No matter how careful developers are or how comprehensive tests are applied before deployment, there will always be some level of issues to deal with in production. When it comes to managing issues and ensuring application quality, two main metrics should be on our radar: time to discover and time to resolve issues.

Azure Functions has recently released its new version “Azure Functions 3.0” and it is generally available now. This blog is all about the upgraded version and how far it is scaled up from the previous versions. Any business architecture will involve Azure Functions, this need provokes the necessity of upgradation in such resources.

As a team that does pure serverless, we place a lot of emphasis on fast deployments. Lately, though, as our codebase has gotten larger, and the number of interactions between the microservices has increased, we have come up against the classic problem of excessively long test execution times in our serverless continuous integration.

At this moment, billions of people are rushing to the internet for work, entertainment, shopping - everything, really. It’s great that we developed this virtual world and can keep the lights on, despite what’s happening outside. On the other hand, cloud systems and developers are under pressure to meet an unparalleled demand. At Dashbird, we have always thought developers deserve the most efficient tools to discover and resolve issues in order to keep cloud apps running smoothly.

The experts from Azure Functions team has yet again joined us for the monthly webcast. Given the unprecedented time, this webcast happened a bit unusual where the folks joined from their home rather from Channel 9 studio and which made this webcast even more unique and exciting. In this session, Jeff Hollan, Eduardo and Alex Karcher have joined to give us the picture of the latest happenings in the Azure Functions space.

Unit tests and integration tests are vitally important, but sometimes even those aren’t sufficient to ensure that critical services in your application will function smoothly in production. In those cases, adding a staging step to our CI/CD process allows us to test a feature with real data in a less supervised environment. For example, here at Lumigo we decided to use it for our Node.js tracer.