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DevOps Engineer Learning Path

A structured path for DevOps engineers who want to integrate the FCC framework into CI/CD pipelines, manage protocol bridges (A2A/MCP), configure observability, and automate persona-driven workflows. This path emphasizes the DevOps personas, protocol engineering, event bus, and dashboard operations.

Estimated time: 8--12 hours

Prerequisites: Python 3.10+, familiarity with CI/CD (GitHub Actions, GitLab CI), Docker basics, comfort with YAML configuration and command-line tools.

Quick-Start Checklist

# Activity Resource Time
1 Install FCC and run your first simulation Quickstart 15 min
2 Explore the CLI commands and dashboard system CLI Reference 20 min
3 Study the event bus and observability pipeline Notebook 05: Event Bus & Observability 30 min
4 Learn protocol integration (A2A, MCP) Notebook 13: Protocol Integration 45 min
5 Understand JV governance and cross-org compliance Notebook 14: JV Governance 45 min
6 Operate the Protocol Explorer Streamlit: protocol_explorer.py 30 min
7 Operate the Ecosystem Dashboard Streamlit: ecosystem_dashboard.py 30 min
8 Configure quality gates for CI integration Guidebook Ch. 9: Governance 30 min
9 Set up OTel-based tracing for production Observability Integration Guide 30 min
10 Run CLI dashboards: ecosystem, quality fcc dashboard ecosystem, fcc dashboard quality 20 min

Key Personas for DevOps Engineers

DevOps (3 personas)

ID Name Phase Why It Matters
PBD Pipeline Builder for DevOps Build Designs CI/CD pipeline definitions with quality gates
DVE DevOps Validation Engineer Critique Validates infrastructure-as-code and deployment configs
JUS Just-in-Time Update Specialist Ops Manages rolling updates, canary deployments, rollback

Protocol Engineering (6 personas)

ID Name Phase Why It Matters
ASD A2A Specification Designer Create Designs Agent-to-Agent protocol specifications
MTA MCP Tool Author Create Builds Model Context Protocol tool definitions
EBO Event Bus Orchestrator Build Configures event routing, filtering, replay
WSM WebSocket Manager Build Manages real-time communication channels
PCA Protocol Compliance Auditor Critique Validates protocol implementations against specs
AMG A2A-MCP Gateway Build Bridges A2A and MCP protocol ecosystems

Supporting Personas

ID Name Why It Matters
ASC Automation Script Crafter Writes deployment scripts, health checks, runbooks
GCA Governance Compliance Auditor Audits compliance across governance tiers
TS Traceability Specialist Maintains bidirectional traceability matrices

Skill Progression

Stage 1: CLI and Event System (2--3 hours)

Goal: Master the FCC CLI, event bus, and observability layer.

  • Complete the Quickstart and explore all fcc CLI subcommands
  • Complete Notebook 05 to understand the 81 event types, EventBus, EventFilter, and EventSerializer
  • Run fcc dashboard ecosystem and fcc dashboard quality to see project health
  • Configure JSON file exporters for span and metric data

Milestone: You can subscribe to simulation events, filter by event type, and export traces to JSON.

Stage 2: Protocol Integration (3--4 hours)

Goal: Understand and configure A2A/MCP protocol bridges for agent communication.

  • Complete Notebook 13 (Protocol Integration): A2A agent cards, MCP tool definitions, protocol bridge patterns
  • Browse protocols in the protocol_explorer.py Streamlit app
  • Study the WebSocket architecture for real-time agent communication
  • Read the Protocol Bridge Patterns developer guide

Milestone: You can configure an A2A agent card for a persona and expose it via MCP tools.

Stage 3: Governance and Quality Gates (2--3 hours)

Goal: Integrate FCC quality gates into CI/CD pipelines.

  • Read Guidebook Chapter 9 (Governance) for constitution tiers, quality gates, and compliance
  • Configure quality gates in YAML and validate them with fcc validate
  • Set up fcc validate-docs as a CI step
  • Complete Notebook 14 (JV Governance) for cross-organization compliance

Milestone: You have a CI pipeline step that runs fcc validate and fails the build on quality gate violations.

Stage 4: Production Observability (1--2 hours)

Goal: Instrument FCC simulations with OpenTelemetry for production monitoring.

  • Study the fcc.observability module: FccTracer, FccMetrics, @traced decorator
  • Configure OTel exporters (console, JSON file, or external collectors)
  • Use instrument_simulation_engine() and instrument_action_engine() for automatic tracing
  • Build a monitoring dashboard using exported metrics

Milestone: You have OTel-instrumented simulation runs with traces and metrics flowing to your observability stack.

Application Purpose When to Use
protocol_explorer.py Browse A2A/MCP protocol definitions When designing protocol integrations
ecosystem_dashboard.py View cross-project health and dependencies For operational monitoring
workflow_dashboard.py Monitor workflow execution progress During simulation runs

CI/CD Integration Recipes

Quality gate check in GitHub Actions

- name: FCC Quality Validation
  run: |
    pip install -e .
    fcc validate --strict
    fcc validate-docs --format json > validation-report.json

Event export for pipeline artifacts

from fcc.messaging.bus import EventBus
from fcc.messaging.serialization import EventSerializer

bus = EventBus()
serializer = EventSerializer()
# Subscribe and serialize events for artifact storage
bus.subscribe("*", lambda event: serializer.to_json_file(event, "events/"))

Connections to Other Paths

  • Data Scientist path: Learn how to build ML pipelines that your CI/CD system deploys with the Data Scientist path
  • Product Manager path: Understand governance from a stakeholder perspective with the Product Manager path
  • Educator path: If you train teams on FCC, see the Educator path

Further Reading