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Serverless is arguably the next big thing after blockchain and one of the major players in this field is, of course – AWS Lambda. In essence, it allows you to run your code without provisioning or managing any servers. You only pay for when your code is actually running.
You can run code for any type of application or backend service you can think of, and do it with zero infrastructure administration. Sounds like something you want to know more about? To get started, these are the basic terms you should know:
A lambda function is a group of related statements that perform a specific task in your application. It consists of code and any dependencies that are associated with it. Each lambda function has its associated configuration information (name, description, entry point, and resource requirements).
The main benefit of using lambda functions is that as your application grows larger, it breaks your application into small modular chunks which makes it more organized and manageable in the long run.
Along with lambda functions, event sources are the core components of AWS Lambda. Event source is an entity that publishes events, and a lambda function is a custom code that processes the events. An event source can be an AWS service or developer-created application that produces events that trigger a function to run. Check out AWS Lambda supported event sources here.
Essentially, an invocation is called up to execute a specific lambda function. These are triggers for the code of the function to start running. Invocations can be either synchronous or asynchronous.
Event source mapping is a configuration of AWS services in which an event source is tied to a specific lambda function. It enables automatic invocation of a lambda function when specific events occur.
When you create a lambda function, you can specify configuration information, such as the amount of memory and maximum execution time that you allow for your function. When that function is invoked, AWS Lambda launches an Execution Context based on the configuration settings you have provided.
A cold start happens when a lambda function is invoked after not being used for an extended period of time and it results in increased invocation latency. Since this can potentially negatively affect the end-user experience with your application, this topic has been covered a lot lately.
Is there something crucial we missed? Let us know in the comments section!
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.