🎯🗒️Harvinder Atwal - Collected Quotes

"Agile practices can bring discipline to data science through support for the values and principles of DataOps. However, just as there is no perfect agile framework or set of practices for software development, there is no single set of best agile practices for data science. The right practices to use are context and organization specific and help data analytics teams become more adaptable and collaborative and tighten feedback loops to produce faster (and better) results. The successful application of agile and Lean thinking to data analytics requires observation, constant experimentation, and adjustment." (Harvinder Atwal, "Practical DataOps: Delivering Agile Data Science at Scale", 2020)

"DataOps does not prescribe a particular agile framework, set of practices, artifacts, or roles. Nonetheless, instead of inventing new ways of working, it is better to adapt existing proven practices and combining them as needed. The following are useful agile practices aligned with DataOps principles. However, none are compulsory, and if you find they do not add value, do not use them. Agile frameworks are not mutually exclusive, and practices are situation and context-dependent. You can explore alternatives as long as you stay true to DataOps values and principles." (Harvinder Atwal, "Practical DataOps: Delivering Agile Data Science at Scale", 2020)

"DataOps is not a project. The first iteration of DataOps is not the last. With minimum viable DataOps in place and benefits publicized, the next stage is to expand practices to more domains and epics. The second objective is to get to a tipping point where it becomes more compelling to continue the journey of implementing DataOps practices, principles, and values than to resist them. Results speak louder than words. It remains essential to avoid diversions into time-consuming political battles with hard-to-change departments or to waste time developing a large-scale change management program." (Harvinder Atwal, "Practical DataOps: Delivering Agile Data Science at Scale", 2020) 

"DataOps methodology is the best way to eliminate barriers, collaborate, and maximize the chances of success. DataOps turns data science and analytics from the craft industry it is today in most organizations into a slick manufacturing operation. DataOps enables rapid data product development and creates an assembly line that converts raw data from multiple sources into production data products with a minimum of waste. (Harvinder Atwal, "Practical DataOps: Delivering Agile Data Science at Scale", 2020) 

"DataOps requires that data scientists, data analysts, and data engineers have quick access to data, tools, and infrastructure to eliminate bottlenecks. That is, they need to be able to access, add, or modify data quickly by themselves. We term this availability to data self-service. Through self-service, data analytics professionals can create data products in far less time than with traditional approaches." (Harvinder Atwal, "Practical DataOps: Delivering Agile Data Science at Scale", 2020)

"DataOps should be part of a well-thought-out data strategy that lays the foundation for a transformation. Actually, all organizations that want to use data for data-sharing or analytical purposes need a data strategy. The only variation will be the depth of strategy and complexity of use cases. A start-up’s data strategy might not need the same detail and span as a multinational corporation, but it should still define a means to prepare for the future." (Harvinder Atwal, "Practical DataOps: Delivering Agile Data Science at Scale", 2020)

"DevOps effectiveness increases when there is less heterogeneity in the technology stack. Complexity increases the probability of errors and slows down the flow of deployment because teams find it hard to scale their expertise and apply consistent patterns across data pipelines. The focus of data analytics teams after adopting version control should be to standardize and simplify the set of technologies they use from languages, libraries, and databases to data engineering tools." (Harvinder Atwal, "Practical DataOps: Delivering Agile Data Science at Scale", 2020)

"The final stage of DevOps for DataOps is to automate the build of pipeline environments and give data pipeline developers self-serve ability to create, test, and deploy changes." (Harvinder Atwal, "Practical DataOps: Delivering Agile Data Science at Scale", 2020) 

"Unless dealing with a greenfield situation, it is not possible to jump straight to the end state of all analytical work following the DataOps methodology. Respecting the principles of agile and DevOps, the movement to the end goal must be in iterative, small, and frequent steps." (Harvinder Atwal, "Practical DataOps: Delivering Agile Data Science at Scale", 2020) 

"While there are undoubtedly success stories, there is also plenty of evidence that substantial investment in data science is not generating the returns expected for a majority of organizations." (Harvinder Atwal, "Practical DataOps: Delivering Agile Data Science at Scale", 2020) 

🌁Software Engineering: DevOps (Definitions)

"An application delivery philosophy that stresses communication, collaboration, and integration between software developers and their information technology (IT) counterparts in operations. DevOps is a response to the interdependence of software development and IT operations. It aims to help an organization rapidly produce software products and services." (Pierre Pureur & Murat Erder, "Continuous Architecture", 2015)

DevOps is an approach based on lean and agile principles in which business owners and the development, operations, and quality assurance departments collaborate to deliver software in a continuous manner that enables the business to more quickly seize market opportunities and reduce the time to include customer feedback. Indeed, enterprise (Sanjeev Sharma & Bernie Coyne, "DevOps For Dummies" 2nd Ed, 2015)

