The Present and Future of DevOps — Part 1

Hand-in-Hand with Artificial Intelligence and Machine Learning [AI/ML]

DataOps

DevOps is known to accelerate the total build to deploy lifecycle. It uses automation to accelerate the total process. DevOps leverages Infrastructure as Code (IaC) and implements Continuous Integration and Continuous Delivery for software releases. On the other hand, DataOps aims to reduce the time taken for data analytics. The total process focuses on cutting down the time from strategy to modeling, which will lead to the extraction of more value from the project. All-in-all, DataOps combines the functionality and practices of DevOps, analytics, and Agile development to curate a solution that extracts value.

Automation and DevOps

Organizations need to embrace evolution to make shifts with their business strategy that complement the changing world. Thoughts must be given to a more streamlined, efficient, and productive software delivery. Automation enables faster integration and delivery, but emphasis must be provided to the whole system before automating the modules.

Security and DevOps

Security is a term that induces competence and confidence in a practice. Computing and security are the two that run parallel to each other. With the evolution of computing technology, security issues have also evolved. Innovation runs both ways; new technologies and security threats run concurrently.

Continued in Part 2

In Part 2 of this blog series, I will discuss my thoughts on:

  • Containerization
  • Kubernetes
  • DevOps Delivery
  • Platform as a Service (PaaS)
  • Software as a Service (SaaS)
  • DevOps Network Support
  • Expansion of Responsibilities
  • The Future of DevOps

Upcoming Articles

  1. The Present and Future of DevOps — Part 2

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