The Difference between DevOps, PrivacyOps & AIOps

Ever since the industrial revolution, humans have been looking at ways to simplify their operations, whether that be manufacturing, or development. Fast forward to the present and we are still trying to gain maximum output from minimum input. If we look at this specifically in the IT sector, several frameworks have surfaced which promote the concept of more output from minimal input. These frameworks can be categorized into DevOps, PrivacyOps and AIOps.

In this article we will discuss each framework and how it helps to improve an organization’s IT department and software development processes.

SEE ALSO: Moogsoft Enterprise 8.0 interview: “AIOps is here to stay”

DevOps

DevOps is probably the most used and popular framework out of the three. This is the first agile software development framework that increases software velocity.

According to the study by Forrester, only 17% of teams can use delivery software fast enough. Before the concept of DevOps, teams were created to handle separate tasks of the same software. One team is tasked with gathering business requirements for a given software program and writing its code. Then the QA team tests the program in an isolated development environment. Once requirements are met, the code is released for operations to deploy.

The deployment teams are further scattered into groups such as networking and databases. This causes a disparity in the organization and the back and forth can add bottlenecks in the operation.

The DevOps framework promotes a collaborative cross-functional environment where all three teams share responsibility for maintaining the system and preparing the software to run on that system.

PrivacyOps

Global privacy regulations are on the rise, which has given birth to the PrivacyOps framework. This approach brings together the IT department with legal teams to help organizations comply with privacy regulations.

PrivacyOps is the combination of practices, and cross-functional collaboration to improve an organization’s ability to comply with global privacy regulations with efficiency and effectiveness.

The PrivacyOps framework brings together legal, data, IT, and information security teams under one roof to collaborate and communicate for the most essential practices of privacy compliance.

The PrivacyOps framework is based on the following:

System of Engagement

The system of engagement brings collaboration between teams towards the privacy-related information in a safe and secure platform. This is deemed more reliable than sending personal data over messaging systems or emails for review and approvals.

System of Insights

Using AI, bots, and intuitive visualization, it provides real-time insights about all aspects of privacy compliance, including PI data risks, DSR fulfillment status, regulatory compliance posture, vendor risks, user consent, etc. in one place.

System of Automation and Orchestration

Automates and orchestrates complex tasks like DSR fulfillment, PI Data linking, consent lifecycle management, recording audit records, etc. to reduce cost and avoid penalties.

System of Records

Help organizations keep a record of all privacy-related information such as PI linkage graphs, assessments, data maps, regulatory templates, and vendor documents in one place.

Incorporating PrivacyOps can offer your organization with the following benefits:

• Better understanding of data privacy regulations and compliance requirements within the organization
• Real-time view of all data privacy risks
• Accomplish and maintain compliance in an efficient and effective manner
• Ensures reliability of various aspects of privacy compliance across the organization.
• Increased expertise and privacy understanding of teams within the organization
• Enable effective collaboration across various teams
• Unique market position with trust-based relationships with both prospective and current clients.

AIOps

AIOps is the incorporation of artificial intelligence and machine learning into the DevOps framework. The integration of artificial intelligence can have the following results in the IT industry:

• AIOps can allow processing of all types of data generated by your systems with speed and precision. This will ensure fidelity and data integrity, resulting in a comprehensive analysis and tangible results.
• AIOps can help analyze data creating actionable insights that can then be used by DevOps engineers can then distinguish the need for infrastructure adjustments.
• After identifying event patterns, automated triggers can be set in place. This means that when statistics show certain events that always lead to a particular result that requires specific actions to be performed to rectify the issue, DevOps engineers can create the triggers and automate the responses to such events.

AIOps integration can allow organizations to enjoy the following benefits:

• Uninterrupted product availability
• Preemptive problem solving
• Removal of data silos
• Automation
• Collaboration

SEE ALSO: IBM open sources toolkit for AI development with Jupyter Notebook

Key Takeaway

Organizations are developing new ways to simplify their operations. The evolution of DevOps to AIOps and now PrivacyOps is a clear indication these frameworks will continue to evolve and adapt which will further help organizations create single teams that work in collaboration towards several organizational goals and objectives.

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