"Is a method for software development and management that integrates the development and deployment cycles to achieve a more agile, continuous evolution of software-based products and services" (Diego R López & Pedro A. Aranda, "Network Functions Virtualization: Going beyond the Carrier Cloud", 2015)

"DevOps is a mindset, a culture, and a set of technical practices. It provides communication, integration, automation, and close cooperation among all the people needed to plan, develop, test, deploy, release, and maintain a Solution." (Dean Leffingwell, "SAFe 4.5 Reference Guide: Scaled Agile Framework for Lean Enterprises" 2nd Ed., 2018)

"Short for development operations, an information technology environment in which development and operations are tightly tied together, yielding small incremental releases to gain user feedback." (O Sami Saydjari, "Engineering Trustworthy Systems: Get Cybersecurity Design Right the First Time", 2018)

"The practice of incorporating developers and members of operations and quality assurance (QA) staff into software development projects to align their incentives and enable frequent, efficient, and reliable releases of software products." (Shon Harris & Fernando Maymi, "CISSP All-in-One Exam Guide" 8th Ed., 2018)

"The tighter integration between the developers of applications and the IT department that tests and deploys them. DevOps is said to be the intersection of software engineering, quality assurance, and operations." (William Stallings, "Effective Cybersecurity: A Guide to Using Best Practices and Standards", 2018)

"A software engineering practice that aims at unifying software development (Dev) and software operation (Ops)." (Jun Bi et al, "Automatic Address Scheduling and Management for Broadband IP Networks", Emerging Automation Techniques for the Future Internet, 2019)

"Develop operations, or DevOps, is an agile methodology that merges the functions of software development and operations in the enterprise software development domain. This approach has been adopted in the networking world to facilitate a programmable approach to network operations. Often when applied to networking the term is changed to NetOps." (Patrick Moore, "Model-Centric Fulfillment Operations and Maintenance Automation", Emerging Automation Techniques for the Future Internet, 2019)

"Practices and technologies that promote tighter coupling of software development (Dev) and operations (Ops) - typically marked by more automation, continuous monitoring, shorter development cycles and higher deployment frequencies. A key driver for security policy automation. DevSecOps is a related term that refers to practices and technologies that aim to embed security in DevOps practices." (Myo Zarny et al, "Network Security Policy Automation: Enterprise Use Cases and Methodologies", 2019)

"Development and operations is an abbreviation for 'development' and 'operations'; is a software engineering methodology for managing software development (Dev) and technology operations (Ops). The main aim of DevOps is to enable automation and tracing for all phases of software implementation, from integration, testing, releasing to deployment and infrastructure management." (Antoine Trad & Damir Kalpić, "Using Applied Mathematical Models for Business Transformation", 2020)

"Development and operations (DevOps) has been adopted by prominent software and service companies (e.g., IBM) to support enhanced collaboration across the company and its value chain partners. In this way, DevOps facilitates uninterrupted delivery and coexistence between development and operation facilities, enhances the quality and performance of software applications, improving end-user experience, and help to simultaneous deployment of software across different platforms." (Kamalendu Pal & Bill Karakostas, "Software Testing Under Agile, Scrum, and DevOps", 2021)

"DevOps is a sprint-based approach that can catch coding flaws during the development of code due to security reviews, rework on previous sprint cycles, and testing." (David A Bird, "Hacker and Non-Attributed State Actors", Real-Time and Retrospective Analyses of Cyber Security, 2021)

"It is a set of practices emerging to bridge the gaps between operation and developer teams to achieve a better collaboration." (Mirna Muñoz, "Boosting the Competitiveness of Organizations With the Use of Software Engineering", 2021)

"It is a way to work were the software is rapidly developed and immediately deployed for operating in a computational productive environment. It is continuous delivery product development lifecycle. It must automate the development process. DevOps is both a culture and a set of technologies and tools used for automation." Laura C Rodriguez-Martinez et al, "Service-Oriented Computing Applications (SOCA) Development Methodologies: A Review of Agility-Rigor Balance", 2021)

"People from software development and operations work together to enhance the speed of delivery of new software features. It is a concept for bridging the gap between software development and software operations and integrating the logic of common responsibility for the complete software delivery lifecycle into one cross-functional team." (Anna Wiedemann et al, "Transforming Disciplined IT Functions: Guidelines for DevOps Integration", 2021)

"DevOps is a set of tools and processes that help automate IT operations." (Aniruddha Deswandikar,"Engineering Data Mesh in Azure Cloud", 2024)

"DevOps is a catch‑all term for the blending of roles between developers and operations engineers. As the barriers between roles such as database administrator, systems administrator, and software engineer have eroded, the term DevOps has emerged as a way of describing the intersection of responsibilities from all these camps, and their increasing interrelation in the lifecycle of a product. A crucial enabling aspect of this movement is the increased use of automation in building, deploying, and monitoring large applications." (NGINX) [source]

