Reshaping the DevOps role for higher productivity in 2023

What is DevOps?

DevOps is a set of practices that combines software development (Dev) and information-technology operations (Ops) to shorten the development life cycle and provide continuous delivery with high software quality. It aims to establish a culture and environment where building, testing, and releasing software can happen rapidly, frequently, and more reliably. DevOps emphasizes collaboration, communication, and integration between software developers and IT professionals. It aims to improve the speed and reliability of software releases, and to reduce the time it takes to deliver new features and capabilities to users.

The emerging role of a DevOps engineer

A DevOps engineer is responsible for designing, implementing, and maintaining the infrastructure and tools needed to build, test, and deploy software applications. This can include tasks such as setting up and configuring build servers, defining and automating deployment processes, and establishing monitoring and logging systems to ensure the reliability and performance of the software.

In addition to technical responsibilities, a DevOps engineer often plays a key role in promoting a culture of collaboration and continuous improvement within an organization. This can involve working closely with software developers to understand their needs and help them to adopt best practices for coding and testing, as well as collaborating with IT operations teams to ensure that systems are robust, scalable, and secure.

Overall, the goal of a DevOps engineer is to help organizations develop and deliver high-quality software more efficiently and effectively, through the use of automation, collaboration, and a focus on continuous improvement.

Technology platforms that DevOps engineers use these days

There are many different technology platforms that DevOps engineers use, depending on the specific needs and goals of an organization. Some of the most common platforms and tools include:

Version control systems: Git, Mercurial, and Subversion are among the most popular version control systems used by DevOps engineers to manage and track changes to code.

Continuous integration and delivery (CI/CD) tools: Jenkins, Travis CI, and CircleCI are examples of popular CI/CD tools that allow developers to automate the build, test, and deployment process for their code.

Infrastructure as code (IaC) tools: Tools like Terraform, CloudFormation, and Ansible allow DevOps engineers to automate the provisioning and management of infrastructure resources, such as servers, networks, and storage.

Containerization and orchestration tools: Docker and Kubernetes are examples of tools that allow DevOps engineers to package applications into lightweight containers and manage the deployment and scaling of those containers across a cluster of servers.

Monitoring and logging tools: Tools like Nagios, Datadog, and Splunk allow DevOps engineers to monitor the performance and availability of their systems and applications, and to troubleshoot issues as they arise.

Collaboration and communication tools: Tools like Slack, Jira, and Asana are commonly used by DevOps engineers to collaborate with team members and track progress on tasks and projects.

These are a small sample of the many tools and platforms that DevOps engineers may use. The specific tools and technologies used can vary widely depending on the needs and goals of an organization.

DevOps Engineers collaborate with Artificial intelligence to drive productivity

Artificial intelligence (AI) and machine learning (ML) are increasingly being used in DevOps to automate and improve various aspects of the software development and delivery process. Some examples of how AI and ML are being used in DevOps include:

Automated testing: AI and ML can be used to create and run tests for software applications automatically, helping to identify defects and issues earlier in the development process.

Predictive analytics: AI and ML can be used to analyze data from various sources, such as performance and usage metrics, to identify patterns and trends that can help predict future behavior and issues. This can help DevOps teams proactively address potential problems before they occur.

Self-healing systems: AI and ML can be used to build systems that can automatically detect and fix issues as they arise, helping to reduce downtime and improve reliability.

Automated deployment: AI and ML can be used to automate the deployment of software updates and releases, helping to reduce the time and effort required to deliver new features and capabilities to users.

Overall, the use of AI and ML in DevOps can help organizations to improve the speed, reliability, and quality of their software releases, and to better manage and optimize the performance of their systems and applications.

Artificial Intelligence and Machine Learning companies driving DevOps

There are many companies that offer AI and ML solutions for DevOps. Here are a few examples:

AppDynamics: A company that offers AI-powered performance monitoring and management tools for cloud-native and hybrid applications.

Datadog: A company that offers a cloud-based monitoring and analytics platform that uses AI and ML to help organizations optimize the performance and reliability of their applications.

