Tranforming cloud from server to serverless
I used AWS lambda in one of project which was developed by company I am currently in. My current company is AWS partner network …
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What is AWS Lambda?
AWS Lambda is a serverless computing platform that lets users run code without provisioning or managing servers. With Lambda, users can run code for virtually any type of app or backend service—all with zero administration. It takes of requirements to…
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What is AWS Lambda?
AWS Lambda is a serverless computing platform that lets developers run code without provisioning or managing servers. With Lambda, users can run code for virtually any type of app or backend service—all with zero administration. It takes care of requirements to run and scale code with high availability. Users pay only for the compute time they consume—there is no charge when their code is not running.
Developers uploading to Lambda don’t have to deal with their code’s environment. It’s a “serverless” service which lets outside code or events invoke functions. Lambda doesn’t store data, but it allows access to other services which do. Users can set up their code to automatically trigger from other AWS services or call it directly from any web or mobile app.
AWS Lambda Technical Details
| Deployment Types | Software as a Service (SaaS), Cloud, or Web-Based |
|---|---|
| Operating Systems | Unspecified |
| Mobile Application | No |
Frequently Asked Questions
AWS Lambda is a serverless computing platform that lets users run code without provisioning or managing servers. With Lambda, users can run code for virtually any type of app or backend service—all with zero administration. It takes of requirements to run and scale code with high availability.
Reviewers rate Usability highest, with a score of 9.
The most common users of AWS Lambda are from Mid-sized Companies (51-1,000 employees).
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My team uses AWS Lambda in two primary ways: as a back end service and as middle-ware for log processing. As a backend, Lambda provides the compute for APIs fronted by AWS API Gateway or one-off tasks that can be handled in the cloud by a small piece of code. As a middle-ware for log processing, Lambda processes logs ingested by AWS Kenesis by feeding them into AWS Cloudwatch and third-party logging services.
Lambda provides an interface to managed compute resources without the overhead of the team having to mange servers or other resources.
Lambda provides an interface to managed compute resources without the overhead of the team having to mange servers or other resources.
- Lambda provides multiple methods for triggering functions, this includes AWS resources and services and external triggers like APIs and CLI calls.
- The compute provided my Lambda is largely hands off for operations teams. Once the function is deployed, the management overhead is minimal since there are no servers to maintain.
- Lambda's pricing can be very cost effective given that users are only charged for the time the function runs and associated costs like network or storage if those are used. A function that executes quickly and is not called often can cost next to nothing.
- Developing test cases for Lambda functions can be difficult. For functions that require some sort of input it can be tough to develop the proper payload and event for a test.
- For the uninitiated, deploying functions with Infrastructure as Code tools can be a challenging undertaking.
- Logging the output of a function feels disjointed from running the function in the console. A tighter integration with operational logging would be appreciated, perhaps being able to view function logs from the Lambda console instead of having to navigate over to CloudWatch.
- Sometimes its difficult to determine the correct permissions needed for Lambda execution from other AWS services.
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- We have simplified log fiie ingestion using Lambda functions. The return has been less time worrying about getting logs from source to ingestion; one the process is in place the team is nearly 100% hands off.
- We have begun taking a more API focused approach by using API Gateway as the interface to business processes and Lambda as the back end compute. Moving away from server based back ends places us on a path to reducing overall spend in compute costs.
- Lambda functions allow us to easily interface with third party services through APIs. This simplifies access management since the function can be granted permissions and access to the function can be gated with API keys and other authentication methods.
I have used Azure Functions and Google Cloud Functions. In comparison, AWS Lambda is a bit more difficult to configure out of the gate. But in most cases once the function is in place and running the operation becomes completely hands-off. While I've used Azure Functions and Google Cloud Functions, my team selected Lambda because the rest of our resources already run in AWS. Keeping the functions in the same account as the other resources (like S3 buckets and API Gateways) simplifies access management and deployments.
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The tight integration with API Gateway was the main factor for using AWS Lambda.
I would spend more time looking at the CLI projects focused on deploying and managing Lambda functions. Particularly, I mean services like SAM CLI, Serverless, Zappa and Claudia. The majority of the AWS resources operated by my team are created using Terraform which allows us to capture infrastructure as code. However, Terraform may not be the best way to deploy and manage lambda functions. But if all you have is a hammer, every problem looks like a nail. Taking a step back, one of the other tools I mentioned might have allowed for our APIs and functions to be implemented easier.