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Building software is a team game. Development teams appreciate collaborative workflows. DevOps implies fostering intra-team collaboration to an even greater extent. It sounds rational and excessive simultaneously. On the one hand, developers, testers, system administrators, and project managers always act as a crew to release a product. Hardly anybody can deny the decades of such a practice. The tighter the coordination of staff, the better the production process. Another collaboration tightener seems to be redundant. 

On the other hand, truly trouble-free workflows rarely exist. Technical errors, organizational failures, delays, and misunderstandings are still common things that compromise development lifecycles. In such a context, a better approach to the production process will never hurt. DevOps is in everyone’s ears today. Some call it a cultural shift in software development, while others consider DevOps a disruptive philosophy. 

What is DevOps? Isn’t it merely a reinvention of the wheel? And why is understanding DevOps important in the modern competitive environment? Let’s together dissect the phenomenon to find answers to those questions.

From Where did the Term ‘DevOps’ Come?

Development and operations constitute a traditional division in the waterfall SDLC. The segregation between writing code and operating deployed systems has an explicit logical and technical background. At least, that was the case before 2009 when Patrick Debois coined a synergetic acronym to merge two different activities: Dev (development) and Ops (operations). Was that a radical idea at the time? Indeed, it was. Combining programming, QA, deployment, and integration into a single unified workflow did not sound intuitive back then. 

What prerequisites for DevOps could we detect at that stage of software evolution? Super apps and heavy social-media platforms were gaining momentum. Furthermore, advanced hardware technologies supported the wave of mobile gadgets covering the planet. The continuous enlargement of development teams for building increasingly sophisticated software started resulting in various problems. 

The larger the staff, the tougher the coordination between team members. The more complex the product, the bigger the responsibilities such motley teams must share. Releasing a multifaceted product becomes a mess when operations specialists have little idea about the programmers’ routines and vice versa. Hence, complex software often faces bad infinity loops when seemingly finished products must go back to production for improvements, corrections, and bug-fixing. 

Delays and bugs don’t align with customer expectations. Disappointed users cause lost revenue, if not the commercial failure of the product. Never-ending competition encourages developers to boost their productivity and efficiency by any means. Thus, enough reasons have been accumulated to allow the DevOps movement to emerge. 

However, mass adoption of the new approach has not occurred instantly. It’s still having trouble finding its way into many organizations due to a sort of inertia inherent in software product development. In addition, the very Agile nature of DevOps provides quite a space for broad interpretations. No once-and-for-all established definition takes place. Many practitioners don’t mind if their development routines differ from what other people practice and call DevOps processes. That’s why no consensus is required to accept the phenomenon as either a culture, a philosophy, a movement, or anything else. You name it, as they say; understanding what’s behind the name is more crucial.

What Does DevOps Mean? 

Instead of breaking a lance over terminology to find a generally agreed-upon definition, we should focus on what the DevOps model allows us to achieve. Shortening the software development life cycle by applying a specific collaborative culture to the process can be the most inclusive objective in our context. 

We need a different mindset to turn a bad infinity loop into a good one. This means abandoning the negative legacy of the waterfall SDLC with its post-production tambourine dances. We should replace it with a smooth, self-perpetuating workflow, where borders between coding, testing, deployment, and integrations become pretty conditional. A good infinity loop of total awareness should start driving the entire team to faster releases in an errorless manner.

Why does using the infinity loop metaphor make sense here? It appropriately symbolizes how collaboration and communication let development stages harmoniously follow each other. It shows the phases through which all team members move to maintain alignment for better quality in less time. The development phases—such as discovering, planning, building, and testing—flow smoothly into operations via deployment with monitoring and gathering continuous feedback. After that, fresh insights energize a subsequent iteration of development routines, and the next loop appears. It’s better to imagine DevOps as a chain of many interweaving loops, representing a small part of an extensive, continuous process. 

The DevOps model of web development services requires interdisciplinary skills when engineers from one department face no constraints in grasping what engineers from the other department do. A sort of hybridization takes place to contribute to the entire workflow. A programmer-as-a-tester is more effective than a pure QA engineer. A sysadmin with coding skills can bring more benefits to the project than a pure coder. Hence, a lone genius creating miracle code in seclusion is not about the progressive conception of a valuable employee.

