About 90% of all Lambda functions monitored by Dashbird on AWS Lambda are running Nodejs and Python runtimes. Is this purely a reflection of the general popularity of these programming languages?

Lumigo’s System Map is a real-time visualization of your entire application. A bird’s eye view of the whole stack with filters that allow you to drill down into a subset of your infrastructure. Our systems have grown exponentially both in scale and complexity. AWS takes care of scaling automatically, ensuring your application will scale gracefully regardless of the programming language, load, or location.

Microsoft Azure has been growing rapidly from the past couple of years and many new advancements have been done to increase the productivity of the users. Microsoft has also been constantly working on different monitoring capabilities to keep the users well informed about the status and availability of their resources. One such resource is the Azure service health which notifies the user about the availability and health status of each resource in different Azure regions.

Since launching in 2014, AWS Lambda has dramatically grown in popularity. Lambda allows you to run code 7without having to manage the underlying compute resources. From a monitoring standpoint, you no longer have the need or ability to observe traditional performance metrics like CPU and memory. That doesn't mean you don't need to keep an eye on other things, though. So what metrics should you monitor for your Lambda functions?

Lumigo’s Transaction Timeline lets you see in a glance the flow of a transaction across its components and the latency caused by each, allowing you to easily identify bottlenecks and issues. Distributed tracing is a popular method for monitoring and profiling transactions in a microservices architecture. It’s what developers use to pinpoint failures, performance drops and other problems.

In the fast-moving and demanding world of software development, it is critical for organizations to utilize solutions that help streamline server setup in a scalable and affordable manner. Serverless computing solutions were developed in response to these requirements.

From the development and operations side, launching a new software application can be quite challenging. Deciding which tools to use, how to organize the task pipeline, managing collaboration among team members, monitoring performance and potential issues after launch, etc. It’s not easy to get it done right. Dashbird recently went through all of this. Behind the scenes, our amazing development team worked really hard to overcome all challenges and deliver the best value to our users.

Custom Handler is a feature in Azure Functions which lets you bring your own command, script, or executable, and hook it up to Azure Functions Triggers and Bindings. Custom Handler implements a lightweight Web Server. In other words, you can write your own APIs, in any language i.e. it need not be a language supported by Azure functions. You can just hook up your Azure function host with your custom API and let your function act as a proxy.

Lumigo’s Auto-Tracing allows you to implement distributed tracing on your Lambda functions with 3-clicks and no manual code changes. If you’ve already decided to move to a serverless infrastructure, you probably understand the importance of monitoring your AWS Lambdas and what it might entail. For the few out there that are still wondering what monitoring AWS Lambda means, I’ll break it down for you in a couple of steps.