When moving from a monolith to a distributed system, tracing and debugging can get really hard. Luckily, there are some things you can do to make it easier.
Self-service API management is crucial because it empowers API consumers to design their own API proxy endpoints—but a pattern is key to its successful implementation.
Real-time test management tools help aid effective collaboration among Agile team members—which is vital for prioritizing bugs in a risk-based software testing approach.
If compliance and security are a concern, you can set up Cassandra clusters with encryption in mind using SSL while ensuring nodes can still communicate with each other.
Creating an Octopus step template to create and push a Docker image to DockerHub is a good way to move from a VM to Containers while keeping the current infrastructure.
This in-depth look at how to Spring Boot Docker images to the Amazon EC2 Container Registry provides a good example of Spring, Java, the cloud, and container usage.
Failing fast isn't unique to DevOps but it's an incredibly important strategy. Practicing failures and mitigating resulting issues is a standard function of DevOps teams.
It's tempting to provision more memory to your VM than you need, but that can cause headaches—and containers might make it worse. The answer lies in auto-scaling.
Microservies and Docker have become the peanut butter and jelly of modern app delivery. They allow organizations to work in a consistent, isolated runtime environment.
Docker Swarm makes it relatively easy to scale apps. With the help of Terraform and Packer, you can set up scaling for an app using cloud-native infrastructure.
DevOps one-stop shop solutions can slow you down over time. Tools that equal a stage to an environment deployment miss out on the real power of deployment pipelines.
Sibanjan Das offers up a tutorial for building a web-based cluster and prediction analysis application through using R with the open source Shiny framework. Oh yeah, and he embedded the app directly into this DZone article... shine on you crazy data scientist.
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