Speed up secure software program releases with new built-in blue/inexperienced deployments in Amazon ECS

Whereas containers have revolutionized how improvement groups bundle and deploy functions, these groups have needed to fastidiously monitor releases and construct customized tooling to mitigate deployment dangers, which slows down delivery velocity. At scale, improvement groups spend precious cycles constructing and sustaining undifferentiated deployment instruments as an alternative of innovating for his or her enterprise.

Beginning right this moment, you should utilize the built-in blue/inexperienced deployment functionality in Amazon Elastic Container Service (Amazon ECS) to make your software deployments safer and extra constant. This new functionality eliminates the necessity to construct customized deployment tooling whereas providing you with the arrogance to ship software program updates extra steadily with rollback functionality.

Right here’s how one can allow the built-in blue/inexperienced deployment functionality within the Amazon ECS console.

You create a brand new “inexperienced” software surroundings whereas your current “blue” surroundings continues to serve reside site visitors. After monitoring and testing the inexperienced surroundings totally, you route the reside site visitors from blue to inexperienced. With this functionality, Amazon ECS now gives built-in performance that makes containerized software deployments safer and extra dependable.

Beneath is a diagram illustrating how blue/inexperienced deployment works by shifting software site visitors from the blue surroundings to the inexperienced surroundings. You’ll be able to study extra on the Amazon ECS blue/inexperienced service deployments workflow web page.

Amazon ECS orchestrates this whole workflow whereas offering occasion hooks to validate new variations utilizing artificial site visitors earlier than routing manufacturing site visitors. You’ll be able to validate new software program variations in manufacturing environments earlier than exposing them to finish customers and roll again near-instantaneously if points come up. As a result of this performance is constructed immediately into Amazon ECS, you may add these safeguards by merely updating your configuration with out constructing any customized tooling.

Getting began
Let me stroll you thru an illustration that showcases methods to configure and use blue/inexperienced deployments for an ECS service. Earlier than that, there are a number of setup steps that I want to finish, together with configuring AWS Identification and Entry Administration (IAM) roles, which you’ll find on the Required sources for Amazon ECS blue/inexperienced deployments Documentation web page.

For this demonstration, I wish to deploy a brand new model of my software utilizing the blue/inexperienced technique to reduce threat. First, I have to configure my ECS service to make use of blue/inexperienced deployments. I can do that by the ECS console, AWS Command Line Interface (AWS CLI), or utilizing infrastructure as code.

Utilizing the Amazon ECS console, I create a brand new service and configure it as common:

Within the Deployment Choices part, I select ECS because the Deployment controller sort, then Blue/inexperienced because the Deployment technique. Bake time is the time after the manufacturing site visitors has shifted to inexperienced, when on the spot rollback to blue is offered. When the bake time expires, blue duties are eliminated.

We’re additionally introducing deployment lifecycle hooks. These are event-driven mechanisms you should utilize to enhance the deployment workflow. I can choose which AWS Lambda operate I’d like to make use of as a deployment lifecycle hook. The Lambda operate can carry out the required enterprise logic, however it should return a hook standing.

Amazon ECS helps the next lifecycle hooks throughout blue/inexperienced deployments. You’ll be able to study extra about every stage on the Deployment lifecycle levels web page.

• Pre scale up
• Put up scale up
• Manufacturing site visitors shift
• Check site visitors shift
• Put up manufacturing site visitors shift
• Put up take a look at site visitors shift

For my software, I wish to take a look at when the take a look at site visitors shift is full and the inexperienced service handles the entire take a look at site visitors. Since there’s no end-user site visitors, a rollback at this stage could have no influence on customers. This makes Put up take a look at site visitors shift appropriate for my use case as I can take a look at it first with my Lambda operate.

Switching context for a second, let’s give attention to the Lambda operate that I exploit to validate the deployment earlier than permitting it to proceed. In my Lambda operate as a deployment lifecycle hook, I can carry out any enterprise logic, resembling artificial testing, calling one other API, or querying metrics.

Inside the Lambda operate, I need to return a hookStatus. A hookStatus could be SUCCEEDED, which is able to transfer the method to the following step. If the standing is FAILED, it rolls again to the blue deployment. If it’s IN_PROGRESS, then Amazon ECS retries the Lambda operate in 30 seconds.

