Kubernetes is an extensible and portable open source platform to manage containerized workloads and services, it promotes both declarative configuration writing and automation. It's basically a large, rapidly expanding ecosystem with a wealth of services, support, and tools.
Google made the Kubernetes project open source in 2014. Kubernetes development draws on Google's decade and a half of experience in managing load and scale in production, along with best ideas and practices from the community.
Google Kubernetes Engine (GKE), formerly known as Google Container Engine, is a management and orchestration system for Docker containers running on Google's public cloud services.
Google Container Engine is based on Kubernetes, Google's open source container management system. Businesses often use Google Kubernetes Engine to do the following:
- Create or resize Docker container clusters.
- Create container pods, replication controllers, jobs, services, or load balancers.
- Resize application handlers.
- Upgrade container clusters.
- Debug container clusters.
Users can interact with Google Kubernetes Engine using the gcloud CLI o Google Cloud Platform Console. Software developers frequently use Google Kubernetes Engine to create and test new business applications. Administrators also use containers to better meet the scalability and performance requirements of business applications, such as web servers.
Google has acknowledged that users have difficulties to properly configure Kubernetes and introduced the new service called "GKE Autopilot" with the aim of simplifying the deployment and management of nodes.
Observers say about Kubernetes that first, it has gained critical importance in the container orchestration space, and second, its complexity is both a barrier to adoption and a frequent cause of errors.
"Despite six years of progress, Kubernetes is still proving to be very complex," wrote Drew Bradstock, product lead for Google Kubernetes Engine (GKE), in a post announcing Autopilot. "And what we've seen over the past year is that many companies welcome Kubernetes with open arms, but grapple with its complexity."
Much of GKE is already a managed service, but Google introduced Autopilot, a deployment service for GKE, which automatically adds a new thin layer of management.
One of the differences between the two lies, among other things, at the management level. Kubernetes works with nodes (individual servers), clusters (a series of physical or virtual servers), containers (where programs run), and pods (a group of one or more containers on a node). While GKE manages at the cluster level, Autopilot also includes nodes and pods in its administration tool.
The best place to understand the features and limitations of Autopilot is in its documentation, noting the options marked "preconfigured" (which means they cannot be changed) so that administrators have less work.
Essentially, it is another way to buy and manage GKE resources that offers less flexibility, but more convenience. Since Google handles more of the setup, it offers a higher SLA of 99.9% uptime for autopilot modules in multiple areas.
“With the launch of Autopilot, GKE users can now choose between two different modes of operation, each with its own level of control over their GKE clusters and related GKE responsibilities.
“GKE already offers a state-of-the-art level of automation that makes setting up and operating a Kubernetes cluster easier and more cost-effective than DIY and other managed offerings; The autopilot represents a significant advance. In addition to the fully managed control plane that GKE has always provided, using the autopilot mode of operation automatically applies industry best practices and can eliminate all node management operations, thus maximizing the efficiency of your cluster and contributing to to strengthen security.
Source: https://cloud.google.com