/google-cloud-solution-build-deploy-agents

Product mappings

Use the following list to identify the appropriate Google Cloud products and features for each component in the confirmed technical decomposition:

Table of Contents

<a id="cloud-run-networking"></a>Cloud Run networking

• Recommended primary configuration: Regional External Application Load Balancer combined with Cloud Armor for HTTP/HTTPS/WebSocket ingress, and Direct VPC egress for Cloud Run private network access.
• Alternative product 1: Global External Application Load Balancer
  • Pros: Single anycast IP, global IPv6 termination, and low-latency routes to globally distributed backend services.
  • Cons: Terminates TLS globally at edge locations, which might not comply with strict regional data residency regulations.
• Alternative product 2: Internal Application Load Balancer
  • Pros: Securely exposes Cloud Run services internally within the VPC to meet internal ingress criteria, terminates TLS with trusted certificates, and supports Cloud Armor backend security policies.
  • Cons: Requires that you configure serverless network endpoint groups (NEGs) as backends and manage load balancer resources.
• Alternative product 3: Private Service Connect interface
  • Pros: Secure private VPC connections for Gemini Enterprise Agent Runtime that uses network attachments.
  • Cons: Limited to RFC 1918 routable subnet ranges, requires proxy setup for non-routable/internet destinations.

<a id="frontend"></a>Frontend

• Recommended primary product: Cloud Run
• Alternative product 1: Firebase App Hosting
  • Pros: Automated builds and deployment pipeline from GitHub, optimized for modern framework integrations.
  • Cons: Less control over container configurations, limits customization of low-level networking.
• Alternative product 2: Google Kubernetes Engine (GKE)
  • Pros: Maximum control over routing, scaling, and custom container runtimes.
  • Cons: Significant infrastructure management complexity and cost overhead.

<a id="agent-development-framework"></a>Agent development framework

• Recommended primary product: Agent Development Kit (ADK).

<a id="agent-to-agent-communication"></a>Agent-to-agent communication

• Recommended primary product: Agent Gateway for governed Agent2Agent (A2A) connectivity.
  • Pros: Provides client-to-agent ingress, agent-to-anywhere egress, and natively integrates IAM, Model Armor, Agent Registry, and Agent Identity.

<a id="agent-runtime"></a>Agent runtime

• Recommended primary product: Gemini Enterprise Agent Runtime
  • Pros: Fully managed runtime that supports built-in memory/sessions (Agent Platform Sessions), secure code execution sandbox, and native connection to remote MCP servers (like those hosted on Cloud Run).
  • Cons: Limited to the supported languages (see the supported Language list) and doesn't host custom Model Context Protocol (MCP) servers directly (they must be hosted externally on Cloud Run or GKE).
• Alternative product 1: Cloud Run
  • Pros: Serves custom container instances scaling to zero; highly performant when hosting custom language engines, local API layers, or custom MCP servers.
  • Cons: Requires managing container builds and continuous delivery configurations, can't host or serve Gemini models.
• Alternative product 2: Google Kubernetes Engine (GKE)
  • Pros: Maximum infrastructure control, stateful pods, custom scaling.
  • Cons: High operational complexity and overhead.

<a id="agent-registry"></a>Agent registry

• Recommended primary product: Agent Registry
  • Pros: Provides a unified catalog for agents, tools, and MCP servers. Optimizes routing in multi-agent (A2A) paths.

<a id="model-runtime"></a>Model runtime

• Recommended primary product: Gemini Enterprise Agent Platform
• Alternative product 1: Cloud Run
  • Pros: Serverless hosting for containerized open/custom models like Gemma. Can be configured to autoscale.
  • Cons: Cannot serve Google Gemini models.
• Alternative product 2: Google Kubernetes Engine (GKE)
  • Pros: Maximum control over inference server on GPU/TPU nodes, cheap for predictable high volume.
  • Cons: Cannot run Google Gemini models, high cluster management overhead.

