Appreciate that makes this a bit harder to debug, but it does seem clear that there are issues with the ECS CLI scale command. Not only do we plan on publishing some additional deep dive posts here on the containers blog covering other aspects of ECS and capacity providers, but we also are actively working on expanding the capabilities we offer. When the scaling policy reduces N, it is adjusting the number of instances but it has no control over which instances actually terminate. I've since switched to aws-cli for this as it seems a bit more robust. In order to determine M, we need to have a concept of tasks that the customer is trying to run that don’t fit on existing instances. We run a couple of cli calls to get the Auto Scaling group details which is required for the next command where we create the capacity provider. In order to convert M and N into a metric that is compatible with target tracking scaling, we must obey the requirement that the “metric value must increase or decrease proportionally to the number of instances in the Auto Scaling group.” With this requirement in mind, our formula for CapacityProviderReservation is (as stated previously): There are a few special cases where this formula is not used. ECS will ensure the ASG scales in and … Thanks for letting us know we're doing a good Ideally, CAS would calculate a value for M that is optimal – that is, no bigger and no smaller than it needs to be to run all provisioning tasks. Once CAS has determined M, why don’t we just directly set the desired capacity of the ASG (in other words, just force an update to N so that N = M)? The AWS Copilot CLI is a tool for developers to build, release and operate production ready containerized applications on Amazon ECS and AWS Fargate. With AWS Fargate, you no longer have to provision, configure, or scale clusters of virtual machines to run containers. In this blog post, I’m going to deep dive on exactly how CAS works. Specifies the number of instances to maintain in your AWS announced Cluster Auto Scaling for ECS in December 2019. ecs-cli scale Modifies the number of container instances in your cluster. cluster_config_name. Step 2. Containerise the Mythical Mysfits monolith Lab 2. Given N and M, this metric has a very simple definition: To put it in plain language, the metric is the ratio of how big the ASG needs to be relative to how big it actually is, expressed as a percentage. Managed scaling is enabled with a target capacity of 100, and managed termination protection is enabled. But I don't know how to do it using AWS CLI. the documentation better. ECS Cluster Auto Scaling (CAS) is a new capability for ECS to manage the scaling of EC2 Auto Scaling Groups (ASG). The scaling behavior is built on the assumption that the “metric value must increase or decrease proportionally to the number of instances in the Auto Scaling group.” CapacityProviderReservation is designed for this assumption. Hi Team, I have created an ECS cluster in AWS. profile configured using the configure profile command. Hi Team, I have created an ECS cluster in AWS. Scale in would never happen if we included daemon services). As we will see later, we also define a new CloudWatch metric based on N and M, called the CapacityProviderReservation. Defaults to the cluster configured using the configure command. Please refer to your browser's Help pages for instructions. So, in order to achieve all three design goals, CAS relies on AWS Auto Scaling in addition to instance termination protection. Instead, the scaling policy will adjust N to achieve a value close to the target value, with a preference for the metric to be less than the target value if possible. ... after all these calculations we call the AWS CLI command aws ecs update-service to update the ECS service to the new number of ECS tasks, only errors are printed to stdout to avoid the huge default output from this CLI … For example, if you set the target value to 50, the scaling policy will try to adjust N so that the equation M / N X 100 = 50 is true. AWS Management Console. Installing AWS-CLI. For example, if the target value is 75, and M = 10 instances, it is not possible for M / N X 100 to equal 75, since N must be a whole number. I've since switched to aws-cli for this as it seems a bit more robust. This command changes the The weight value designates the relative percentage of the total number of tasks launched that should use the specified capacity provider.. For example, if you have a strategy that contains two capacity providers and both have a weight of 1, then when the base is satisfied, the tasks will be split evenly across the two capacity providers. ECS Service Level Autoscaling. Scale the tasks: ecs-cli compose --project-name ecsdemo-frontend service scale 3 \ --cluster-config container-demo ecs-cli compose --project-name ecsdemo-frontend service ps \ --cluster-config container-demo We can see that our containers have now been evenly distributed across all 3 … RunTask is called with nine more tasks. The Amazon ECS CLI can only manage