cloudsql_setup

Name: cloudsql_setup
Author: VeerMuchandi

15stars1forks

How to install cloudsql_setup?

veermuchandi/rad-skills/cloudsql_setup

$npx -y skills add VeerMuchandi/rad-skills --skill cloudsql_setup

Installs into the current project.

Summary

Provisions a PostgreSQL Cloud SQL instance, database, database user, and registers connection details in Secret Manager using Terraform.

Files · 1

View on GitHub

SKILL.md

1	# Cloud SQL Setup Skill
2
3	This skill allows you to easily provision a PostgreSQL database on Google Cloud Platform using Terraform. It automatically enables required APIs, configures a secure database instance, creates a database and a user with a secure auto-generated password, and registers all connection parameters in Secret Manager for use by ADK agents.
4
5	## Prerequisites
6	- Terraform Version: `v1.5+` (Recommended `v1.14+`)
7	- GCP Project: Active Google Cloud Project with billing enabled.
8	- Permissions:
9	- `roles/sqladmin.admin` (to manage Cloud SQL)
10	- `roles/secretmanager.admin` (to manage secrets)
11	- `roles/serviceusage.serviceUsageConsumer` (to enable services)
12
13	## Skill Directory Structure
14	```text
15	cloudsql_setup/
16	├── SKILL.md # This instructions file
17	├── resources/
18	│ └── templates/
19	│ ├── main.tf # Core Terraform resources
20	│ ├── variables.tf # Customizable variables
21	│ └── outputs.tf # Secret IDs and Connection Name outputs
22	└── scripts/
23	└── deploy_db.py # Helper Python script to orchestrate deployment
24	```
25
26	## 1. How to Use this Skill (Step-by-Step)
27
28	### Step 1: Initialize the Deployment Workspace
29	Create a dedicated deployment directory outside your agent code package to prevent Terraform state/binaries from being packaged with the agent.
30
31	```bash
32	mkdir -p deploy_db
33	```
34
35	### Step 2: Copy the Templates
36	Copy the templates from this skill to your new `deploy_db` folder.
37	(Note: Replace `<path_to_skill>` with the path of this skill folder, e.g. `skills/cloudsql_setup` or `~/.gemini/config/skills/cloudsql_setup`)
38
39	```bash
40	cp -r <path_to_skill>/resources/templates/* deploy_db/
41	```
42
43	### Step 3: Configure Deployment (`deploy_db/terraform.tfvars`)
44	Create a file named `deploy_db/terraform.tfvars` and set the following parameters:
45
46	```hcl
47	project_id = "your-gcp-project-id"
48	region = "us-central1"
49	instance_name_prefix = "my-adk-db"
50	database_flavor = "postgres" # or "mysql"
51	database_version = "POSTGRES_15" # or "MYSQL_8_0"
52	database_name = "my_agent_db"
53	db_username = "db_user"
54	secret_prefix = "my_agent_" # secrets will be created with prefix: my_agent_
55	deletion_protection = false # Set to true for production database
56	```
57
58	### Step 4: Run Terraform
59	Navigate to the `deploy_db` directory, initialize, and deploy the resources:
60
61	```bash
62	cd deploy_db
63	terraform init
64	terraform apply -auto-approve
65	```
66
67	### Step 5: Capture Output
68	Upon successful completion, Terraform outputs the connection details and Secret Manager secret IDs:
69	```hcl
70	connection_name = "your-project:us-central1:my-adk-db-xxxx"
71	secret_ids = {
72	db_connection_name = "my_agent_db_connection_name"
73	db_name = "my_agent_db_name"
74	db_password = "my_agent_db_password"
75	db_user = "my_agent_db_user"
76	}
77	```
78
79	### Option B: Using the Orchestration Helper Script (Recommended)
80	You can automate the deployment, secrets creation, and database schema initialization in a single step using the helper Python script.
81
82	1. Create Schema File (e.g. `schema.sql`):
83	```sql
84	CREATE TABLE IF NOT EXISTS items (
85	id SERIAL PRIMARY KEY,
86	name VARCHAR(100) NOT NULL,
87	description TEXT
88	);
89	```
90
91	2. Run the Script:
92	```bash
93	python3 <path_to_skill>/scripts/deploy_db.py \
94	--project "your-gcp-project-id" \
95	--sql-file "schema.sql"
96	```
97
98	This script will run the Terraform deployment and then connect to the Cloud SQL instance over secure IAM-auth using the Python connector to execute the statements in your SQL file.
99
100	---
101
102	## 2. Connecting ADK Agent to Cloud SQL
103	To use the newly created database in your ADK agent:
104
105	1. Add Dependencies: Include these in your agent's `requirements.txt`:
106	```text
107	cloud-sql-python-connector[pg8000]
108	SQLAlchemy
109	google-cloud-secret-manager
110	```
111	2. Access Secrets in Agent: Refer to the `secret_ids` generated. Set environment variables on the deployed agent containing the secret IDs, and use the Cloud SQL Python Connector library to access the database.
112
113	---
114
115	## 3. Troubleshooting & Learnings
116
117	### 3.1. PostgreSQL User Deletion (`cannot be dropped because some objects depend on it`)
118	- The Issue: When running `--destroy` (or `terraform destroy`), if you populated the database (created tables, sequences, etc.) using that user, PostgreSQL will block dropping the user because of these dependent objects.
119	- The Workaround: Simply re-run the destroy command. Since the database itself was already deleted during the first run, the user's dependencies are resolved and the second run will complete cleanly.

