1. Long-Term Data Retention for AI Compliance with Event Store Cloud

    Python

    To achieve long-term data retention for AI compliance using Event Store Cloud, you will typically need to create an Event Store Cloud managed cluster, where your events will be stored. Then, set up scheduled backups to ensure your data is backed up regularly and securely stored. These backups can later be used to restore the data if needed. It's also a best practice to create the necessary network infrastructure within Event Store Cloud for your managed cluster to operate within.

    Below is a Pulumi program to create these resources using Event Store Cloud on Pulumi:

    1. An Event Store Cloud project (Project).
    2. A VPC network within Event Store Cloud (Network).
    3. A managed cluster in Event Store Cloud (ManagedCluster).
    4. A scheduled backup policy for this cluster (ScheduledBackup).

    Each step is annotated with comments explaining the purpose of the code.

    import pulumi import pulumi_eventstorecloud as eventstorecloud # Create a new project in Event Store Cloud project = eventstorecloud.Project("ai-compliance-project", name="ai-compliance-project") # Create a network within Event Store Cloud. This network is equivalent # to a VPC in the cloud infrastructure sense where your managed cluster will operate. network = eventstorecloud.Network("network", projectId=project.id, name="escloud-vpc", resourceProvider="aws", # Specify the cloud provider for the network. region="us-west-2", # Specify the region where the network should be created. cidrBlock="10.0.0.0/24") # The block of IPs to use for the network. This range should not overlap with other networks you have. # Creates a managed cluster in Event Store Cloud managed_cluster = eventstorecloud.ManagedCluster("managed-cluster", projectId=project.id, networkId=network.id, topology="single-node", # The cluster topology. "single-node" or "multi-node" are the options. instanceType="F1", # The instance type of the cluster. This depends on your compliance requirements for performance and capacity. diskSize=100, # The disk size in GB. Ensure sufficient space for long-term data retention. serverVersion="21.6.0", # The version of EventStoreDB to use. diskType="general-purpose", # The disk type. Select one that matches your requirements for performance and cost. projectionLevel="off") # Projection level decides the event indexing strategy. # Create a scheduled backup for the managed cluster scheduled_backup = eventstorecloud.ScheduledBackup("scheduled-backup", projectId=project.id, sourceClusterId=managed_cluster.id, description="Daily Backup", schedule="0 0 * * *", # The backup schedule in cron format; this is for daily backups at midnight. maxBackupCount=7) # The number of backups to keep. This ensures one week of backups is retained. # Export the IDs of the created resources pulumi.export("project_id", project.id) pulumi.export("network_id", network.id) pulumi.export("managed_cluster_id", managed_cluster.id) pulumi.export("scheduled_backup_id", scheduled_backup.id)

    This program uses Pulumi to automate the provisioning and management of Event Store Cloud resources which are crucial for long-term data retention and compliance in AI applications. Pulumi enables you to describe infrastructure as code and perform repeatable and reliable deployments.

    Key Steps:

    • Project Creation: A project in Event Store Cloud serves as a container for your resources. It helps in grouping related infrastructure for better management and billing.
    • Network Creation: Setting up a network within Event Store Cloud ensures that your managed cluster is secured and operates in an isolated environment.
    • Managed Cluster Creation: The managed cluster is where your event data is stored. It is essential for the functioning of your AI applications and for compliance purposes. The cluster configuration depends on your specific use case and requirements for data storage, performance, and cost.
    • Scheduled Backups: Regularly scheduled backups are crucial for disaster recovery and compliance. They ensure that you have historical data snapshots that can be restored if data loss or corruption occurs.

    The ManagedCluster and ScheduledBackup resources ensure you have a secured, versioned, and backed-up Event Store, which is vital for achieving compliance with data protection regulations in AI systems.

    To run this code, you need to set up Pulumi and have access to Event Store Cloud with permissions to create projects, networks, and clusters. Save this code to a __main__.py file and run pulumi up to deploy your infrastructure.