4 Techniques Serverless Platforms Use to Balance Performance and Cost

In my recent post on InfoQ, I discuss the techniques that serverless platforms use “under the hood” to balance performance and cost.

Serverless computing is for many the logical next step in cloud computing, moving applications to a set of higher-level abstractions and offloading more of the low-level operational work to the cloud provider (regardless of whether that is a public one or an internal infrastructure team). It promises reliable performance on-demand while directly linking the pricing to the resources used.

Being active as both a researcher and software engineer in the serverless computing domain, my aim is to give you an idea of what is going on under the covers of the current state-of-the-art serverless platforms—especially with regards to performance and its impact on cost, and how you can influence these tradeoffs.

Read the full article on InfoQ to learn:

The cost and performance models are two of the key drivers of the popularity of serverless and Function-as-a-Service (FaaS).
Cold starts have gone down a lot, from multiple seconds to 100s of milliseconds, but there is still much space for improvement.
There are various techniques that are being used to improve the performance of serverless functions, most of which focus on reducing or avoiding cold starts.
These optimizations are not free; it is a trade-off between performance and cost, which depends on the requirements of your application.
Currently, closed-source serverless services offered by public clouds offer few options for users to influence these trade-offs. Open-source FaaS frameworks that can run anywhere (such as Fission) offer full flexibility to tweak these performance/cost tradeoffs.
Serverless computing is not just about paying for the resources that you use; it is about only paying for the performance you actually need.

Erwin van Eyk

Erwin works at the intersection between industry and academia. As a software engineer at Platform9, he contributes to Fission: an open-source, Kubernetes-native, Serverless platform. At the same time, he is a researcher investigating “Function Scheduling and Composition in FaaS Deployments” in the International Research Team @large at the Delft University of Technology. As a part of this, he leads the industry and academia combined serverless research effort at the SPEC Cloud Research Group.