# Elastic Container Service 1. [TL;DR](#tldr) 1. [How it works](#how-it-works) 1. [EC2 launch type](#ec2-launch-type) 1. [Fargate launch type](#fargate-launch-type) 1. [Standalone tasks](#standalone-tasks) 1. [Services](#services) 1. [Resource constraints](#resource-constraints) 1. [Storage](#storage) 1. [EBS volumes](#ebs-volumes) 1. [EFS volumes](#efs-volumes) 1. [Docker volumes](#docker-volumes) 1. [Bind mounts](#bind-mounts) 1. [Execute commands in tasks' containers](#execute-commands-in-tasks-containers) 1. [Troubleshooting](#troubleshooting) 1. [Invalid 'cpu' setting for task](#invalid-cpu-setting-for-task) 1. [Further readings](#further-readings) 1. [Sources](#sources) ## TL;DR _Tasks_ are the basic unit of deployment.
They are instances of the set of containers specified in their own _task definition_. Tasks model and run one or more containers, much like Pods in Kubernetes.
Containers **cannot** run on ECS unless encapsulated in a task. _Standalone tasks_ start a single task, which is meant to perform some work to completion and then stop (much like batch processes would).
_Services_ run and maintain a defined number of instances of the same task simultaneously, which are meant to stay active and act as replicas of some service (much like web servers would). Tasks are executed depending on their _launch type_ and _capacity providers_: - On EC2 instances that one owns, manages, and pays for. - On Fargate (an AWS-managed serverless environment for containers execution). Unless explicitly restricted or capped, containers in tasks get access to all the CPU and memory capacity available on the host running it. By default, containers behave like other Linux processes with respect to access to resources like CPU and memory.
Unless explicitly protected and guaranteed, all containers running on the same host share CPU, memory, and other resources much like normal processes running on that host share those very same resources.
Usage ```sh # List services. aws ecs list-services --cluster 'clusterName' # Scale services. aws ecs update-service --cluster 'clusterName' --service 'serviceName' --desired-count '0' aws ecs update-service --cluster 'clusterName' --service 'serviceName' --desired-count '10' # Wait for services to be running. aws ecs wait services-stable --cluster 'clusterName' --services 'serviceName' … # Delete services. # Cannot really be deleted if scaled above 0. aws ecs delete-service --cluster 'clusterName' --service 'serviceName' aws ecs delete-service --cluster 'clusterName' --service 'serviceName' --force # List task definitions. aws ecs list-task-definitions --family-prefix 'familyPrefix' # Deregister task definitions. aws ecs deregister-task-definition --task-definition 'taskDefinitionArn' # Delete task definitions. # The task definition must be deregistered. aws ecs delete-task-definitions --task-definitions 'taskDefinitionArn' … # List tasks. aws ecs list-tasks --cluster 'clusterName' aws ecs list-tasks --cluster 'clusterName' --service-name 'serviceName' # Get information about tasks. aws ecs describe-tasks --cluster 'clusterName' --tasks 'taskIdOrArn' … # Wait for tasks to be running. aws ecs wait tasks-running --cluster 'clusterName' --tasks 'taskIdOrArn' … # Access shells on containers in ECS. aws ecs execute-command \ --cluster 'clusterName' --task 'taskId' --container 'containerName' \ --interactive --command '/bin/bash' ```
Real world use cases ```sh # Get the ARNs of tasks for specific services. aws ecs list-tasks --cluster 'testCluster' --service-name 'testService' --query 'taskArns' --output 'text' # Get the private IP Address of containers. aws ecs describe-tasks --output 'text' \ --cluster 'testCluster' --tasks 'testTask' \ --query "tasks[].attachments[].details[?(name=='privateDnsName')].value" # Connect to the private DNS name of containers in ECS. curl -fs "http://$(\ aws ecs describe-tasks --cluster 'testCluster' --tasks "$(\ aws ecs list-tasks --cluster 'testCluster' --service-name 'testService' --query 'taskArns' --output 'text' \ )" --query "tasks[].attachments[].details[?(name=='privateDnsName')].value" --output 'text' \ ):8080" # Delete services. aws ecs delete-service --cluster 'testCluster' --service 'testService' --force # Delete task definitions. aws ecs list-task-definitions --family-prefix 'testService' --output 'text' --query 'taskDefinitionArns' \ | xargs -n '1' aws ecs deregister-task-definition --task-definition # Wait for tasks to be running. aws ecs list-tasks --cluster 'testCluster' --family 'testService' --output 'text' --query 'taskArns' \ | xargs -p aws ecs wait tasks-running --cluster 'testCluster' --tasks while [[ $(aws ecs list-tasks --query 'taskArns' --output 'text' --cluster 'testCluster' --service-name 'testService') == "" ]]; do sleep 1; done ```
## How it works Tasks must be registered in _task definitions_ **before** they can be launched. Tasks can be executed as [Standalone tasks] or [services].