People who liked this also viewed

6 picks

Type

azure-storageAzure Storage Services including Blob Storage, File Shares, Queue Storage, Table Storage, and Data Lake. Answers questions about storage access tiers (hot, cool, cold, archive), when to use each tier,SkillsJul 2026471k1.3k
supabase-postgres-best-practicesPostgres performance optimization and best practices from Supabase. Use this skill when writing, reviewing, or optimizing Postgres queries, schema designs, or database configurations.SkillsJul 2026302k2.4k
supabaseUse when doing ANY task involving Supabase. Triggers: Supabase products (Database, Auth, Edge Functions, Realtime, Storage, Vectors, Cron, Queues); client libraries and SSR integrations (supabase-js, SkillsJul 2026179k2.4k
convex-quickstartCreates or adds Convex to an app. Use for new Convex projects, npm create convex@latest, frontend setup, env vars, or the first npx convex dev run.SkillsJul 202690k39
convex-performance-auditAudits Convex performance for reads, subscriptions, write contention, and function limits. Use for slow features, insights findings, OCC conflicts, or read amplification.SkillsJul 202689k39
convex-setup-authSets up Convex auth, identity mapping, and access control. Use for login, auth providers, users tables, protected functions, or roles in a Convex app.SkillsJul 202689k39

cloudsql_setup

15stars1forks

View on GitHub

How to install cloudsql_setup?

veermuchandi/rad-skills/cloudsql_setup

$npx -y skills add VeerMuchandi/rad-skills --skill cloudsql_setup

Installs into the current project.

Summary

Provisions a PostgreSQL Cloud SQL instance, database, database user, and registers connection details in Secret Manager using Terraform.

