Introduction

As HulakZen evolves into an email validation and multichannel marketing platform, its infrastructure needs to support reliable deployments, background processing, horizontal scaling, and secure communication between services.

HulakZen includes services for frontend delivery, backend APIs, email validation, campaign processing, and integrations with Amazon Simple Email Service (Amazon SES). These workloads can be packaged as Docker containers and orchestrated using Amazon Elastic Container Service (Amazon ECS).

This article explores how Amazon ECS with the EC2 launch type can provide a flexible foundation for running HulakZen's containerized workloads on AWS.

Architecture status: This article presents a proposed architecture and practical implementation approach. The examples do not imply that the complete architecture described here has already been deployed in HulakZen's production environment.

1. Why Amazon ECS with EC2?

Amazon ECS is a fully managed container orchestration service that helps deploy, manage, and scale containerized applications.

With the EC2 launch type, ECS schedules containers onto Amazon EC2 instances that you manage as container capacity. AWS manages the ECS control plane, while you remain responsible for the underlying EC2 capacity, operating system maintenance, and related infrastructure.

For HulakZen, this approach offers several advantages:

• Control over compute resources: Select EC2 instance types based on API, validation, and worker workloads.

• Container orchestration: Manage multiple Docker services through ECS task definitions and services.

• Horizontal scaling: Increase the number of application tasks as demand grows.

• Flexible background processing: Run email validation and campaign workers separately from the API.

• AWS integration: Integrate with Amazon ECR, Application Load Balancer, CloudWatch, IAM, and Amazon SES.

• Cost management: Choose instance families and capacity strategies that fit workload requirements.

Amazon ECS with EC2 is particularly useful when workloads require more control over compute capacity or when running a combination of long-running API services and background workers.

2. Proposed HulakZen Architecture

The following diagram illustrates a possible production architecture for HulakZen using ECS on EC2.

The frontend and backend API can run as ECS services. Validation and campaign processing can run as separate services or workers, depending on how their jobs are scheduled and consumed.

The Application Load Balancer routes incoming HTTP or HTTPS requests to registered application targets. Background workers normally do not need public load-balancer access.

The exact design should be adjusted to the application's current networking, database, queue, and deployment requirements.

3. AWS Components Used in the Architecture

Redis and MongoDB are not automatically provided by ECS. They must be deployed or connected to separately, with appropriate security, backups, monitoring, and availability configuration.

4. Containerizing HulakZen Services

Before deploying an application to ECS, each service needs a container image.

A typical HulakZen deployment may include separate images for:

• Frontend

• Backend API

• Email validation worker

• SES or campaign mailer

Each service should have its own Dockerfile or an appropriately configured shared build process. Separate images make it easier to deploy, scale, and troubleshoot services independently.

Example Dockerfile

The following is an illustrative Dockerfile for a Node.js service. Adjust the build steps, application entry point, and dependencies to match the actual HulakZen service.

Code / Command
FROM node:22-alpine

WORKDIR /app

COPY package*.json ./

RUN npm ci --omit=dev

COPY . .

ENV NODE_ENV=production
ENV PORT=3000

EXPOSE 3000

CMD ["npm", "start"]

For a production application, use a suitable supported Node.js version, pin dependencies, run the application as a non-root user where practical, and avoid copying secrets into the image.

.dockerignore: The following files and directories are excluded from the Docker build context.

node_modules
.git
.env
.env.*
coverage
npm-debug.log

Do not copy production credentials, API keys, or database passwords into Docker images.

5. Build and Push Images to Amazon ECR

Amazon Elastic Container Registry stores the images that ECS tasks will use.

Create an ECR repository for each service or use a repository strategy appropriate for your release process.

Example repository names:

hulakzen-frontend
hulakzen-backend
hulakzen-validation-worker
hulakzen-ses-mailer

Authenticate Docker to ECR

Set the correct AWS Region and account ID before running the commands.

Code / Command
aws sts get-caller-identity

aws ecr get-login-password --region ap-south-1 \
  | docker login \
      --username AWS \
      --password-stdin ACCOUNT_ID.dkr.ecr.ap-south-1.amazonaws.com

Replace ACCOUNT_ID with the AWS account ID returned by your AWS account configuration.

Build and tag an image

Run the following commands from the relevant service's source directory.

Code / Command
docker build -t hulakzen-backend .

docker tag hulakzen-backend:latest \
  ACCOUNT_ID.dkr.ecr.ap-south-1.amazonaws.com/hulakzen-backend:latest

Push the image

Code / Command
docker push \
  ACCOUNT_ID.dkr.ecr.ap-south-1.amazonaws.com/hulakzen-backend:latest

Repeat the process for the other services.