Whatever the _launch type_: 1. On launch, a task is created and moved to the `PROVISIONING` state.
While in this state, ECS needs to find compute capacity for the task and neither the task nor its containers exist. 1. ECS selects the appropriate compute capacity for the task based on its launch type or capacity provider configuration. Tasks will fail immediately should there be not enough compute capacity for the task in the launch type or capacity provider. When using a capacity provider with managed scaling enabled, tasks that can't be started due to a lack of compute capacity are kept in the `PROVISIONING` state while ECS provisions the necessary attachments. 1. ECS uses the container agent to pull the task's container images. 1. ECS starts the task's containers. 1. ECS moves the task into the `RUNNING` state. ### EC2 launch type Starts tasks onto _registered_ EC2 instances. Instances can be registered: - Manually. - Automatically, by using the _cluster auto scaling_ feature to dynamically scale the cluster's compute capacity. ### Fargate launch type Starts tasks on dedicated, managed EC2 instances that are **not** reachable by the users. Instances are automatically provisioned, configured, and registered to scale one's cluster capacity.
The service takes care itself of all the infrastructure management for the tasks. ### Standalone tasks Refer [Amazon ECS standalone tasks]. Meant to perform some work, then stop similarly to batch processes. Can be executed on schedules using the EventBridge Scheduler. ### Services Refer [Amazon ECS services]. Execute and maintain a defined number of instances of the same task simultaneously in a cluster. Tasks executed in services are meant to stay active until decommissioned, much like web services.
Should any of such tasks fail or stops, the service scheduler will launch another instance of the same task to replace the one that failed. One can optionally expose services behind a load balancer to distribute traffic across the tasks that the service manages. The service scheduler will replace unhealthy tasks should a container health check or a load balancer target group health check fail.
This depends on the `maximumPercent` and `desiredCount` parameters in the service's definition. If a task is marked unhealthy, the service scheduler will first start a replacement task. Then: - If the replacement task is `HEALTHY`, the service scheduler stops the unhealthy task. - If the replacement task is also `UNHEALTHY`, the scheduler will stop either the unhealthy replacement task or the existing unhealthy task to get the total task count equal to the `desiredCount` value. Should the `maximumPercent` parameter limit the scheduler from starting a replacement task first, the scheduler will: - Stop unhealthy tasks one at a time at random in order to free up capacity. - Start a replacement task. The start and stop process continues until all unhealthy tasks are replaced with healthy tasks.
Should the total task count still exceed `desiredCount` once all unhealthy tasks have been replaced and only healthy tasks are running, healthy tasks are stopped at random until the total task count equals `desiredCount`. The service scheduler includes logic that throttles how often tasks are restarted if they repeatedly fail to start.
If a task is stopped without having entered the `RUNNING` state, the service scheduler starts to slow down the launch attempts and sends out a service event message.
This prevents unnecessary resources from being used for failed tasks before one can resolve the issue.
On service update, the service scheduler resumes normal scheduling behavior. Available service scheduler strategies: - `REPLICA`: places and maintains the desired number of tasks across one's cluster.
By default, tasks are spread across Availability Zones. Use task placement strategies and constraints to customize task placement decisions. - `DAEMON`: deploys **exactly** one task on **each** active container instance meeting all of the task placement constraints for the task.
There is no need to specify a desired number of tasks, a task placement strategy, or use Service Auto Scaling policies when using this strategy. Fargate does **not** support the `DAEMON` scheduling strategy. ## Resource constraints ECS uses the CPU period and the CPU quota to control the task's CPU **hard** limits **as a whole**.
When specifying CPU values in task definitions, ECS translates that value to the CPU period and CPU quota settings that apply to the cgroup running **all** the containers in the task. The CPU quota controls the amount of CPU time granted to a cgroup during a given CPU period. Both settings are expressed in terms of microseconds.
