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  1. Stackups
  2. Application & Data
  3. Serverless
  4. Serverless Task Processing
  5. AWS Fargate vs AWS Lambda

AWS Fargate vs AWS Lambda

OverviewDecisionsComparisonAlternatives

Overview

AWS Lambda
AWS Lambda
Stacks26.0K
Followers18.8K
Votes432
AWS Fargate
AWS Fargate
Stacks650
Followers413
Votes0

AWS Fargate vs AWS Lambda: What are the differences?

Key Differences Between AWS Fargate and AWS Lambda

AWS Fargate and AWS Lambda are both serverless technologies offered by Amazon Web Services (AWS) that allow developers to focus on writing code without managing the underlying infrastructure. However, there are several key differences between the two services that are important to note:

  1. Deployment Model:

    • AWS Fargate: Fargate provides a container-centric serverless compute engine, where developers package their application into containers and specify the resources needed for each container. These containers are then scheduled and managed by Fargate.
    • AWS Lambda: Lambda, on the other hand, operates on a function-centric serverless model, where developers write and upload individual functions that automatically scale and run in response to events. Lambda takes care of the execution environment and handles the scaling and resource allocation for each function.
  2. Runtime Execution:

    • AWS Fargate: With Fargate, applications run continuously and are responsible for handling their own state and concurrency. They can leverage features like web servers, persistent storage, and background processes.
    • AWS Lambda: Lambda functions are event-driven and typically have a short duration. They are stateless and designed to handle a single request at a time. Lambda automatically manages any concurrency and scaling requirements.
  3. Cost Model:

    • AWS Fargate: Fargate operates on a pay-per-use pricing model, where customers are charged based on the amount of CPU and memory resources their containers consume and the duration of their runtime.
    • AWS Lambda: Lambda also follows a pay-per-use pricing model, but it is based on the number of invocations and the amount of time each function takes to execute. Lambda functions are billed in 100ms increments.
  4. Supported Use Cases:

    • AWS Fargate: Fargate is suitable for long-running applications, microservices, and batch processing workloads that require more control over the execution environment, the ability to run containers with specific resource requirements, and persistent storage.
    • AWS Lambda: Lambda is well-suited for event-driven architectures, serverless web applications, and stream processing use cases. It excels in scenarios where functions can be triggered by various AWS services, such as S3, DynamoDB, or API Gateway.
  5. Integration and Ecosystem:

    • AWS Fargate: Fargate integrates seamlessly with other AWS services, allowing developers to take advantage of features like Elastic Load Balancers, Amazon VPC, and AWS CloudFormation. It also works well in conjunction with container orchestration platforms like Amazon ECS and Kubernetes.
    • AWS Lambda: Lambda has extensive integrations with AWS services, enabling developers to easily build serverless architectures that leverage services like S3, DynamoDB, SNS, and more. It also supports a variety of event sources, including HTTP endpoints, CloudWatch Events, and S3.
  6. Flexibility and Control:

    • AWS Fargate: Fargate offers more control and flexibility over the underlying infrastructure and resources. Developers have the ability to specify CPU and memory requirements for their containers, as well as configure networking and security settings.
    • AWS Lambda: Lambda abstracts away the underlying infrastructure, providing a highly managed environment. Developers have less control over the execution context and resource allocation, but benefit from the automatic scaling and availability provided by the service.

In summary, AWS Fargate is a container-centric serverless compute engine that allows developers to run and manage containers, while AWS Lambda is a function-centric serverless compute service that executes individual functions in response to events. Fargate provides more control over the infrastructure and supports long-running applications, while Lambda excels in event-driven use cases and integrates seamlessly with other AWS services.

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Advice on AWS Lambda, AWS Fargate

Tim
Tim

CTO at Checkly Inc.

Sep 18, 2019

Needs adviceonHerokuHerokuAWS LambdaAWS Lambda

When adding a new feature to Checkly rearchitecting some older piece, I tend to pick Heroku for rolling it out. But not always, because sometimes I pick AWS Lambda . The short story:

  • Developer Experience trumps everything.
  • AWS Lambda is cheap. Up to a limit though. This impact not only your wallet.
  • If you need geographic spread, AWS is lonely at the top.

