Tag: Karpenter

In the evolving cloud-native landscape, enterprises utilizing Amazon Elastic Kubernetes Service (Amazon EKS) often encounter challenges that hinder their pursuit of operational efficiency and cost-effectiveness. Notable among these challenges are the costs associated with Cross Availability Zone (AZ) traffic, with difficulties associated with achieving seamless scalability, hurdles in provisioning right-sized instances for nodes, and intricacies […]

In today’s cloud-native landscape, efficient management of event-driven workloads is essential for real-time data processing. Traditional autoscaling often falls short amidst unpredictable event volumes, leading to inefficiencies and increased costs. Amazon Elastic Kubernetes Service (EKS), which is a managed container orchestration platform and is well-suited for deploying container-based applications. By integrating Kubernetes Event-Driven Autoscaling (KEDA) […]

Introduction Karpenter is an open-source, high-performance Kubernetes cluster autoscaler that automatically provisions new nodes in response to unschedulable pods. Customers choose Karpenter for many reasons, such as improving the efficiency and cost of running workloads in their clusters. Karpenter works by configuring a custom resource called Provisioner. This Provisioner sets constraints on the nodes that […]

Introduction Karpenter is a Kubernetes node lifecycle manager created by AWS, initially released in 2021 with the goal of minimizing cluster node configurations. Over the past year, it has seen tremendous growth, reaching over 4900 stars on GitHub and merged code from more than 200 contributors. It is in the process of being donated to […]

Introduction Cluster autoscaler, has been the de facto industry standard autoscaling mechanism on kubernetes since the very early version of the platform. However, with the evolving complexity and number of containerized workloads, our customers running on Amazon Elastic Kubernetes Service (Amazon EKS) started to ask for a more flexible way to allocate compute resources to […]

Introduction Karpenter is an open-source cluster autoscaler that provisions right-sized nodes in response to unschedulable pods based on aggregated CPU, memory, volume requests, and other Kubernetes scheduling constraints (e.g., affinities and pod topology spread constraints), which simplifies infrastructure management. When using Cluster Autoscaler as an alternative autoscaler, all Kubernetes nodes in a node group must […]

This post was co-written with Ophir Zahavi, Cloud Engineering Manager, H2O.ai Introduction H2O.ai is a visionary leader in democratizing artificial intelligence (AI) by rapidly provisioning AI platforms that help businesses make better decisions. Our company’s SaaS platform, built on AWS, H2O AI Managed Cloud, enables businesses to build productive models and gain insights from their […]

Introduction In November 2021, AWS introduced Karpenter, an open-source high-performance Kubernetes Cluster Autoscaler licensed under the Apache License 2.0. Karpenter helps improve your application availability and cluster efficiency by rapidly launching right-sized compute resources in response to changing application load. Since its release, we’ve been seeing an increase in customers migrating from Kubernetes Cluster Autoscaler […]

Introduction CoStar is well known as a market leader for Commercial Real Estate data, but they also run major home, rental, and apartments websites —including apartments.com—that many have seen advertised by Jeff Goldblum. CoStar’s traditional Commercial Real Estate customers are highly informed users that use large and complex data to make critical business decisions. Successfully […]

This post was coauthored by Jesse Gonzalez, Sr. Staff Site Reliability and Naveen Puvvula, Sr. Eng Manager, Reliability Engineering at Life360 Introduction Life360 offers advanced driving, digital, and location safety features and location sharing for the entire family. Since its launch in 2008, it has become an essential solution for modern life around the world, […]