inputs	User, role, resource context
Outputs	Access decision (allow/deny) based on role and permissions
Verify Method	Test
Acceptance Criteria:	Define standard roles (owner, admin, developer, viewer) Support custom roles Enforce permissions consistently across API Log access decisions

3.7 Cloud Platform Integration

REQ-API-INTEGRATION-001: Railway Integration

Property	Value
ID	`REQ-API-INTEGRATION-001`
Requirement	The API SHALL integrate with Railway platform via `POST /api/v1/integrations/railway` for seamless deployment orchestration.
Rationale	Railway is primary deployment target for Sparki platform requiring native integration.
Inputs	Railway project ID, API token, deployment parameters
Outputs	Railway deployment execution with status tracking
Verify Method	Test + Demonstration
Acceptance Criteria:	Support Railway API authentication Deploy to Railway projects Stream deployment logs Support health checks

REQ-API-INTEGRATION-002: Multi-Platform Support (Render, Fly.io, Vercel)

Property	Value
ID	`REQ-API-INTEGRATION-002`
Requirement	The API SHALL support multiple deployment platforms via pluggable adapter system.
Rationale	Developer choice of deployment platform requires unified deployment interface abstraction.
Inputs	Platform-specific credentials and deployment parameters
Outputs	Platform-agnostic deployment execution instance
Verify Method	Test
Acceptance Criteria:	Support Render, Fly.io, Vercel platforms Enable pluggable adapter system for future platforms Abstract platform differences

3.8 Observability & Metrics

REQ-API-OBS-001: Prometheus Metrics

Property	Value
ID	`REQ-API-OBS-001`
Requirement	The API SHALL export Prometheus metrics via `/metrics` endpoint with `sparki.*` namespace and standardized labels.
Rationale	Prometheus metrics enable comprehensive observability and integration with monitoring systems.
Inputs	API operations and performance data
Outputs	Prometheus metrics in standardized format
Verify Method	Test
Acceptance Criteria:	Export HTTP metrics (latency, request count, error rate) Export build metrics (duration, success rate) Export deployment metrics

Key Metrics:

sparki_api_request_duration_seconds (histogram)
sparki_api_request_errors_total (counter)
sparki_build_duration_seconds (histogram)
sparki_build_success_total (counter)
sparki_deployment_duration_seconds (histogram)
sparki_pipeline_execution_total (counter)

REQ-API-OBS-002: Structured Logging

Property	Value
ID	`REQ-API-OBS-002`
Requirement	The API SHALL produce structured JSON logs with correlation IDs and standardized field naming.
Rationale	Structured logging enables efficient log aggregation, searching, and analysis.
Inputs	Log events from API operations
Outputs	JSON-formatted log entries with standardized structure
Verify Method	Test
Acceptance Criteria:	Log all API requests with correlation IDs Include trace context in all logs Use consistent field naming Log errors with stack traces

4. Non-Functional Requirements

4.1 Performance Requirements

Requirement	Target	Measurement Method	Rationale
API Response Time (P95)	<50ms	Prometheus histograms	Exceptional developer experience
Framework Detection	<2 seconds	Build metrics	Instant project analysis
Pipeline Generation	<500ms	API latency tracking	Seamless workflow
Log Query Performance	<200ms	Query latency metrics	Instant troubleshooting
WebSocket Connection Latency	<100ms	Connection metrics	Real-time feedback experience
TUI Responsiveness	<200ms	CLI metrics	Snappy terminal experience

4.2 Scalability Requirements

Requirement	Target	Measurement Method	Rationale
Concurrent Developers	1M+	Load testing	Global developer market scale
Concurrent API Requests	100K+/sec	Load testing	Peak traffic handling
Concurrent Build Executions	10K+	Pipeline metrics	Massive deployment concurrency
Projects per Workspace	10K+	Database scaling	Large engineering organizations
Deployments per Project per Day	1K+	Deployment tracking	Continuous deployment support

4.3 Reliability Requirements

Requirement	Target	Measurement Method	Rationale
Availability SLA	99.95%	Uptime monitoring	Enterprise-grade mission-critical workload
Build Execution Success Rate	>99%	Build success metrics	Reliable build automation
Data Durability	99.999%	Storage durability	Enterprise data protection standard
Recovery Time Objective (RTO)	<15 minutes	Incident tracking	Minimal service disruption
Recovery Point Objective (RPO)	<5 minutes	Backup verification	Minimal data loss

4.4 Security Requirements

Requirement	Target	Measurement Method	Rationale
Authentication Standard	OAuth 2.0/JWT	Security audit	Industry-standard authentication
Data Encryption (In Transit)	TLS 1.3	Security scanning	Encrypted communication
Data Encryption (At Rest)	AES-256	Encryption audit	Secure data storage
Access Control	RBAC	Permission testing	Fine-grained access control
Audit Logging	100% coverage	Log audit	Compliance and forensics
Rate Limiting	Adaptive	Traffic analysis	DoS protection

