Kubernetes (K8s) is an open-source container orchestration platform which automates the deployment, scaling and management of containerized applications.
Its creation can be traced back to Google’s internal container orchestration system, called Borg.In 2014, Google open-sourced a version of Borg which is called Kubernetes.
A kubernetes cluster is a set of machines, called nodes, that are used to run containerized applications. There are 2 core pieces in a kubernetes cluster: The first is the control plane which is responsible for managing the state of the cluster. The second is the set of worker nodes. This nodes run the containerized application workload. The containerized application runs in a pod, which are the smallest deployments units in kubernetes which hosts one or more containers.
Container adoption and the widespread use of Kubernetes have become mainstream, experiencing global growth, especially within large organizations. According to SlashData, there are currently 6 million developers globally utilizing Kubernetes, constituting 35% of all backend developers.
Kubernetes Latest Releases & Highlights
Kubernetes releases currently happen approximately three times per year.
The release process can be thought of as having three main phases:
- Enhancement Definition
Kubernetes v1.27: Chill Vibes (On April 2023)
This release encompasses a total of 60 enhancements, with 18 of them progressing to the Alpha stage, 29 advancing to Beta, and 13 achieving Stable status.
The primary focus of this release includes a strategic move to freeze the ‘k8s.gcr.io’ image registry, replacing it with the now widely available ‘registry.k8s.io,’ a change that has been in effect for several months.
A significant milestone in this release is the graduation of Mutable Scheduling Directives for Jobs to GA. This advancement empowers the modification of a Job’s scheduling directives before its initiation, providing custom queue controllers the capability to influence pod placement. Simultaneously, the actual pod-to-node assignment is delegated to kube-scheduler.
Another noteworthy development is the stabilization of DownwardAPIHugePages, marking its transition to a stable state. Additionally, the introduction of Pod Scheduling Readiness, now in beta, ensures that upon creation, pods are immediately ready for scheduling. The Kubernetes scheduler diligently identifies nodes to accommodate all pending Pods, enhancing overall scheduling efficiency.
Furthermore, the release includes the beta rollout of Node Log Access via Kubernetes, a feature designed to assist cluster administrators in debugging issues with services on nodes. This functionality enables administrators to query service logs, streamlining the troubleshooting process. Overall, these enhancements collectively contribute to the continued evolution and improvement of the Kubernetes platform.
Kubernetes v1.28: A New (alpha) Mechanism For Safer Cluster Upgrades
In Kubernetes version 1.28, a notable alpha feature is introduced—the mixed version proxy. This functionality allows an HTTP request for a resource to be directed to the appropriate API server, particularly in situations where a cluster encompasses multiple API servers operating at different versions. This becomes particularly useful during a cluster upgrade or when implementing runtime configuration changes to the cluster’s control plane.
During a cluster upgrade, the existing ‘kube-apiservers’ may operate at diverse versions, each potentially serving different sets of built-in resources (groups, versions, and resources). In such a scenario, a resource request might be handled by any of the available API servers, potentially leading to the request reaching an API server that lacks awareness of the requested resource. This mismatch could result in an incorrect 404 not found error.
Moreover, the improper handling of 404 errors could have significant consequences, such as the incorrect blocking of namespace deletion or the inadvertent garbage collection of objects. Therefore, the introduction of the mixed version proxy in Kubernetes 1.28 addresses these challenges by ensuring that resource requests are appropriately directed, mitigating the risk of errors and potential adverse outcomes during cluster upgrades or control plane configuration adjustments.
In response to ongoing DevOps trends, Kubernetes services is proactively embracing innovations to remain at the forefront. As organizations persist in modernizing their IT infrastructure and embracing cloud-based services, Kubernetes stands out as a potent tool for implementing DevOps strategies in numerous upcoming workloads. Companies offering kubernetes consulting services will therefore lead this transition phase.
Microservices are small, independent services that work together to form a larger application. These services are easier to develop, deploy, and scale independently, which makes them an ideal workload for DevOps strategies. Kubernetes are designed and built this way.
Serverless computing allows organizations to run code without managing servers. This workload can be used for functions triggered by events, such as processing user data or handling real-time data streams.
Artificial Intelligence and Machine Learning & Block chain technology:
AI and ML workloads require continuous integration and deployment to improve accuracy and reduce error rates. Kubernetes strategies can help organizations automate the process of training and deploying models.
Blockchain technology can be used to create more secure and transparent DevOps workflows, reducing the risk of errors and security breaches.
Internet of Things (IoT):
IoT devices generate a vast amount of data, which needs to be processed and analyzed in real time. Kubernetes strategies can help organizations deploy and manage the software that runs on IoT devices and the infrastructure that processes the data.
Cloud-native applications are designed to run on cloud infrastructure, taking full advantage of their scalability and availability features. Kubernetes can help organizations deploy these applications in a scalable and reliable way with minimal downtime.
In conclusion, being a Kubernetes consulting company or adopting Kubernetes(DevOps) in organizations can significantly streamline the deployment process and reduce errors through continuous integration and delivery, automated testing, and infrastructure as code which helps to increase development speed and reduce employee workload stress.