IT-reliant companies have swiftly and iteratively utilized the DevOps approach to produce products. While AWS and Azure entered the market sooner, Google entered the fray with its products that support DevOps. The practice, which brings together development and operations, demands many resources and puts a massive onus on the cloud providers.
Additionally, the plethora of tools is bound to confound those new to the cloud. While we spoke about DevOps on AWS and Azure, in this blog, we shall look at Google Cloud and how it supports the DevOps practice.
Overview of Google Cloud
AWS sparked the cloud revolution, and Microsoft took the cue and created Azure. AWS and Azure have become some of their parent companies’ most lucrative revenue streams. Google Cloud Platform, the youngest in this race, captured its fair share of the market and clinched the third spot in the cloud race as of now.
GCP’s growth fuelled its compatibility with open-source tools such as Kubernetes and other clouds. While multi-cloud strategies are only spawning, GCP came out with Anthos, which supports hybrid and multi-cloud strategies.
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What exactly is DevOps
Due to the flawed working model, development and operations teams were at loggerheads in the olden era. While the development team created a tool, the operations unit would find flaws, sometimes sending the development team back to their drawing board. While perfection was ultimately achieved, the rollout was often delayed. The expenses time was always on the higher side. Finally, after much ado, both the teams were combined.
The production approach changed greatly as the developers and ops members worked in unison to roll out the deliverables as iterative updates. The short and multiple updates allowed the DevOps members to prep the deliverables quickly with flaws that wouldn’t send them to square one.
However, this approach requires considerable digital resources as collaboration is immensely high. From codes being stored on the cloud, which should allow easy access but secure storage, to testing environments, the DevOps team is resource-extensive and effort-intensive. The latter has been achieved with GCP’s massive library of digital tools.
It is worth noting that DevOps has become immensely popular and has spawned various other production approaches, such as DevSecOps. So, without further ado, let’s dive into the crux of the blog.
How to proceed with DevOps on GCP?
Google is popular for many things. From its search engine to GCP, some know it to be the originator of Kubernetes, the tool most DevOps engineers favor. While AWS and Azure have Kubernetes tools, GCP has Google K8S Engine (GKE). The tool is the industry’s first wholly managed Kubernetes tool, allowing users to realize four different autoscaling K8s. It also lends them multi-cluster support.
What sets it apart from its competition is that one can manage the containers entirely from GKE and rest easy, as it is heavily fortified with Identity and Access Management security. In addition, it makes DevOps life smoother, as it comes with the auto-repair option, which automatically fixes a damaged node.
Useful Link: EKS Vs. AKS Vs. GKE: Which is the right Kubernetes platform for you?
As the DevOps team makes progress swiftly, it is imperative to monitor the progress of the stacks, and GCP comes packed with Stackdriver. The tool can be utilized for monitoring purposes and provides insights on compute engine infrastructure health. It also provides additional intelligence upon network and storage usage.
The metrics are valuable as the company can view the resources used and the overall health of its infrastructure. It is also widely accepted that GCP’s operations are relatively cheaper as Google sweetens the pot with discounts to keep the users hooked to the cloud.
Another critical element in DevOps is Continuous Delivery or Continuous Deployment (CI/CD). While it sounds technical, DevOps breaks down one massive deliverable into many iterative updates. This approach effectively requires the DevOps team to glacially dole out the updates until the project’s completion.
Google’s Cloud Build helps in this aspect, as one can swiftly develop software in all programming languages and choose from 15 machine types. Google doubled the productivity quotient by ingraining the tool with multi-cloud support.
Imbibing the same spirit is Cloud Deploy, which allows DevOps to create a deployment pipeline with GKE at the core. It seamlessly integrates with the DevOps ecosystem and allows you to use Jenkins. While Cloud Build is all about developing, Cloud Deploy is the dedicated CD tool that provides insights into deployment success ratio and frequency. Google layered these tools with adequate security as every tool is fortified with Google Cloud’s central security,y and can be audited easily using Google’s infrastructure.
While all these sound great, users can make a costly effort to create the CI/CD pipeline, considering the expenses, Google itself suggests using Tekton, an open-source platform that helps DevOps stitch together the CI/CD pipeline. After due testing, one can build and deploy the deliverables across various cloud platforms and on-premises IT infrastructure.
Useful Link: DevOps Implementation in Manufacturing Sector
While there are various other tools in GCP’s arsenal, two of its own are noteworthy. Security is paramount in the age of data breaches, and Google has fired on all cylinders by releasing two products: Artifact Registry and Binary Authorization. The former is a container registry from which one can manage and secure the infrastructure artifacts.
In addition, it is a hub from which one can manage the containers and use Google’s tools and runtime applications. The Registry also supports native artifact protocols, and this support makes it relatively easy to use with the CI/CD pipeline.
Binary Authorization enables the deployment of workloads. It is effectively a security mechanism that ensures only trusted workloads are deployed. The mechanism can enforce signature validation, which shall give the DevOps team and organization better control over who alters or modifies the existing infrastructure. The verification will remove the chances of unauthorized changes, which can damage or render the infrastructure useless.
In conclusion
AWS, Azure, and GCP are in a league of their own. Each has exceptional tools that propel productivity. However, restricting oneself to one cloud will only be counterproductive, and one should consider adopting a multi-cloud strategy to keep up with the competition.
While multi-cloud sounds enticing, it brings on the potential risk of draining away the monetary assets if you rope in unwanted tools. This aspect should motivate you to contact Veritis, a leading DevOps consulting company. Veritis has advised the creation of unique, cost-effective solutions without compromising anywhere. So, reach out to us and find a solution that will take you to new heights.
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