DevOps has become a digital transformation strategy for many organizations. It is about software development and operations teams working together and engineering and automating their practices. This will lead to writing codes for small changes and test and deploy those small changes very rapidly. This was an amazing step forward and a wonderful software practice.
But now, in the modern environment, we’re facing even more challenges. We need software applications to work at an amazingly large web-scale and deal with microservices, containerization, and service mesh. In this modern world of containers and Kubernetes, the applications need to scale up the infrastructure running when the load is high. And when there’s no load, it needs to scale down and do this all dynamically in a very complex way across many applications and microservices.
To address these modern operational challenges, GitOps comes into play. Before I talk about GitOps, let me tell you what Git is and what Ops is briefly.
Git is a distributed version control system where we manage our source code. It can have text, certificate, or configuration files. We maintain all these files using Git, and we also use it for collaborating with different team members.
Ops term comes from the same DevOps term, where we used to do release, deploy, operate, and monitor applications as a part of the operations.
GitOps is a process that is used for the continuous deployment of a cloud-native application. This process is developer-centric, which uses a developer-friendly tool like Git for operating infrastructure. Git here is the single source of truth for all the infrastructure and application deployment automation.
It is an operational framework, and it takes the DevOps best practices used for application development. These are version control, collaboration, compliance, CI/CD, and it applies them for infrastructure automation. In a nutshell, GitOps has three main components.
It is a combination of infrastructure as code (IaC), merge requests as your agent of change, and CI/CD automation.
Below are the benefits of using GitOps in your organization:
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GitOps is a fairly new (2017) style of implementing DevOps practices that has quickly grown in popularity. This 3-part blog series will:
The term GitOps was coined in a blog post titled “GitOps—Operations by Pull Request” published on August 7, 2017 by Alexis Richardson, the CEO of Weaveworks. However, the fundamental concepts that underpin the GitOps methodology were largely devised by Google and codified in the now-famous Site Reliability Engineering book that was published in March 2016. However, SRE is a very Google-specific methodology that at the time was difficult to implement anywhere else. This has changed in the intervening years, but in the meantime GitOps has evolved to fill in some of the tools and practices that make it possible for everyone to manage systems the way Google does internally.
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SQL stands for Structured Query Language. SQL is a scripting language expected to store, control, and inquiry information put away in social databases. The main manifestation of SQL showed up in 1974, when a gathering in IBM built up the principal model of a social database. The primary business social database was discharged by Relational Software later turning out to be Oracle.
Models for SQL exist. In any case, the SQL that can be utilized on every last one of the major RDBMS today is in various flavors. This is because of two reasons:
1. The SQL order standard is genuinely intricate, and it isn’t handy to actualize the whole standard.
2. Every database seller needs an approach to separate its item from others.
Right now, contrasts are noted where fitting.
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If you’re using Helm for deployment what happens when you also use GitOps? GitOps lends itself easily in a Kubernetes environment when you have static YAML used declaratively. Helm is a software package manager that simplifies deployment of applications and services to OpenShift Container Platform clusters. In this episode, we’ll walk through how to integrate Helm in your GitOps workflow and cover what steps and tools are needed.
What is GitOps Guide to the Galaxy?
Every other Thursday at 3am ET hosts Christian Hernandez and Chris Short sit down to discuss everything in the GitOps universe, from end-to-end CICD pipelines to creating Git workflows.
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GitOps offers a way to automate and manage infrastructure. It does this by using the same DevOps best practices that many teams already use, such as version control, code review, and CI/CD pipelines.
Companies have been adopting DevOps because of its great potential to improve productivity and software quality. Along the way, we’ve found ways to automate the software development lifecycle. But when it comes to infrastructure setup and deployments, it’s still mostly a manual process.
With GitOps teams can automate the infrastructure provisioning process. This is due to the ability to write your infrastructure as code (IaC) with the use of declaration files. We can store them in a Git repository, exactly as we store application development code.
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In Part 1 of this series, we laid the groundwork with a background of Gitops and a deep dive into the tools needed to optimise the principles of the methodology. In Part 2 of this 3-part series, we’ll get started with the initial implementation steps that will set you up for success in optimizing GitOps on Google Cloud Platform. So, now that we have a general understanding of GitOps principles and the available tools, let’s dive into how you can use these tools to get up and running.
For the purposes of this example, I have made the following tool selections:
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