Expanding an SDLC beyond software development as such is one of the critical advantages of DevOps. No department is siloed in itself any longer: the DevOps values apply equally to security engineers and programmers, for example. They should adopt the new culture by sharing a joint vision and using a relevant toolset. DevOps tools reflect the basics with which the entire process runs. Automation and collaboration are the primary capabilities of any tool involved. At the same time, continuous integration (CI) and continuous delivery (CD) belong to the specific techniques of iterative improvements inherent in the DevOps toolchain. But more about the tools later.

DevOps Fundamentals

devops as a set of progressive models

Any movement (philosophy, culture, etc.) needs some conceptual pillars to be based upon. DevOps is no exception, and has what is known as CAMS: Culture, Automation, Measurement, and Sharing. John Willis and Damon Edwards introduced the acronym in 2010. CAMS is simply the DevOps motto that reflects four primary values of the model. Why only those four? Many agree that CAMS is enough to distinguish the model from other types of SDLC. It does not mean that the other approaches have nothing in common with automation or, for instance, sharing. But CAMS precisely describes what DevOps devotees appreciate the most. 


Culture is a broad notion that comprises many behavioral patterns attributed to the DevOps model. Continuous communication and collaboration, along with shared responsibility, belong to those patterns. The culture encourages every team member to bear responsibility for the entire project from A to Z and assist other staff in fulfilling their duties. Nobody can say, “It’s not my business,” since everyone cares about everything within the project. It’s like a company’s morale policy, but with no top-to-bottom coercion. 

Another aspect of the culture implies gradual changes across the entire SDLC when early problem-solving provides numerous opportunities for rolling any iteration back to set things right. 


Everything that can be automated must be automated. No compromises are acceptable regarding manual operations at any process by any department. All time-consuming activities should be abandoned if we strive to shorten an SDLC. The executives responsible for toolset selection should keep the automation of processes in mind to avoid leaving any facility and team members untouched. Fortunately, software evolution never stands still, and the market offers more automated solutions for every taste that only strengthen the existing benefits of DevOps.


Key performance indicators (KPIs) reveal how effectively one process or another runs. The more metrics you can measure across your workflow, the better. Data-driven assessment of progress eliminates uncertainty and helps optimize performance. KPI measurements go one by one to provide a holistic picture of your SDLC at any given moment. Continuous tracking of all activities is one of the typical DevOps processes. 


Sharing knowledge across the entire team entails improved collective intelligence. Sharing is about transparency: the more ample and frequent feedback from your colleagues, the easier you can find and fix any issue on the go. Bearing personal responsibility is stressful unless you share it with someone else. Collective decision-making and group work lie in the very essence of the DevOps model. Sharing problems with the team can result in faster and simpler problem-solving and, consequently, more effective workflows.

DevOps Techniques

devops as a set of progressive models

Almost all DevOps practices can be grouped under the common “continuous” refrain. Development, testing, deployment, monitoring, delivery, and integration all have “continuous” as an adjective. What “continuous” means in each case is worth considering.

Continuous Development (Integration)

All code changes from various programmers can be integrated into a single mainline. In many examples, this happens in a full or semi-automated mode. A central code repository becomes a hub for all developers who avoid integration conflicts that way. The more frequently they share their code, the fewer integration issues occur. Continuous development is an integral part of overall performance optimization. As they say, two minds are better than one, and continuous integration allows developers to use collective intelligence, however diverse their individual modules can be. Furthermore, cutting their work into small portions provides developers with easier testing and faster production.

Continuous Testing

“Continuous” in this context means “automated.” QA engineers use various tools for automated testing: UFT, Selenium, and the like. But more important is a different approach to quality: everyone is in charge of it, not only testers. This implies a continuous code circulation between programmers and QA engineers when their skills supplement each other in the earliest possible bug-fixing. Thus, vulnerabilities inherent in any preceding version almost automatically disappear from any subsequent one. This happens when a properly configured testing environment is spread across all departments: development, testing, and operations. Continuous monitoring by sysadmins adds to quality assurance as well. 

Continuous Delivery

Continuous delivery implies ready-to-deploy pieces of code arriving at operations via properly conducted testing. Sometimes, they’re exposed directly to end users. Still, sometimes, they have to go back to development with failures detected by continuous monitoring. High-performing teams can deliver updates two to three times a day. But even a weekly deployment belongs to continuous delivery. Development, testing, and deployment merge into a unified process that enables automated code to be delivered to a production environment. The smaller the release, the lower the chance of causing a critical failure for the whole project. Some sort of impact minimization takes place with such frequent deployments. Continuous delivery rightfully belongs to one of the most explicit examples of benefits of DevOps.

