DevOps

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:

Whether you're building apps or baking cheesecake, trusting the ingredients you work with and making sure you have a transparent process to get them into your final product is one of the most important things.

This post examines how to manage application budget and security with Cloudbees

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.

This post examines a pipeline developed to demonstrate the concept of Continuous Verification in detail