Monitoring platform for keeping systems up and running at all times.
Full stack visibility across the entire stack.
Detect and resolve any incident in record time.
Conform to industry best practices.
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.
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.
Node.js is undoubtedly the most widely used, with Java8 and Python following behind.
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.
Let’s look at the functions and how they perform now.
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.
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!
Today we are announcing a new, updated pricing model and the end of free tier for Dashbird.
In this article, we’re covering 4 tips for AWS Lambda optimization for production. Covering error handling, memory provisioning, monitoring, performance, and more.
In this article we’ll go through the ins and outs of AWS Lambda pricing model, how it works, what additional charges you might be looking at and what’s in the fine print.
Dashbird was born out of our own need for an enhanced serverless debugging and monitoring tool, and we take pride in being developers.
Dashbird gives us a simple and easy to use tool to have peace of mind and know that all of our Serverless functions are running correctly. We are instantly aware now if there’s a problem. We love the fact that we have enough information in the Slack notification itself to take appropriate action immediately and know exactly where the issue occurred.
Thanks to Dashbird the time to discover the occurrence of an issue reduced from 2-4 hours to a matter of seconds or minutes. It also means that 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.
I mean, it is just extremely time-saving. It’s so efficient! I don’t think it’s an exaggeration or dramatic to say that Dashbird has been a lifesaver for us.
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.