As organizations increasingly adopt cloud environments, efficiently scaling applications has become essential. Amazon Web Services (AWS) provides several tools to meet this demand, including Amazon ECS (Elastic Container Service) and AWS Fargate. These two cloud infrastructure containers the deployment and management of containerized applications. Stateless workloads are handled effectively with these tools, but scaling stateful applications that depend on persistent data presents additional complexities and requires specialized strategies.
To ensure your application scales smoothly without losing its state, it’s important to follow proven best practices and strategies. In this blog, we’ll walk through these approaches and demonstrate how Amazon ECS and AWS Fargate can be used to scale stateful applications effectively.
What are stateful applications?
A stateful application retains persistent data across multiple sessions or instances. In contrast to stateless applications, which treat each request independently, stateful applications preserve information between interactions. Common examples of stateful applications include databases, caching systems (such as Redis or Memcached), and any application that requires storing user data, preferences, or session details.
For example, in an ecommerce application, when a user adds an item to their shopping cart, that action must be preserved across multiple interactions. If the application does not maintain state, the contents of cart would be lost each time the page is refreshed.
Stateful applications often face challenges in cloud-native environments, where containers (by design) are ephemeral and can be stopped, started, and replicated at any time.
Amazon ECS and AWS Fargate overview
Amazon ECS
It is a fully managed container orchestration service that simplifies the deployment, management, and scaling of containerized applications. It supports two launch types, such as Amazon EC2, which provides control over the underlying infrastructure, and AWS Fargate, which allows you to run containers without managing servers. For teams that outgrow ECS or seek tighter Kubernetes integration, understanding the considerations involved in transitioning from ECS to EKS can help in making informed architectural decisions.
With ECS, you define task definitions that specify how your application containers should operate, including the required compute and storage resources. The service automates key operational tasks, such as container placement, scaling, and load balancing. This allows you to concentrate on building your applications instead of managing the underlying infrastructure.
AWS Fargate
AWS Fargate is a serverless compute engine for containers that works with both Amazon ECS and Amazon EKS (Elastic Kubernetes Service). Fargate eliminates the need to manage EC2 instances by providing a fully managed environment for running containers. You only need to define the CPU and memory requirements for your containers, and Fargate automatically handles the provisioning, scaling, and management of the underlying compute resources.
Fargate is ideal for scaling applications without requiring the management of underlying infrastructure. This approach is especially appealing to developers who prefer to concentrate on application logic rather than operational overhead. For some teams, this transition also becomes part of a broader shift in architecture, such as moving from ECS to EKS in evolving container strategies.
Challenges of scaling stateful applications
Scaling stateful applications in a containerized environment presents several challenges, including:
- Data persistence: Containers are inherently ephemeral. If a container is stopped or replaced, its data is lost unless it is explicitly persisted outside the container.
- Stateful service discovery: As containers scale up and down, stateful services must discover each other dynamically to maintain consistent connections.
- Data consistency: In a distributed system, ensuring consistency across multiple instances of the application is often complex, especially when state is shared across containers.
- Storage: State should be stored on durable and scalable storage solutions because containers do not inherently maintain persistent storage.
Strategies to scale stateful applications with Amazon ECS and AWS Fargate
Scaling stateful applications on ECS with Fargate requires thoughtful architecture and the proper use of AWS services to ensure the state is preserved and accessed efficiently. Let’s dive into strategies that will help you achieve scalable, stateful applications:
Use Amazon EFS for persistent storage
Since containers are ephemeral, stateful applications need persistent storage solutions. Amazon Elastic File System (EFS) offers scalable, shared file storage that can be mounted directly to ECS tasks. By using EFS, you can ensure that data remains available and intact even when containers are stopped, restarted, or replaced.
How to use EFS with ECS and Fargate
- Create an EFS file system in your AWS account.
- Mount the EFS volume to your ECS task definition by specifying it as a volume in your task definition.
- Define a mount point in the container to access the EFS volume, ensuring that all containers can access the same stateful data.
By leveraging Amazon EFS, your containers gain persistent access to data. This ensures that your stateful application can scale without the risk of data loss during container restarts or redeployments.
Leverage Amazon RDS or Amazon Aurora for databases
For stateful applications that rely on databases, AWS offers Amazon RDS (Relational Database Service) and Amazon Aurora, which are fully managed relational databases that handle scaling, availability, and backups for you. These services ensure that your database scales in response to demand without manual intervention.