When the CPU quota equals the CPU period, a cgroup can execute up to 100% on one vCPU (or any other fraction that totals to 100% for multiple vCPUs). The CPU quota has a maximum of 1000000us, and the CPU period has a minimum of 1ms. Use these values to set the limits for the tasks' CPU count. When changing the CPU period with**out** changing the CPU quota, the task will have different effective limits than what is specified in the task definition. The 100ms period allows for vCPUs ranging from 0.125 to 10. Task-level CPU and memory parameters are ignored for Windows containers. The `cpu` value must be expressed in _CPU units_ or _vCPUs_.
_vCPUs_ are converted to _CPU units_ when task definitions are registered. The `memory` value can be expressed in _MiB_ or _GB_.
_GB_s are converted to _MiB_ when tasks definitions are registered. These fields are optional for tasks hosted on EC2.
Such tasks support CPU values between 0.25 and 10 vCPUs. these fields are optional Task definitions specifying `FARGATE` as value for the `requiresCompatibilities` attribute, **even if they also specify the `EC2` value**, **are required** to set both settings **and** to set them to one of the couples specified in the table.
Fargate task definitions support **only** those [specific values for tasks' CPU and memory][fargate tasks sizes]. | CPU units | vCPUs | Memory values | Supported OSes | Notes | | --------- | ----- | ------------------------------------------- | -------------- | -------------------------------- | | 256 | .25 | 512 MiB, 1 GB, or 2 GB | Linux | | | 512 | .5 | Between 1 GB and 4 GB in 1 GB increments | Linux | | | 1024 | 1 | Between 2 GB and 8 GB in 1 GB increments | Linux, Windows | | | 2048 | 2 | Between 4 GB and 16 GB in 1 GB increments | Linux, Windows | | | 4096 | 4 | Between 8 GB and 30 GB in 1 GB increments | Linux, Windows | | | 8192 | 8 | Between 16 GB and 60 GB in 4 GB increments | Linux | Requires Linux platform >= 1.4.0 | | 16384 | 16 | Between 32 GB and 120 GB in 8 GB increments | Linux | Requires Linux platform >= 1.4.0 | The task's settings are **separate** from the CPU and memory values that can be defined at the container definition level.
Should both a container-level `memory` and `memoryReservation` value be set, the `memory` value **must be higher** than the `memoryReservation` value.
If specifying `memoryReservation`, that value is guaranteed to the container and subtracted from the available memory resources for the container instance that the container is placed on. Otherwise, the value of `memory` is used. ## Storage Refer [Storage options for Amazon ECS tasks]. | Volume type | Launch type support | OS support | Persistence | Use cases | | ---------------- | ------------------- | -------------- | -------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------- | | [EBS volumes] | EC2
Fargate | Linux | _Can_ be persisted when used by a standalone task
Ephemeral when attached to tasks maintained by a service | Transactional workloads | | [EFS volumes] | EC2
Fargate | Linux | Persistent | Data analytics
Media processing
Content management
Web serving | | [Docker volumes] | EC2 | Linux, Windows | Persistent | Provide a location for data persistence
Sharing data between containers | | [Bind mounts] | EC2
Fargate | Linux, Windows | Ephemeral | Data analytics
Media processing
Content management
Web serving | ### EBS volumes Refer [Use Amazon EBS volumes with Amazon ECS]. One can attach **at most one** EBS volume to each ECS task, and it **must be a new volume**.
One **cannot** attach existing EBS volume to tasks. However, one _can_ configure a new EBS volume at deployment to use the snapshot of an existing volume as starting point. Provisioning volumes from snapshots of EBS volumes that contains partitions is **not** supported. EBS volumes can be configured at deployment **only** for services that use the _rolling update_ deployment type **and** the _Replica_ scheduling strategy. Containers in a task will be able to write to the mounted EBS volume **only** if the container runs as the `root` user. ECS automatically adds the `AmazonECSCreated` and `AmazonECSManaged` reserved tags to attached volumes.
