1. High-Throughput Model Serving with Atlas Peering


    Creating a high-throughput model serving setup usually involves deploying machine learning models on servers positioned for efficient data transfer and low latency access. With Atlas Peering, the specific use case may involve connecting your cloud resources to MongoDB Atlas, which is MongoDB's fully-managed database-as-a-service platform. Peering connections can provide a private and direct network connection between your cloud resources (such as virtual machines serving models) and your MongoDB Atlas cluster.

    In the context of Pulumi, we would need to create resources with a cloud provider to host our models and set up network peering with MongoDB Atlas. This example focuses on using MongoDB Atlas and assumes that you have a MongoDB Atlas project set up.

    Here's a program written in Python that demonstrates how you can achieve this with Pulumi. This Pulumi program will:

    1. Create a VPC to host our resources.
    2. Create a peering connection between the VPC and MongoDB Atlas.
    3. Configure routes for the peering connection.
    import pulumi import pulumi_mongodbatlas as mongodbatlas import pulumi_aws as aws # Replace these variables with your actual Project ID and Container ID from MongoDB Atlas atlas_project_id = 'your_atlas_project_id' atlas_container_id = 'your_atlas_container_id' # Configure your AWS region (choose the one that is close to your Atlas cluster to reduce latency) aws_region = aws.get_region() # Create an AWS VPC for our model serving infrastructure serving_vpc = aws.ec2.Vpc('serving_vpc', cidr_block='') # Create a subnet where the actual model serving instances will live serving_subnet = aws.ec2.Subnet('serving_subnet', vpc_id=serving_vpc.id, cidr_block='', availability_zone=aws_region.name) # Create a MongoDB Atlas network peering resource atlas_peering_connection = mongodbatlas.NetworkPeering('atlas_peering_connection', atlas_cidr_block='', # The CIDR block of your Atlas cluster aws_account_id=serving_vpc.owner_id, vpc_id=serving_vpc.id, project_id=atlas_project_id, container_id=atlas_container_id, provider_name='AWS') # Add routes to the VPC route table for the Atlas CIDR block route = aws.ec2.Route('route', route_table_id=serving_vpc.main_route_table_id, destination_cidr_block=atlas_peering_connection.atlas_cidr_block, vpc_peering_connection_id=atlas_peering_connection.id) # Export the VPC and subnet IDs as stack outputs pulumi.export('serving_vpc_id', serving_vpc.id) pulumi.export('serving_subnet_id', serving_subnet.id)

    In this program:

    • We import the necessary Pulumi modules for AWS and MongoDB Atlas.
    • We define the AWS region to ensure resources are provisioned close to the Atlas cluster.
    • We create a VPC and a subnet using AWS resources where the model serving instances will be hosted.
    • We set up the network peering connection with mongodbatlas.NetworkPeering. This forms a bridge between the AWS VPC and MongoDB Atlas.
    • We add a route to the VPC's main route table to allow direct access to MongoDB Atlas via this peering connection.
    • Finally, we export the IDs of the VPC and subnet as stack outputs so that they can be accessed and used to set up additional resources or reference outside of Pulumi.

    Please remember to replace placeholder values (your_atlas_project_id, your_atlas_container_id, and the CIDR blocks) with actual values from your MongoDB Atlas setup.

    By establishing a peering connection, this allows direct network connectivity between your AWS infrastructure and MongoDB Atlas, which can help reduce data transfer costs and enhance the performance of your applications that are hosted within AWS and require access to your Atlas database.