How to use RDS or Aurora with ECS
- Launch an Amazon RDS or Aurora database instance to host your stateful data.
- Modify your ECS task definition to configure containers to connect to the database via a secure endpoint.
- Use Amazon RDS Read Replicas for horizontal scaling to handle increased read traffic, and leverage Aurora Auto Scaling for automatic database scaling.
By using Amazon RDS or Aurora, you can offload the management of your stateful data and focus on scaling your ECS tasks while ensuring your database grows with the demand.
Stateful service discovery with AWS Cloud Map
As stateful applications scale, their components often need to locate and communicate with one another dynamically. AWS Cloud Map provides a service discovery mechanism that allows you to register and discover services running within your ECS tasks. Cloud Map helps containers find the right endpoints by keeping an up-to-date list of services they can connect to.
How to use AWS Cloud Map for service discovery
- Create a Cloud Map service to register ECS tasks that act as stateful services.
- Use the Cloud Map service discovery API in your ECS task definition to resolve service names and endpoints as tasks scale dynamically.
ECS services can scale seamlessly with Cloud Map, which provides a consistent service discovery mechanism. This enables stateful applications to maintain reliable communication without requiring manual configuration.
Horizontal scaling with ECS service auto scaling
With ECS and AWS Fargate, you can set up auto scaling to scale your stateful application based on demand. ECS allows you to configure auto scaling rules for your service that automatically increase or decrease the number of running tasks based on CPU or memory usage, as well as custom metrics from Amazon CloudWatch.
Designing an automation-friendly deployment setup can enhance the reliability of scaling actions and ensure services are deployed consistently across environments.
How to set up ECS auto scaling
- Define auto scaling policies in your ECS service.
- Set scaling triggers based on metrics like CPU utilization or memory usage.
- Configure target tracking policies to scale your application according to user-defined thresholds.
Auto scaling ensures that your stateful application remains highly available and can handle increased load, all while minimizing resource wastage when demand is low.
Implement session management for stateful applications
Stateful applications often require session management, where the user’s session is maintained across multiple requests. When scaling with ECS, consider using Elastic Load Balancing (ELB) and Sticky Sessions (session affinity) to ensure that user sessions are routed to the same container instance.
How to configure sticky sessions
- Use Application Load Balancer (ALB) with your ECS tasks.
- Enable sticky sessions on your ALB by configuring session cookies.
- Ensure your containers share session information (either in EFS or an external database).
Maintaining session state throughout a user’s interactions requires consistent routing of their requests to the same container. Sticky sessions enable this by ensuring that each user’s requests are directed to a specific container instance
How Xavor helps you scale stateful applications with ECS and Fargate
At Xavor, we understand that scaling stateful applications in containerized environments requires more than just infrastructure; it demands deep architectural insight, performance tuning, and seamless integration of AWS services. With decades of experience in cloud-native application development and a team of AWS-certified experts, Xavor enables organizations to design, deploy, and scale stateful applications on Amazon ECS and AWS Fargate with confidence.
If you’re migrating legacy systems, building new microservices, or optimizing existing workloads, Xavor offers customized solutions for:
- Persistent storage architecture using Amazon EFS, ensuring data durability across container restarts.
- Database design and management leveraging Amazon RDS and Aurora with built-in scaling and resilience.
- Service discovery and orchestration using AWS Cloud Map to maintain consistent connections as services scale.
- Auto scaling strategy that aligns ECS task counts with real-time metrics and business needs.
- Session and state management using sticky sessions, secure load balancing, and distributed caching.
By collaborating closely with your engineering and DevOps teams, we help you adopt AWS best practices while minimizing operational overhead and risk. Our proven approach accelerates your time-to-scale and improves application reliability, even under dynamic and high-traffic conditions.
Conclusion
Scaling stateful applications with Amazon ECS and AWS Fargate involves selecting the right persistent storage, database, and service discovery solutions while leveraging the scalability features of ECS and Fargate. You can ensure that your stateful applications not only scale but also maintain the integrity of their state and data by following these strategies.
AWS provides a complete set of tools and services that support stateful workloads in the cloud. This helps ensure reliability and efficiency throughout deployment and operations.
Implementing best practices like using Amazon EFS for storage, Amazon RDS or Aurora for databases, and ECS service auto scaling helps you scale stateful applications on AWS with confidence. This approach meets user needs while keeping complexity and operational overhead to a minimum.
Need help architecting your stateful application for scale?
Email us at [email protected] to schedule a free consultation with our AWS solutions team.
