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AWS Batch

90
250
+ 1
6
Serverless

1.3K
1.2K
+ 1
28
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AWS Batch vs Serverless: What are the differences?

Developers describe AWS Batch as "Fully Managed Batch Processing at Any Scale". 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. On the other hand, Serverless is detailed as "The most widely-adopted toolkit for building serverless applications". 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.

AWS Batch and Serverless belong to "Serverless / Task Processing" category of the tech stack.

Serverless is an open source tool with 31.3K GitHub stars and 3.53K GitHub forks. Here's a link to Serverless's open source repository on GitHub.

Decisions about AWS Batch and Serverless
Tim Nolet

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 Batch
Pros of Serverless
  • 3
    Containerized
  • 3
    Scalable
  • 14
    API integration
  • 7
    Supports cloud functions for Google, Azure, and IBM
  • 3
    Lower cost
  • 1
    3. Simplified Management for developers to focus on cod
  • 1
    Auto scale
  • 1
    5. Built-in Redundancy and Availability:
  • 1
    Openwhisk

Sign up to add or upvote prosMake informed product decisions

Cons of AWS Batch
Cons of Serverless
  • 3
    More overhead than lambda
  • 1
    Image management
    Be the first to leave a con

    Sign up to add or upvote consMake informed product decisions

    - No public GitHub repository available -

    What is 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.

    What is 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.

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

    What companies use AWS Batch?
    What companies use Serverless?
    Manage your open source components, licenses, and vulnerabilities
    Learn More

    Sign up to get full access to all the companiesMake informed product decisions

    What tools integrate with AWS Batch?
    What tools integrate with Serverless?

    Sign up to get full access to all the tool integrationsMake informed product decisions

    What are some alternatives to AWS Batch and Serverless?
    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.
    Beanstalk
    A single process to commit code, review with the team, and deploy the final result to your customers.
    Airflow
    Use Airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The Airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command lines utilities makes performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress and troubleshoot issues when needed.
    Kubernetes
    Kubernetes is an open source orchestration system for Docker containers. It handles scheduling onto nodes in a compute cluster and actively manages workloads to ensure that their state matches the users declared intentions.
    NGINX
    nginx [engine x] is an HTTP and reverse proxy server, as well as a mail proxy server, written by Igor Sysoev. According to Netcraft nginx served or proxied 30.46% of the top million busiest sites in Jan 2018.
    See all alternatives