Today, majority of organizations who are building modern digital cloud native applications are making the strategic platform investment to containerize these mission-critical, revenue generating applications. The benefits of containerization include faster time to market with new capabilities, application elasticity to easily handle peak demand, and the benefits of portability through hybrid or mulitcloud deployments. Organizations are seeing the benefits: 85% of organizations have become cloud-native and 86% of those are using container platforms for more applications (“Container Adoption Statistics…”).
This blog is part of a series in which we share some of the results from our State of Performance in Modern Applications Survey. Want to binge read the results? Download the full report here.
Topics: Cloud Native
This article was originally published by The New Stack.
Kubernetes “won” and has become the most widely used container orchestration platform for deploying, scaling, and managing containers. The offspring of Borg has grown up and is in Production. Part of the benefits of Kubernetes is that it can be deployed on many different platforms, or choices for infrastructure providing compute, storage and network resources: on-prem or public cloud; build your own or great commercial offers like OpenShift or the growing provider/Kubernetes-as-a-Service market that includes GKE, EKS, AKS (more about that later); down to VMs or bare metal. The choice is yours.
In my last post I discussed the need for software to be able to make decisions—and how having a full-stack understanding of Pivotal Cloud Foundry with the underlying infrastructure is critical to accurately determining the right actions. If the actions aren’t specific and accurate, you can’t automate them! So, let’s dig into these actions and how they map back to Turbonomic’s unique analysis of the full stack.
Pivotal Cloud Foundry - Why is it Complex?
Containers and microservices are rapidly taking hold as they enable faster deployment of applications, services, and scaling on demand. The catch: more moving parts, greater density, and more layers to manage.