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What is Google Kubernetes Engine?

Container Engine takes care of provisioning and maintaining the underlying virtual machine cluster, scaling your application, and operational logistics like logging, monitoring, and health management.
Google Kubernetes Engine is a tool in the Containers as a Service category of a tech stack.

Who uses Google Kubernetes Engine?

Companies
230 companies reportedly use Google Kubernetes Engine in their tech stacks, including Shopify, 9GAG, and RD Station.

Developers
235 developers on StackShare have stated that they use Google Kubernetes Engine.

Google Kubernetes Engine Integrations

Bitnami, Docker, Google Cloud Endpoints, Kubernetes, and Buddy are some of the popular tools that integrate with Google Kubernetes Engine. Here's a list of all 17 tools that integrate with Google Kubernetes Engine.

Why developers like Google Kubernetes Engine?

Here’s a list of reasons why companies and developers use Google Kubernetes Engine
Google Kubernetes Engine Reviews

Here are some stack decisions, common use cases and reviews by companies and developers who chose Google Kubernetes Engine in their tech stack.

Kir Shatrov
Kir Shatrov
Production Engineer at Shopify · | 13 upvotes · 44.5K views
atShopifyShopify
Memcached
Redis
MySQL
Google Kubernetes Engine
Kubernetes
Docker

At Shopify, over the years, we moved from shards to the concept of "pods". A pod is a fully isolated instance of Shopify with its own datastores like MySQL, Redis, Memcached. A pod can be spawned in any region. This approach has helped us eliminate global outages. As of today, we have more than a hundred pods, and since moving to this architecture we haven't had any major outages that affected all of Shopify. An outage today only affects a single pod or region.

As we grew into hundreds of shards and pods, it became clear that we needed a solution to orchestrate those deployments. Today, we use Docker, Kubernetes, and Google Kubernetes Engine to make it easy to bootstrap resources for new Shopify Pods.

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Emanuel Evans
Emanuel Evans
Senior Architect at Rainforest QA · | 12 upvotes · 53.1K views
atRainforest QARainforest QA
Terraform
Helm
Google Cloud Build
CircleCI
Redis
Google Cloud Memorystore
PostgreSQL
Google Cloud SQL for PostgreSQL
Google Kubernetes Engine
Kubernetes
Heroku

We recently moved our main applications from Heroku to Kubernetes . The 3 main driving factors behind the switch were scalability (database size limits), security (the inability to set up PostgreSQL instances in private networks), and costs (GCP is cheaper for raw computing resources).

We prefer using managed services, so we are using Google Kubernetes Engine with Google Cloud SQL for PostgreSQL for our PostgreSQL databases and Google Cloud Memorystore for Redis . For our CI/CD pipeline, we are using CircleCI and Google Cloud Build to deploy applications managed with Helm . The new infrastructure is managed with Terraform .

Read the blog post to go more in depth.

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Nick Rockwell
Nick Rockwell
CTO at NY Times · | 9 upvotes · 6K views
atThe New York TimesThe New York Times
Kubernetes
Google Kubernetes Engine
Google App Engine
Amazon EC2
#Migration
#Cloudmigration
#AWStoGCPmigration
#GCP
#AWS

So, the shift from Amazon EC2 to Google App Engine and generally #AWS to #GCP was a long decision and in the end, it's one that we've taken with eyes open and that we reserve the right to modify at any time. And to be clear, we continue to do a lot of stuff with AWS. But, by default, the content of the decision was, for our consumer-facing products, we're going to use GCP first. And if there's some reason why we don't think that's going to work out great, then we'll happily use AWS. In practice, that hasn't really happened. We've been able to meet almost 100% of our needs in GCP.

So it's basically mostly Google Kubernetes Engine , we're mostly running stuff on Kubernetes right now.

