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GKE Workload Optimization

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GKE Workload Optimization

1 hora 30 minutos 7 créditos

GSP769

Google Cloud Self-Paced Labs

Overview

One of the many benefits of using Google Cloud is its billing model that bills you for only the resources you use. With that in mind, it's imperative that you not only allocate a reasonable amount of resources for your apps and infrastructure, but that you make the most efficient use of them. With GKE there are a number of tools and strategies available to you that can reduce the use of different resources and services while also improving your application's availability.

This lab will walk through a few concepts that will help increase the resource efficiency and availability of your workloads. By understanding and fine-tuning your cluster's workload, you can better ensure you are only using the resources you need and optimizing your cluster's costs.

What you'll do

  • Configure container-native load balancing for load balancing through ingress for more efficient routing to your pods

  • Walk through a single-pod load test of a Kubernetes application for understanding app load capacity

  • Configure a liveness probe for a Kubernetes application in order to define meaningful prerequisite conditions for automatic pod reboots

  • Configure a readiness probe for a Kubernetes application in order to ensure that traffic reaches the application endpoints successfully

  • Configure a Pod Disruption Budget for ensuring application availability

Únase a Qwiklabs para leer este lab completo… y mucho más.

  • Obtenga acceso temporal a Google Cloud Console.
  • Más de 200 labs para principiantes y niveles avanzados.
  • El contenido se presenta de a poco para que pueda aprender a su propio ritmo.
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