<a id="model-selection"></a>Model selection

• Recommended primary product (Text): Gemini Flash
• Recommended primary product (Audio/Video): Gemini Flash with Gemini Live API
• Alternative product 1: Gemini Pro
  • Pros: Highest capability for reasoning, complex instructions, context tracking, and multi-agent coordination.
  • Cons: Higher request cost and latency, which makes it less suitable for real-time conversational requirements.

<a id="model-input-and-output-inspection"></a>Model input and output inspection

For security, always include model input and output inspection.

• Recommended primary product: Model Armor

<a id="vpc-connection-to-databases"></a>VPC connection to databases

An agent sends queries through this connector to securely access resources in the Virtual Private Cloud (VPC) network used for storage resources in this architecture.

• Recommended primary product: Serverless VPC Access connector
• Alternative product 1: Direct VPC egress
  • Pros: Lower latency, lower resource cost, and avoids throughput scaling bottlenecks.
  • Cons: Requires specific routing and subnet configurations.

<a id="agent-memory"></a>Agent memory

Short-term memory

• Recommended primary product: Agent Platform Sessions
  • Pros: Native, built-in managed memory for Gemini Enterprise Agent Runtime, low-ops, the default choice for most cases since it eliminates the need to provision and manage external databases.
  • Cons: Requires an Agent Runtime instance and is limited to the managed Agent Platform Sessions service (regional availability applies), although the agent itself can still run on Cloud Run or GKE.
• Alternative product 1: Memorystore for Redis Cluster
  • Pros: High performance, sub-millisecond read/write latency. Ideal escalation path when you require microsecond response times and high throughput.
  • Cons: Requires managing Redis nodes, VPC routing/peering configuration, and has a higher base cost.
• Alternative product 2: Firestore
  • Pros: Fully managed NoSQL database with serverless scaling, excellent for persistent state storage.
  • Cons: Higher latency compared to in-memory stores, which might affect real-time interactive applications.
• Alternative product 3: Cloud SQL (with ADK DatabaseSessionService)
  • Pros: Strong relational guarantees and ACID compliance for complex querying over session state.
  • Cons: Higher connection overhead and latency, and requires managing database instances.

Long-term memory

• Recommended primary product: Memory Bank
• Alternative product 1: Firestore
  • Pros: Serverless, highly scalable document database that is ideal for storing large volumes of persistent knowledge.
  • Cons: Requires custom implementation for semantic search, embedding, and retrieval logic compared to purpose-built memory solutions.

<a id="database-for-search-and-retrieval"></a>Database (for search and retrieval)

• Recommended primary product: Google Cloud Databases Use the recommendations listed on this page to help the user choose the appropriate database option (e.g., Cloud SQL, AlloyDB).
• Alternative product 1: Compute Engine (for self-hosted databases)
  • Pros: Full control over database configurations, OS accessibility, and custom database engines or extensions.
  • Cons: High operational overhead to manually manage backups, patching, scaling, and high availability.

<a id="agent-tools"></a>Agent tools

• API Management Platform (Enterprise Scale):
  • Recommended product: Apigee API hub.
  • Use case: Best for managing, securing, and monitoring a large number of API-based tools at an enterprise scale. It allows agents to connect to data instantly through prebuilt connectors or custom APIs.
• Model Context Protocol (MCP):
  • Recommended primary products:
    • Google Cloud MCP servers (fully managed by Google for connecting to Google Cloud services).
    • Cloud Run or GKE (for deploying custom, self-hosted MCP servers as containerized applications).
    • Use case: Best for building modular or multi-agent systems that require interoperable and reusable tools, decoupling the agent's logic from specific tool implementations.
• Built-in Tools:
  • Recommended primary framework: Agent Development Kit (ADK).
  • Use case: Best for common tasks (e.g., web search, code execution in a secure environment) to accelerate initial development without configuring external communication protocols.
• Custom Function Tools:
  • Use case: Best for integrating with specific internal or third-party APIs that do not have an MCP server, or for exposing an "agent-as-a-tool" function in multi-agent orchestration.