5. Integration Patterns

5.1 External Service Integration

┌─────────────┐
│  Sparki API │
├─────────────┤
│  Fiber Core │
├──────┬──────┴──────┬──────────┬────────────┐
│      │             │          │            │
├──────▼────┐  ┌─────▼────┐  ┌─▼───────┐  ┌─▼──────────┐
│ PostgreSQL │  │  Redis   │  │ S3/Blob │  │ Cloud APIs │
│ Database   │  │  Cache   │  │ Storage │  │ (Railway)  │
└────────────┘  └──────────┘  └─────────┘  └────────────┘

5.2 Cloud Platform Adapters

Railway: Native API integration for projects and deployments
Render: Blueprint and environment variable configuration
Fly.io: App deployment and scaling configuration
Vercel: Project and environment detection

6. API Response Formats

6.1 Standard Response Structure

{
  "success": true,
  "data": {
    "id": "proj_123",
    "name": "my-project",
    "framework": "next.js",
    ...
  },
  "meta": {
    "timestamp": "2025-12-03T10:30:45Z",
    "correlation_id": "req_xyz789"
  }
}

6.2 Error Response Structure

{
    "success": false,
    "error": {
        "code": "PROJECT_NOT_FOUND",
        "message": "Project with ID 'proj_123' not found",
        "details": {
            "project_id": "proj_123"
        }
    },
    "meta": {
        "timestamp": "2025-12-03T10:30:45Z",
        "correlation_id": "req_xyz789"
    }
}

7. Technology Stack

Component	Technology	Rationale
HTTP Framework	Go Fiber	Ultra-fast, minimal allocations
Database	PostgreSQL	ACID compliance, scaling support
Caching	Redis/Valkey	Sub-millisecond operations
Object Storage	S3/MinIO/Azure Blob	Scalable artifact storage
Observability	Prometheus/ELK/Jaeger	Industry-standard open-source stack
Containerization	Docker	Universal deployment format
Orchestration	Kubernetes	Enterprise deployment standard

8. Success Metrics

Metric	Year 1 Target	Measurement Method
API Response Time (P95)	<50ms	Prometheus monitoring
Framework Detection Accuracy	>99%	Test suite coverage
Build Success Rate	>99%	Build metrics
Platform Uptime	99.95%+	Uptime monitoring
Developer Adoption	100K+	Active user tracking

Document History:

Version	Date	Author	Changes
1.0	2025-12-03	Sparki Engineering	Initial API SRS creation

Getting Started

User Guides

Deployment & Operations

DevOps

API Reference

Architecture

Specifications

Forgery Advanced Specs

System Requirements Specs

UI Specifications

Monetization

Integration

Testing

Reports & Status

​Sparki API System Requirements Specification

​1. Introduction

​1.1 Purpose

​1.2 Concepts

​1.3 Scope

​1.4 Definitions

​1.5 Document Conventions

​2. System Overview

​2.1 System Context

​2.2 System Objectives

​3. Functional Requirements

​3.1 Project Detection & Analysis

​REQ-API-DETECT-001: Framework Auto-Detection

​REQ-API-DETECT-002: Dependency Analysis

​REQ-API-DETECT-003: Build System Detection

​3.2 Pipeline Management

​REQ-API-PIPELINE-001: Intelligent Pipeline Generation

​REQ-API-PIPELINE-002: Pipeline Customization & Override

​REQ-API-PIPELINE-003: Multi-Pipeline Management

​3.3 Pipeline Execution & Orchestration

​REQ-API-EXEC-001: Build Execution

​REQ-API-EXEC-002: Test Execution & Reporting

​REQ-API-EXEC-003: Linting & Security Scanning

​3.4 Build & Pipeline Status

​REQ-API-STATUS-001: Real-Time Log Streaming

​REQ-API-STATUS-002: Build Status & Metrics

​3.5 Deployment Management

​REQ-API-DEPLOY-001: Deployment Configuration

​REQ-API-DEPLOY-002: Deployment Orchestration (via Loco)

​REQ-API-DEPLOY-003: Rollback & Deployment History

​3.6 User & Workspace Management

​REQ-API-USER-001: User Account Management

​REQ-API-USER-002: Workspace Management

​REQ-API-USER-003: Role-Based Access Control (RBAC)

​3.7 Cloud Platform Integration

​REQ-API-INTEGRATION-001: Railway Integration

​REQ-API-INTEGRATION-002: Multi-Platform Support (Render, Fly.io, Vercel)

​3.8 Observability & Metrics

​REQ-API-OBS-001: Prometheus Metrics

​REQ-API-OBS-002: Structured Logging

​4. Non-Functional Requirements

​4.1 Performance Requirements

​4.2 Scalability Requirements

​4.3 Reliability Requirements

​4.4 Security Requirements

​5. Integration Patterns

​5.1 External Service Integration

​5.2 Cloud Platform Adapters

​6. API Response Formats

​6.1 Standard Response Structure

​6.2 Error Response Structure

​7. Technology Stack

​8. Success Metrics