Metrics processor

When monitoring cloud it is not unusual to have a variety of metrics types (latencies, status codes, rates). Visualizing overall state of the service based on those metrics is not an easy task in this case. It is desired to have something like a semaphore to visualize overall "health" of the component (green - up and running, yellow - there are some issues, red - complete outage). Depending on the used TSDB there might be no way to do this at all.

metrics-processor is there to address 2 primary needs:

• convert series of raw metrics of different types into single semaphore-like metric
• inform status dashboard once certain component status is not healthy.

Project Structure

• src/ - Rust source code
• doc/ - Documentation sources (mdbook)
• tests/ - Integration and validation tests
• specs/ - Feature specifications and implementation plans
• playbooks/ - Operational playbooks

Documentation

The project uses mdbook for documentation. Source files are in doc/.

Building Documentation

# Install mdbook (if not already installed)
cargo install mdbook mdbook-mermaid

# Build documentation
mdbook build doc/

# Output will be in docs/
open docs/index.html

Serving Documentation Locally

# Serve with live reload (rebuilds on changes)
mdbook serve doc/

# Open http://localhost:3000 in your browser

Documentation Contents

Section	Description
Getting Started	Quickstart guide, project structure, development workflow
Architecture	System overview, diagrams, data flow
API Reference	REST endpoints, authentication, examples
Configuration	Config schema, examples, validation
Integration	TSDB interface, adding new backends
Modules	Rust module documentation
Guides	Troubleshooting, deployment

| Testing | Testing guide, fixtures, coverage |

Testing

Running Tests

# Run all unit tests
cargo test

# Run tests with output
cargo test -- --nocapture

# Run specific test module
cargo test common::tests

# Run tests in parallel (default)
cargo test -- --test-threads=4

E2E Integration Tests

End-to-end tests validate the complete pipeline using real Docker containers (go-carbon + carbonapi).

Prerequisites

• Docker installed and running
• Ports available: 2003, 8080, 3005, 9999

Running E2E Tests

# Run E2E tests (Docker containers are managed automatically)
cargo test --test integration_e2e_reporter -- --ignored --nocapture

The E2E test validates 4 scenarios:

Scenario	Expected Weight	Description
healthy	0	All metrics within thresholds
degraded_slow	1	API response time > 1200ms
degraded_errors	1	Success rate < 65%
outage	2	100% API failures

For details, see Testing Guide.

Test Coverage

# Install cargo-tarpaulin (if not already installed)
cargo install cargo-tarpaulin

# Run coverage report
cargo tarpaulin --out Html

# Open coverage report
open tarpaulin-report.html

JSON Schema for Configuration

A JSON Schema for configuration validation is auto-generated during build:

# Schema is generated to doc/schemas/config-schema.json
cargo build

# Use in your IDE for YAML autocomplete and validation