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AWS Lambda

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AWS Step Functions

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AWS Lambda vs AWS Step Functions: What are the differences?

AWS Lambda: Automatically run code in response to modifications to objects in Amazon S3 buckets, messages in Kinesis streams, or updates in DynamoDB. 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 Step Functions: Build Distributed Applications Using Visual Workflows. AWS Step Functions makes it easy to coordinate the components of distributed applications and microservices using visual workflows. Building applications from individual components that each perform a discrete function lets you scale and change applications quickly.

AWS Lambda belongs to "Serverless / Task Processing" category of the tech stack, while AWS Step Functions can be primarily classified under "Cloud Task Management".

9GAG, Asana, and CircleCI are some of the popular companies that use AWS Lambda, whereas AWS Step Functions is used by Clever, Froothaus, and MessageMedia. AWS Lambda has a broader approval, being mentioned in 1023 company stacks & 614 developers stacks; compared to AWS Step Functions, which is listed in 19 company stacks and 7 developer stacks.

Decisions about AWS Lambda and AWS Step Functions

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

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Pros of AWS Lambda
Pros of AWS Step Functions
  • 127
    No infrastructure
  • 82
    Cheap
  • 69
    Quick
  • 57
    Stateless
  • 47
    No deploy, no server, great sleep
  • 9
    AWS Lambda went down taking many sites with it
  • 6
    Event Driven Governance
  • 5
    Auto scale and cost effective
  • 5
    Extensive API
  • 5
    Easy to deploy
  • 4
    VPC Support
  • 2
    Integrated with various AWS services
  • 5
    Integration with other services
  • 4
    Pricing
  • 4
    Easily Accessible via AWS Console
  • 3
    Complex workflows
  • 2
    Scalability
  • 2
    High Availability
  • 2
    Workflow Processing

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Cons of AWS Lambda
Cons of AWS Step Functions
  • 5
    Cant execute ruby or go
  • 0
    Can't execute PHP w/o significant effort
    Be the first to leave a con

    Sign up to add or upvote consMake informed product decisions

    What is AWS Lambda?

    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.

    What is AWS Step Functions?

    AWS Step Functions makes it easy to coordinate the components of distributed applications and microservices using visual workflows. Building applications from individual components that each perform a discrete function lets you scale and change applications quickly.

    Need advice about which tool to choose?Ask the StackShare community!

    What companies use AWS Lambda?
    What companies use AWS Step Functions?
    See which teams inside your own company are using AWS Lambda or AWS Step Functions.
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    What tools integrate with AWS Lambda?
    What tools integrate with AWS Step Functions?

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    Blog Posts

    GitHubPythonNode.js+47
    50
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    GitHubDockerAmazon EC2+23
    12
    6359
    JavaScriptGitHubPython+42
    52
    19886
    What are some alternatives to AWS Lambda and AWS Step Functions?
    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.
    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.
    AWS Elastic Beanstalk
    Once you upload your application, Elastic Beanstalk automatically handles the deployment details of capacity provisioning, load balancing, auto-scaling, and application health monitoring.
    Google App Engine
    Google has a reputation for highly reliable, high performance infrastructure. With App Engine you can take advantage of the 10 years of knowledge Google has in running massively scalable, performance driven systems. App Engine applications are easy to build, easy to maintain, and easy to scale as your traffic and data storage needs grow.
    AWS Batch
    It enables developers, scientists, and engineers to easily and efficiently run hundreds of thousands of batch computing jobs on AWS. It dynamically provisions the optimal quantity and type of compute resources (e.g., CPU or memory optimized instances) based on the volume and specific resource requirements of the batch jobs submitted.
    See all alternatives