How can DevOps teams reap the advantages of AI?

April 15, 2022

iauro Team

Contributing immensely to the global software solutions ecosystem. DevOps | Microservices | Microfrontend | DesignThinking LinkedIn

The process of managing a DevOps environment is a complex task. Due to the sheer volume of data in today’s dynamic and distributed application settings, DevOps teams struggle to efficiently absorb and use the information to identify and resolve customer issues. Consider a team combing through exabytes of data in search of important events that precipitated an occurrence; they would spend hundreds of hours simply attempting to locate the issue.

DevOps’s future will be AI-driven. Because humans are incapable of handling the huge amounts of data and computation required for daily operations, artificial intelligence will become a vital tool for computing and analysis, revolutionising how teams design, deliver, deploy, and manage applications.

How is Artificial Intelligence transforming the DevOps space?

Artificial intelligence is poised to become the next competitive force in the DevOps space and here are a few reasons why:-

1. DevOps revolutionising product development process and automation of CI/CD pipeline

With the emergence of Microservices and agile approaches, developers began producing software in smaller, incremental cycles as modular independent services as opposed to following the classic waterfall style of software development. DevOps enables enterprises to more effectively handle microservices, SOA, and agile systems. It combines heterogeneous systems into a unified whole. It enables you to create a continuous integration/continuous delivery pipeline and automate the entire process.

Pipelines for continuous integration (CI) or continuous delivery (CD) are implemented to ensure that services are delivered in a systematic and well-organized manner. These pipelines incorporate comprehensive analysis and automated procedures throughout the software development process. DevOps is the pipeline’s backbone, as it is through this team that software can be generated and tested concurrently, particularly throughout the integration process.

2. The amalgamation of new technologies in DevOps

Cloud technology and services are easily integrated into DevOps processes since they complement them. Businesses that rely heavily on developers for operations frequently leverage cloud computing to boost developers’ productivity and efficiency. Cloud computing enables developers to exert greater control over their components, which results in faster response times. By integrating cloud software and resources to streamline the code development, management, and deployment processes, business teams may accelerate production, eliminate human error, and enable repeatability.

Cloud and DevOps, as a hybrid methodology, could be used to illustrate the appropriate operational strategies and activities associated with various cloud platforms or resources, such as SaaS, IaaS, or PaaS applications. Due to this approach, the dynamics of development and operations in a service-oriented environment are fundamentally different. While these services enable rapid deployment and management of applications across an infrastructure, they can be difficult to maintain across teams.

3. The role of new-age technologies in transforming the way businesses deliver solutions to customers

Customer Relationship Management has taken a turn ever since new-age technologies were introduced. It enables businesses to perform several tasks easily and efficiently. They include:-

 

  • Analysing customer records and business data collected through sales, e-commerce activity, emails, IoT produced data, and social media, among other sources, to generate automatic insights.
  • Assist sales representatives in focusing on the most promising leads through the analysis of engagement data and powerful lead scoring tools.
  • Assist in determining the ideal person to contact in order to secure the opportunity.

4. Role of AI in DevOps to improve communication between teams and prediction of factors leading to bottleneck for projects

DevOps teams are increasingly relying on artificial intelligence and augmented tools to boost efficiency and ensure continuous workflow. With the appropriate tools, communication, the management of routine assignments and processes, as well as security concerns, may all be addressed. DevOps teams may greatly boost the speed and scope of their work by leveraging AI and machine learning techniques.

 

Intelligent tools can assist in automating procedures and suggesting performance improvements in order to produce higher-quality code and reduce the number of errors in less time.

5. Diagnosing organisational issues, failures in patterns and increasing system efficiency

Machine learning-based code vulnerability detection can accurately identify anomalies and notify DevOps teams in real-time. AI is proving to be excellent at detecting bugs and making auto-suggestions for code improvement.

 

Advanced DevOps teams leverage artificial intelligence (AI) to evaluate and uncover new insights across all development tools, application performance monitoring (APM), software quality assurance (QA), and release cycle systems. DevOps teams at a large enterprise supply chain management (SCM) software supplier are leveraging AI to understand why certain projects succeed and produce good code, while others become mired in eternal review and code rewrite cycles.

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