Files · 1

View on GitHub

SKILL.md

1	# Cloud SQL Setup Skill
2
3	This skill allows you to easily provision a PostgreSQL database on Google Cloud Platform using Terraform. It automatically enables required APIs, configures a secure database instance, creates a database and a user with a secure auto-generated password, and registers all connection parameters in Secret Manager for use by ADK agents.
4
5	## Prerequisites
6	- Terraform Version: `v1.5+` (Recommended `v1.14+`)
7	- GCP Project: Active Google Cloud Project with billing enabled.
8	- Permissions:
9	- `roles/sqladmin.admin` (to manage Cloud SQL)
10	- `roles/secretmanager.admin` (to manage secrets)
11	- `roles/serviceusage.serviceUsageConsumer` (to enable services)
12
13	## Skill Directory Structure
14	```text
15	cloudsql_setup/
16	├── SKILL.md # This instructions file
17	├── resources/
18	│ └── templates/
19	│ ├── main.tf # Core Terraform resources
20	│ ├── variables.tf # Customizable variables
21	│ └── outputs.tf # Secret IDs and Connection Name outputs
22	└── scripts/
23	└── deploy_db.py # Helper Python script to orchestrate deployment
24	```
25
26	## 1. How to Use this Skill (Step-by-Step)
27
28	### Step 1: Initialize the Deployment Workspace
29	Create a dedicated deployment directory outside your agent code package to prevent Terraform state/binaries from being packaged with the agent.
30
31	```bash
32	mkdir -p deploy_db
33	```
34
35	### Step 2: Copy the Templates
36	Copy the templates from this skill to your new `deploy_db` folder.
37	(Note: Replace `<path_to_skill>` with the path of this skill folder, e.g. `skills/cloudsql_setup` or `~/.gemini/config/skills/cloudsql_setup`)
38
39	```bash
40	cp -r <path_to_skill>/resources/templates/* deploy_db/
41	```
42
43	### Step 3: Configure Deployment (`deploy_db/terraform.tfvars`)
44	Create a file named `deploy_db/terraform.tfvars` and set the following parameters:
45
46	```hcl
47	project_id = "your-gcp-project-id"
48	region = "us-central1"
49	instance_name_prefix = "my-adk-db"
50	database_flavor = "postgres" # or "mysql"
51	database_version = "POSTGRES_15" # or "MYSQL_8_0"
52	database_name = "my_agent_db"
53	db_username = "db_user"
54	secret_prefix = "my_agent_" # secrets will be created with prefix: my_agent_
55	deletion_protection = false # Set to true for production database
56	```
57
58	### Step 4: Run Terraform
59	Navigate to the `deploy_db` directory, initialize, and deploy the resources:
60
61	```bash
62	cd deploy_db
63	terraform init
64	terraform apply -auto-approve
65	```
66
67	### Step 5: Capture Output
68	Upon successful completion, Terraform outputs the connection details and Secret Manager secret IDs:
69	```hcl
70	connection_name = "your-project:us-central1:my-adk-db-xxxx"
71	secret_ids = {
72	db_connection_name = "my_agent_db_connection_name"
73	db_name = "my_agent_db_name"
74	db_password = "my_agent_db_password"
75	db_user = "my_agent_db_user"
76	}
77	```
78
79	### Option B: Using the Orchestration Helper Script (Recommended)
80	You can automate the deployment, secrets creation, and database schema initialization in a single step using the helper Python script.
81
82	1. Create Schema File (e.g. `schema.sql`):
83	```sql
84	CREATE TABLE IF NOT EXISTS items (
85	id SERIAL PRIMARY KEY,
86	name VARCHAR(100) NOT NULL,
87	description TEXT
88	);
89	```
90
91	2. Run the Script:
92	```bash
93	python3 <path_to_skill>/scripts/deploy_db.py \
94	--project "your-gcp-project-id" \
95	--sql-file "schema.sql"
96	```
97
98	This script will run the Terraform deployment and then connect to the Cloud SQL instance over secure IAM-auth using the Python connector to execute the statements in your SQL file.
99
100	---
101
102	## 2. Connecting ADK Agent to Cloud SQL
103	To use the newly created database in your ADK agent:
104
105	1. Add Dependencies: Include these in your agent's `requirements.txt`:
106	```text
107	cloud-sql-python-connector[pg8000]
108	SQLAlchemy
109	google-cloud-secret-manager
110	```
111	2. Access Secrets in Agent: Refer to the `secret_ids` generated. Set environment variables on the deployed agent containing the secret IDs, and use the Cloud SQL Python Connector library to access the database.
112
113	---
114
115	## 3. Troubleshooting & Learnings
116
117	### 3.1. PostgreSQL User Deletion (`cannot be dropped because some objects depend on it`)
118	- The Issue: When running `--destroy` (or `terraform destroy`), if you populated the database (created tables, sequences, etc.) using that user, PostgreSQL will block dropping the user because of these dependent objects.
119	- The Workaround: Simply re-run the destroy command. Since the database itself was already deleted during the first run, the user's dependencies are resolved and the second run will complete cleanly.

People who liked this also viewed

6 picks

Type