Choosing the Best Compute Service for Your Serverless Application: Fargate vs Lambda Functions

Serverless computing is a cloud-based execution model where the cloud provider (AWS) is responsible for provisioning, scaling, and managing the underlying infrastructure. It allows developers to build and run applications and services without the need to manage servers, virtual machines, or container orchestration. Serverless computing on AWS is enabled by services such as AWS Lambda, AWS Fargate, and others, but in this article, we’ll focus on those two. Both services are part of the broader AWS serverless ecosystem, but they differ in their deployment models and target use cases.

The choice between Fargate and Lambda can significantly impact the architecture, scalability, performance, and cost of your serverless application. Selecting the right service (or combination of services) requires a thorough understanding of your application's requirements, existing infrastructure, and team capabilities. Making an informed decision can help you optimise your serverless application for efficiency, cost-effectiveness, and overall success.

AWS Fargate

Fargate is a serverless compute engine for containers that allows you to run containers without having to manage the underlying infrastructure. It provides a fully managed container runtime environment, handling the provisioning, scaling, and management of the compute resources needed to run your containers. Fargate removes the need for you to provision, configure, and scale the container host infrastructure, such as Amazon EC2 instances.

Key Benefits of Fargate 

• Fargate abstracts away server and infrastructure management, allowing you to focus on building and deploying your containerized applications. You simply define your container specifications, and Fargate handles the rest, including provisioning the right amount of computing, memory, and networking resources.
• Fargate automatically scales the number of containers running your application based on changes in traffic or demand. It provides the necessary computing resources (CPU and memory) to support the desired number of container instances. This eliminates the need to manually provision and manage the underlying infrastructure, such as EC2 instances.
• Fargate handles all the infrastructure-related tasks, such as cluster management, container scheduling, and scaling. You don't need to worry about tasks like provisioning, configuring, and scaling the container host infrastructure. This allows you to focus on building and deploying your containerized application without deep infrastructure management expertise.

AWS Lambda

Lambda is a serverless computing service that allows you to run code without provisioning or managing servers. It executes your code in response to events or direct invocations, automatically scaling the execution of your functions based on the incoming workload. Lambda abstracts away the server and runtime management, allowing you to focus on writing and deploying your application code.

Key Benefits of Lambda

•  Lambda functions are designed to be triggered by events, such as HTTP requests, database updates, or message queue events.
• This event-driven architecture promotes a more decoupled, scalable, and serverless approach to application development.
• Lambda automatically scales the execution of your functions based on the incoming event volume or trigger invocations.
• You only pay for the compute time used when your functions are executed, with no upfront costs or need to provision infrastructure.
• Lambda works well with a wide range of AWS services, making it easy to connect your applications to services like API Gateway, DynamoDB, S3, SNS, and SQS.

Deployment Model

Fargate and containers offer a familiar approach. You package your application as a Docker container and upload it to Fargate. Fargate then provisions the resources needed to run your containers. This container-based deployment with Fargate is flexible and portable. It lets you reuse existing Docker practices from on-premise or virtual machine environments. You also gain more control over the runtime environment and dependencies within your containers.

Lambda and functions take a different approach. Here, you define your application logic as stateless, event-driven functions. You upload your code snippets as Lambda functions, and Lambda manages the execution resources. This function-based deployment is lightweight and focused on individual pieces of logic. It encourages an event-driven, microservices architecture where your application is broken down into small, independent functions triggered by events. This promotes a loosely coupled, highly scalable, and distributed application design.

Scalability and Concurrency

Fargate: Container-Level Scaling for Predictable Workloads

Fargate automatically scales your containerized application by adding or removing containers based on traffic. This allows for faster scaling compared to manual EC2 instance management. Fargate handles the underlying infrastructure, so you only need to focus on your application code. This container-level scaling is ideal for applications with predictable scaling patterns or those that require long-running or stateful workloads.

Lambda: Function-Level Scaling for Bursty Traffic

Lambda scales by automatically executing multiple instances of your function concurrently as demand increases. It has built-in concurrency limits to control the maximum number of functions running at once, which you can adjust based on your application's needs. Lambda's function-level scaling and event-driven architecture are perfect for applications with unpredictable scaling needs or short-lived, stateless workloads. However, Lambda functions have a maximum execution time of 15 minutes. This makes them ideal for short-lived tasks but may not be suitable for long-running processes.