#AWStoGCPmigration #cloudmigration #migration

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Omar Mehilba
Omar Mehilba
Co-Founder and COO at Magalix · | 8 upvotes · 30.3K views
atMagalixMagalix
Python
Go
Amazon EC2
Google Kubernetes Engine
Microsoft Azure
Kubernetes
#Autopilot

We are hardcore Kubernetes users and contributors. We loved the automation it provides. However, as our team grew and added more clusters and microservices, capacity and resources management becomes a massive pain to us. We started suffering from a lot of outages and unexpected behavior as we promote our code from dev to production environments. Luckily we were working on our AI-powered tools to understand different dependencies, predict usage, and calculate the right resources and configurations that should be applied to our infrastructure and microservices. We dogfooded our agent (http://github.com/magalixcorp/magalix-agent) and were able to stabilize as the #autopilot continuously recovered any miscalculations we made or because of unexpected changes in workloads. We are open sourcing our agent in a few days. Check it out and let us know what you think! We run workloads on Microsoft Azure Google Kubernetes Engine and Amazon EC2 and we're all about Go and Python!

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Ido Shamun
Ido Shamun
at The Elegant Monkeys · | 6 upvotes · 1.9K views
atDailyDaily
Kubernetes
Google Kubernetes Engine
Netlify
#Frontend

I was thinking what could be the best option for deploying Daily's #frontend applications. On one side there is Netlify , promoting and encouraging the JAM stack, very easy to deploy and manage your deployments. And on the other side, Kubernetes , specifically Google Kubernetes Engine as I don't like to manage my own clusters. Kubernetes provides much more options, in terms of deployment strategy, networking, etc but requires far more configurations. As I don't have any SSR on my applications, I decided that the ease of use of Netlify is the number one priority for the project.

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Robert Jefe Lindstädt
Robert Jefe Lindstädt
Head of Engineering at Tillhub GmbH · | 2 upvotes · 520 views
atTillhub GmbHTillhub GmbH
Google Kubernetes Engine

Google Kubernetes Engine no-ops. Maintaining reliable Kubernetes setup is not priority for the product driven engineering team. GKE makes it incredibly simple and cost-effective to run our container applications

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Google Kubernetes Engine's Features

  • Docker support - Improve the predictability of your deployments with Docker containers. Containers make it easy to deploy applications across environments.
  • Better ops - Give ops a better system, starting with a managed compute cluster. Container Engine takes care of provisioning and maintaining the underlying virtual machines and operational logistics like logging, monitoring, and health management.
  • Declarative management - Use declarative syntax to define your application requirements. Container Engine will actively manage your application, ensuring your containers are running and scheduling additional as needed.
  • Scalable - Run multiple containers in a single virtual machine, or scale to many as your application grows. Container Engine makes it easy to manage your containers across a group of virtual machines.
  • Powered by Kubernetes - Container Engine is powered by the open source Kubernetes technology. Join the discussion on Kubernetes and be part of the growing community.
  • Decoupled apps - Let developers focus on code, with very few constraints. Create loosely coupled microservice apps that are more robust and easier to maintain and extend.

Google Kubernetes Engine Alternatives & Comparisons

What are some alternatives to Google Kubernetes Engine?
Google App Engine
Google has a reputation for highly reliable, high performance infrastructure. With App Engine you can take advantage of the 10 years of knowledge Google has in running massively scalable, performance driven systems. App Engine applications are easy to build, easy to maintain, and easy to scale as your traffic and data storage needs grow.
Amazon EC2 Container Service
Amazon EC2 Container Service lets you launch and stop container-enabled applications with simple API calls, allows you to query the state of your cluster from a centralized service, and gives you access to many familiar Amazon EC2 features like security groups, EBS volumes and IAM roles.
AWS Fargate
AWS Fargate is a technology for Amazon ECS and EKS* that allows you to run containers without having to manage servers or clusters. With AWS Fargate, you no longer have to provision, configure, and scale clusters of virtual machines to run containers.
Amazon EKS
Amazon Elastic Container Service for Kubernetes (Amazon EKS) is a managed service that makes it easy for you to run Kubernetes on AWS without needing to install and operate your own Kubernetes clusters.
Docker Cloud
Docker Cloud is the best way to deploy and manage Dockerized applications. Docker Cloud makes it easy for new Docker users to manage and deploy the full spectrum of applications, from single container apps to distributed microservices stacks, to any cloud or on-premises infrastructure.
See all alternatives

Google Kubernetes Engine's Followers
282 developers follow Google Kubernetes Engine to keep up with related blogs and decisions.
Fabio Fraga Machado
Jamal Moosvi
Karol Danko
nagano564
kryskros2
Spy Kab
Eric Sherrill
Suraj Nath
Himansu Sekhar
Ggicci T'ang