Scaling Read Operations with DigitalOcean Database Clusters

Question

Pulumi · Accepted Answer

When you need to scale the read operations in your DigitalOcean database cluster, you can do so by adding read replicas. Read replicas are copies of your primary database that handle read-only queries, which can distribute the workload and lead to more efficient overall database performance.

To scale your read operations using Pulumi and DigitalOcean, you would typically follow these steps:
1. Define your database cluster resource, configuring it with the desired number of nodes to handle your read operations.
2. Create read-only users if necessary, who will connect to your read replicas instead of your primary database.
3. Optionally, set up additional databases or configure the firewall to manage access to the database cluster.

Below is a Pulumi program written in Python that illustrates how to scale read operations with a DigitalOcean Database Cluster by setting up a cluster with multiple nodes. Note that this program does not create extra read-only users but assumes that you're doing so if required for your use case.

```python
import pulumi
import pulumi_digitalocean as digitalocean

# Initialize a new DigitalOcean project.
project = digitalocean.Project("my-database-project",
    name="my-database-project",
    description="A DigitalOcean project for database scaling",
    purpose="Scale read operations for a production environment",
    environment="Production",
    is_default=False)

# Create a new database cluster with multiple nodes to handle read operations.
database_cluster = digitalocean.DatabaseCluster("read-scale-cluster",
    engine="pg",  # The type of the engine used ('pg' for PostgreSQL, 'mysql' for MySQL, etc.)
    version="13",  # The version of the database engine
    size="db-s-1vcpu-1gb",  # The size slug indicating the CPU and memory
    region="nyc3",  # The region slug to deploy the database cluster in
    node_count=2,  # The number of nodes in the database cluster for read scaling
    project_id=project.id, # Associates the project with the created database cluster
)

# The cluster's connection information as an output.
primary_endpoint = pulumi.Output.all(database_cluster.host, database_cluster.port, database_cluster.user).apply(
    lambda args: f"{args[2]}@{args[0]}:{args[1]}"
)

# Export the connection string for the database cluster, it can be used to connect to the primary database directly.
pulumi.export("primary_endpoint", primary_endpoint)

# Optionally, you can add firewall rules, create extra databases, or create read-only users using other
# DigitalOcean Pulumi Resources. For example, digitalocean.DatabaseDb and digitalocean.DatabaseUser.
```

In the program above:
- We create a new project to organize our resources within DigitalOcean.
- We define a `DatabaseCluster` using the `digitalocean.DatabaseCluster` resource. 
  - The `engine` property specifies the type of database, in this case, "pg" for PostgreSQL.
  - We specify the database version with the `version` property.
  - The `size` property is provided to allocate the right amount of resources. DigitalOcean provides different slugs representing various preconfigured resource allocations.
  - `region` is set to where the cluster should be deployed. Use a region closest to your application's users for reduced latency.
  - The `node_count` property is key to scaling read operations. It sets the number of nodes in the cluster. For read scaling, you can increase this number depending on the read workload.
  - All resources are associated with the project we created earlier by passing the project ID.
- We create an output `primary_endpoint` to hold the connection string information for the primary database node in the cluster, which can be used to make direct connections.
- Finally, we export the `primary_endpoint` so it can be easily accessed after deployment.

Please adapt the properties according to your actual needs, like `engine`, `version`, `size`, and `region`. The number of nodes, determined by `node_count`, can be increased to handle the anticipated read load.

This program doesn't show the creation of read-only users, but you can use the `digitalocean.DatabaseUser` resource for defining users with read-only permissions and then connect to read replicas using their credentials.

You would run this program using the Pulumi CLI, with commands such as `pulumi up` to create or update resources or `pulumi destroy` to delete resources. Ensure that you have DigitalOcean access configured in your environment, such as through environment variables or the Pulumi configuration.