Continuous Monitoring

Continuous monitoring provides analyzing feedback from both the team and end-users. Detecting code pitfalls when executed in a product environment delivers valuable insights to developers. At the same time, continuous monitoring is more inclusive to cover the entire SDLC from planning to deployment. The goal is to identify the root causes of possible failures in real time. Anything that potentially threatens user experience must be detected and fixed before UX degradation goes too far. Preventing performance issues proactively is what continuous monitoring is aimed at. A corresponding monitoring infrastructure should also be available in development to detect performance issues before they affect production.

In addition to these continuous practices, some other specific aspects of the DevOps culture should be mentioned. They are integral components of the common matrix and are also important.

Infrastructure-as-a-Code (IaC)

This management approach facilitates all continuous practices mentioned above. Setting your infrastructure configurations quickly and consistently means treating all your working environments in complexity. Networks, virtual machines, on-premise facilities, and clouds should follow automatically-scripted scenarios to minimize manual infrastructure management. This is about easily scaling your SDLC when the script adds another environment to your infrastructure when necessary. Programmers and testers can hardly be against virtual machines, for instance, that behave akin to a production environment to test their code as early as possible. 


This architectural approach enables an application to consist of several independent services integrated into a cohesive operation mode. Each microservice can be configured individually to protect the other ones from its particular problems when they arise. Hence, even a total failure of one service does not affect the entire application. Due to inner structural diversification, the approach follows frequent deployments when the system is kept stable. Microservice architecture distinguishes DevOps-made apps from monolithic legacy systems in which any single vulnerability threatens the entire app.

Agile Planning

In contrast to conventional project management, Agile planning divides the project into numerous short stages called sprints (iterations). Each sprint implies a separate attempt to check a particular development idea for viability. The shorter the sprint, the bigger the number of releases. Multiple iterations provide an SDLC with sufficient flexibility in terms of feature design. Developers face no limits in creativity when they build every function of the future app in a recurrent trial-and-error mode. The Agile approach involves the entire team in each iteration to make sure that every piece of code successfully passes through development, testing, and operations.

Why Adopt DevOps?

devops as a set of progressive models

Many may doubt whether the DevOps workflow is a panacea against typical SDLC drawbacks. When a development company is delighted with its workflow, shifting to DevOps may seem unnecessary. However, the competitive advantages of DevOps allowing their rivals to do better and earn more can make such companies change their mind. Sometimes, pretty apparent disadvantages of the traditional non-DevOps SDLC remain unrecognizable until they are intentionally articulated. What makes your traditional workflow less efficient than it can be?

1. Siloed Teams

Mutual support through tight communication is rarely inherent in the traditional SDLC, where developers, test engineers, and system administrators work separately within their specific agendas. They mainly deal with a piece of code that moves gradually from development to operations. The responsibility framework of each department is quite tight and straightforwardly defined. When testers detect a bug, they don’t care how developers can fix it—their job is not about problem-solving. The same relates to sysadmins, project managers, executives, etc. On the other hand, developers do not care about testing and operations. Hence, the general approach to the final product is reactive rather than proactive. Needless to say that such a way of building apps is time-consuming and, therefore, inefficient.

2. Increased Problem Probability

Development and testing follow each other in a unit-by-unit order when a module (a piece of code) is exposed to testing after leaving programmers altogether. Hence, units go through tests individually in certain isolation. A bug detected in one unit appears irrelevant to similar bugs in other units. Therefore, fixing issues of one particular unit does not help decrease the overall problem probability by any means. The task segregation inherent in conventional SDLCs does not allow the team to predict and proactively neutralize many post-release problems due to poor intra-team collaboration.

3. Rework and Overtime Expenditures

The lack of communication between siloed departments leads to late reactions to end-user’s troubles with the product. Sometimes, updates and bug-fixing require rolling back the entire project, and a failed release may look fake. In addition to a significant degree of customer disappointment, a need for overtime rework may occur for many team members. It’s like surgery in medical treatment, which is always less healthy than timely preventive procedures.

4. Managerial Constraints

The insufficient transparency of siloed workflows results in various mismanagement situations and ill decision-making. Project managers and executives remain in uncertainty while siloed departments keep working with poor coordination. They must make numerous corrections in the preliminarily-made working plans, since bugs and failures cannot be predicted completely. In their attempts to correlate workflows of different departments on the go, leaders become fully involved in time-consuming routines instead of building business strategies.

