Open source components have become a basic building block in today’s software development process. It’s no surprise that 60%-80% of the codebase in 92% of modern applications is open source — they provide us with tried-and-true code that allows us to save time and focus on creating the secret sauce that will make our products the next great tech innovation.

Open-sourced by Google in 2014, Kubernetes is a container orchestrator. That means it enables users to deploy and manage apps distributed and deployed in containers. It takes care of scaling, self-healing, load-balancing, rolling updates, etc. The project is managed by the Cloud Native Computing Foundation (CNCF) along with multiple other open source projects, and you can find it here on GitHub.

The cloud native stack, also referred to as the new stack, is composed of the new cloud-independent counterparts of cloud managed services. As enterprises moved to the cloud, they started leveraging cloud managed services such as AWS’ DynamoDB or GCP’s BigQuery. Very convenient, these on-demand services significantly increased developer productivity. Being proprietary, they only work on that specific cloud, however — a significant drawback.

Kubernetes has become the de-facto solution for container orchestration. While it has, in some ways, simplified the management and deployment of your distributed applications and services, it has also introduced new levels of complexity. When maintaining a Kubernetes cluster, one must be mindful of all the different abstractions in its ecosystem and how the various pieces and layers interact with each other in order to avoid failed deployments, resource exhaustion, and application crashes.

Two malicious Python libraries, jeilyfish (with a capital i and a lowercase L in the original name) and python3-dateutil, were detected on PyPI (Python Package Index) on December 1st. They were typosquatting similar named legitimate libraries jellyfish (with a double lowercase L) and python-dateutil libraries, a malicious technique aiming to trick developers to use the similar named modified libraries.

Organizations are rapidly moving more and more mission-critical applications to Kubernetes (K8s) and the cloud to reduce costs, achieve faster deployment times, and improve operational efficiencies, but are struggling to achieve a strong security posture because of their inability to apply conventional security practices in the cloud environment. Commitment to cloud security grows, but security safeguards are not keeping up with the increased use of the various cloud platforms.

Single-node deployments of Kubernetes are more common than what one would expect. In some scenarios, single-node clusters make much more sense. For development purposes or testing, there’s no need to deploy a full-blown production-grade cluster. Single-node deployments are also handy for appliances and IoT applications since they have a much smaller footprint. Enter MicroK8s, a tool by Canonical that enables you to easily deploy a lightweight single-node cluster in your local environment.

If you have selected Gitlab as your git provider, you may automatically think about selecting GitlabCI as your CI/CD solution as well. Using the same vendor for source control and CI/CD might seem natural, but is not always the best combination. In fact, choosing a “good-enough” option just because it is part of the same solution is unwise in the long run if it doesn’t cover your needs.

Big data, AI, machine learning, and numerous others are all buzzwords we seem to throw around lightly in recent years. Even though they are hugely different from one another, they all have one thing in common. Data! Huge amounts of data that need to be managed. The downside of that is that the more data you have the more of a headache it is to store, query, and make sense of.

Kubernetes 1.17 is about to be released! This short-cycle release is focused on small improvements and house cleaning. There are implementation optimizations all over the place, new features like the promising topology aware routing, and improvements to the dual-stack support. Here is the list of what’s new in Kubernetes 1.17.