For production releases, prefer immutable version tags such as a Git commit SHA or release number rather than relying only on latest. This makes deployments easier to reproduce and roll back.

6. Create an Amazon ECS Cluster

An ECS cluster is a logical grouping for ECS tasks and services.

In the AWS Management Console:

1. Open Amazon ECS.

2. Navigate to Clusters.

3. Choose Create cluster.

4. Enter a cluster name, such as hulakzen-production.

5. Select the EC2 infrastructure configuration appropriate for the intended deployment.

6. Configure the required infrastructure and monitoring options.

7. Create the cluster.

For an EC2-backed cluster, ECS needs registered container instances with sufficient CPU, memory, networking, and other resources to place tasks.

A cluster can exist without having enough registered EC2 capacity to run the requested tasks. Verify that capacity is available before deploying services.

7. Configure EC2 Container Capacity

The EC2 launch type requires EC2 instances that can register with the ECS cluster.

For production, a common design is to use an EC2 Auto Scaling Group with an ECS capacity provider.

The Auto Scaling Group manages the number of EC2 instances, while the ECS capacity provider helps ECS scale that capacity in response to task placement requirements.

Instance configuration

The EC2 container instances should have:

• A supported ECS-optimized Amazon Machine Image or another correctly configured ECS container host.

• An instance profile with the required ECS container-instance permissions.

• Network access to the ECS control plane, ECR, CloudWatch, and other required AWS services.

• Security groups that restrict access to necessary ports and destinations.

• Sufficient CPU and memory for the workloads assigned to the instances.

• Monitoring, patching, and lifecycle management.

Use private subnets for application container instances where possible. Provide required outbound access through NAT or suitable VPC endpoints, depending on the services and connectivity design.

Capacity provider considerations

For production workloads, consider:

1. Creating an EC2 Auto Scaling Group with suitable instance types.

2. Configuring instances to join the intended ECS cluster.

3. Creating an ECS capacity provider associated with the Auto Scaling Group.

4. Associating the capacity provider with the ECS cluster.

5. Setting appropriate capacity-provider strategies for ECS services.

The precise console workflow depends on the chosen ECS infrastructure setup. Confirm that the EC2 instances register successfully and that the capacity provider reports usable capacity.

Do not assume that increasing the number of ECS tasks automatically increases EC2 capacity unless the capacity provider and Auto Scaling integration have been configured accordingly.

8. Define an ECS Task Definition

An ECS task definition describes how a container should run. It includes the image, CPU and memory requirements, port mappings, environment configuration, logging, and IAM roles.

Below is a simplified example for a backend API. Replace the example image URI, log group, and application settings with your actual values.

Code / Command
{
  "family": "hulakzen-backend",
  "networkMode": "awsvpc",
  "requiresCompatibilities": ["EC2"],
  "cpu": "512",
  "memory": "1024",
  "executionRoleArn": "arn:aws:iam::ACCOUNT_ID:role/ecsTaskExecutionRole",
  "taskRoleArn": "arn:aws:iam::ACCOUNT_ID:role/hulakzenBackendTaskRole",
  "containerDefinitions": [
    {
      "name": "backend",
      "image": "ACCOUNT_ID.dkr.ecr.ap-south-1.amazonaws.com/hulakzen-backend:RELEASE_TAG",
      "essential": true,
      "portMappings": [
        {
          "containerPort": 3000,
          "protocol": "tcp"
        }
      ],
      "logConfiguration": {
        "logDriver": "awslogs",
        "options": {
          "awslogs-group": "/ecs/hulakzen-backend",
          "awslogs-region": "ap-south-1",
          "awslogs-stream-prefix": "backend"
        }
      }
    }
  ]
}

Important task definition settings

• Task execution role: Allows ECS to perform tasks such as pulling private ECR images and sending container logs to CloudWatch.

• Task role: Grants the application only the AWS permissions it needs at runtime.

• CPU and memory: Must fit the EC2 capacity available to the cluster.

• Network mode: awsvpc gives each task its own elastic network interface and security-group configuration.

• Logging: CloudWatch Logs provides a central location to inspect container output.

The execution role and task role serve different purposes. Do not grant application-level permissions to the execution role merely for convenience.

9. Deploy the Backend as an ECS Service

An ECS service maintains the desired number of running tasks and can replace tasks that stop unexpectedly.