5. Late and Costly Updates

Implementing updates and changes can take weeks, if not months, when developers, testers, and sysadmins work without continuous coordination. They use different tools to fulfill their specific tasks, having little to no idea what’s going on in neighboring teams. Project managers can hardly help much since they themselves see quite a conditional holistic picture. Even an insignificant code change must pass through the entire chain of an SDLC to be finally implemented. Every failure detected at operations requires developers and testers to interrupt their current work to decide who should fix it and how. Queues and delays start accumulating to form production bottlenecks that inevitably lead to wasting time and money. 

How DevOps Contributes to Staff

The benefits-vs-effort ratio can show why DevOps is important in general. However, some team members may suppose this culture is less relevant to them than to other specialists. Do QA engineers benefit from DevOps as much as developers do? And what about sysadmins and executives? Explanations and examples follow.


Working in a tightly collaborative mode allows developers to act more independently, as contradictory as this may sound. The secret is in setting a development working environment that correlates with operations. Such a hybrid space makes the duties of both developers and operations continuously overlap. Activities in the IT infrastructure are no longer a blind spot for developers. They can do what they do with no time-consuming approvals from sysadmins. Setting and resetting servers happens automatically in a transparent manner. At the same time, developers arrange their working environment in the way they need.

Their creativity faces no limits when all necessary resources (storage, computing power, networks, etc.) are at arm’s length. Developers appear to have more time for trying various options in coding, running advanced testing scenarios, and fixing issues with fewer interruptions. No sudden calls from operations about a down site, and no nasty surprises from testers. Every team member is aware of everything happening across the entire SDLC in real time. DevOps processes deliver much better job satisfaction to all staff in general, and developers in particular.

QA Specialists

A QA engineer is the most demanding position in the DevOps model. Continuous releases that can follow each other hour by hour are a tough challenge for testers. They are forced to implement automated testing algorithms to cope with such an intensive flow of deployments. Otherwise, manual testing can form a bottleneck in the workflow. If testers skip some pieces of code due to lack of time, there is a risk that the disappointed end-users will refuse to pay for under-tested software. 

QA engineers must set up their testing environment akin to a production environment to harmonize continuous testing with continuous delivery. Fortunately, developers and operations engineers realize the challenge of testers to assist them in doing their job with the maximum possible support. Hence, QA specialists in DevOps are more than testers: they are integrators of combined efforts that the entire team makes for quality. 

On the one hand, the responsibility for QA that testers share with other departments makes testing routines less stressful. On the other hand, the same shared responsibility significantly elevates the status of testers in the DevOps paradigm. Both aspects deliver a better quality of life and stronger self-respect to QA engineers.


Usually, it’s not a big deal to find the extreme in any traditional SDLC when the system goes down after another release. Nobody but a system administrator has to solve deployment problems. DevOps sysadmins look at things in a different way. They benefit from frequent releases incapable of introducing significant vulnerabilities to the system. Furthermore, smaller deployments conducted during working hours can barely result in critical system failure. Operations merged with development can distribute risks between sysadmins and developers almost equally. 

Experienced DevOps sysadmins never rely on manual operations only. Automation tools and self-written scripts help them reduce routine tasks: the more automated the deployment, the more stable the system is against human error. In contrast to traditional SDLCs, DevOps processes imply developers be widely involved in operations. Moreover, interchangeable positions are the norm in the model: a developer who knows operations is as popular as a sysadmin with programming skills. Such specialists can easily find better career opportunities with higher salaries. More personal time with fewer stressful situations adds to the appeal of DevOps for system administrators. 

Marketers and Stakeholders

The DevOps culture is about more than just technical routines. All enterprise departments utilize DevOps advantages to increase productivity and satisfy customers better. As soon as a new product or feature reaches end-users, product managers and marketers get real-life customer feedback. Since DevOps provides faster and more frequent releases, the customer reaction appears at marketers’ disposal earlier. This entails valuable insights into outperforming possible rivals and beating the competition. In addition, an Agile approach to changes and improvements helps DevOps practitioners shorten time-to-market and quickly implement the desired features to occupy a particular business niche.

Stakeholders achieve greater influence on developers in DevOps. This happens not due to oppressive behavior, but because of the increased mutual understanding between all team members. Continuous communication generates an intra-company collaborative spirit that makes technicians care about business needs. Product managers can get better market opportunities with more stable systems that induce higher customer satisfaction. Faster releases of features that meet users’ expectations bring higher revenue to the company and foster its competitive capabilities. 


