Getting Smarter With DevOps
In software application, there was a time when user experience was compromised for functionality. From the increasing need for innovation on the systems side of technology came DevOps, the practice of operations and development engineers working together in the entire service lifecycle — from design through the development process to production support. The DevOps methodology dictates that development and operations teams collaborate and communicate to ensure rapid delivery.
In the software industry, there is an inherent assumption that projects will run late. Upon application delivery, businesses can be afraid of the software being breakable. Even once a site is live, unexpected problems may be picked up by admins or helpdesk. And when people are siloed, the frequency of these problems increases: Developers, RMs, admins, and the QA team.
The traditional process is wasteful, prone to problems, and prone to the problem of “pass on the problem.” DevOps — as a philosophy, method, movement, or methodology — says there is a better way. Teams built around people who can be developers, admins, and testers are magnificent teams.
At core, DevOps is an approach. Mark Warren, director of product marketing for a source code management and collaboration platform maker, says DevOps is “a thing everybody wants but nobody wants to do.” Interesting and important is the fact that DevOps for hybrid clouds will soon become de rigueur for process transformation in medium and large enterprises.
In order to better fit outsourcing engagements into a DevOps-enabled enterprise, organizations will have to get smarter about how they construct their relationships with outside support.
DevOps at the organizational level is driven largely at three levels: The development team, the QA team, and the IT team. Each entity tries to solve the problem of reducing GTM for any application or software product.
The DevOps automation challenge can be addressed with a functional aggregator that solves the issues of collaboration between teams — development, QA, and IT — which is required to successfully implement the automation of any SDLC pipeline. This involves continued integration: Continued deployment / delivery, agile development, testing, and automated infrastructure provisioning, scaling and decommissioning. Achieving this modular requirement at three different BU levels to bring about a change in DevOps implementation calls for a modular architecture.
A good, modular DevOps solution can bring about the right amount of change in clients’ environments, keeping in mind existing investments at various LOB levels — and while causing the least possible disruption in existing methodologies and processes. It remains an enterprise-level challenge to re-utilize an investment in such a solution while bringing about a single pane of orchestration to encompass a multi-tool landscape.
Similarly, a good DevOps solution can accelerate software delivery via a Continuous Delivery environment. It can leverage your existing ALM tool investments, use industry best practices, and offer a self-service mechanism for Dev-Test provisioning in cloud or hybrid environments.
Organizations must rethink their development strategy — right from infrastructure agility to the blueprint deployment. AThese aspects include: consultancy, reference architecture, demo/PoC, dedicated DevOps CoE, implementation, optimization and sustenance.
Similarly, a good DevOps solution can also accelerate software delivery via a Continuous Delivery environment. It can leverage your existing ALM tool investments, use industry best practices, and offer a self-service mechanism for Dev-Test provisioning in cloud or hybrid environments.
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