Next-Generation DevOps: Self-Learning Systems

The massive enterprise movement toward all things “digital” has accelerated the adoption of DevOps in all kinds of projects, but particularly in digital transformation initiatives. Apart from the productivity benefits gained by automating software development and rollout, the increased agility has helped move DevOps adoption to gain critical mass in a relatively short time.

However, challenges remain, particularly in ensuring the alignment of the three dimensions of business systems enabled by DevOps—people, process and technology—are coordinated enough to achieve desired outcomes. The “churn” in each of these three dimensions with every software release—particularly given constantly changing technology, constantly evolving operating procedures to support business requirements and end users and the impact the churn has on the “people” dimension—cannot be underestimated.

To mitigate this churn, it is essential to implement a DevOps “composite system” that manages it methodically and systematically to bring some order to the seemingly chaotic mess of managing multiple moving systems at the same time. The composite system should essentially be able to deliver the following capabilities to address people, process and technology:

A Visibility Dashboard for all Stakeholders in the DevOps Value Chain

Visibility and relevance of their work is of prime importance for people to feel connected to a mission. In a typical software development life cycle (SDLC) in an Agile methodology executed through DevOps, there are many stakeholders involved, including business stakeholders, developers, testers, and support services personnel. In an integrated life cycle of constant and continuous software development, testing and rollout, the cycle can seem complex and never-ending. For a successful and motivated team committed to do their best, systems should provide a visibility dashboard customized to each individual based on their role in a project. The dashboard could involve gamification and relative performance visibility of trends at an individual and group/project level.

The purpose of such a dashboard is not just to improve visibility and individual performance but also bring in alignment and connect each member of a DevOps team with a broader mission of the project/company.

Event-driven Technology Automation Spurred by API Integration

The sheer complexity and number of technologies and platforms involved in a DevOps life cycle can be unnerving and intimidating at the same time. Ultimately, the aim of deploying technology to a process is to simplify and create efficient systems. To this end, DevOps technology architecture must be governed by two critical design principles:

  1. An event-driven architecture that enables asynchronous integration of data generated by different tools and technologies involved.
  2. An API-enabled interface at each level of DevOps process flow so that a change in underlying tooling does not (or should not) have an impact on the business.

Data Driven Self-Learning Systems to Constantly Streamline and Improve Processes

In systems heavily laden with interconnected tools and technology, a typical DevOps process is heavily automated. However, this is just a “first generation” maturity of DevOps evolution. Just as with the people dimension, where team members are constantly measured, benchmarked and improved, systems and processes need to evolve continuously.

Because of automation, integrated DevOps systems generate lots of data (systemic/process-related data including build cycle times, testing cycle times and operational data such as issue resolution) that can be harnessed and plowed back in. Next-gen maturity in DevOps is achieved through a data-enabled feedback engine that constantly improves the quality of DevOps processes and their performance. Advanced data analytics and machine learning algorithms can be implemented to monitor, track and improve DevOps performance metrics.

In summary, to implement next-generation DevOps, organizations need to consider a holistic approach to manage changes at people, technology and process levels. Each of these dimensions require unique needs and a keen understanding of what it takes to make a DevOps system work for all stakeholders involved.

The article was originally published on and is re-posted here by permission.

Madhavan Krishnan

Vice President of Cloud Computing Practice & Leader - Millennial Solutions Group, Virtusa. Madhavan is an experienced technology practitioner with a strong business orientation. He has more than 17 years of Global IT industry experience in multiple technology and business roles. In his current role, he is the head of Cloud computing practice in Virtusa with responsibility for competency development, client solutions, practice team development from Asia and P&L. Madhavan is an active contributor to the company’s millennial solutions strategy and an active exponent of impact of convergence effect of multiple technology trends at the intersection of Cloud, Mobility and Big Data. Madhavan’s experience cuts across different dimensions of the IT Services business including Global Delivery, Enterprise Architecture, incubating and scaling technology practices with P & L responsibility; presales and business development. Madhavan’s strength is in driving adoption of technology led business solutions for clients in both Global and emerging markets. He helped kick start and scaled several technology practices for a large IT Services provider from ground up including RFID /M2M and Mobility practice, Manufacturing and Retail Domain Solutions group and launching / running Cloud business. Madhavan is an active participant in various industry and client forums like CII, MAIT, RFID World Asia and was a member of RFID Integration Consortium in 2005. He has authored and published several technology and business papers over the years.

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