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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.
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.
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
Pros of AWS Batch
- Containerized3
- Scalable3
Pros of Serverless
- API integration14
- Supports cloud functions for Google, Azure, and IBM7
- Lower cost3
- 3. Simplified Management for developers to focus on cod1
- Auto scale1
- 5. Built-in Redundancy and Availability:1
- Openwhisk1
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Cons of AWS Batch
- More overhead than lambda3
- Image management1