Should one remove these tags from the volumes, ECS won't be able to manage it anymore. Volumes attached to tasks which are managed by a service are **not** preserved, and are **always** deleted upon task's termination. One **cannot** configure EBS volumes for attachment to ECS tasks running on AWS Outposts. ### EFS volumes Refer [Use Amazon EFS volumes with Amazon ECS]. Allows tasks with access to the same EFS volumes to share persistent storage. Tasks **must**: - Reference the EFS volumes in the `volumes` attribute of their definition. - Reference the defined volumes in the `mountPoints` attribute in the containers' specifications.
```json { "volumes": [{ "name": "myEfsVolume", "efsVolumeConfiguration": { "fileSystemId": "fs-1234", "rootDirectory": "/path/to/my/data", "transitEncryption": "ENABLED", "transitEncryptionPort": integer, "authorizationConfig": { "accessPointId": "fsap-1234", "iam": "ENABLED" } } }], "containerDefinitions": [{ "name": "container-using-efs", "image": "amazonlinux:2", "entryPoint": [ "sh", "-c" ], "command": [ "ls -la /mount/efs" ], "mountPoints": [{ "sourceVolume": "myEfsVolume", "containerPath": "/mount/efs", "readOnly": true }] }] } ```
EFS file systems are supported on - EC2 nodes using ECS-optimized AMI version 20200319 with container agent version 1.38.0. - Fargate since platform version 1.4.0 or later (Linux). **Not** supported on external instances. ### Docker volumes TODO ### Bind mounts TODO ## Execute commands in tasks' containers Refer [Using Amazon ECS Exec to access your containers on AWS Fargate and Amazon EC2], [A Step-by-Step Guide to Enabling Amazon ECS Exec], [`aws ecs execute-command` results in `TargetNotConnectedException` `The execute command failed due to an internal error`] and [Amazon ECS Exec Checker]. Leverage ECS Exec, which in turn leverages SSM to create a secure channel between one's device and the target container. It does so by bind-mounting the necessary SSM agent binaries into the container while the ECS (or Fargate) agent starts the SSM core agent inside the container.
The agent, when invoked, calls SSM to create the secure channel. In order to do so, the container's ECS task must have the proper IAM privileges for the SSM core agent to call the SSM service. The SSM agent does **not** run as a separate container sidecar, but as an additional process **inside** the application container.
Refer [ECS Execute-Command proposal] for details. Whe whole procedure is transparent and does **not** compel requirements changes in the container's content. Requirements: - The required SSM components must be available on the EC2 instances hosting the container. Amazon's ECS optimized AMI and Fargate 1.4 include their latest version already. - The container's image must have `script` and `cat` installed.
Required in order to have command logs uploaded correctly to S3 and/or CloudWatch. - The task's role (**not** the Task's _execution_ role) must have specific permissions assigned.
Policy example ```json { "Version": "2012-10-17", "Statement": [ { "Sid": "RequiredSSMPermissions", "Effect": "Allow", "Action": [ "ssmmessages:CreateControlChannel", "ssmmessages:CreateDataChannel", "ssmmessages:OpenControlChannel", "ssmmessages:OpenDataChannel" ], "Resource": "*" }, { "Sid": "RequiredGlobalCloudWatchPermissions", "Effect": "Allow", "Action": "logs:DescribeLogGroups", "Resource": "*" }, { "Sid": "RequiredSpecificCloudWatchPermissions", "Effect": "Allow", "Action": [ "logs:CreateLogStream", "logs:DescribeLogStreams", "logs:PutLogEvents" ], "Resource": "arn:aws:logs:eu-west-1:012345678901:log-group:/ecs/log-group-name:*" }, { "Sid": "OptionalGlobalS3Permissions", "Effect": "Allow", "Action": "s3:GetEncryptionConfiguration", "Resource": "arn:aws:s3:::ecs-exec-bucket" }, { "Sid": "OptionalSpecificS3Permissions", "Effect": "Allow", "Action": "s3:PutObject", "Resource": "arn:aws:s3:::ecs-exec-bucket/*" }, { "Sid": "OptionalKMSPermissions", "Effect": "Allow", "Action": "kms:Decrypt", "Resource": "arn:aws:kms:eu-west-1:012345678901:key/abcdef01-2345-6789-abcd-ef0123456789" } ] } ```
- The service or the `run-task` command that start the task **must have the `enable-execute-command` set to `true`**.
Examples ```sh aws ecs run-task … --enable-execute-command aws ecs update-service --cluster 'stg' --service 'grafana' --enable-execute-command --force-new-deployment ```
- **Users** initiating the execution: - Must [install the Session Manager plugin for the AWS CLI]. - Must be allowed the `ecs:ExecuteCommand` action on the ECS cluster.
