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State of Lambda Functions in 2020 by Dashbird


2020 – what a ride it’s been! The state of the world this year has definitely been unpredictable and ever more surprising. So for some interesting insights and stability, we’ve turned to Lambdas. Namely, the state of Lambda functions in 2020! 


Ever wondered how others look without their face masks on? At Dashbird, we get to (metaphorically speaking) see what everyone looks like behind their serverless masks (read: stacks), and identify trends and patterns. Our platform gives us the ability to look at the state of Lambda. Sharing is caring and we’re happy to share these insights with you, offering the chance to compare and contrast your Lambda functions to others, or just have a nose around. 


For reference, here’s our article on the state of Lambda functions in 2019.


What’s a “normal” amount of Lambda functions? 

As we know, there is no “normal” but we see an average of 147 Lambda functions per client in total. A slight increase from our 2019 figures of 123 functions. 

average number of Lambda functions

What about their runtimes? 

Node.js is undoubtedly the most widely used, with Java8 and Python following behind. 


Lambda runtimes usage


And, what’s the regional spread? 

There’s no change here as us-east-1 and eu-west-1 remain the most popular, but it’s great to know that over half of Dashbird accounts use more than one region. 


AWS Lambda Regions


Digging into the Functions 

Let’s look at the functions and how they perform now. 


Average code size


Average memory size


Average timeouts


We can see that Java leads in all of these areas, which makes sense given its nature of a lengthier startup but also its smooth running once set up. 


X-Ray is being used with 16% of the functions on average

X-Ray usage


So, how did you compare? What we can say is, everyone has a nose and a mouth under their mask – they often just look and feel a bit different from yours!

Made by Developers for Developers

Our history and present are deeply rooted in building large-scale cloud applications on state-of-the-art technology. Dashbird was born out of our own need for an enhanced serverless debugging and monitoring tool, and we take pride in being developers.

10,000+ developers trust Dashbird

Dashbird helped us reduce the time to discovery from 2-4 hours to a matter of seconds. This means we’re saving dozens of hours in developer time, which not only can be funneled into improving the product but also means hundreds of dollars are saved every month.

Great onboarding: it takes just a couple of minutes to connect an AWS account to an organization in Dashbird. The UI is clean and gives a good overview of what is happening with the Lambdas and API Gateways in the account.

Dashbird provides an easier interface to monitor and debug problems with our Lambdas. Relevant logs are simple to find and view. Dashbird’s support has been good, and they take product suggestions with grace.

Great UI. Easy to navigate through CloudWatch logs. Simple setup.

Dashbird helped us refine the size of our Lambdas, resulting in significantly reduced costs. We have Dashbird alert us in seconds via email when any of our functions behaves abnormally. Their app immediately makes the cause and severity of errors obvious.

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