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Implementing Cypress Testing into a Codefresh Pipeline Cypress.iois a next generation front end testing tool built for the modern web. It is utilized by developers or QA engineers building web applications using modern JavaScript frameworks. They are an extremely robust end-to-end testing platform, and are very extensible. Cypress can test anything that runs in a browser. This makes it a very powerful tool, and perfect to implement into a CI/CD pipeline. For this we’ll need an application to work with.

Have you ever been tasked with pipelining out an existing application in a new tool? This can be a long and daunting task. Especially if your application is multi-service, and mono-repo. I’m not going to get into all of hows and whys of multi-repo vs mono-repo today, but there is always a use case or operational model for each. One of the biggest issues I have run into with multi-serivce mono-repo apps is getting the container builds to work the first time.

So far we've covered infrastructure, the serverless shop, and CICD. But how do you know what's going on in your code and your infrastructure? That's where observability comes into the picture. We'll dive into using Wavefront to see what's going on.

Building the infrastructure to run the ACME Serverless Fitness Shop is just as important as the shop itself. With Infrastructure as Code, you can program your cloud environment whether they're containers, VMs, or functions.

In part one of the series on the ACME Serverless Fitness Shop, we've gone over the tools and technologies. Now, it's time to dive into the depths. Let's check out how CircleCI plays an important role in the lifecycle of the shop and how continuous verification works in serverless apps!

As more and more applications convert to cloud native with Kubernetes as a normalizing layer the ability to have portability between public clouds also becomes easier. Theoretically, the app can now move easily between AWS/Azure/GCP. However, a couple of issues are always in the back of developer’s minds:  Do I connect to cloud services like ML/AI, DevOps tool chains, DBs, Storage, etc? This might lock me in. Should I roll my own database or use a cloud services like CosmosDB, Azure Postgres DB, etc.

Deploying applications into the cloud is the norm. Majority of these applications are landing on AWS, GCP or Azure. In addition, more and more of these applications are also using containers and utilizing Kubernetes. Kubernetes is becoming more mainstream and the “mainstay” in many organizations. Adoption is growing, as are the number of options for Kubernetes and multiple methods to help build and manage them. There are many Kubernetes choices to deploy your containerized application:

What choices do you need to think about when moving to serverless? How can you use Continuous Verification with serverless? We'll dive into that and more in our series on building the ACME Serverless Fitness Shop. First up, choosing the tools and technology.

Microservices and serverless give us as developers an incredible amount of freedom. We can choose our language and we can decide where and when to deploy our service. One of the biggest challenges, though, is figuring out how things go wrong and how to fix it.

Thinking of leveraging both k8s and serverless functions? This blog provides details on how to do it on Azure.