Personal blog of Yzmir Ramirez

AWS announced some big updates to its Lambda serverless function service today. For starters, starting today it will be able to deliver functions with up to 10MB of memory and 6 vCPUs (virtual CPUs). This will allow developers building more compute-intensive functions to get the resources they need.

“Starting today, you can allocate up to 10 GB of memory to a Lambda function. This is more than a 3x increase compared to previous limits. Lambda allocates CPU and other resources linearly in proportion to the amount of memory configured. That means you can now have access to up to 6 vCPUs in each execution environment,” the company wrote in a blog post announcing the new capabilities.

Serverless computing doesn’t mean there are no servers. It means that developers no longer have to worry about the compute, storage and memory requirements because the cloud provider — in this case, AWS — takes care of it for them, freeing them up to just code the application instead of deploying resources.

Today’s announcement combined with support for support for the AVX2 instruction set, means that developers can use this approach with more sophisticated technologies like machine learning, gaming and even high performance computing.

One of the beauties of this approach is that in theory you can save money because you aren’t paying for resources you aren’t using. You are only paying each time the application requires a set of resources and no more. To make this an even bigger advantage, the company also announced, “Starting today, we are rounding up duration to the nearest millisecond with no minimum execution time,” the company announced in a blog post on the new pricing approach.

Finally the company also announced container image support for Lambda functions. “To help you with that, you can now package and deploy Lambda functions as container images of up to 10 GB in size. In this way, you can also easily build and deploy larger workloads that rely on sizable dependencies, such as machine learning or data intensive workloads,” the company wrote in a blog post announcing the new capability.

All of these announcements in combination mean that you can now use Lambda functions for more intensive operations than you could previously, and the new billing approach should lower your overall spending as you make that transition to the new capabilities.

AWS launched Lambda in 2015 and with it helped popularize serverless computing. You simply write code (event triggers) and AWS deals with whatever compute, memory and storage you need to make that work. Today at AWS re:Invent in Las Vegas, the company announced several new features to make it more developer friendly, while acknowledging that even while serverless reduced complexity, it still requires more sophisticated tools as it matures

It’s called serverless because you don’t have to worry about the underlying servers. The cloud vendors take care of all that for you, serving whatever resources you need to run your event and no more. It means you no longer have to worry about coding for all your infrastructure and you only pay for the computing you need at any given moment to make the application work.

The way AWS works is that it tends to release something, then builds more functionality on top of a base service as it sees increasing requirements as customers use it. As Amazon CTO Werner Vogels pointed out in his keynote on Thursday, developers debate about tools and everyone has their own idea of what tools they bring to the task every day.

For starters, they decided to please the language folks introducing support for new languages. Those developers who use Ruby can now use Ruby Support for AWS Lambda. “Now it’s possible to write Lambda functions as idiomatic Ruby code, and run them on AWS. The AWS SDK for Ruby is included in the Lambda execution environment by default,” Chris Munns from AWS wrote in a blog post introducing the new language support.

If C++ is your thing, AWS announced C++ Lambda Runtime. If neither of those match your programming language tastes, AWS opened it up for just about any language with the new Lambda Runtime API, which Danilo Poccia from AWS described in a blog post as “a simple interface to use any programming language, or a specific language version, for developing your functions.”

AWS didn’t want to stop with languages though. They also recognize that even though Lambda (and serverless in general) is designed to remove a level of complexity for developers, that doesn’t mean that all serverless applications consist of simple event triggers. As developers build more sophisticated serverless apps, they have to bring in system components and compose multiple pieces together, as Vogels explained in his keynote today.

To address this requirement, the company introduced Lambda Layers, which they describe as “a way to centrally manage code and data that is shared across multiple functions.” This could be custom code used by multiple functions or a way to share code used to simplify business logic.

As Lambda matures, developer requirements grow and these announcements and others are part of trying to meet those needs.

 Most companies today develop applications and deploy them on servers — whether on-premises or in the cloud. That means figuring out how much server, storage and database power they need ahead of time, and deploying all of the hardware and software it takes to run the application. Suppose you didn’t want to deal with all of that and were looking for a new model that handled all of… Read More

 Amazon Web Services announced a new service today called Lambda, a stateless event-driven compute service for dynamic applications that doesn’t require provisioning of any compute infrastructure. As AWS’s CTO Werner Vogels pointed out, this will enable programmers to reduce their overall development effort. You simply write the code and define the event triggers, and it will run… Read More