Kubernetes orchestrates the management of containerized applications, with an emphasis on declarative configuration. A DevOps engineer creates deployment files specifying how to spin up a Kubernetes cluster, which establishes a blueprint for how containers should handle the application workloads.

After a span of 5 long years, we've bid farewell to Cycle's old portal. Our engineering team has been working tirelessly over the last 10 months to bring a fresh, new interface to the platform for our users. This new design encapsulates the wealth of insights we've gained during this period. Just last week, we took the decisive step of launching it into production, and the initial feedback has been overwhelmingly positive.

Microservices architecture has become increasingly popular in modern software development due to its scalability, resilience, and flexibility. However, with the benefits of microservices come the challenges of debugging and monitoring these distributed systems. Using the Istio service mesh, OpenTelemetry distributed tracing, and Apica’s Kubernetes-native observability platform, developers can easily collect and visualize performance data in real-time to identify and fix issues quickly.

Why you should monitor Kubernetes in SCOM Kubernetes is one of the most prominent container orchestration platforms available today. As cloud-native and container solutions gain attention, so does Kubernetes. With the new incline towards cloud-native application development, there is a big focus on software development and how to migrate to the cloud. What cannot be forgotten is what needs to be taken care of once the applications are up and running – monitoring.

Cloud deployments and containerization let you provision infrastructure as needed, meaning your applications can grow in scope and complexity. The results can be impressive, but the ability to expand quickly and easily makes it harder to keep track of your system as it develops. In this type of Kubernetes deployment, it’s essential to track your containers to understand what they’re doing.

Kubernetes, the de-facto standard for container orchestration, supports two deployment options: imperative and declarative. Because they are more conducive to automation, declarative deployments are typically considered better than imperative. A declarative paradigm involves: The issue with the declarative approach is that YAML manifest files are static.

A paradigm-shifting concept has emerged in the dynamic and ever-evolving world of modern software development — Environment as a Service (EaaS). This innovative approach has swiftly become a cornerstone of streamlined development processes, offering developers the means to effortlessly provision, manage, and collaborate within diverse software environments.

Kubernetes serves as a robust tool for managing and orchestrating applications across multiple computers. These computers are referred to as 'nodes.' Picture nodes as fundamental units in the ecosystem of your applications. Every node possesses its own computing resources, encompassing memory, processing capabilities, and storage capacity. Your apps are hosted and run by nodes. They give your apps the room and resources they need to work.

Welcome to the world of Kubernetes - a powerful container orchestration platform. Before we dive deep into the concepts of Kubernetes, let's grasp the concept of containers - a lightweight, and isolated units that package applications along with their dependencies, ensuring seamless deployment and portability. In this blog, you will witness Kubernetes incredible abilities. It can handle the ups and downs of your applications, ensuring they scale seamlessly, even when facing tough challenges.

As Kubernetes continues its ascent as a leading container orchestration platform, it's common for users to encounter a perplexing choice between two prominent workload controllers: StatefulSets and Deployments. Despite both controllers being instrumental in managing high-availability workloads, they diverge significantly in terms of features and use cases. Grasping these distinctions is pivotal for fine-tuning the performance and scalability of your Kubernetes infrastructure.