Within the following instance, I arrange my validation with a Lambda operate that performs file add as a part of a take a look at suite for my software.

import json
import urllib3
import logging
import base64
import os

# Configure logging
logger = logging.getLogger()
logger.setLevel(logging.DEBUG)

# Initialize HTTP shopper
http = urllib3.PoolManager()

def lambda_handler(occasion, context):
    """
    Validation hook that assessments the inexperienced surroundings with file add
    """
    logger.data(f"Occasion: {json.dumps(occasion)}")
    logger.data(f"Context: {context}")
    
    attempt:
        # In an actual state of affairs, you'd assemble the take a look at endpoint URL
        test_endpoint = os.getenv("APP_URL")
        
        # Create a take a look at file for add
        test_file_content = "This can be a take a look at file for deployment validation"
        test_file_data = test_file_content.encode('utf-8')
        
        # Put together multipart type knowledge for file add
        fields = {
            'file': ('take a look at.txt', test_file_data, 'textual content/plain'),
            'description': 'Deployment validation take a look at file'
        }
        
        # Ship POST request with file add to /course of endpoint
        response = http.request(
            'POST', 
            test_endpoint,
            fields=fields,
            timeout=30
        )
        
        logger.data(f"POST /course of response standing: {response.standing}")
        
        # Examine if response has OK standing code (200-299 vary)
        if 200 

When the deployment reaches the lifecycle stage that’s related to the hook, Amazon ECS mechanically invokes my Lambda operate with deployment context. My validation operate can run complete assessments in opposition to the inexperienced revision—checking software well being, operating integration assessments, or validating efficiency metrics. The operate then indicators again to ECS whether or not to proceed or abort the deployment.

As I selected the blue/inexperienced deployment technique, I additionally have to configure the load balancers and/or Amazon ECS Service Join. Within the Load balancing part, I choose my Utility Load Balancer.

Within the Listener part, I exploit an current listener on port 80 and choose two Goal teams.

Pleased with this configuration, I create the service and look forward to ECS to provision my new service.

Testing blue/inexperienced deployments
Now, it’s time to check my blue/inexperienced deployments. For this take a look at, Amazon ECS will set off my Lambda operate after the take a look at site visitors shift is accomplished. My Lambda operate will return FAILED on this case because it performs file add to my software, however my software doesn’t have this functionality.

I replace my service and test Pressure new deployment, understanding the blue/inexperienced deployment functionality will roll again if it detects a failure. I choose this selection as a result of I haven’t modified the duty definition however nonetheless have to set off a brand new deployment.

At this stage, I’ve each blue and inexperienced environments operating, with the inexperienced revision dealing with all of the take a look at site visitors. In the meantime, based mostly on Amazon CloudWatch Logs of my Lambda operate, I additionally see that the deployment lifecycle hooks work as anticipated and emit the next payload:

[INFO]	2025-07-10T13:15:39.018Z	67d9b03e-12da-4fab-920d-9887d264308e	Occasion: 
{
    "executionDetails": {
        "testTrafficWeights": {},
        "productionTrafficWeights": {},
        "serviceArn": "arn:aws:ecs:us-west-2:123:service/EcsBlueGreenCluster/nginxBGservice",
        "targetServiceRevisionArn": "arn:aws:ecs:us-west-2:123:service-revision/EcsBlueGreenCluster/nginxBGservice/9386398427419951854"
    },
    "executionId": "a635edb5-a66b-4f44-bf3f-fcee4b3641a5",
    "lifecycleStage": "POST_TEST_TRAFFIC_SHIFT",
    "resourceArn": "arn:aws:ecs:us-west-2:123:service-deployment/EcsBlueGreenCluster/nginxBGservice/TFX5sH9q9XDboDTOv0rIt"
}

As anticipated, my AWS Lambda operate returns FAILED as hookStatus as a result of it did not carry out the take a look at.

[ERROR]	2025-07-10T13:18:43.392Z	67d9b03e-12da-4fab-920d-9887d264308e	File add take a look at failed: HTTPConnectionPool(host="xyz.us-west-2.elb.amazonaws.com", port=80): Max retries exceeded with url: / (Attributable to ConnectTimeoutError(, 'Connection to xyz.us-west-2.elb.amazonaws.com timed out. (join timeout=30)'))

As a result of the validation wasn’t accomplished efficiently, Amazon ECS tries to roll again to the blue model, which is the earlier working deployment model. I can monitor this course of by ECS occasions within the Occasions part, which gives detailed visibility into the deployment progress.

Amazon ECS efficiently rolls again the deployment to the earlier working model. The rollback occurs near-instantaneously as a result of the blue revision stays operating and able to obtain manufacturing site visitors. There isn’t any end-user influence throughout this course of, as manufacturing site visitors by no means shifted to the brand new software model—ECS merely rolled again take a look at site visitors to the unique steady model. This eliminates the everyday deployment downtime related to conventional rolling deployments.

I may also see the rollback standing within the Final deployment part.

All through my testing, I noticed that the blue/inexperienced deployment technique gives constant and predictable habits. Moreover, the deployment lifecycle hooks present extra flexibility to manage the habits of the deployment. Every service revision maintains immutable configuration together with process definition, load balancer settings, and Service Join configuration. Which means that rollbacks restore precisely the identical surroundings that was beforehand operating.

Further issues to know
Listed below are a few issues to notice:

• Pricing – The blue/inexperienced deployment functionality is included with Amazon ECS at no extra cost. You pay just for the compute sources used through the deployment course of.
• Availability – This functionality is offered in all industrial AWS Areas.

Get began with blue/inexperienced deployments by updating your Amazon ECS service configuration within the Amazon ECS console.

Comfortable deploying!
— Donnie