Monitoring large scale serverless applications
You can find more resources and articles about serverless on our blog: https://dashbird.io/blog/
You can find more resources and articles about serverless on our blog: https://dashbird.io/blog/
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. Money makes the wold go round. Unfortunately, it is a necessity in almost all spheres of life. You can live without it or with lesser amounts of it, but it makes it all harder. If you wish to have it, first, you need to give it, as always. Even AWS Lambda is not free.
The world of cloud computing has been revolutionized by a solution called serverless computing. It has been an absolute joy for developers to use. Before this innovation, developers had to worry about the resources powering their code. Since the launch of serverless computing, the developer’s focus on operating-system and hardware architecture is now a thing of the past. It handles all the server management while focusing on what you do well — writing good quality code.
This article will cover how the health of your serverless application can be measured and improved. Technology and its implementation methodology evolve with time very rapidly. Cost efficiency and productivity are the key drivers of technological evolution these days. With the advent of the cloud, infrastructure costs have been brought down significantly. Serverless technology adds icing to the cake!
Serverless development has been turning heads in the market for quite some time now. But it has yet to be accepted by the majority in the development community. With AWS Lambda, Azure Functions, and IBM’s Open Whisk, the market is poised to take a different route in this field. Most of these organizations are spending a lot of money to make the market accept this new paradigm using serverless computing.
Being a developer is awesome. Writing code, solving problems, and thinking of ingenious solutions for complicated algorithms is what we live for. But, the grass is not always so green on this side of the fence. Sooner or later, you need to get your hands dirty and deploy the app you worked so hard on. Deployments are not always easy. To be blunt, they can be challenging and time-consuming. That’s what we’ll solve in this tutorial.