# Cloud management ## How load balancing strategy affects pod utilization and rightsizing accuracy **June 18, 2026** **10 MIN READ** Load balancing is one of the most consequential decisions in your cluster. It directly affects CPU and memory utilization, HPA scaling decisions, and what you’re paying for at the end of the month. And yet, it tends to be very low on most teams’ lists. The factor most teams don’t account for is whether their load balancer understands what a request is. That distinction, surprisingly, lies in the difference between Layer 4 vs Layer 7 of your network stack. Layer 4 vs Layer 7: What’s the difference? How load balancing functions differently at each layer: Layer 4 (transport layer) load balancing … By Ilan Ovadia R&D Team Lead ## How to avoid costly instance selection mistakes in Karpenter **February 19, 2026** **5 MIN READ** Your Karpenter configuration can make or break your cluster’s efficiency. Configure it poorly and you risk locking yourself into expensive nodes that never consolidate. I have seen clusters where Karpenter was installed correctly, yet costs increased, and the root cause was almost always the same: NodePool design. The key is to configure it widely enough to give it the breadth to make the best decisions for you. This guide provides steps to design NodePools that give Karpenter enough flexibility to optimize while protecting you from costly mistakes. First, Understand What Karpenter Is Optimizing Before tuning anything, clarify how Karpenter works. What … By Ido Slonimsky Tech Lead, Zesty ## Why “Accurate Requests” Still Lead to Cloud Resource Waste **January 29, 2026** **6 MIN READ** If you’re operating Kubernetes in production, you probably know this story: you analyze metrics, tune CPU and memory requests, validate them against historical data, and roll changes out carefully. And even though pods are no longer wildly overprovisioned, the cloud bill stays pretty much the same. If that’s familiar, it’s not necessarily caused by poor execution, but likely a result of how K8s is designed to balance elasticity and safety. Accurate requests are necessary, but don’t eliminate waste on their own. This article is a step-by-step guide that explains where that waste comes from, how to recognize it, and how to … By Ido Slonimsky Tech Lead, Zesty ## How to deal with workloads HPA can’t handle **December 11, 2025** **7 MIN READ** HPA has become one of the most relied-upon tools in Kubernetes operations, mostly due to its ability to cover many common scaling event use cases. However, there are workloads even HPA can’t help. A DaemonSet that claims resources on every node with no ability to scale. A Postgres primary in a StatefulSet, which does not support multiple primary replicas. A batch Job that spikes unpredictably and HPA has no bearing over. These cases expose the limits of replica-based scaling, reminding us that Kubernetes has more workload patterns than HPA was ever meant to address. This article breaks down why HPA falls short in … By Ilan Ovadia R&D Team Lead ## How to secure Kubernetes workloads using Pod Identity **September 29, 2025** **3 MIN READ** When running workloads in Kubernetes, applications often need to interact with external cloud services -like pulling data from an S3 bucket. Traditionally, this meant hardcoding secrets or access keys into pods, which is risky, hard to rotate, and painful to manage at scale. In short, the old approach tied application identity directly to long-lived secrets, which doesn’t scale well and introduces security risks. Pod Identity solves this by giving pods a secure, temporary identity without relying on static credentials. What is Pod Identity? Pod Identity is a way to connect Kubernetes Service Accounts with cloud provider identities (like AWS IAM Roles). … By Ilya Pisatzkov Solution Architect ## How to make your Kubernetes applications spot interruption-tolerant **September 01, 2025** **5 MIN READ** Spot Instances are one of the most powerful levers we have for cutting cloud costs. They’re also one of the riskiest to use if not done right. The reason is simple: Spot capacity can vanish at any time. When AWS needs the capacity back, your nodes get interrupted, and if your workloads can’t survive that, you’ll be paged into a fire drill. But this doesn’t have to be the story. Kubernetes gives us tools, and AWS gives us signals, that let us design systems where Spot interruptions are a nuisance rather than a disaster. This article walks you through the practices … By Ido Slonimsky Tech Lead, Zesty