[0:00]Hello, everyone. My name is Elizabeth and I'm a solutions architect here at AWS. Today, I'm going to walk you through an introduction to Amazon Elastic Container Service, also known as ECS. I'll be covering what ECS is, the components that make up ECS, and when to use ECS. Then, I'll walk through a quick demo where I deploy a sample containerized application to ECS using the AWS console. First, let's start with what exactly is Amazon ECS. Amazon ECS is a fully managed container orchestration service that helps you easily deploy, manage, and scale containerized applications. What this means is that ECS takes care of the operational heavy lifting of managing your container workloads, such as provisioning and scaling infrastructure, scheduling containers, and monitoring their health. So, you can focus on building and innovating your applications instead of managing the underlying infrastructure. ECS integrates with other AWS services, such as Elastic Load Balancing for load balancing and routing traffic, Amazon Route 53 for DNS management, Amazon CloudWatch for monitoring and logging, and AWS Identity and Access Management for secure access control. These integrations allow you to build robust and scalable containerized applications with ease. Next, let's dive into the core components that make up Amazon ECS. The first component is the ECS cluster. An ECS cluster is a logical grouping of tasks or services that you deploy and manage together. It's essentially a compute environment where your containerized applications run. The next component is a task definition. A task definition is a blueprint for your application. It describes how your application should run, including the Docker image to use, CPU and memory requirements, environment variables, and port mappings. It's like a recipe for your containerized application. The next component is a task. A task is an instance of a task definition running on an ECS cluster. It represents a single running container or a group of related containers that work together to form a part of your application. Think of it as a running instance of your application based on the task definition blueprint. And the final component is a service. An ECS service allows you to run and maintain a specified number of copies of a task definition simultaneously. It ensures that your desired number of tasks are always running, even if a task fails or stops. The service can also integrate with Elastic Load Balancing to distribute traffic across your tasks and support auto-scaling to adjust the number of tasks based on demand. Now that we have a good understanding of what ECS is and its components, let's explore when to use Amazon ECS. ECS is a great choice when you need a fully managed container orchestration service that simplifies the deployment, management, and scaling of containerized applications. It's a good fit for microservices architectures where you break down your application into smaller, independently deployable services. ECS also offers flexible compute options, allowing you to choose between Amazon EC2 instances for more control over your infrastructure or AWS Fargate for a serverless experience where AWS manages the underlying infrastructure. This flexibility allows you to optimize costs and operational overhead based on your specific needs. You can also use ECS for batch processing workloads, running long-running services, and even machine learning inference. Now let's jump into a quick demo. In this demo, I'll be deploying a sample containerized application to ECS using the AWS console. This application will consist of a simple engine X web server that will serve a static HTML page. I'll walk through the process of creating an ECS cluster, defining a task definition, and deploying a service to run our containerized application. First, I'll navigate to the ECS console and select clusters. Here, you'll see a list of your existing clusters. I'll create a new cluster by clicking the Create Cluster button. I'll then be prompted to choose a cluster template. I'll select the EC2 Linux plus networking template, as I want to provision my own EC2 instances. Next, I'll configure the cluster by giving it a name, demo cluster, and choosing an EC2 instance type. I'll stick with the default T2 micro. Then, I'll specify the number of instances I want in my cluster. I'll choose one for this demo. Then, I'll select an existing key pair. Finally, I'll choose to create a new security group and allow inbound traffic on port 80 to enable access to our web server. I'll click the create button to create our cluster. It will take a few minutes for the cluster to be provisioned, including the EC2 instance. While our cluster is being created, let's move on to creating a task definition. I'll navigate to the task definitions section of the ECS console and click the create new task definition button. I'll then choose the EC2 launch type compatibility since we're using EC2 instances in our cluster. Next, I'll configure the task definition by giving it a name, engine X task def. I'll then specify the task memory and task CPU. I'll enter 512 for memory and 256 for CPU. Next, I'll add a container to our task definition. I'll give the container a name, engine X, and specify the image to use, which will be the latest engine X image from Docker Hub. I'll also set the port mapping to 80 for both the host and container ports to expose our web server. I'll click add to add the container and then click create to create our task definition. Now that our cluster and task definition are ready, let's create a service to run our engine X container. I'll navigate back to our demo cluster and click the create button under the services tab. I'll then configure the service by selecting the EC2 launch type and choosing our engine X task def task definition. I'll also set the desired tasks to one to run a single instance of our engine X container. I'll give the service a name, engine X service, and leave the remaining settings as default. I'll click next step, then next step again, and finally create service to create our service. Our service is now being created and our engine X container is being deployed to our cluster. Once the service is active, we can view the running task by navigating to the tasks tab. We can also verify that our web server is running by accessing the public IP of our EC2 instance. I'll navigate to the EC2 console, select our running instance, and copy its public IP. I'll paste the IP into my browser and we should see the engine X welcome page, which confirms that our containerized application is successfully running on ECS. In conclusion, Amazon ECS is a powerful and flexible container orchestration service that simplifies the deployment, management, and scaling of containerized applications. By understanding its core components and when to use it, you can leverage ECS to build robust, scalable, and highly available applications. I hope this introduction has been helpful in getting you started with Amazon ECS. Thank you for watching.