1. Session Store for User Personalization with AWS Redis


    To create a session store for user personalization with AWS Redis using Pulumi, you'll typically use the AWS Elasticache service with a Redis cache cluster. AWS Elasticache provides a fully managed in-memory data store, compatible with Redis, which makes it ideal for use cases like session stores where fast read and write access to data is required.

    Here's what we're doing:

    1. Create an Elasticache Cluster: We'll provision an Elasticache Redis cluster that will serve as the session store.
    2. Configure Security Groups: We'll configure a security group to control access to the Redis cluster.
    3. Export Connection Details: Finally, we'll export the Redis cluster's endpoint address and port number, which you would use to connect your application to the Redis session store.

    Let's get started with the Pulumi Python program:

    import pulumi import pulumi_aws as aws # Create a security group for the Redis cluster redis_security_group = aws.ec2.SecurityGroup('redisSecurityGroup', description='Enable Redis port access', egress=[{ 'from_port': 0, 'to_port': 0, 'protocol': '-1', 'cidr_blocks': [''], }], ingress=[{ 'from_port': 6379, 'to_port': 6379, 'protocol': 'tcp', 'cidr_blocks': [''], # Only for demonstration purposes! In production, restrict to your app's IP range. }] ) # Create an Elasticache Redis cluster redis_cluster = aws.elasticache.Cluster('redisCluster', engine='redis', # You can customize these parameters according to your needs: node_type='cache.t2.micro', # Example node type, choose according to your usage num_cache_nodes=1, # Single node for demonstration purposes. Consider replication for production. parameter_group_name='default.redis3.2', security_group_ids=[redis_security_group.id], # For production, you should provision in specific subnets and use a replication group for high-availability ) # Export the Redis endpoint address and port, to use with your applications pulumi.export('redis_endpoint', redis_cluster.cache_nodes.apply(lambda nodes: nodes[0]['address'])) pulumi.export('redis_port', redis_cluster.cache_nodes.apply(lambda nodes: nodes[0]['port']))

    In this program:

    • We first set up an AWS security group redisSecurityGroup, which defines the ingress rules to allow traffic on the port that Redis uses (default: 6379).
    • The aws.elasticache.Cluster resource creates a new Redis cluster. We set properties like:
      • engine: We specify that we want Redis.
      • node_type: Which affects the price and performance. Pick the type that matches your workload.
      • num_cache_nodes: The number of nodes in the cluster. Starting with one, but for production workloads, you may want more nodes for more capacity and for failover purposes.
      • security_group_ids: Associates the Redis cluster with the security group we defined earlier.
    • The last part of the script exports the endpoint address and the port of the Redis cluster. This information is typically used to configure the application that will access the Redis cluster.

    The result of this program is a Redis cluster hosted on AWS Elasticache, which your application can use for session storage or other in-memory data storage needs. Remember to adjust the ingress rules to limit traffic only from your application servers and to use multiple nodes in a replication group for a production used case.