DevOps has been instrumental in transforming IT responsiveness to business, as is evident by the fact that we have enterprises from all walks of life including Banks adopting DevOps. It’s certainly not a thing that hip web companies do now. However, with this rush to “do” DevOps comes the noise associated with it and hence, the confusions. I’ve been asked quite a bit off late we’re practicing Lean Kanban already how would DevOps help us? or even Do we need to do DevOps when we’re practicing lean? This blog is an attempt at two things, at showing how DevOps borrows Lean principles and it’s really not an either/or equation between these practices as they complement each other. DevOps While there are many definitions of DevOps the one I like to stick to is: "A cultural and professional movement that stresses communication, collaboration and integration between software developers and IT operations professionals while automating the process of software delivery and infrastructure changes". While there wasn’t necessarily anything more to DevOps than an observe and solve sort of cycle initially. Over the years we’ve had a more formalised way of working in DevOps. I’d still say most of it is common sense but then creating a structure or nomenclature does help majority of human beings to identify better. DevOps therefore has certain principles that make up most of what we know as DevOps today. Lean Most of us would know Lean well enough; the classic definition in IT industry context is "Lean IT applies the key ideas behind lean production to the development and management of IT products and services". And to know more about Lean Production you can start from here. Let’s look at the lean principles before I elaborate on this blog’s theme. 1. Define value precisely from the perspective of the end customer 2. Identify the entire value stream for each service, product or product family and eliminate waste 3. Make the remaining value-creating steps flow 4. As flow is introduced, let the customer pull what the customer wants when the customer wants it 5. Pursue perfection

DevOps is the acronym given to the combination of Development and Operations. It refers to a collaborative approach to make the Application Development team and the IT Operations team of an organization to seamlessly work with better communication. It is a philosophy that encourages adopting iterative software development, automation, and programmable infrastructure deployment and maintenance. DevOps emphasizes building trust and better liasioning between developers and system administrators. This helps the organization in aligning technological projects to business requirements. Changes rolled out are usually small and reversible, which the entire team begins to comprehend. DevOps is visualized as an infinite loop comprising the steps: plan, code, build, test, release, deploy, operate, monitor, then back to plan, and so on. While the visualization helps us understand how DevOps works, let us try to dig a little deeper to figure out which are the different DevOps tools, and how they help an organization. 1. Build Automation 2. Continuous Integration and Continuous Deployment 3. Infrastructure as Code 4. Configuration Management 5. Orchestration 6. Monitoring 7. Microservices Once you start following DevOps methodologies, it finds one way or the other to make the software act in a similar way right from development to production, via testing. It deploys changes individually, thus making bugs easily visible. These, once discovered, lead to code improvements through investigations and constant feedback channels. While developers run live software and IT Ops are involved in design meetings – both of them, along with other specialists, can contribute to investigations and feedback channels, which help foster a DevOps culture. With the cycle time from ideation to software going live reduced, your organization can capitalize on market opportunities, thus providing you with a competitive advantage for your business. Evolution of DevOps Originally coined by Patrick Debois, DevOps has become a critical discipline for realizing the benefits of Agile that ensures that rapid, iterative code development results in rapid, iterative code deployment! While Agile’s gained popularity, often at cross-purposes with the more formal and “heavy” ITIL methods popular with IT in the early and mid-2000s, DevOps resonated with both sides. Organizations that have adopted ITIL can also implement DevOps, especially for Cloud-based applications. Starting with The Phoenix Project, by Gene Kim, DevOps has steadily gained popularity and supporters and is seen today as a crucial element of any Agile technology organization. Consequently, large corporations and all sorts of technology vendors now support DevOps. DevOps jobs have become ever more popular – and the norm – in Hitech organizations. With the emergence of AI and ML in all aspects of the software lifecycle, AI for DevOps is starting to make DevOps even more smart, fast and seamless – tho’ a lot remains to be done.

