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AWS Lambda vs Cloudflare Workers: What are the differences?
Introduction:
AWS Lambda and Cloudflare Workers are two popular serverless computing services that allow developers to run code without managing servers. However, there are key differences between the two platforms that developers should consider when choosing which one to use for their projects.
Deployment Environment: AWS Lambda runs on the AWS cloud infrastructure, allowing users to deploy and run functions in the AWS ecosystem. In contrast, Cloudflare Workers run on Cloudflare's global network, allowing for lower latency and faster response times due to its distributed edge locations.
Programming Languages: AWS Lambda supports a wide range of programming languages such as Node.js, Python, Java, and C#, while Cloudflare Workers primarily support JavaScript for writing serverless functions, limiting the choice of languages available for developers.
Pricing Model: AWS Lambda charges users based on the number of requests and the duration of each request, along with any additional services used. On the other hand, Cloudflare Workers offer a pay-as-you-go pricing model based on the number of invocations, CPU time, and memory usage, potentially leading to cost savings for certain workloads.
Integration with Other AWS Services: AWS Lambda seamlessly integrates with other AWS services like S3, DynamoDB, and API Gateway, allowing developers to build complex serverless applications using a wide range of AWS services. In comparison, Cloudflare Workers have limited integration with external services and are primarily designed to work within the Cloudflare ecosystem.
Performance: Cloudflare Workers have the advantage of running on Cloudflare's global network of data centers, resulting in lower latency and faster response times for users accessing applications deployed with Workers. AWS Lambda, while powerful, may experience slightly higher latency due to the nature of cloud computing infrastructure.
Scalability: AWS Lambda provides auto-scaling capabilities to handle varying workloads and can scale functions based on demand. Cloudflare Workers also provide scalability but are limited by the capacity of Cloudflare's network, which may affect performance during sudden traffic spikes.
In Summary, AWS Lambda and Cloudflare Workers differ in their deployment environment, programming languages, pricing models, integration with other services, performance, and scalability, offering developers a choice based on their specific requirements and use cases.
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 โ way too much complexity
- Managed Kubernetes in various flavors โ still too much complexity
- Zeit โ Maybe, but no Docker support
- Elastic Beanstalk โ 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 ๐ค
- Ops Experience / OX ๐ (?)
- Cost ๐ต
- Lock in ๐
Read the full post linked below for all details
Pros of AWS Lambda
- No infrastructure129
- Cheap83
- Quick70
- Stateless59
- No deploy, no server, great sleep47
- AWS Lambda went down taking many sites with it12
- Event Driven Governance6
- Extensive API6
- Auto scale and cost effective6
- Easy to deploy6
- VPC Support5
- Integrated with various AWS services3
Pros of Cloudflare Workers
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Cons of AWS Lambda
- Cant execute ruby or go7
- Compute time limited3
- Can't execute PHP w/o significant effort1