Operational Complexity

Fargate: Focus on Container Deployment

Fargate simplifies container management by handling everything from cluster setup and scheduling to infrastructure scaling. You just provide your container image, and Fargate will take care of the rest. This lets you focus on building and deploying your application without needing deep infrastructure expertise.

Lambda: Serverless Simplicity

Lambda offers true serverless development. You upload your code and define event triggers. Lambda manages the underlying servers, runtime environment, and scaling based on incoming events. Functions are inherently stateless and event-driven, eliminating the complexity of managing long-running applications, servers, operating systems, or runtime environments.

Cost Considerations

Fargate's Per-Second Billing

Fargate charges on a per-second basis for the compute resources used by your containers. The cost is determined by the amount of CPU and memory provisioned for your containers. You pay for the entire duration that your containers are running, even during idle periods. This billing model may be more cost-effective for long-running or predictable workloads, where you can optimise by right-sizing your container resources.

Lambda's Per-Invocation Billing

Lambda charges on a per-invocation basis, which means you only pay for the compute time used when your functions are executed. The cost is determined by the duration of the function execution and the amount of memory allocated to the function. There is also a free tier that provides a certain number of free invocations and compute time per month. This billing model is well-suited for event-driven, short-lived workloads (maximum of 15 minutes) with variable usage patterns.

Common Use Cases and Recommendations 

When to Choose Fargate: Stateful, Long-Running Workloads

Fargate excels at running applications that need to maintain state and have predictable scaling patterns. Here are some ideal use cases:

• Stateful applications: Online gaming platforms rely on Fargate to keep player sessions consistent across instances.
• Monolithic applications: Traditional web applications with complex structures are well-suited for Fargate's containerised approach.
• Microservices with stable traffic: If your microservices have predictable traffic, Fargate allows for efficient resource allocation by right-sizing containers.
• Custom runtime environments: Need a specific runtime or complex networking? Fargate offers more control over the infrastructure compared to Lambda.
• Migrating from Kubernetes: Fargate integrates well with Amazon EKS, making it easier to migrate existing Kubernetes applications.

When to Choose Lambda: Event-Driven, Short-Lived Workloads

Lambda shines for applications that are easily broken down into small, stateless functions triggered by events. Here's where it excels:

• Serverless backends: Break down web and mobile backends into independent Lambda functions for tasks like handling HTTP requests or database operations.
• Highly variable workloads: Marketing campaign websites with sudden traffic spikes can handle the surge effectively with Lambda's automatic scaling.
• Social media platforms: Lambda can handle surges in user activity on social media platforms by dynamically scaling services like authentication or content delivery.
• Rapid prototyping: Build and deploy new features quickly with Lambda's reduced operational overhead.
• Cost-sensitive applications: For applications with variable usage patterns, Lambda's pay-per-use billing aligns well with costs. This is ideal for seasonal apps or webhook processing in SaaS applications.

Combining Fargate and Lambda for Optimal Results

Many applications can benefit from a hybrid approach that combines both Fargate and Lambda. This is ideal for scenarios with:

• Mixed workloads: A media streaming service can use Fargate for core video processing while handling user interactions, analytics, and notifications with Lambda functions.
• Microservices with diverse needs: A microservices architecture can deploy critical services on Fargate for stability and utilize Lambda for event-driven or variable functionalities.
• Optimising cost and performance: A data processing pipeline can benefit from Fargate for the initial data tasks requiring consistent resources. Then, it can switch to Lambda for cost-effective analysis triggered by events.

By using both Fargate and Lambda strategically, you can achieve a balance of performance, scalability, and cost-efficiency for your application.

Conclusion

Choosing between Fargate and Lambda hinges on your application's needs. Fargate tackles long-running, stateful workloads requiring consistent computing, while Lambda is ideal for short-lived, event-driven tasks with variable usage. Consider your existing infrastructure, desired scalability, resource needs, budget, and team expertise to make the best choice. In some cases, a hybrid approach using both Fargate and Lambda can optimise performance, scalability, and cost-effectiveness for your serverless application.