GitLab is the open DevOps platform, delivered as a single application. This makes GitLab unique and creates a streamlined software workflow, unlocking your organization from the constraints of a pieced-together toolchain. Learn how GitLab offers unmatched visibility and higher levels of efficiency in a single application across the DevOps lifecycle. The GitLab code was originally written in Ruby, with some parts later rewritten in Go. GitLab was initially launched as a source code management solution to collaborate with his team on software development. GitLab is a web-based DevOps lifecycle tool that provides a Git repository manager providing wiki, issue-tracking, and continuous integration and deployment pipeline features, using an open-source license, developed by GitLab Inc.

How does GitLab work?

GitLab is the open DevOps platform, delivered as a single application. This makes GitLab unique and creates a streamlined software workflow, unlocking your organization from the constraints of a pieced-together toolchain. Learn how GitLab offers unmatched visibility and higher levels of efficiency in a single application across the DevOps lifecycle. The GitLab code was originally written in Ruby, with some parts later rewritten in Go. GitLab was initially launched as a source code management solution to collaborate with his team on software development.

Why use GitLab?

The main benefit of using GitLab is that it allows all the team members to collaborate in every phase of the project. GitLab offers tracking from planning to creation to help developers automate the entire DevOps lifecycle and achieve the best possible results.

GitLab Component..

GitLab has different components working together to provide complete DevOps and project management solutions.

GitLab CI/CD..

Continuous Integration (CI) works by pushing small code chunks to your application’s codebase hosted in a Git repository, and, to every push, run a pipeline of scripts to build, test, and validate the code changes before merging them into the main branch. Continuous Delivery and Deployment (CD) consist of a step further CI, deploying your application to production at every push to the default branch of the repository. GitLab CI/CD is configured by a file called .gitlab-ci.yml placed at the repository’s root. The scripts set in this file are executed by the GitLab Runner.

How do I learn GitLab?

You can also take paid GitLab certification training – intended specifically for an audience who wants to clear their GitLab exam. Anyone interested in learning and clearing their GitLab can approach DevOpsSchool – their courses can be Joined ONLINE as instructor-led, live & interactive sessions.

What is AIOps?

If we will predict the future then what is the most exciting and perhaps the most disruptive tech trends of the coming years? It’s “artificial intelligence (AI)”. It is going to enables people to rethink how can we integrate the information, analyze the data, and use the resulting insights to improve decision making.

The same AI concept can enhance businesses IT operations immensely. AIOps is going to be a next generation of software intelligence where we can leverage the power of “artificial intelligence (AI)”. This concpet is introduced by analyst firm Gartner in the year 2017. The term AIOps is a amalgamation of artificial intelligence and IT operations. It refers to directly and indirectly automate and enhance IT operations – utilizing data analytics, machine learning (ML) other advanced analytics technologies.

Why we need AIOps?

As digital services become the new norm, clients/consumers/users now have multiple options and are increasingly prepared to walk away if they will face and problems or issues with your product.

In the modern process of development, digital services often contain hundreds of millions of lines of code and billions of dependencies and with multicloud, open source environments, tangled web of interconnected cloud platforms, microservices, containers, serverless architecture, and orchestration platforms makes it more complicated to manage effectively in real time when it takes just a small issue in a single line of code to trigger a storm of alerts.

It is nearly impossible for the tradictional operations teams to manually find the root cause of a problem that affects multiple services and raises thousands of events per second. In response, AI and machine learning have emerged as a means to relieve some of the manual intervention required. In the journey towards digital transformation, AIOps can make life better of your engineers and in the same time it can benefit the organization by reducing their cloud costs, improve cloud security compliance, and reduce alerts fatigue is by bringing intelligent machine operations through AIOps.

What are the benefits of AIOps?

• It breaks down data silos
• AIOps eliminates IT operational noise
• Reduced downtime – It delivers a seamless user experience
• It overcomes monitoring and analytics challenges.
• Improved collaboration.
• Improved business ROI IT productivity
• Digital transformation success
• Improve performance monitoring and service delivery
• Pattern Discovery
• It automates the tasks
• AIOps possess the ability to radically reduce IT operations costs.
• Drasticaly improves the problem-solving and deployment

What is difference between DevOps and AIOps?

What is the future of AIOps?

• According to Gartner, 30% of the large companies will be using artificial intelligence for IT operations (AIOps) by 2023.
• Enterprises who wants to not only survive but succeed in today’s digital economy must take into consideration the use of AI in IT operations.
• Official Docker certfication recognized and acceptable worldwide.
• AIOps market experienced a growth of 87% in recent 3 years – from 1.73 billion in 2017 to 13.51 billion USD in 2020. And recent researhces also predicts that AIOps the will experience further 21.05% growth between 2021 and 2026, reaching up to USD 40.91 billion in market size.

Reference:- devopsschool.com