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Java, being the oldest and most popular programming language in the world (according to TIOBE Index) has some advantages and disadvantages for using AWS Lambda. One of the biggest problems being slow cold starts, yet it often outperforms other languages in consecutive executions (depending, of course, on what task is performed).
As with any piece of code, it’s important to handle possible failures and to ensure that you get alerted as soon as problems occur. We’re going to go through common failures of Java based AWS Lambda functions and how to handle them with Dashbird.
First off, let’s go through the common failure types that we should acknowledge.
Since java applications must be compiled before they can be deployed to AWS, they are immune to a parsing errors happening during their executions – these get picked up while building the standalone jar file. This means you have one less thing to worry about.
An exception is a problem that arises during the execution of a program. When an Exception occurs the normal flow of the program is disrupted and the program/Application terminates abnormally, which is not recommended, therefore, these exceptions are to be handled.
Exceptions can be caused either user error, programmer error or by physical resources that have failed. Following are some scenarios where an exception occurs.
Unchecked exeptions
Exception in thread "main" java.lang.ArrayIndexOutOfBoundsException: 5 at Exceptions.Unchecked_Demo.main(Unchecked_Demo.java:8)Except
Apart from Java specific errors, programmers have to think about failures that are specific to Lambda functions. In Runtime-agnostic Best Practices we have covered most of the problems that cause headaches to serverless developers.
We aim to improve Dashbird every day and user feedback is extremely important for that, so please let us know if you have any feedback about our features and error handling! We would really appreciate it!
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Dashbird is a monitoring, debugging and intelligence platform designed to help serverless developers build, operate, improve, and scale their modern cloud applications on AWS environment securely and with ease.
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.