1. Using aws elasticloadbalancingv2 with emr

    TypeScript

    In order to integrate AWS Elastic Load Balancing (ELB) with Amazon EMR (Elastic MapReduce), you would commonly create a Load Balancer that directs traffic to an EMR cluster. AWS EMR clusters are managed Hadoop frameworks that are used for processing large amounts of data. ELB can be used to improve the accessibility and distribute the traffic across the instances in the EMR cluster.

    Here's a basic overview of how you could set this up using Pulumi with TypeScript:

    1. First, ensure you have the AWS Pulumi provider installed and configured.
    2. You'll then create an aws.elasticloadbalancingv2.LoadBalancer resource. Specify the type of load balancer according to your needs: it can be application or network.
    3. Next, create an aws.elasticloadbalancingv2.TargetGroup for the Load Balancer to route requests to the instances in the EMR cluster.
    4. Create an aws.elasticloadbalancingv2.Listener and connect it to the Load Balancer and Target Group.
    5. Finally, set up an EMR cluster with aws.emr.Cluster, with instance groups that correspond to the Target Group created.

    Below is the TypeScript code demonstrating the setup:

    import * as aws from "@pulumi/aws"; // Create a new load balancer of type 'application' or 'network', depending on your needs const loadBalancer = new aws.elasticloadbalancingv2.LoadBalancer("emr-loadbalancer", { loadBalancerType: "application", // or network subnets: ["subnet-xxxxxxxxxxxxx"], // VPC Subnets securityGroups: ["sg-xxxxxxxxxxxxx"], // Configure your security groups }); // Create a new target group const targetGroup = new aws.elasticloadbalancingv2.TargetGroup("emr-targetgroup", { port: 80, protocol: "HTTP", targetType: "instance", // or 'ip' if you are targeting instances by IP directly vpcId: "vpc-xxxxxxxxxxxxx", // Your VPC ID }); // Create a listener for the load balancer const listener = new aws.elasticloadbalancingv2.Listener("emr-listener", { loadBalancerArn: loadBalancer.arn, port: 80, defaultActions: [{ type: "forward", targetGroupArn: targetGroup.arn, }], }); // Create an EMR cluster const cluster = new aws.emr.Cluster("emr-cluster", { releaseLabel: "emr-5.29.0", // specify your EMR release label masterInstanceType: "m4.large", slaveInstanceType: "m4.large", instanceCount: 3, // number of instances for the EMR cluster applications: ["Hadoop", "Spark"], // specify your applications ec2Attributes: { subnetId: "subnet-xxxxxxxxxxxxx", // VPC subnet ID emrManagedMasterSecurityGroup: "sg-xxxxxxxxxxxxx", // Security group for master node emrManagedSlaveSecurityGroup: "sg-xxxxxxxxxxxxx", // Security group for slave nodes // Additional attributes as needed }, }); // Export the DNS name of the load balancer export const loadBalancerDnsName = loadBalancer.dnsName; // Export the EMR cluster ID export const emrClusterId = cluster.id;

    This program creates a load balancer that can distribute traffic across the nodes of an EMR cluster. It sets up a target group to track the group of instances and then attaches them to a listener on the load balancer.

    Keep in mind that this is a basic setup and that in reality, you would likely need to configure additional aspects like:

    • Enhanced VPC routing for EMR
    • Fine-tuning security group ingress and egress rules
    • Advanced load balancer settings like stickiness and health checks

    This Pulumi setup assumes you have the necessary AWS infrastructure and permissions in place. If you are new to AWS or Pulumi, you might need to set up foundational resources like a VPC or IAM roles first.

    For more details, please check the ELB LoadBalancer documentation and the EMR Cluster documentation.

    Remember that running this Pulumi program will create real resources on AWS and incur costs. Make sure you review the resource definitions and tweak them as necessary for your use case.


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