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Production-grade Agent Operations (AgentOps) Platform

Project description

🕹️ AgentOps Cockpit

AgentOps Cockpit Trinity

"Infrastructure gives you the pipes. We give you the Intelligence."

The developer distribution for building, optimizing, and securing AI agents on Google Cloud.


📽️ The Mission

Most AI agent templates stop at a single Python file and an API key. The AgentOps Cockpit is for developers moving into production. It provides framework-agnostic governance, safety, and cost guardrails for the entire agentic ecosystem.

  • Governance-as-Code: Audit your agent against Google Well-Architected best practices with the Evidence Bridge—real-time citations for architectural integrity.
  • SME Persona Audits: Parallelized review of your codebase by automated Principal SMEs across FinOps, SecOps, Architecture, and Quality.
  • Agentic Trinity: Dedicated layers for the Engine (Logic), Face (UX), and Cockpit (Ops).
  • A2A Connectivity: Implements the Agent-to-Agent Transmission Standard for secure swarm orchestration.
  • MCP Native: Registration as a Model Context Protocol server for 1P/2P/3P tool consumption.

🏗️ The Agentic Trinity

We divide the complexity of production agents into three focused pillars:

graph TD
   subgraph Trinity [The Agentic Trinity 2.0]
       E(The Engine: Reasoning)
       F(The Face: Interface)
       C(The Cockpit: Operations)
       S{Sovereignty & Compliance}
   end
   E <--> C
   F <--> C
   E <--> F
   E -.-> S
   F -.-> S
   C -.-> S
   style Trinity fill:#f8fafc,stroke:#334155,stroke-width:2px
   style S fill:#0ea5e9,color:#fff,stroke:#0284c7
  • ⚙️ The Engine: The reasoning core. Built with ADK, FastAPI, and Vertex AI.
  • 🎭 The Face: The user experience. Adaptive UI surfaces and GenUI standards via the A2UI spec.
  • 🕹️ The Cockpit: The operational brain. Cost control, semantic caching, shadow routing, and adversarial audits.
Ecosystem Integrations

🏛️ v1.3: The "Autonomous Architect" Standard (NEW)

Evolving from a compliance tool to an autonomous evolution engine. See the v1.3 Roadmap.

  • 🚀 Context-Aware Patching: Moving from templates to LLM-Synthesized PRs that match your project's style.
  • 🧪 Digital Twin Simulation: make simulation-run for high-concurrency "Stress-Reasoning" test. Read Guide.
  • 🧗 Hill Climbing Optimization: Iterative prompt tuning to reach the Global Peak. Read Guide.
  • 🌍 Strategic Exit Strategy: Automated TCO reports and migration plans for moving between cloud providers.

🚀 Key Innovation: The "Intelligence" Layer

🛡️ Red Team Auditor (Adversarial SRE)

Don't wait for your users to find prompt injections. Use the built-in Adversarial Evaluator to launch self-attacks against your agent, testing for PII leaks, instruction overrides, and multilingual jailbreaks.

🧠 Hive Mind (Semantic Caching)

Reduce LLM costs by up to 40%. The Hive Mind checks for semantically similar queries in 10ms, serving cached answers for common questions without calling the LLM.

🏛️ Arch Review & Autonomous Evolution

Every agent in the cockpit is graded against a framework-aware checklist. The Cockpit intelligently detects your stack and runs a tailored Architecture Review. v1.3 introduces Autonomous Evolution—the ability to synthesize code fixes directly from audit findings.

🕹️ MCP Connectivity Hub (Model Context Protocol)

Stop building one-off tool integrations. The Cockpit provides a unified hub for MCP Servers. Connect to 1P/2P/3P tools via the standardized Model Context Protocol for secure, audited tool execution. Start the server with make mcp-serve.

🗄️ Situational Database Audits

The Cockpit now performs platform-specific performance and security audits for AlloyDB, Pinecone, BigQuery, and Cloud SQL.


🛡️ Advanced Governance & Discovery

Modern agents don't just live in agent.py. The Cockpit uses a centralized Discovery Engine to intelligently map your project:

  • .gitignore Compliance: Zero-noise scanning that respects your project's ignore rules.
  • Library Isolation: Intelligently ignores hits in venv or node_modules to focus on your code.
  • Config-Driven: Use cockpit.yaml to define custom entry points, exclusions, and CI/CD thresholds.

⌨️ Master Command Registry

The Cockpit is available as a first-class CLI and a comprehensive Makefile-based operational toolkit.

Registry Description
🕹️ Makefile Commands Standard local development and orchestration shortcuts.
🚀 UVX Master Guide Portable, zero-install commands for CI/CD and automation.

🧑‍💼 Principal SME Persona Approvals

The Cockpit now features a Multi-Persona Governance Board. Every audit result is framed through the lens of a Principal Engineer in that domain:


🚀 1-Click Production Pipeline

make deploy-prod triggers the following lifecycle:

  1. Runs the Quick Safe-Build (make audit).
  2. Compiles production frontend assets.
  3. Deploys the Engine to Google Cloud Run.
  4. Deploys the Face to Firebase Hosting.

🤝 Ecosystem & Attribution

The AgentOps Cockpit is designed to leverage and secure the best-of-breed tools in the Google Cloud ecosystem. We explicitly acknowledge and leverage the excellent work from:

  • GoogleCloudPlatform/agent-starter-pack: We leverage this as a core reference for the Agent Development Kit (ADK) patterns and Vertex AI Agent Engine integration.
  • A2A Standard: Our implementation follow the Agent-to-Agent Transmission Protocol for swarm intelligence.

Reference: Google Cloud Architecture Center - Agentic AI Overview

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