The ScaleOps Blog

In Kubernetes, the availability during planned and unplanned disruptions is a critical necessity for systems that require high uptime. Pod Disruption Budgets (PDBs) allow for the management of pod availability during disruptions. With PDBs, one can limit how many pods of an application could be disrupted within a window of time, hence keeping vital services running during node upgrades, scaling, or failure. In this article, we discuss the main components of PDBs, their creation, use, and benefits, along with the best practices for improving them for high availability at the very end.

When managing large-scale Kubernetes clusters, efficient resource utilization is key to maintaining application performance while controlling costs. But certain workloads, deemed “unevictable,” can hinder this balance. These pods—restricted by Pod Disruption Budgets (PDBs), safe-to-evict annotations, or their role in core Kubernetes operations—are anchored to nodes, preventing the autoscaler from adjusting resources effectively. The result? Underutilized nodes that drive up costs and compromise scalability. In this blog post, we dive into how unevictable workloads challenge Kubernetes autoscaling and how ScaleOps’ optimized pod placement capabilities bring new efficiency to clusters through intelligent automation.

The Kubernetes Vertical Pod Autoscaler (VPA) is a critical component for managing resource allocation in dynamic containerized environments. This guide explores the benefits, limitations, and best practices of Kubernetes VPA, while offering practical insights for advanced Kubernetes users.

The Kubernetes Horizontal Pod Autoscaler (HPA) adjusts the number of active pods in real time based on resource needs, ensuring efficient scaling for applications. This blog covers how HPA works, setup examples, best practices, and more, for a complete autoscaling strategy.

Unchecked Kubernetes costs can become a serious drain on resources, particularly as clusters scale and workloads fluctuate. For teams managing cloud-native environments, the challenge is balancing efficiency with cost-effectiveness—avoiding waste without compromising performance. In this guide, we’ll dive into actionable strategies and tools to help you keep Kubernetes costs under control, focusing on the most common pain points and the best ways to tackle them head-on.

As Kubernetes becomes the backbone of modern application deployment, platform engineering teams face the challenge of managing its resource complexity. While Kubernetes provides the flexibility and scalability necessary to handle containerized workloads, ensuring efficient resource management is critical for both innovation and operational efficiency. Mismanagement can lead to performance bottlenecks, higher costs, and downtime. This is where intelligent automation platforms like ScaleOps step in, dramatically simplifying resource management.

Kubernetes is hailed for its scalability and flexibility, but managing its resources effectively can be a challenge that results in unnecessary costs. As cloud-based applications scale, organizations often overlook hidden inefficiencies that waste resources, leading to inflated bills. This blog post highlights best practices for optimizing Kubernetes resources to ensure cost efficiency.

Many organizations choose on-premise or hybrid cloud environments for greater control, compliance, and performance. ScaleOps enhances these setups with simple deployment, unified management, and powerful automation. It supports air-gapped environments, ensures cost efficiency through resource optimization, and offers seamless management across infrastructure types, helping organizations maximize their on-premise and hybrid investments with ease.

Managing Kubernetes resources is complex, and static tools often can’t keep up with changing demands. ScaleOps automates resource management, adjusting in real-time to traffic spikes and workload changes. Key benefits include continuous monitoring, zero downtime scaling, and proactive optimization. Simplify Kubernetes operations with ScaleOps for efficient, reliable performance.