By Dan Paik, Product Manager, Container Engine
Next week, we will roll out Kubernetes 1.8 to Google Container Engine for early access customers. In addition, we are advancing significant new functionality in Google Cloud to give Container Engine customers a great experience across Kubernetes releases. As a result, Container Engine customers get new features that are only available on Google Cloud Platform, for example highly available clusters, cluster auto-scaling and auto-repair, GPU hardware support, container-native networking and more.
Since we founded Kubernetes back in 2014, Google Cloud has been the leading contributor to the Kubernetes open source project in every release including 1.8. We test, stage and roll out Kubernetes on Google Cloud, and the same team that writes it, supports it, ensuring you receive the latest innovations faster without risk of compatibility breaks or support hassles.
Let’s take a look at the new Google Cloud enhancements that make Kubernetes run so well.
Earlier this week we announced that Google Compute Engine, Container Engine and many other GCP services have moved from per-minute to per-second billing. We also lowered the minimum run charge to one minute from 10 minutes, giving you even finer granularity so you only pay for what you use.
Many of you appreciate how quickly you can spin up a cluster on Container Engine. We’ve made it even faster – improving cluster startup time by 45%, so you’re up and running faster, and better able to take advantage of the pricing minimum-time charge. These improvements also apply to scaling your existing node pools.
A long-standing ask has been high availability masters for Container Engine. We are pleased to announce early access support for high availability, multi-master Container Engine clusters, which increase our SLO to 99.99% uptime. You can elect to run your Kubernetes masters and nodes in up to three zones within a region for additional protection from zonal failures. Container Engine seamlessly shifts load away from failed masters and nodes when needed. Sign up here to try out high availability clusters.
In addition to speed and simplicity, Container Engine automates Kubernetes in production, giving developers choice, and giving operators peace of mind. We offer several powerful Container Engine automation features:
Container Engine now takes better advantage of GCP’s unique, software-defined network with first-class Pod IPs and multi-cluster load balancing.
Machine learning, data analytics and Kubernetes work especially well together on Google Cloud. Container Engine with GPUs turbocharges compute-intensive applications like machine learning, image processing, artificial intelligence and financial modeling. This release brings you managed CUDA-as-a-Service in containers. Big data is also better on Container Engine with new features that make GCP storage accessible from Spark on Kubernetes.
As more enterprises use Container Engine, we are actively improving extensibility so you can match Container Engine to your environment and standards.
We designed Container Engine with enterprise security and reliability in mind. This release adds several new enhancements.
In Kubernetes 1.7, we added view-only workload, networking, and storage views to the Container Engine user interface. In 1.8, we display even more information, enable more operational and development tasks without having to leave the UI, and improve integration with Stackdriver and Cloud Shell.
The following features are all generally available:
In addition, Audit Logging is available to early access customers. This features enables you to view your admin activity and data access as part of Cloud Audit Logging. Please complete this form to take part in the Audit Logging early access program.
Container Engine customers are global. To keep up with demand, we’ve expanded our global capacity to include our latest GCP regions: Frankfurt (europe-west3), Northern Virginia (us-east4) and São Paulo (southamerica-east1). With these new regions Container Engine is now available in a dozen locations around the world, from Oregon to Belgium to Sydney.
Customers of all sizes have been benefiting from containerizing their applications and running them on Container Engine. Here are a couple of recent examples:
Mixpanel, a popular product analytics company, processes 5 trillion data points every year. To keep performance high, Mixpanel uses Container Engine to automatically scale resources.
“All of our applications and our primary database now run on Google Container Engine. Container Engine gives us elasticity and scalable performance for our Kubernetes clusters. It’s fully supported and managed by Google, which makes it more attractive to us than elastic container services from other cloud providers,” says Arya Asemanfar, Engineering Manager at Mixpanel.
RealMassive, a provider of real-time commercial real estate information, was able to cut its cloud hosting costs in half by moving to microservices on Container Engine.
“What it comes down to for us is speed-to-market and cost. With Google Cloud Platform, we can confidently release services multiple times a day and launch new markets in a day. We’ve also reduced our cloud hosting costs by 50% by moving to microservices on Google Container Engine,” says Jason Vertrees, CTO at RealMassive.
Bitnami, an application package and deployment platform, shows you how to use Container Engine networking features to create a private Kubernetes cluster that enforces service privacy so that your services are available internally but not to the outside world.
In a few days, all Container Engine customers will have access to Kubernetes 1.8 in alpha clusters. These new updates will help even more businesses run Kubernetes in production to get the most from their infrastructure and application delivery. If you want to be among the first to access Kubernetes 1.8 on your production clusters, please join our early access program.