Dynatrace: A company that offers AI-powered performance monitoring and management tools for cloud-native and hybrid applications.

New Relic: A company that offers a cloud-based monitoring and analytics platform that uses AI and ML to help organizations optimize the performance and reliability of their applications.

Splunk: A company that offers a range of AI and ML-powered tools for data analysis and visualization, including tools for application performance monitoring and log analysis.

The future of DevOps engineer role

The role of a DevOps engineer is likely to continue evolving as new technologies and practices emerge. Here are a few trends that may shape the future of the DevOps engineer role:

Increased automation: As automation technologies such as AI and ML continue to advance, DevOps engineers may focus more on designing and implementing automated solutions for tasks such as testing, deployment, and monitoring.

Continued focus on security: As organizations become increasingly reliant on software and digital systems, the importance of security in the software development and delivery process is likely to continue to grow. DevOps engineers may play a key role in ensuring the security and compliance of systems and applications.

Greater collaboration and communication: The role of the DevOps engineer is likely to continue to emphasize collaboration and communication across various teams and functions, as organizations seek to improve the speed and efficiency of their software development and delivery processes.

Growing importance of cloud and hybrid environments: As more organizations adopt cloud computing and hybrid environments, DevOps engineers may need to have expertise in managing and optimizing these types of environments.

Overall, the role of a DevOps engineer is likely to continue to evolve and change as new technologies and practices emerge. It will be important for DevOps engineers to stay abreast with these developments and to continue learning and adapting as the field evolves.

The demand and supply gap of DevOps engineers

There is currently a high demand for skilled DevOps engineers, as organizations increasingly seek to adopt agile, collaborative approaches to software development and delivery. According to data from the Bureau of Labor Statistics, employment of computer and information technology occupations, including DevOps engineers, is projected to grow 11% from 2019 to 2029, faster than the average for all occupations.

However, there may be a gap between the demand for DevOps engineers and the supply of qualified candidates. A survey by the DevOps Institute found that 69% of respondents reported a skills gap in their organizations, with a lack of skilled DevOps professionals cited as the main challenge. This may be due in part to the rapidly evolving nature of the field, which requires professionals to continually learn and adapt to new technologies and practices.

Overall, the demand for skilled DevOps engineers is likely to continue to be strong as organizations seek to improve the speed and reliability of their software development and delivery processes. However, there may be a gap between demand and supply, and it may be challenging for organizations to find qualified candidates.

Where can you get DevOps certified?

There are many organizations that offer DevOps certifications. Some examples include:

DevOps Institute: The DevOps Institute offers a range of DevOps certifications, including the DevOps Leader (DOL), DevOps Practitioner (DOP), and DevOps Fundamentals (DOF) certifications.

AWS: Amazon Web Services (AWS) offers a range of DevOps-related certifications, including the AWS Certified DevOps Engineer – Professional certification.

Azure: Microsoft Azure offers a range of DevOps-related certifications, including the Azure DevOps Engineer Expert certification.

Red Hat: Red Hat offers a range of DevOps-related certifications, including the Red Hat Certificate of Expertise in Ansible Automation.

DASA: offers a range of DevOps-related certifications, they are an industry body at the cutting edge of innovation.

These are just a few examples of the many organizations that offer DevOps certifications. The specific certifications and requirements can vary widely, so it's important to research the options and choose a certification that aligns with your goals and experience.

About the author

Arjun worked on the future of work and future of skills for India. He was working for a silicon valley company (EdCast) and their tech was being used by the Government of India for a very strategic initiative for the country - futureskillsprime.in. FutureSkills Prime is a digital upskilling and reskilling initiative by the Government of India on emerging tech like Artificial Intelligence, Big Data and 8 other technologies. He led that initiative for the nation.

He's the founder of Mhymatch that is addressing the challenge of recruiting talent in the tech space. Finding the right talent is a time consuming process and utilizes expensive resources. Using Artificial Intelligence, Big Data and Machine Learning technologies we help companies through the entire process of recruitment through sourcing, screening, assessing and interviewing.

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