Digital Transformation (DX) is one of the, if not the, most crucial initiatives that many organizations have undertaken or are taking up. The perfect storm of a wide range of technologies such as SaaS, Mobile, Robotics, IoT (Internet of things), Virtual Reality (VR), etc. is playing a crucial role in the Digital Transformation (DX) of companies. However, it is our belief that Artificial Intelligence (AI) and Machine Learning (ML) will be the key technologies that will propel organizations through the Digital Transformation. Let’s dive in: 1. What is Artificial Intelligence (AI)? 2. The Resurgence of AI 3. Applications of AI in Real World 4. Implications of AI in Workplace 5. What’s Ahead? 6. Digité & Artificial Intelligence Thinking about Artificial Intelligence (AI) may seem like thinking of a futuristic world akin to those in science fiction movies, but in actuality, the lines between reality and fiction have blurred. AI is changing the world and the lives of people and is becoming the engine of growth of economies and organizations. Whether it is a simple Google Search, a conversation with Amazon Alexa or Google Home or Apple’s Siri, or a simple Chatbot on some website you visited, you may already be interacting with AI/ ML-driven tools and – well – bots – in many of your daily activities!  This, without a doubt, is changing the way we perform our daily activities, organize our work, our business and how we take decisions in our everyday lives. According to International Data Corporation (IDC), at least 40% of organizations will have a fully staffed Digital Leadership Team versus a Single DX Executive Lead to accelerate enterprise-wide DX initiatives. 40% of all DX initiatives will be related to AI. Web interfaces will be quite diversified, with 30% of all web browsing sessions will be done using Augmented Reality (AR) and about 50% of all new mobile applications will have voice as their main interface for people to use them. Artificial Intelligence (AI) is here to stay and is leading an industrial revolution to make organizations more competitive and efficient. AI has already become a strategic factor to generate sustained growth and provide a competitive advantage to organizations. The challenge for all of us is how we manage the changes needed in organization structure, management culture and the investment needed in the development of skills so that the workforce has the capability to adapt to this global trend that we already find in our professional and personal lives. https://www.digite.com/blog/digital-transformation-and-artificial-intelligence/

https://www.digite.com/blog/Waterfall-vs-Agile-Project-Management-Approaches

What Does Adopting Agile at Scale Mean? The idea of scaling agile is to enable you to adapt and stay competitive by responding quickly and adequately to customers’ needs and adding delightful touches to keep customers coming back for more. Ultimately, and in practical terms, it means spreading agile working to every team at every level and in every department — including top management, and reducing coordination and control to a minimum. The main tools for this are autonomous teams, alignment on values and goals, and accountability and transparency at every level — both up and down what remains of an original hierarchical structure. Obviously, you’ll be dealing with different issues spreading agile to one or more teams within the same department, than when making the jump to departments beyond software engineering or IT (where agile originated). The variety in scaled agile frameworks, the structure and practices they advocate, and what specific issues they address, varies. Which one will suit you most depends on what stage you’re in on your agile journey and how well what a framework is designed to accomplish fits your aspirations for scaling agile and eventually becoming an agile business. Now, this is important, there’s a lot more to do than adopt a framework. What Are the Real Challenges in Scaling Agile? A framework helps you avoid reinventing the wheel with regard to the structure, processes and the principles to follow for you to become agile. But the real challenges in an agile transition are at a completely different level. They have to do with the mindset and the culture you need to become truly agile: letting go off (much of your) control and trusting that everyone wants to perform at their best.

What is Agility in teams and business? Agility is the ability of an individual, team, or organization to adapt and respond rapidly, creatively, effectively, and flexibly to market changes for better outcomes to all stakeholders. In the current VUCA (Volatile, Uncertain, Complex and Ambiguous) environment, both Threats and Opportunities arrive faster than ever. This is being further accelerated by the disruptive nature of technology that is forcing the reimaging of old ways. Businesses must embrace agility to adapt faster and thrive or face the prospect of becoming irrelevant and perhaps extinct. Among other things, it involves scanning the (business) environment, seeking inputs, detecting changes, analyze, and understanding the impact of the changes, and best responding to the (business) challenges. What is an Agile Mindset? Though this term is used widely, it doesn’t have a good, agreed-upon definition. In most cases, it gets defined as a set of attitudes and behaviors that allow for value delivery, being open, facilitating collaboration, teamwork, creative thinking, rapid iteration, continuous improvement, etc. Some others define it even more broadly – the mindset that allows agile to flourish is the agile mindset. Yet others define it as an agile mindset as opposed to a fixed mindset.

Project management software is a tool that helps you plan, manage and execute your projects in a disciplined way. Project management software is used by a wide range of companies to enable project planning, resource allocation and scheduling of activities. Till recent times, Project Management was thought to be just a hand-drawn concept following a set methodology. But now with Project Management software, a user or an organization can carry out all the steps of Project Management on a designated tool, usually customized to suit the requirements of the team/ project. A Project is made up of a series of interrelated tasks each with its peculiarities and the use of project management software is inevitable, as it helps managers to analyze the interactions between the tasks and plan them efficiently, identifying the most advantageous paths for the team to follow during task execution.

SwiftEnterprise simplifies enterprise project management for large businesses by making it easy to plan, schedule and manage resources using agile and AI-enabled approach.