To deploy the backend:

1. Open the ECS cluster.

2. Choose Create service.

3. Select the backend task definition and its revision.

4. Choose the EC2 launch type or the appropriate capacity-provider strategy.

5. Configure the desired task count.

6. Configure the VPC, private subnets, and task security group.

7. Configure an Application Load Balancer if the API should receive incoming traffic.

8. Select the target group and the correct container port.

9. Configure health checks and deployment settings.

10. Create the service and monitor its deployment.

For an internet-facing application, the Application Load Balancer can reside in public subnets while the ECS tasks run in private subnets.

The load balancer security group should accept only the required public traffic, typically HTTPS. The task security group should allow application traffic from the load balancer security group rather than from arbitrary internet sources.

Health checks

Configure health checks that accurately reflect whether the service can receive requests.

For example, an application might expose:

Note: /health

Use this endpoint only if it is implemented by the actual application. Configure the load balancer's health-check path, port, response matcher, interval, and thresholds to match the service.

Avoid making a health endpoint depend on every optional downstream integration if that would cause healthy application instances to be removed unnecessarily. Design readiness checks according to the service's actual requirements.

10. Run Validation and Campaign Workers Separately

Email validation and campaign processing can consume different resources from ordinary API requests.

For that reason, HulakZen can separate request handling from background processing.

A potential workflow is:

Code / Command
User submits a validation request
              |
              v
       Backend API
              |
              v
      Queue / Job Store
              |
              v
    Validation Worker Tasks
              |
              v
       Result Storage
              |
              v
      API returns results

For a Redis-based architecture, BullMQ can coordinate queued jobs and worker execution. The exact design depends on job durability, retry behavior, concurrency, and throughput requirements.

Benefits of separate workers

• Scale API tasks independently from validation tasks.

• Control worker concurrency to avoid overloading external mail servers or other dependencies.

• Retry recoverable failures without repeating the original user request.

• Monitor queue depth and processing latency.

• Isolate background-processing failures from user-facing traffic.

Use idempotent job processing where possible. A retry should not accidentally send the same campaign email multiple times or create duplicate billing or validation records.

Worker scaling signals

Possible signals include:

• Queue depth.

• Age of the oldest queued job.

• Average job processing duration.

• CPU and memory utilization.

• Application-specific processing throughput.

CPU utilization alone may not accurately represent a queue-based workload. For a production system, queue depth and job age can be more useful indicators of whether more workers are needed.

11. Integrate Amazon SES

Amazon SES can provide the email-sending capability for HulakZen's transactional and campaign workloads.

A worker can retrieve queued campaign jobs, prepare the message, and call the SES API using its task role.

A secure integration should include:

• Verified sending identities and the required DNS records.

• Appropriate SES sending permissions.

• Bounce and complaint processing.

• Rate limits and retry policies.

• Campaign suppression and unsubscribe handling where applicable.

• Monitoring of sending activity and delivery outcomes.

• Separation between validation results and actual campaign delivery.

Grant the SES permissions required by the application rather than using broad administrative permissions.

SES account status, sending quotas, verified identities, and regional configuration must be checked in the AWS account being used. Do not assume that a sending quota or production-access status is automatically available in every Region.

12. Configure Logging and Monitoring

Amazon CloudWatch can centralize container logs and infrastructure metrics.

For HulakZen, useful monitoring targets include:

Create alarms for important failures rather than relying solely on dashboards.

For example, an alarm can notify the operations team if the number of healthy load-balancer targets falls below the required threshold or if the backend reports an unusual increase in errors.

Container logs should be structured and should not expose passwords, access tokens, email contents, or other sensitive data unnecessarily.

13. Scale ECS Services and EC2 Capacity

ECS and EC2 capacity scaling solve different problems.

ECS service scaling changes the number of tasks running an application.

EC2 capacity scaling changes the number of container instances available to run those tasks.

A service might be configured to increase its task count when CPU utilization or queue depth rises. The cluster must also have enough EC2 capacity to place those additional tasks.

For an EC2-backed cluster, consider both layers:

1. Configure ECS service auto scaling.

2. Configure an ECS capacity provider and its associated Auto Scaling Group.

3. Define minimum and maximum EC2 capacity.

4. Ensure scale-out happens quickly enough for the workload.

5. Review placement constraints and available CPU and memory.

6. Monitor scale-in behavior to avoid terminating instances that still host important tasks.

For background workers, scaling based on queue depth or job age may provide a more direct response to demand than CPU-only scaling.

