Operations | Monitoring | ITSM | DevOps | Cloud

The combination of SNS to SQS to Lambda is a common sight in serverless applications on AWS. Perhaps triggered by messages from an API function. This architecture is great for improving UX by offloading slow, asynchronous tasks so the API can stay responsive. It presents an interesting challenge for observability, however. Because observability tools are not able to trace invocations through this combination end-to-end. In X-Ray, for example, the trace would stop at SNS.

Over the last few years, Microsoft has built excellent tooling around different technologies. Today, everything is available and achievable through the Azure Portal, which helps manage complex solutions. However, this brings in challenges when it comes to managing the distributed resources. The struggle to keep track of messages or know the flow of messages through these distributed resources is growing day by day.

There are numerous types of services and processes in place to make software development more accessible and efficient for programmers. One ready-for-launch service developers can access remotely is Function as a Service, abbreviated as (FaaS).

Serverless backends have different monitoring challenges when compared with traditional applications, mostly due to the distributed and proprietary nature of serverless. Making monitoring and debugging efficient for serverless requires a unique set of tools and techniques. In this article, we’ll discuss the challenges of debugging serverless backends and how to utilize third party tools to improve the monitoring process.

When you build a cloud-based application, you can choose to deploy the resources using the GUI (Graphical User Interface) or CLI (Command Line Interface) provided by the cloud provider. This approach can work well with just a handful of resources, but as the complexity of your application increases, it can become difficult to manage the infrastructure manually.

Serverless technologies let us do more with less effort, time and energy. They let us focus on creating user value and let the cloud handle undifferentiated heavy-lifting like scaling and securing the underlying infrastructure that runs our code. Serverless technologies have allowed me to accomplish tasks as a solo engineer that used to take a whole team of engineers to accomplish, and I’m able to complete these tasks in a fraction of the time and cost to my customers.

In my previous post, I explained How to retrieve Azure Key Vault Secrets using Azure Functions, where you can understand Key Vault URL and the Secret name to retrieve a secret generically, you could use it inside all your Logic App Standard workflows, whether they use the same Key Vault resource or different ones.

This is the second post in a 2 part blog series on debugging, monitoring and tracing NodeJS Lambda applications. If you haven’t yet seen part 1, check it out here (it’s a great read!) Now let’s get back into our post with one of the most commonly experienced issues when it comes to Lambda functions, Cold Starts.