The setup

Recently, I was doing a brainstorm at a startup here in Berlin on the future of their infrastructure. They were ready to move on from their initial, almost 100% Ec2 + Chef based setup. Everything was on the table. But we crossed out a lot quite quickly:

  • Pure, uncut, self hosted Kubernetes — way too much complexity
  • Managed Kubernetes in various flavors — still too much complexity
  • Zeit — Maybe, but no Docker support
  • Elastic Beanstalk — Maybe, bit old but does the job
  • Heroku
  • Lambda

It became clear a mix of PaaS and FaaS was the way to go. What a surprise! That is exactly what I use for Checkly! But when do you pick which model?

I chopped that question up into the following categories:

  • Developer Experience / DX 🤓
  • Ops Experience / OX 🐂 (?)
  • Cost 💵
  • Lock in 🔐

Read the full post linked below for all details

357k views357k
Comments

Detailed Comparison

AWS Lambda
AWS Lambda
AWS Fargate
AWS Fargate

AWS Lambda is a compute service that runs your code in response to events and automatically manages the underlying compute resources for you. You can use AWS Lambda to extend other AWS services with custom logic, or create your own back-end services that operate at AWS scale, performance, and security.

AWS Fargate is a technology for Amazon ECS and EKS* that allows you to run containers without having to manage servers or clusters. With AWS Fargate, you no longer have to provision, configure, and scale clusters of virtual machines to run containers.

Extend other AWS services with custom logic;Build custom back-end services;Completely Automated Administration;Built-in Fault Tolerance;Automatic Scaling;Integrated Security Model;Bring Your Own Code;Pay Per Use;Flexible Resource Model
No clusters to manage; seamless scaling; Integrated with Amazon ECS and EKS
Statistics
Stacks
26.0K
Stacks
650
Followers
18.8K
Followers
413
Votes
432
Votes
0
Pros & Cons
Pros
  • 129
    No infrastructure
  • 83
    Cheap
  • 70
    Quick
  • 59
    Stateless
  • 47
    No deploy, no server, great sleep
Cons
  • 7
    Cant execute ruby or go
  • 3
    Compute time limited
  • 1
    Can't execute PHP w/o significant effort
Cons
  • 2
    Expensive
Integrations
No integrations available
Docker
Docker
Amazon EC2 Container Service
Amazon EC2 Container Service
Amazon CloudWatch
Amazon CloudWatch
AWS IAM
AWS IAM
Amazon VPC
Amazon VPC

What are some alternatives to AWS Lambda, AWS Fargate?

Amazon EC2 Container Service

Amazon EC2 Container Service

Amazon EC2 Container Service lets you launch and stop container-enabled applications with simple API calls, allows you to query the state of your cluster from a centralized service, and gives you access to many familiar Amazon EC2 features like security groups, EBS volumes and IAM roles.

Google Kubernetes Engine

Google Kubernetes Engine

Container Engine takes care of provisioning and maintaining the underlying virtual machine cluster, scaling your application, and operational logistics like logging, monitoring, and health management.

Azure Functions

Azure Functions

Azure Functions is an event driven, compute-on-demand experience that extends the existing Azure application platform with capabilities to implement code triggered by events occurring in virtually any Azure or 3rd party service as well as on-premises systems.

Google Cloud Run

Google Cloud Run

A managed compute platform that enables you to run stateless containers that are invocable via HTTP requests. It's serverless by abstracting away all infrastructure management.

Containerum

Containerum

Containerum is built to aid cluster management, teamwork and resource allocation. Containerum runs on top of any Kubernetes cluster and provides a friendly Web UI for cluster management.

Serverless

Serverless

Build applications comprised of microservices that run in response to events, auto-scale for you, and only charge you when they run. This lowers the total cost of maintaining your apps, enabling you to build more logic, faster. The Framework uses new event-driven compute services, like AWS Lambda, Google CloudFunctions, and more.

Google Cloud Functions

Google Cloud Functions

Construct applications from bite-sized business logic billed to the nearest 100 milliseconds, only while your code is running

Knative

Knative

Knative provides a set of middleware components that are essential to build modern, source-centric, and container-based applications that can run anywhere: on premises, in the cloud, or even in a third-party data center

OpenFaaS

OpenFaaS

Serverless Functions Made Simple for Docker and Kubernetes

Azure Container Service

Azure Container Service

Azure Container Service optimizes the configuration of popular open source tools and technologies specifically for Azure. You get an open solution that offers portability for both your containers and your application configuration. You select the size, the number of hosts, and choice of orchestrator tools, and Container Service handles everything else.

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