So far, we have extensively covered KEDA and its ability to scale Kubernetes pods using various metrics: Horizontal Pod Autoscaling with Kubernetes Event-Driven Autoscaler (KEDA) Scaling Amazon Elastic Kubernetes Service Workloads with KEDA and Ama...
In a previous article, we demonstrated how to scale pods based on HTTP traffic using KEDA and CloudWatch. We utilized CloudWatch to store and retrieve the metrics for our application and, based on that, scale the number of pods. But is there a way to...
In our article, Scaling Amazon Elastic Kubernetes Service Workloads with KEDA and Amazon CloudWatch, we suggested using the OTEL Collector to send application metrics to CloudWatch. Today, we will show how to do this in two different ways: Deploying...
In this article, we'll explore another practical use case of KEDA, where we scale an application dynamically in response to message traffic. This involves leveraging the combined power of Amazon EKS Cluster, KEDA, and the AWS SQS. Pre-requisites Ins...
In our previous post, Horizontal Pod Autoscaling with Kubernetes Event-Driven Autoscaler, we explored how to scale an application based on events (Azure Service Bus). Today, we aim to scale an application running in Amazon EKS based on a metric (requ...
Autoscaling is a technique that automatically scales Kubernetes (K8s) workloads up or down, depending on historical resource usage. There are two pod-level auto-scalers: Horizontal Pod Autoscaler (HPA) adjusts the number of replicas of an applicatio...
