Articles

The goal for a successful continuous delivery process is to minimize the time it takes for development teams to go from idea to usable software by practicing agile techniques and automating the entire software delivery system: build, deploy, test, release. This Refcard explains detailed patterns and anti-patterns for core areas of CD, including the delivery and deployment phases, rollbacks, pipeline observability and monitoring, documentation, as well as communication across teams and within the organization.
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Misconfigurations are the leading cause behind security incidents in Kubernetes-orchestrated or otherwise containerized environments. Without proper configuration in place, applications would run into problems ranging from noncompliance and inconsistencies to performance bottlenecks, security vulnerabilities, and functionality failure. Therefore, configuration management is a critical component in a software development lifecycle for maintaining systems in a desired, consistent state.

According to Red Hat’s State of Kubernetes Security report, misconfigurations were the leading cause behind security incidents in Kubernetes-orchestrated or otherwise containerized environments. Without proper configuration in place, applications would run into problems ranging from noncompliance and inconsistencies to performance bottlenecks, security vulnerabilities, and functionality failure. This would make cloud-native systems unstable and cause them to become a liability to businesses. For this reason, configuration management is a critical component in a software development lifecycle for maintaining systems in a desired, consistent state. However, the way configuration management is done has been evolving over the years. This post traces the history of configuration management, focusing on how GitOps handles this critical aspect of running cloud-native applications today.

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Stream-Aligned and Platform Teams

The 2021 State of DevOps report identifies two types of teams as the way high-maturity teams organize themselves: stream-aligned teams and platform teams. The idea of a « platform » or « internal developer platform » is fundamental to GitOps. While a GitOps pipeline begins with committing code to a Git repository, it is made possible by a platform that paves the way for that new code to move in an automated way from the repository to a production environment.

The platform is how the Ops team provisions resources such as cloud services, storage, service meshes, and security and monitoring tools in a ready-made template. These templates are created even before they are needed and made available to any developer within the organization. The big shift due to this is that developers need not raise a ticket for the resources they need: they can pick a ready-made template and deploy their code in a matter of minutes. From the Ops side, they have peace of mind knowing they have configured this template and that it follows security protocol by default. It does not require developers to separately configure security for deployments.

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It’s that time of year again when we get the Red Hat Summit 2022 call for papers!

This year seemed to be a perfect time to go all in with sessions around our architectures based on a series of talks we’ve designed to showcase the various aspects we cover. Some are vertical aligned and others are just customer domains, but all of them include extensive research into how to implement successful architectures at scale.

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Our profession evolves every year, whether through the introduction of a new tool, a new cloud service, or a new working method. This constant evolution requires the establishment of a learning culture to continuously share experiences and ideas, thus encouraging everyone to gain new knowledge each year.

Obviously, this demands a portion of our working time and an online library of training resources maintained by entities with authority in the domain. These entities are responsible for updating the content to allow us to continuously improve our skills, sometimes to advance in our career in order to aim for an internal or external evolution. Therefore, relying on trusted education partners is important to ensure the highest-quality learning content.

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article imageIn our previous article from this series we talked about the example predictive analysis architecture found in an edge medical diagnosis solution for the healthcare industry.

The process was laid out how we approached the use case and how portfolio solutions are the base for researching a generic architecture. It continued by discussion how we approached the use case by researching successful customer portfolio solutions as the basis for a generic architecture.

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Today’s world regards time as of paramount importance. This said, the disruptive tech-enabled innovations are foremost meant to save both business owners’ and users’ time. The industry of software development is based upon the same postulates – the sooner the better, provided that timely product deliverables are coupled with efficiency and convenience.

The Continuous Integration (CI) and Continuous Delivery (CD) practices are among popular software engineering industry trends that help cut costs, time, and risks associated with delivering changes. Yet another trend to optimize the industry lies in applying DevOps methods, oriented to increase the efficiency of development and operation processes, and to speed up product delivery.

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Set Up Kubernetes Cluster

First, we need a Kubernetes cluster. You may use an existing one or set up a new one. For this tutorial, we chose to use GKE (Google Kubernetes Engine).

Just follow the quick start to create a cluster. To save your money, the default pool with only one node is sufficient for our testing. For node image type, use the default Container-Optimized OS; for machine type, please select one with at least 8G mem. After creating the cluster, go ahead to configure kubectl to connect to the cluster following this guide.

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In part one of this series on Best Practices for Building and Designing Containers for Kubernetes, we looked at how to separate config from code in Kubernetes and why you need to do that. Specifically, we examined how config maps and environment variables are defined and configured. In this post, we continue that important discussion with a look at secrets management, what secrets are, and how you manage them.

Managing Public Configuration Information in Kubernetes

Not all configuration information is safe to keep out in the “public” and many, if not most, Kubernetes-hosted workloads need usernames/passwords, tokens, keys or other private information to securely connect to other services. There are a variety of options worth exploring here, each with its own set of positives and negatives.

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