Google Kubernetes Engine

DevOps / Build, Test, Deploy / Containers as a Service
Avatar of shosti
Senior Architect at Rainforest QA

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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Why Rainforest QA Moved from Heroku to Google Kubernetes Engine (rainforestqa.com)
13 upvotes1 comment476K views
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Avatar of ruswerner
Lead Engineer at StackShare

We began our hosting journey, as many do, on Heroku because they make it easy to deploy your application and automate some of the routine tasks associated with deployments, etc. However, as our team grew and our product matured, our needs have outgrown Heroku. I will dive into the history and reasons for this in a future blog post.

We decided to migrate our infrastructure to Kubernetes running on Amazon EKS. Although Google Kubernetes Engine has a slightly more mature Kubernetes offering and is more user-friendly; we decided to go with EKS because we already using other AWS services (including a previous migration from Heroku Postgres to AWS RDS). We are still in the process of moving our main website workloads to EKS, however we have successfully migrate all our staging and testing PR apps to run in a staging cluster. We developed a Slack chatops application (also running in the cluster) which automates all the common tasks of spinning up and managing a production-like cluster for a pull request. This allows our engineering team to iterate quickly and safely test code in a full production environment. Helm plays a central role when deploying our staging apps into the cluster. We use CircleCI to build docker containers for each PR push, which are then published to Amazon EC2 Container Service (ECR). An upgrade-operator process watches the ECR repository for new containers and then uses Helm to rollout updates to the staging environments. All this happens automatically and makes it really easy for developers to get code onto servers quickly. The immutable and isolated nature of our staging environments means that we can do anything we want in that environment and quickly re-create or restore the environment to start over.

The next step in our journey is to migrate our production workloads to an EKS cluster and build out the CD workflows to get our containers promoted to that cluster after our QA testing is complete in our staging environments.

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19.6K views
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We are building a product that runs both on-prem and on our Google Kubernetes Engine clusters, and I am working on building a monitoring solution.

Our app is dockerized and usually deployed using Kubernetes.

I am currently looking into tools for centralized logging, but there is a catch. Some of our customers do not allow exporting the logs to our cloud solution; so basically, I am looking for a solution that will work for all 3 use cases:

  1. Cloud clusters

  2. On-prem which can report to our central cloud logging solution

  3. On-prem which can be only accessed locally

We are currently using GCP Logging since it's pretty easy to get started with, but if it does not answer our use case, we are fine with replacing it.

I was considering ELK, but in my experience, it can be pretty complicated to manage.

Are there other recommended solutions?

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4 upvotes8K views