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Serverless is a quickly-maturing technology and, if you’ve followed its evolution over the past several years, you’ve likely seen a host of great (and not-so-great) documentation of its technology and practices. Now that serverless is a much more mainstream topic for reputable outfits to report on, it’s become easier to comb through serverless fact and fiction in the media.

This blog focuses on implementing the Dependency Injection design pattern to the Azure Functions. For a better understanding of Dependency Injection and Azure Function, Let’s take a simple Cab booking validation scenario, in which there will be a Function app implemented with the Dependency Injection that validates the user email Id that is valid or not. Before diving into the orchestration, let us know what the Dependency Injection is.

In the second of our new series of posts, Yan Cui highlights the key insights from the Amazon Builders’ Library article, Using load shedding to avoid overload, by AWS Principal Engineer (AWS Lambda) David Yanacek.

This blog will brief on Azure Logic App Triggers. Let us see a short introduction of what a Logic App is and how does it work before getting deep into Logic App Triggers.

Serverless can bring opportunities by making DevOps more accessible to folks new to the industry. It can also bring opportunities to folks already in the industry that want to spend more time focusing on adding business value. But many technologists, seasoned or otherwise, hear a lot about serverless but don’t always know how to get started.

In the first article in our new series, Yan Cui highlights the key insights from the Amazon Builders’ Library article, Timeouts, retries and backoff with jitter, by AWS Senior Principal Engineer Marc Brooker.

There are scenarios where we want to de-couple logic across multiple logic apps. Generally, this is a straight forward endeavor, unless the downstream logic app has a long-running process. When this does occur, the client (or publisher) will experience an HTTP timeout if the request takes more than 2 minutes. This scenario is captured within the Azure Logic Apps documentation.

Among the many, MANY announcements at re:Invent this year is one that settles a years-long debate or concern amongst people considering using AWS Lambda to build serverless applications: cold starts. AWS Lambda is now 5 years old. For all of that time, there’s been a concern about latency the first time a function is called. Well, fret no more: with Provisioned Concurrency you can pay a tiny fee to know Lambda functions are always available.

This blog focuses on Dashboard capabilities in Serverless360 and its use cases. Let us take a simple cab booking application scenario to have a better understanding of the Composite Application Dashboard.

When we introduced Secondary Storage two years ago, it was a deliberate compromise between economy and performance. Compared to Honeycomb’s primary NVMe storage attached to dedicated servers, secondary storage let customers keep more data for less money. They could query over longer time ranges, but with a substantial performance penalty; queries which used secondary storage took many times longer to run than those which didn’t.