AWS Lambda use cases: 6 inspirational examples
Tags: aws, serverless, devops, programming
Published: 2021-12-06 14:47:38

Since being launched in 2014, the AWS Lambda service has [spread fast](https://dashbird.io/blog/challenges-opportunities-going-serverless/) amongst developers and cloud architects, for it is easy to use, and there is a [significant cost benefit](https://dashbird.io/blog/aws-lambda-pricing-model-explained/) (pay-per-use basis). 

**AWS Lambda** is an Amazon Web Services serverless deployment platform that you can use in the AWS cloud environment with basically no overhead. It will save you much time and resources using Lambda for performing code tasks for **websites, applications, and services running on AWS**. AWS Lambda is an event-driven computing cloud with many uses. In this article, we will present you with some of the best AWS Lambda use cases.

1\. Swift document conversion
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For those who are providing documents to users, there is always a problem because there is **no standard document format that will satisfy the desires of all users**. Some would want it in HTML format, while others would like to download it as a PDF file or even in some more specialized document format.

You can, of course, make and store copies of all document formats that are most likely to be requested by a user. However, soon you will find out that this **takes a substantial amount of storage capacity**, which you can extend for a considerable **cost**, or you can just save your resources by using AWS Lambda. AWS Lambda can **swiftly retrieve the required document, format and convert it**, and finally, serve it back to the user for a download or a display on a page.

2\. Processing video
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This case is helpful for those of you who have **stored video files on an S3 bucket**. For now, you have an instance that polls the bucket regularly. It idles until a new file is uploaded, then it downloads the file, processes it somehow, and then drives it back to your origin server.

The problem is you have an instance that's **sitting idle for a good part of the day**. It's doing nothing when no new video is uploaded and costs you money, and your computer resources are used 24/7 for no reason.

Using Lambda, in this case, allows you to **upload your script** (Java, JavaScript, Python, etc.) and **design code to provoke an event when a new file is uploaded to the bucket**, which will lead to the file being processed and pushed back to your origin server. And that's how easily Lambda can **save your resources**.

3\. Operating Serverless websites
---------------------------------

This might be the best way to take advantage of the [pricing model of Lambda](https://dashbird.io/blog/aws-lambda-pricing-model-explained/) and S3 hosted static websites.

Think about hosting the web frontend on S3 and accelerating content transmission with CloudFront caching. The web frontend can send requests to Lambda functions using the API Gateway HTTPS endpoints. Lambda can handle the application logic and persist data to a fully managed database service (RDS for relational or DynamoDB for a non-relational database).

Your Lambda functions and databases can be hosted within a VPC to separate them from other networks. As for Lambda, S3, and API Gateway, you get charged after the traffic incurred, and the **only fixed expense will be running the database service**.

> Learn how to [create your first serverless website in 15 minutes](https://dashbird.io/blog/create-your-first-website-with-serverless-in-15-minutes/).

4\. Security alerts
-------------------

Do you need to be aware of any security breaches in your cloud infrastructure?

Is it imperative to your overall cloud strategy to monitor your logs and to keep an audit trail?

Lambda could help you a lot in this situation.

You can **write a Lambda function to send an alert on a specific event** from Cloudwatch/CloudTrail AWS activity logs. It will notify your designated on-call staff via email, or you could even write a code that will trigger the AWS Lambda to call you on your phone.

5\. Automated file synchronization
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If you have a repository that needs to be **regularly synchronized **to several locations several times a day, you might find AWS Lambda very useful. Many people don't use a dedicated instance for things like this. Often they go and double or even triple up on another instance and just assign this task to it. Depending on a security policy or contention for resources at specific periods during the day, this will prove not to be the best option.

Instead of keeping an instance up and running all day long, chewing away at your budget every month, **you can use a Lambda function** that a scheduled event will trigger, run your synchronization job, and then just go away until the next cycle that it needs to run.

6\. Predictive page rendering
-----------------------------

Are you using predictive page rendering to ready web pages for display based on the user's probability of selecting them? You can use a **Lambda-based application to retrieve documents and multimedia files**, which might be used by the next page requested, and conduct the beginning stages of rendering them for display.

If an outside source is serving multimedia data, the AWS Lambda application can even check for its availability and attempt to use alternate sources if they are not available.

Does your use case fit Lambda's limits?
---------------------------------------

Now, these were all pretty compelling use cases, but obviously, you need to take care of your own, probably rather specific, tasks.

The [limits around AWS Lambda](https://dashbird.io/blog/exploring-lambda-limitations/) usage were increased every year since its release, and things that couldn't be done in 2014 are now in the realm of possibility.

If you can solve your use-case within the following limits, then go for it:

-   Custom runtime support for the programming language of your choice
-   10 GB function size as Docker image
-   50 MB function size as ZIP archives
-   10 GB of memory
-   6 vCPU cores (x86_64/arm64)
-   15 minutes execution time
-   6 MB API event payload
-   265 KB non-API event payload
-   512 MB temporary storage
-   1,000 concurrent invocations

Conclusion
----------

In the end, AWS Lambda should be one of your prime **go-to resources for approaching repetitive or time-exhausting tasks**, along with the other heavy-lifting jobs of the data-processing world. It frees your prime online services to target crucial frontend tasks, such as responding promptly to user requests, and it allows you to offload a lot of processes that would otherwise significantly decelerate your system.

AWS Lambda would provide you with even **more granular control over the services** you wish to deliver to your customers, with a presumption that they can be split out into specific tasks that can be run as functions inside Lambda. It would be well worth your while to master the capabilities of this service, as it can immensely reduce the expenditure of your cloud operations while allowing you to scale your applications to much higher levels formerly not possible and to evaluate how this fits into your overall strategy to provide value to your customers.

In combination with AWS Lambda, you should use some monitoring and error tracking tools like [Dashbird](https://dashbird.io/) to even more secure your data and improve your system's overall stability.

* * * * *

Read more:

[Top 6 lambda monitoring tools](https://dashbird.io/blog/top-aws-lambda-performance-monitoring-tools/)

[AWS Lambda cost optimization strategies that work](https://dashbird.io/blog/aws-lambda-cost-optimization-strategies/)

[Lambda metrics that you should definitely be monitoring](https://dashbird.io/blog/lambda-metrics-monitoring-what-matters/)