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.
So without further ado, here we go.
Java has been in service for decades and is, to this day, a reliable option when choosing the backbone of your stack. With AWS Lambda is no different as it makes a strong candidate for your functions.
Reliable and well-tested libraries. The libraries will make life easy for you through enhanced testability and maintainability of AWS Lambda tasks.
Predictive performance. While Java has slower spin uptime, you can easily predict the memory needs of your functions and to counteract those dreaded colds starts you can just up your memory allocation.
Tooling Support. Java has a wide range of tooling support which includes Eclipse, IntelliJ IDEA, Maven, and Gradle among others.
If you’re wondering how Java remains an efficient AWS lambda language, here is the answer. Java has unique characteristics like multi-thread concurrency, platform independence, security, and object-orientation.
I’m definitely biased but Node.js is probably the best one on this list. I know it has it’s downfalls but the overwhelming support that Node had in the past years has to have its merits.
Modules. As of now, there are 2257 plugins on npm tagged “aws-lambda” which help developers with their applications in a lot of different ways from running Lambda locally to keeping vital functions warm to (avoid cold-starts)[https://dashbird.io/blog/can-we-solve-serverless-cold-starts/].
Spinup times. Node.js has better spin-up times than C# or Java which make it a better option for client-facing applications that risk suffering from uneven traffic distribution.
Community. It’d be amiss if I didn’t mention this as one of the major draw-ins of Node. You can always count on its community support to find a solution to your problem.
Python applications are everywhere. From GUI-based desktops, web frameworks, operating systems, and enterprise applications. In the past few years, we’ve seen a lot of developers adopting Python and it seems like this trend is not stopping.
Unbelievable spin-up times. Python is without a doubt the absolute winner when it comes to spinning up containers. It’s about 100 times faster than Java or C#.
Third-party modules. Like npm, Python has a wide variety of modules available. The feature helps ease interaction with other languages and platforms.
Easy to learn and community support. If you are a beginner, programming languages can be daunting. However, Python has extensive readability and a supportive community to help in its application. The Pythonistas have uploaded over 150,000 support packages to help users.
Simplicity. With Python, you can avoid overcomplicating your architecture.
Read more about Python error handling.
Read more about Python error handling.
The introduction of GO language was a significant move forward for AWS Lambda. Although Go has its share of problems, it’s suitable for a serverless environment and the merits of Go are not to be ignored.
Dashbird is built by serverless developers with specifically AWS Lambda in mind
Go has a remarkable tenacity of 1.x. Unlike other languages like Java, C++, etc, Go has the highest tenacity. Such tenacity rate is a promise of a correct compilation of programs without constant alterations.
Go uses static binaries. It implies that the need for static linking is no more. Besides programming, AWS Lambda programs with Go would help with forward compatibility.
Go offers stability. Its unique tooling, language design, and ecosystem make this programming language stand out.
Net.Core language is definitely one of the popular guys in programming and it’s a welcomed addition to people already relying on AWS for running their .net applications.
NuGet Support. Just like all the other languages supported on Lambda, Net.Core gets module support via NuGet, which makes life for developers a lot easier.
Consistent performance. Net.Core has a more consistent performance result than Node.js or Python as a result of it’s less dynamic nature.
Faster execution Compared to Go, Net.Core has a faster execution time which is not something to be ignored.
If you’re an AWS customer, then you must be familiar with Ruby. Ruby programming language stands out as it reduces complexities for AWS Lambda users.
Third-party module support. The language has unique modules that allow the addition of new elements of class hierarchy at runtime. Strong and supportive community. Thus, it makes it easy to use.
Clean Code. It’s clean code significantly improves AWS Lambda performance.
At first glance performance in a similar and controlled environment, running the same kind of functions isn’t all that different, and until you get these to production you won’t be able to get a definitive conclusion.
Regardless, you’ll need to monitor your serverless setup. That’s where Dashbird comes in. Built by serverless developers with specifically serverless technologies and AWS Lambda in mind. So if you’re building your environments on AWS, Dashbird is here to make sure you’re running smoothly: save you hours..even days – on average, Dashbird users have seen their discovery time of an error reduce by 80% – on debugging, give you customized and actionable insights based on the AWS Well-Architected Framework to further improve your infrastructure, and provide a quick and easy to understand real-time overview of the health and performance of your serverless infrastructure.
You can give Dashbird a try for free:
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.
End-to-end observability and real-time error tracking for AWS applications.