tasks, services, and container instances that Acknowledges that this command may create IAM resources. The Scale ECS Instances button shows up when I create the ECS cluster through the web console. More specifically, when you enable managed scaling and managed termination protection with an ASG capacity provider, ECS does the following for you: The purpose of the CapacityProviderReservation metric is to control the number of instances in the ASG, while also allowing other scaling policies to work with the ASG. No further scaling is required. Let’s call this number M. Let’s also call the current number of instances in the ASG that are already running N. We’ll make extensive use of M and N throughout the rest of the blog post, so it’s important to have a completely clear understanding of how to think about them. © 2020, Amazon Web Services, Inc. or its affiliates. In the first part of this tutorial, we looked at provisioning AWS EC2 resources using the CLI client, and delved into the details of how various networking components function.In this second part, we will look at using containers instead of virtual machines to deploy applications. For this reason, we implemented the option of having ECS dynamically manage instance termination protection on your behalf (thus achieving design goal #2). Nick Coult is a Principal Product Manager for Amazon Elastic Container Service. Doing a little algebra, we see that N = 2 X M. In other words, with a target value of 50, the scaling policy will adjust N until it is exactly twice the number of instances that CAS has estimated are needed to run all of the tasks. As explained later in this blog, this metric is used by CAS to control the scaling of the ASG. Since the third instance is not protected from scale in, it terminates. Now that the instance has terminated, the metric updates again:  N=2, M=2, so CapacityProviderReservation = 100. Target tracking scaling policies manage the capacity of your ASG. With AWS Fargate, you no longer have to provision, configure, or scale clusters of virtual machines to run containers. Step 3. Deploying Docker containers on ECS. I want to describe the cluster with AWS CLI. If at least one instance is not running any tasks (other than daemon service tasks), and there are no tasks in the provisioning state, then M < N. More specifically, M = the number of instances running at least one task (again, we exclude daemon service tasks because they are supposed to run on every instance. I want to describe the cluster with AWS CLI. Thanks for the quick response - I can't be sure I did scale down with ECS CLI but the AsgMaxSize is currently at 1. A huge improvement, as there was no built-in way to scale the EC2 instance for an ECS cluster automatically before. If you've got a moment, please tell us how we can make Design goal #2: CAS should scale in (removing instances) only if it can be done without disrupting any tasks (other than daemon tasks). On the other hand, if N < M, scale out is required because you don’t have enough instances. This algorithm results in M generally being a lower bound on the number of instances needed, and in some cases it will actually be the exact number of instances needed – for example, if all of the provisioning tasks are identical, your ASG is configured to use a single instance type, and your tasks have no placement constraints, then this algorithm results in exactly the right number of instances needed (assuming M falls within the bounds defined in step 5). This is the same step 1 as the previous scenario. This is an introductory guide by AWS on how to deploy microservices - based applications on ECS. In the first part of this tutorial, we looked at provisioning AWS EC2 resources using the CLI client, and delved into the details of how various networking components function.In this second part, we will look at using containers instead of virtual machines to deploy applications. No scaling has been triggered yet, so all three instances are still running. application-autoscaling] ... For example, suppose that you create a step scaling policy to scale out an Amazon ECS service by 25 percent and you specify a MinAdjustmentMagnitude of 2. Defaults to the cluster configured using With CAS, you can configure ECS to scale your ASG automatically, and just focus on running your tasks. AWS Command Line Interface (CLI) ... With ECS and Docker, they can generalize the pipeline and swap the digital biomarkers as needed, allowing them to scale the pattern beyond this use case. aws ecs create-service --cli-input-json file://talk-service-ecs.json Check the service has been correctly registered by navigating to EC2 Container Service > conference-cluster > Services. The third instance can be terminated without disrupting any non-daemon tasks, so M = 2. Scale the adoption platform monolith with an ALB and an ECS Service Lab 4. At the present time, a maximum of 100 tasks can be in the provisioning state for any cluster, and provisioning tasks will wait for capacity for between 10 and 30 minutes before transitioning to “stopped.”