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AWS Lambda vs Google Cloud Run: What are the differences?
Introduction
AWS Lambda and Google Cloud Run are both serverless computing platforms that allow developers to build and deploy applications without managing infrastructure. However, there are several key differences between the two platforms that developers should be aware of before choosing one for their projects.
Performance: AWS Lambda is known for its fast start times and low latency, making it a great choice for applications that require quick response times. On the other hand, Google Cloud Run containers have a longer startup time, but once running, they can handle a high number of concurrent requests, making them more suitable for applications that require high scalability.
Pricing Model: AWS Lambda follows a pay-as-you-go model, where you are billed based on the number of requests and the duration of execution. On the other hand, Google Cloud Run offers a differentiated pricing model, where you are billed based on the CPU allocation and memory usage, allowing you to optimize costs based on your specific application requirements.
Environment Flexibility: AWS Lambda supports a wide range of programming languages, including JavaScript, Python, Java, and C#, providing developers with more flexibility in their choice of language. Google Cloud Run, on the other hand, currently only supports containers, which means you can use any language that can be packaged into a container image.
Integration with Ecosystem: AWS Lambda has a rich ecosystem of services and integrations, including the AWS Serverless Application Model (SAM), AWS Step Functions, and AWS API Gateway, making it easier to build and deploy complex serverless applications. Google Cloud Run integrates well with other Google Cloud services, such as Cloud Build for CI/CD, Cloud Pub/Sub for messaging, and Cloud Logging for monitoring.
Automatic Scaling: Both AWS Lambda and Google Cloud Run offer automatic scaling based on request traffic, but they have different scaling mechanisms. AWS Lambda uses a combination of requests per second and concurrent executions to scale, while Google Cloud Run scales based on the number of concurrent requests.
Deployment Options: AWS Lambda provides a native deployment mechanism through its console, CLI, or AWS CloudFormation, making it easy to manage and deploy functions. Google Cloud Run can be deployed using either the Google Cloud Console or the gcloud command-line tool, and it also integrates well with other deployment tools like Cloud Build.
Summary
In summary, AWS Lambda and Google Cloud Run have key differences in terms of performance, pricing model, environment flexibility, integration with ecosystem, scaling mechanisms, and deployment options. Developers should consider these differences when choosing a serverless platform for their applications.
Run cloud service containers instead of cloud-native services
- Running containers means that your microservices are not "cooked" into a cloud provider's architecture.
- Moving from one cloud to the next means that you simply spin up new instances of your containers in the new cloud using that cloud's container service.
- Start redirecting your traffic to the new resources.
- Turn off the containers in the cloud you migrated from.
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 Google Cloud Run
- HTTPS endpoints11
- Fully managed10
- Pay per use10
- Concurrency: multiple requests sent to each container7
- Deploy containers7
- Serverless7
- Custom domains with auto SSL6
- "Invoke IAM permission" to manage authentication4
- Cons0
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Cons of AWS Lambda
- Cant execute ruby or go7
- Compute time limited3
- Can't execute PHP w/o significant effort1