Full Stack Vs. DevOps

DevOps is a conjugation of the term “development” and “operations” to emphasize how functions integrate across IT teams. DevOps strategies promote seamless building, testing, and deployment of products. It aims to bridge a gap between development and operations teams to streamline the development altogether. Full-stack development represents the ability to operate and design at both user interface level and back-end level and, therefore, a programmer with the full skill set to perform all functions to bring web apps to life.

full-stack-development
There are three segments of web development and design. One is dealing with the user interface or what the customer sees. Front End development is responsible for the crucial elements that make up the presentation of the page. The next is Back End, which handles the processes involved in the web page. It deals with information validation, database management, as well as transactions. As businesses continue to grow, the third segment emerged to accommodate their increasing needs and lucrative goals. Building applications from end-to-end is what makes a full stack developer. It is a more versatile role that is considered the Jack of All Trades.
devops-engineering
DevOps refers to a series of practices performed to perform automated software development processes. It is a conjugation of the term “development” and “operations” to emphasize how functions integrate across IT teams. DevOps strategies promote seamless building, testing, and deployment of products. It aims to bridge a gap between development and operations teams to streamline the development altogether.

Connected Business Frameworks

AIOps

aiops
AIOps is the application of artificial intelligence to IT operations. It has become particularly useful for modern IT management in hybridized, distributed, and dynamic environments. AIOps has become a key operational component of modern digital-based organizations, built around software and algorithms.

Machine Learning

mlops
Machine Learning Ops (MLOps) describes a suite of best practices that successfully help a business run artificial intelligence. It consists of the skills, workflows, and processes to create, run, and maintain machine learning models to help various operational processes within organizations.

Continuous Intelligence

continuous-intelligence-business-model
The business intelligence models have transitioned to continuous intelligence, where dynamic technology infrastructure is coupled with continuous deployment and delivery to provide continuous intelligence. In short, the software offered in the cloud will integrate with the company’s data, leveraging on AI/ML to provide answers in real-time to current issues the organization might be experiencing.

Continuous Innovation

continuous-innovation
That is a process that requires a continuous feedback loop to develop a valuable product and build a viable business model. Continuous innovation is a mindset where products and services are designed and delivered to tune them around the customers’ problems and not the technical solution of its founders.

Technological Modeling

technological-modeling
Technological modeling is a discipline to provide the basis for companies to sustain innovation, thus developing incremental products. While also looking at breakthrough innovative products that can pave the way for long-term success. In a sort of Barbell Strategy, technological modeling suggests having a two-sided approach, on the one hand, to keep sustaining continuous innovation as a core part of the business model. On the other hand, it places bets on future developments that have the potential to break through and take a leap forward.

Business Engineering

business-engineering-manifesto

Tech Business Model Template

business-model-template
A tech business model is made of four main components: value model (value propositions, missionvision), technological model (R&D management), distribution model (sales and marketing organizational structure), and financial model (revenue modeling, cost structure, profitability and cash generation/management). Those elements coming together can serve as the basis to build a solid tech business model.

Read Next: Full-Stack Development, DevOps, DevSecOps.

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Read Next: SecDevOps, Enterprise AI Business Model, IaaS vs PaaS vs SaaS, Business Engineer.

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