. If there is at least one task in the provisioning state, then M > N. We describe in more detail below exactly how M is calculated in this case. AWS CLI tools, available from AWS. This means that half of the instances will not be running any tasks. This is an example project on how to use AWS ECS for our applications. A. Now that one instance is free of non-daemon tasks, the scaling metric is updated:  M=2, N=3, so CapacityProviderReservation=66. Amazon ECS enables users schedule long-running applications, services, and … As we show later in this blog post, the design of CAS meets all three of these goals. create-capacity-provider: Used to create a new capacity provider. Consider the example shown in Figure 4. When AWS published ECS CLI a few years ago, it seemed to be following the precedents set by competitors such as Heroku, to make the containers deployment an easy one-step process. Lastly, if N > M, scale in is possible (but not necessarily required) because you have more instances than you need to run all of your ECS tasks. Since we can’t in general know the optimal value of M, CAS instead tries to make a good estimate. Of course, running your tasks on Fargate instead of EC2 instances eliminates the need for scaling clusters entirely, but not every customer is ready or able to adopt Fargate for all of their workloads. Amazon ECS for Open Application Model. This means, for example, if you call the RunTask API and the tasks don’t get placed on an instance because of insufficient resources (meaning no active instances had sufficient memory, vCPUs, ports, ENIs, and/or GPUs to run the tasks), instead of failing immediately, the task will go into the provisioning state (note, however, that the transition to provisioning only happens if you have enabled managed scaling for the capacity provider; otherwise, tasks that can’t find capacity will fail immediately, as they did previously). instanceWarmupPeriod -> (integer) Step 5. --ecs-profile AWS Fargate on ECS has to respect the default 1 task per second launch limit, and so time to scale from 1 to 3.500 tasks should be around 3.500 seconds, which is about 1 hour. We did this earlier in this section when we added the EC2 capacity to the ECS cluster. On your behalf, Amazon ECS creates an AWS Auto Scaling scaling plan with a target tracking scaling policy based on the target capacity value you specify. AWS provides a set of commands that can be run on AWS-CLI (AWS Command Line Interface) to manage your services. --cluster-config A CLI tool for deploying services in AWS Elastic Container Service - ukayani/ecs-service. (Target tracking scaling has a special case for scaling from zero capacity, where it assumes for the purposes of scaling that the current capacity is one and not zero). The maximum number of container instances that Amazon ECS will scale in or scale out at one time. Note that this does NOT prevent a Spot Instance from being reclaimed, or the instance being terminated manually; it only prevents the ASG from terminating the instance due to scaling. As we demonstrate later, with a target capacity of 100, the ASG will scale out to M instances. However, I cannot get the Scale ECS Instances button to show up when I create the ECS cluster through Terraform. The ASG has three instances (purple boxes, N = 3), each running non-daemon tasks (green boxes). Once the metric goes above the target value of 100, the scaling policy kicks in to adjust the desired count of the ASG upwards from N = 3 to N = 4. Thanks for keeping us updated. While this may be less efficient, it will still reach the correct size eventually. Likewise, if N=0 and M>0, meaning tasks are provisioning but no instances are running, then the CapacityProviderReservation = 200 and N will adjust upwards to add instances to the ASG. (It’s important here to note that that M, which is CAS’ estimate of how many instances are needed to run all of the tasks, is not based on the target value of the scaling policy). Shows the help text for the specified command. AWS CLI allows you can use Linux shells, Windows PowerShell or … Configure AWS CLI for the user you just created above. Update: if you still want to scale down the Fargate Service to 0 Tasks you can certainly do it through setting the Service's DesiredCount to 0.That can be done e.g. desired and maximum instance count in the Auto Scaling group created by the ecs-cli cluster. For now, we haven’t explained how we know what M should be, but for the purposes of discussion, let’s assume that M is what you need. Recall that N is the number of instances already up and running in the ASG. CAS relies on ECS capacity providers, which provide the link between your ECS cluster and the ASGs you want to use. Fetch the instance type and its attributes that the ASG is configured to use. See the User Guide for help getting started. To interact with AWS, aws-cli and awscli-plugin-endpoint need to be At this point, M = 3, N = 3, and CapacityProviderReservation = 100. 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