Set appropriate minimum capacity for critical services and use deployment settings that preserve availability during releases.

14. Secure the Infrastructure

Security should be designed into the ECS deployment from the beginning.

Network security

• Place application tasks in private subnets where practical.

• Restrict inbound traffic using security groups.

• Allow backend traffic from approved sources only.

• Keep database and cache access private.

• Use VPC endpoints where appropriate to reduce reliance on NAT for supported AWS services.

• Avoid exposing Redis, MongoDB, or internal worker ports to the public internet.

IAM security

• Use separate task roles for services with different permissions.

• Apply least-privilege policies.

• Avoid long-lived AWS access keys inside containers.

• Use IAM roles for ECS tasks to access AWS APIs.

• Restrict who can register task definitions, update services, or change deployment infrastructure.

Secrets and configuration

Use AWS Secrets Manager or AWS Systems Manager Parameter Store for sensitive configuration where appropriate.

Do not hardcode production database credentials, email credentials, or API secrets in a Dockerfile, source repository, or task definition's plain-text environment variables.

Container security

• Scan container images for vulnerabilities.

• Use maintained base images.

• Rebuild images when important security updates become available.

• Run containers with reduced privileges where practical.

• Restrict Linux capabilities and filesystem access as appropriate.

• Use deployment gates for critical vulnerabilities, with a process for evaluating and documenting exceptions.

15. CI/CD for HulakZen

A CI/CD pipeline can automate the process from code changes to ECS deployments.

A possible workflow is:

The exact deployment mechanism may use AWS CodePipeline, CodeBuild, GitHub Actions, or another deployment orchestrator.

A reliable pipeline should:

1. Run automated tests.

2. Build the image.

3. Scan the image and dependencies.

4. Push a versioned image to ECR.

5. Update the ECS task definition with the intended image version.

6. Deploy the service.

7. Verify service stability and health checks.

8. Stop or roll back a release if required conditions are not met.

Keep development and production environments separate, including IAM permissions, configuration, secrets, and deployment approvals.

16. Cost Optimization

Running ECS on EC2 requires attention to both the compute capacity and the supporting services.

Potential cost areas include:

• EC2 instances.

• EBS volumes and snapshots.

• Application Load Balancer.

• NAT gateways and data processing.

• CloudWatch log ingestion and retention.

• ECR image storage.

• Redis or another queue service.

• Database compute, storage, and backups.

• Data transfer.

• Amazon SES usage.

Practical optimization steps include:

• Right-size EC2 instances using measured resource utilization.

• Avoid excessive idle capacity while maintaining sufficient availability.

• Use Auto Scaling Group limits and appropriate scale-in policies.

• Set CloudWatch log retention periods.

• Remove obsolete container images according to a retention policy.

• Monitor NAT gateway and data-transfer costs.

• Evaluate Savings Plans or other commitment-based discounts only after understanding steady-state usage.

• Review whether a service is better suited to ECS on EC2 or another compute model.

17. ECS on EC2 vs. AWS Fargate

Amazon ECS supports multiple compute options, including EC2 and Fargate.

Neither option is universally cheaper or better. The choice depends on workload characteristics, operational expertise, utilization, and the level of infrastructure control required.

For HulakZen, ECS on EC2 is a reasonable option to evaluate when control over compute capacity and container placement is important. Fargate is also worth evaluating if reducing host-management overhead is a higher priority.

18. Troubleshooting Common ECS Problems

Always inspect the ECS service events and stopped-task details before changing infrastructure. They often provide the clearest explanation of a failed deployment.

19. Conclusion

Amazon ECS with EC2 offers HulakZen a way to manage containerized application services, background workers, and supporting components using AWS-native orchestration.

By separating the frontend, backend API, validation workers, and campaign processing into appropriately configured services, HulakZen can scale workloads independently and establish a more consistent deployment process.

The key is to configure both layers of capacity correctly: ECS manages application tasks, while EC2 Auto Scaling and capacity providers supply the underlying compute resources. Security, observability, reliable background processing, and controlled deployments are equally important.

This architecture provides a practical foundation to evaluate and implement as HulakZen's workload and operational requirements grow.

20. References

• Amazon ECS Developer Guide

• Amazon ECS task definitions

• Amazon ECS capacity providers

• Amazon ECS service auto scaling

• Amazon ECR User Guide

• Elastic Load Balancing documentation

• Amazon CloudWatch documentation

• Amazon SES documentation