10 Not-So-Well-Known Kubernetes Features Indian DevOps Teams Must Master In 2025

Kubernetes Features for Indian DevOps Teams to Master in 2025

India's thriving tech industry has seen a considerable push towards embracing DevOps practices, and Kubernetes has emerged as a critical element in this journey. This container orchestration system offers a plethora of features intended to streamline the deployment, scaling, and management of containerized applications. To stay ahead of the curve, Indian DevOps teams must not only be aware of the most popular Kubernetes features but also delve into the less-known, yet equally beneficial ones.

1. Topology-Aware Horizontal Pod Autoscaling (HPA)

Traditionally, horizontal pod autoscaling in Kubernetes scales horizontally based on CPU utilization and the number of desired replicas. However, topology-aware HPA takes this to the next level by considering the underlying hardware topology of the system. This feature enhances performance by ensuring that pods are created and scaled on nodes with optimal resources and hardware characteristics, improving overall system efficiency.

2. ForEach Loop for Dependent Jobs

Kubernetes Jobs have been crucial for running one-off tasks or collections of tasks in parallel. However, the introduction of the ForEach feature has expanded this capability even further. It allows users to specify a dependent job template that is iteratively applied for each input item, making it a powerful tool for handling complex, batch-oriented workflows.

3. Workload Identity

Workload Identity plays a vital role by providing automated, short-term credentials for pods, regardless of their underlying infrastructure. This feature simplifies service accounts and token management, ensuring that applications receive the necessary permissions without necessitating complex authentication procedures. This eliminates potential risks and simplifies security assurance.

4. Kustomize Integration

Kustomize, originally a separate project, has now been integrated into Kubernetes Manifest API. It offers developers a robust solution to manage and customize Kubernetes resources through overlays and patches. This powerful addition empowers DevOps teams to comprehend and customize huge, distributed systems in a flexible, human-readable manner.

5. NetworkPolicy API for Service Meshes

Service meshes have been gaining prominence within Kubernetes environments due to their impact on system performance, observability, and service resilience. The NetworkPolicy API directly supports the development and management of service meshes, allowing control of network connectivity and workload functionality. This integration streamlines network resource management and isolates apps and components.

6. Container Runtime Interface (CRI-O)

Container Runtime Interface (CRI-O) serves as a plugin architecture for creating runtime environments. It simplifies the process of creating container engine carriers by offering a common interface between runtimes and Kubernetes. CRI-O allows developers to smoothly transition to new and different container runtimes due to its backend-agnostic design.

7. Custom Metrics API

The Custom Metrics API has ample potential for Kubernetes users looking beyond traditional CPU and memory metrics. It enables the ingestion and usage of any type of metric, allowing teams to build more comprehensive observability strategies. Users can now incorporate application-specific metrics into their cluster-wide monitoring strategies.

8. Open Virtual Networking (OVN)

Open Virtual Networking (OVN) bridges the divide between virtual and physical networking by providing scalable and accurate virtualized networking solutions for cloud and enterprise infrastructures. It gears up users to support advanced networking concepts using open and broad original code that offers great support for virtual network-layer features.

9. Kube-Scheduler Rewrite

The rewritten Kube-Scheduler has overhauled the mechanism for choosing nodes upon which your pods settle. This overhaul ensures robust resource preemption for legacy applications that fails to scale down using built-in mechanisms. In addition, resources on nodes that are fully busy come back into play within minutes due to a brand new time-based, node preemption mechanism.

10. Scalable Persistent Volume Provisioning

Kubernetes clusters now feature enhanced scalable Persistent Volume Provisioning (PSP). It addresses storage needs in large-scale clusters where persistent volume counts run into thousands. The Scalable PSPs allow the USB to quickly react to resource demands, scaling dynamically as the cluster grows, catering to ever-increasing workloads.

Mastering these Kubernetes features can help Indian DevOps teams optimize system performance, simplify management tasks, and enhance security.

As Indian DevOps teams strive to modernize and optimize their applications, understanding these often-overlooked Kubernetes features is a must. Whether it's to optimize resource utilization or streamline workflows, mastering these features is key to remaining competitive in today's rapidly evolving tech landscape.