DevOps Tools in the cloud - Google Cloud Platform
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DevOps Tools in the cloud – Google Cloud Platform

Terry Cox
Terry Cox

Today, we will be completing our series of articles on how DevOps is being enabled in the cloud. Previously, we have talked about the tools and processes that Amazon Web Services and Microsoft Azure have implemented and offered support for on their platform. We will end our investigation today by talking about DevOps on the Google Cloud Platform.

Google Cloud Platform – you truly get what you pay for

Almost any time you consume resources in the cloud, there is an associated cost for those resources over time (with the exception of each cloud vendor’s “free tier,” which will come with a large number of restrictions on size and amount of time they can be used without cost). These costs have evolved over time from daily charges to hourly charges, and in some cases, per minute charges. Google has truly embraced the DevOps mindset of ‘just in time’, is in their billing practices. With Google Cloud Platform, you pay for your resource usage PER SECOND. This means that you do not pay for resource utilization you did not realize simply because you were done before the most granular billing cycle was up.Additionally, discounts can be realized for sustained usage of resources that run for various times and, like the other large cloud vendors, for reserved utilization (which Google calls Committed Use).

DevOps tools on Google Cloud Platform

As you might expect, in addition to some of the billing flexibility that we mentioned above, Google Cloud Platform supports a variety of standard and customized DevOps tools. Some of what you will see on the platform are:

  • Jenkins on Google Container Engine – If you’re looking to extend your Continuous Integration and Continuous Delivery pipeline into the cloud, using Jenkins in the cloud is supported as an ‘instant on’ container on this platform
  • App Engine – When using your DevOps pipeline for development, testing, and deployment, it can be easily integrated with the app engine to customize your runtime and/or full stack operating system as needed
  • Microservices – Supporting application decomposition can further abstract your environment and reduce costs as well as the complexity of managing a full environment, using microservices allows you to get JUST what you need without the ancillary dependencies on libraries, applications, and operating systems
  • Google Container Engine – Google has led the charge when it comes to container clusters based on Kubernetes. Having used this internally for years, Google was able to perfect the clustering that is now commonly used (and supported) across all the major cloud platforms
  • Traditional DevOps Tools – Of course, being a cloud virtual instance provider, you are free to install and configure any ‘traditional’ DevOps tool (Chef, Puppet, Ansible, Salt, Docker, Swarm, etc) within their cloud environment, whether you are moving to the cloud or augmenting your on-premise solutions, you can get the work done the way you want

Where do we end up?

Every one of the major cloud vendors has embraced and enabled DevOps on their platform. Each one supports traditional DevOps tools on any of their instances, exactly the way you might deploy them on premise. Additionally, each vendor has a variety of tools and services that they have chosen to integrate more tightly in their platform either as a directly consumable service or as an ‘instant’ deployable instance for your use.Which of these platforms is best for DevOps? Only you will be able to answer that question. The answer will lie within a number of factors that are specific to your needs and your organization’s structure. However, you can rest assured that you will be able to find a cloud partner that can help you enhance your flexibility as you continue down the DevOps path.Leave us a note and share your cloud DevOps stories, we want to hear from you!

If you missed our first two posts, check them out here:


Part 1 – DevOps tools on AWS


Part 2 – DevOps tools on Microsoft Azure


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