Policy example ```json { "Version": "2012-10-17", "Statement": [{ "Effect": "Allow", "Action": "ecs:ExecuteCommand", "Resource": "arn:aws:ecs:eu-west-1:012345678901:cluster/staging", "Condition": { "StringEquals": { "aws:ResourceTag/application": "appName", "StringEquals": { "ecs:container-name": "nginx" } } }, }] } ```
Procedure: 1. Confirm that the task's `ExecuteCommandAgent` status is `RUNNING` and the `enableExecuteCommand` attribute is set to `true`.
Example ```sh aws ecs describe-tasks --cluster 'staging' --tasks 'ef6260ed8aab49cf926667ab0c52c313' --output 'yaml' \ --query 'tasks[0] | { "managedAgents": containers[].managedAgents[?@.name==`ExecuteCommandAgent`][], "enableExecuteCommand": enableExecuteCommand }' ``` ```yaml enableExecuteCommand: true managedAgents: - lastStartedAt: '2025-01-28T22:16:59.370000+01:00' lastStatus: RUNNING name: ExecuteCommandAgent ```
1. Execute the command.
Example ```sh aws ecs execute-command --interactive --command 'df -h' \ --cluster 'staging' --task 'ef6260ed8aab49cf926667ab0c52c313' --container 'nginx' ``` ```plaintext The Session Manager plugin was installed successfully. Use the AWS CLI to start a session. Starting session with SessionId: ecs-execute-command-zobkrf3qrif9j962h9pecgnae8 Filesystem Size Used Avail Use% Mounted on overlay 31G 12G 18G 40% / tmpfs 64M 0 64M 0% /dev shm 464M 0 464M 0% /dev/shm tmpfs 464M 0 464M 0% /sys/fs/cgroup /dev/nvme1n1 31G 12G 18G 40% /etc/hosts /dev/nvme0n1p1 4.9G 2.1G 2.8G 43% /managed-agents/execute-command tmpfs 464M 0 464M 0% /proc/acpi tmpfs 464M 0 464M 0% /sys/firmware Exiting session with sessionId: ecs-execute-command-zobkrf3qrif9j962h9pecgnae8. ```
Should one's command invoke a shell, one will gain interactive access to the container.
In this case, **all commands and their outputs** inside the shell session **will** be logged to S3 and/or CloudWatch. The shell invocation command and the user that invoked it will be logged in CloudTrail for auditing purposes as part of the ECS ExecuteCommand API call. Should one's command invoke a single command, **only the output** of the command will be logged to S3 and/or CloudWatch. The command itself will still be logged in CloudTrail as part of the ECS ExecuteCommand API call. Logging options are configured at the ECS cluster level.
The task's role **will** need to have IAM permissions to log the output to S3 and/or CloudWatch should the cluster be configured for the above options. If the options are **not** configured, then the permissions are **not** required. ## Troubleshooting ### Invalid 'cpu' setting for task Refer [Troubleshoot Amazon ECS task definition invalid CPU or memory errors] and [Resource constraints].
Cause One specified an invalid `cpu` or `memory` value for the task when registering a task definition using ECS's API or the AWS CLI. Should the task definition specify `FARGATE` as value for the `requiresCompatibilities` attribute, the resource values must be one of the specific pairs supported by Fargate.
Solution Specify a supported value for the task CPU and memory in your task definition.