"DevOps is a collection of best practices and working methods for the software development process whose cumulative goal is to shorten the development life cycle and support practice such as continuous integration, continuous delivery and continuous deployment." (Sum Logic) [source]

"DevOps is a set of practices that works to automate and integrate the processes between software development and IT teams, so they can build, test, and release software faster and more reliably." Atlassian [source] 

"DevOps is the combination of cultural philosophies, practices, and tools that increases an organization’s ability to deliver applications and services at high velocity: evolving and improving products at a faster pace than organizations using traditional software development and infrastructure management processes." (Amazon) [source]

"DevOps refers to a broad range of practices related to the development and operation of software code in production in cloud data centers. DevOps is centered in Agile project management techniques and microservice support. DevOps approaches the entire software development lifecycle with automation based around version control standards." (VMWare) [source]

"The cultural movement that stresses communication, collaboration and integration between software developers and IT operations." (Global Knowledge)

⛩️Michael Hüttermann - Collected Quotes

"Agile development methods require a disciplined approach to ensure that customer feedback, continuous testing, and iterative development actually lead to frequent deliveries of working, valuable software." (Michael Hüttermann et al, "DevOps for Developers", 2013)

"Agile development teams often view metrics as a onetime pointer instead of a continuous measurement. The pointer makes the current state of the software’s internal quality visible. It is then up to the team to decide when to adjust the code base or whether to do so at all. These pointers provide indicators that there’s something worth investigating, but they don’t provide the context and understanding needed to make critical decisions." (Michael Hüttermann et al, "DevOps for Developers", 2013)

"Agile teams often do not distinguish between bugs, enhancements, or change requests. They use a general unit called change to track progress. Change seems to be a valid unit for both development and operations because operations teams primarily think in terms of changes to the production system. Using changes as a shared term for both development and operations makes it easier to stream production issues back to a work backlog (that is ideally shared by both groups)." (Michael Hüttermann et al, "DevOps for Developers", 2013)

"Automation is an essential backbone of DevOps. Automation is the use of solutions to reduce the need for human work. Automation can ensure that the software is built the same way each time, that the team sees every change made to the software, and that the software is tested and reviewed in the same way every day so that no defects slip through or are introduced through human error." (Michael Hüttermann et al, "DevOps for Developers", 2013)

"Conflicts between development and operations teams often originate from time pressures. Typically, a new software release must be deployed quickly. Another scenario that requires operations team to react quickly is when the system is down, and restoring it quickly becomes the highest priority. Th is situation often leads to a blame game where each side accuses the other of causing the problem." (Michael Hüttermann et al, "DevOps for Developers", 2013)

"DevOps is a mix of patterns intended to improve collaboration between development and operations. DevOps addresses shared goals and incentives as well as shared processes and tools. Because of the natural conflicts among different groups, shared goals and incentives may not always be achievable. However, they should at least be aligned with one another." (Michael Hüttermann et al, "DevOps for Developers", 2013)

"DevOps is about team play and a collaborative problem-solving approach. If a service goes down, everyone must know what procedures to follow to diagnose the problem and get the system up and running again. Additionally, all of the roles and skills necessary to perform these tasks must be available and able to work together well. Training and effective collaboration are critical here." (Michael Hüttermann et al, "DevOps for Developers", 2013)

"DevOps is essentially about gaining fast feedback and decreasing the risk of releases through a holistic approach that is meaningful for both development and operations. One major step for achieving this approach is to improve the fl ow of features from their inception to availability. This process can be refined to the point that it becomes important to reduce batch size (the size of one package of changes or the amount of work that is done before the new version is shipped) without changing capacity or demand." (Michael Hüttermann et al, "DevOps for Developers", 2013)

"Essential to improving collaboration is the alignment of incentives across teams as well as the application of shared processes and tools. The main attributes of aligned incentives include a shared definition of quality for the whole project or company and a commitment to it. Aligned with defined quality attributes, visibility and transparency can help to foster collaboration. Incentives must treat the development and operations groups as one team. That is, they should be rewarded for developing many changes that are stable and shipped."(Michael Hüttermann et al, "DevOps for Developers", 2013)

"Stability is often defined as a resilient system that keeps processing transactions, even if transient impulses (rapid shocks to the system), persistent stresses (force applied to the system over an extended period), or component failures disrupt normal processing." (Michael Hüttermann et al, "DevOps for Developers", 2013)

"The advantages of Agile processes, including Scrum and Kanban (a method for delivering software with an emphasis on just-in-time delivery), are often nullified because of the obstacles to collaboration, processes, and tools that are built up in front of operations." (Michael Hüttermann et al, "DevOps for Developers", 2013)