AlloyDB Basics
AlloyDB for PostgreSQL is a managed, PostgreSQL-compatible database service
designed for enterprise-grade performance and availability. It utilizes a
disaggregated compute and storage architecture to scale resources independently.
It also provides AlloyDB AI, a collection of features that includes AI-powered
search (vector, hybrid search, and AI functions), natural language capabilities,
conversational analytics, and inference features like forecasting and model
endpoint management to help developers build AI apps faster.
Quick Start
Enable the AlloyDB API:
gcloud services enable alloydb.googleapis.com --quiet
Create a Cluster:
gcloud alloydb clusters create my-cluster --region=us-central1 \
--password=my-password --network=my-vpc \
--quiet
Note: For production, we recommend using IAM database authentication
instead of passwords. If passwords must be used, use secure secret
management (e.g., Secret Manager) instead of passing passwords in
cleartext.
Create a Primary Instance:
gcloud alloydb instances create my-primary --cluster=my-cluster \
--region=us-central1 --instance-type=PRIMARY --cpu-count=2 \
--quiet
Reference Directory
Core Concepts: Architecture, disaggregated
storage, and performance features.
CLI Usage: Essential gcloud alloydb commands
for cluster and instance management.
Client Libraries & Connectors:
Connecting to AlloyDB using Python, Java, Node.js, and Go.
MCP Usage: Using the AlloyDB remote MCP server
and Gemini CLI extension.
Infrastructure as Code: Terraform
configuration and deployment examples.
IAM & Security: Predefined roles, service
agents, and database authentication.
If you need product information not found in these references, use the
Developer Knowledge MCP server search_documents tool.
---
name: alloydb-basics
description: Manages AlloyDB for PostgreSQL clusters, instances, and backups using gcloud CLI commands.
---
# AlloyDB Basics
AlloyDB for PostgreSQL is a managed, PostgreSQL-compatible database service
designed for enterprise-grade performance and availability. It utilizes a
disaggregated compute and storage architecture to scale resources independently.
It also provides AlloyDB AI, a collection of features that includes AI-powered
search (vector, hybrid search, and AI functions), natural language capabilities,
conversational analytics, and inference features like forecasting and model
endpoint management to help developers build AI apps faster.
## Quick Start
1. **Enable the AlloyDB API:**
```bash
gcloud services enable alloydb.googleapis.com --quiet
```
2. **Create a Cluster:**
```bash
gcloud alloydb clusters create my-cluster --region=us-central1 \
--password=my-password --network=my-vpc \
--quiet
```
*Note: For production, we recommend using IAM database authentication
instead of passwords. If passwords must be used, use secure secret
management (e.g., Secret Manager) instead of passing passwords in
cleartext.*
3. **Create a Primary Instance:**
```bash
gcloud alloydb instances create my-primary --cluster=my-cluster \
--region=us-central1 --instance-type=PRIMARY --cpu-count=2 \
--quiet
```
## Reference Directory
- [Core Concepts](references/core-concepts.md): Architecture, disaggregated
storage, and performance features.
- [CLI Usage](references/cli-usage.md): Essential `gcloud alloydb` commands
for cluster and instance management.
- [Client Libraries & Connectors](references/client-library-usage.md):
Connecting to AlloyDB using Python, Java, Node.js, and Go.
- [MCP Usage](references/mcp-usage.md): Using the AlloyDB remote MCP server
and Gemini CLI extension.
- [Infrastructure as Code](references/iac-usage.md): Terraform
configuration and deployment examples.
- [IAM & Security](references/iam-security.md): Predefined roles, service
agents, and database authentication.
*If you need product information not found in these references, use the
Developer Knowledge MCP server `search_documents` tool.*