## Further readings - [Amazon Web Services] - [Amazon ECS task lifecycle] - AWS' [CLI] - [Troubleshoot Amazon ECS deployment issues] - [Storage options for Amazon ECS tasks] - [EBS] - [EFS] - [Amazon ECS Exec Checker] - [ECS Execute-Command proposal] ### Sources - [Identity and Access Management for Amazon Elastic Container Service] - [Amazon ECS task role] - [How Amazon Elastic Container Service works with IAM] - [Troubleshoot Amazon ECS task definition invalid CPU or memory errors] - [Use Amazon EBS volumes with Amazon ECS] - [Attach EBS volume to AWS ECS Fargate] - [Guide to Using Amazon EBS with Amazon ECS and AWS Fargate] - [Amazon ECS task definition differences for the Fargate launch type] - [How Amazon ECS manages CPU and memory resources] - [Exposing multiple ports for an AWS ECS service] - [Use Amazon EFS volumes with Amazon ECS] - [Amazon ECS services] - [Amazon ECS standalone tasks] - [Using Amazon ECS Exec to access your containers on AWS Fargate and Amazon EC2] - [A Step-by-Step Guide to Enabling Amazon ECS Exec] - [`aws ecs execute-command` results in `TargetNotConnectedException` `The execute command failed due to an internal error`] [bind mounts]: #bind-mounts [docker volumes]: #docker-volumes [ebs volumes]: #ebs-volumes [efs volumes]: #efs-volumes [resource constraints]: #resource-constraints [services]: #services [standalone tasks]: #standalone-tasks [amazon web services]: README.md [cli]: cli.md [ebs]: ebs.md [efs]: efs.md [amazon ecs exec checker]: https://github.com/aws-containers/amazon-ecs-exec-checker [amazon ecs services]: https://docs.aws.amazon.com/AmazonECS/latest/developerguide/ecs_services.html [amazon ecs standalone tasks]: https://docs.aws.amazon.com/AmazonECS/latest/developerguide/standalone-tasks.html [amazon ecs task definition differences for the fargate launch type]: https://docs.aws.amazon.com/AmazonECS/latest/developerguide/fargate-tasks-services.html [amazon ecs task lifecycle]: https://docs.aws.amazon.com/AmazonECS/latest/developerguide/task-lifecycle-explanation.html [amazon ecs task role]: https://docs.aws.amazon.com/AmazonECS/latest/developerguide/task-iam-roles.html [ecs execute-command proposal]: https://github.com/aws/containers-roadmap/issues/1050 [fargate tasks sizes]: https://docs.aws.amazon.com/AmazonECS/latest/developerguide/fargate-tasks-services.html#fargate-tasks-size [how amazon ecs manages cpu and memory resources]: https://aws.amazon.com/blogs/containers/how-amazon-ecs-manages-cpu-and-memory-resources/ [how amazon elastic container service works with iam]: https://docs.aws.amazon.com/AmazonECS/latest/developerguide/security_iam_service-with-iam.html [identity and access management for amazon elastic container service]: https://docs.aws.amazon.com/AmazonECS/latest/developerguide/security-iam.html [install the session manager plugin for the aws cli]: https://docs.aws.amazon.com/systems-manager/latest/userguide/session-manager-working-with-install-plugin.html [storage options for amazon ecs tasks]: https://docs.aws.amazon.com/AmazonECS/latest/developerguide/using_data_volumes.html [troubleshoot amazon ecs deployment issues]: https://docs.aws.amazon.com/codedeploy/latest/userguide/troubleshooting-ecs.html [troubleshoot amazon ecs task definition invalid cpu or memory errors]: https://docs.aws.amazon.com/AmazonECS/latest/developerguide/task-cpu-memory-error.html [use amazon ebs volumes with amazon ecs]: https://docs.aws.amazon.com/AmazonECS/latest/developerguide/ebs-volumes.html [use amazon efs volumes with amazon ecs]: https://docs.aws.amazon.com/AmazonECS/latest/developerguide/efs-volumes.html [using amazon ecs exec to access your containers on aws fargate and amazon ec2]: https://aws.amazon.com/blogs/containers/new-using-amazon-ecs-exec-access-your-containers-fargate-ec2/ [`aws ecs execute-command` results in `TargetNotConnectedException` `The execute command failed due to an internal error`]: https://stackoverflow.com/questions/69261159/aws-ecs-execute-command-results-in-targetnotconnectedexception-the-execute [a step-by-step guide to enabling amazon ecs exec]: https://medium.com/@mariotolic/a-step-by-step-guide-to-enabling-amazon-ecs-exec-a88b05858709 [attach ebs volume to aws ecs fargate]: https://medium.com/@shujaatsscripts/attach-ebs-volume-to-aws-ecs-fargate-e23fea7bb1a7 [exposing multiple ports for an aws ecs service]: https://medium.com/@faisalsuhail1/exposing-multiple-ports-for-an-aws-ecs-service-64b9821c09e8 [guide to using amazon ebs with amazon ecs and aws fargate]: https://stackpioneers.com/2024/01/12/guide-to-using-amazon-ebs-with-amazon-ecs-and-aws-fargate/