The ones who care about the brand’s value most can also explore the practical benefits of DevOps. Suppose a company can deliver top-quality products to customers faster than competitors. In that case, the market share of such a company inevitably grows. The growing market share implies increasing capitalization since investors never miss any potential market leader to fund. Top executives of such successful companies become popular quickly. Their personal achievements merge with the company’s success in the eyes of a business audience. A great deal of new-level opportunities unfolds before the successful top executives in terms of social mobility. 

The progressive DevOps working style can also simplify headhunting. HR executives stop facing trouble with hiring truly talented developers, testers, and sysadmins since highly professional employees always look for respectful employers to work for. This means DevOps will keep getting more and more appealing to solve the notorious staffing problem indirectly. 

DevOps workflows with inherent transparency and communication allow executives to spend less time on internal debates. They can completely focus on building business strategies, since conflict-solving began to fade due to the strong engagement and empathy inside DevOps-centric teams. 

How DevOps Reduces Costs

devops as a set of progressive models

Maximizing profitability is a matter of survival in highly competitive sectors. Software development is one of them. The cost-revenue ratio determines how lucrative your business is. Decreased costs mean increased profits and vice versa. As an efficiency-improving approach to development workflows, DevOps provides considerable potential for various cost reductions in the background of similar technology stacks and team compositions. 

Downtime Cost Reduction 

When your network, service, or website goes down, catastrophic effects for your business won’t take long to arrive. Customers never remain loyal to problematic projects. Your reputation is at stake when downtime happens with your software. It’s impossible to calculate the losses a single short downtime can cause. And a recurrent one can completely destroy your image in the eyes of end-users.

DevOps helps reduce downtime risks with techniques that eliminate the root causes of software failures. Your service (website, application, network, etc.) can go down for various reasons, among which an overloaded infrastructure, spaghetti code, and unfixed bugs are the most typical. The “continuous everything” paradigm inherent in DevOps development prevents many, if not all, downtime-resulting troubles from arising. The tight collaboration between developers, testers, and sysadmins who use performance monitoring tools and automation best practices gives no chance for messy code, poorly tested features, or wrongly deployed updates to reach end-users.

When you build your software under the DevOps model, you can predict exactly what end-users will face with your product. Furthermore, by tracking the performance continuously, you remain aware of what is going on in real time. Thus, your possible downtime costs are reduced significantly almost by default compared to software created with the traditional SDLC.

Deployment Cost Reduction 

Frequently performed deployments beyond DevOps always risk turning into a total mess. The release procedures become chaotic when sysadmins work with no continuous integration and collaboration with developers. Sometimes, a slightly corrected line of code is enough to make the entire release flow like clockwork. However, the opposite scenario is equally probable: a tiny bug missed by testers and developers can make operations writhe in hysterics. 

Any release is potentially stressful and can cause unforeseen expenditures. At the same time, the DevOps pipeline optimizes utilizing all necessary resources such as computing power, storage, bandwidth, workforce, and the like. They all imply related costs that can change the cost-revenue ratio in various proportions. The faster the release, the lower the costs spent. Since DevOps offers the fastest possible highly automated deployments, their costs—not to mention the nervous tension and staff’s emotions—are lowered.

Future Cost Reduction 

Your infrastructure elasticity determines the costs you may face in the future. One of the best practices of DevOps is microservice-based apps. Their modular structure makes the app less vulnerable to varying workloads. If one module goes down, the other ones keep working. Such flexibility reduces the repair costs your app may require in the case of a microservice failure.

Another cost-reducing factor of DevOps is the higher speed with which customer feedback finds its implementation in production. The faster, the cheaper, in such a context. Moreover, the proactive way of doing things in DevOps helps prevent many destructive situations that are rather a norm in purely reactive non-DevOps scenarios.


Even though we can call it a culture, a philosophy, a movement, or even a paradigm, the variety of names can hardly abolish the explicitly beneficial effects that DevOps provides. Faster development of top-quality software is a well-proven outcome that follows DevOps processes. Continuous communication and highly collaborative workflows allow DevOps teams to achieve better business results with faster releases of more reliable products. 

DevOps adoption can be challenging for companies with a long history of traditional software development. At the same time, DevOps is not rocket science: any team can transform otherwise isolated development, testing, and operations into a highly productive, unified flow of creativity and efficiency. The only thing needed is an understanding of DevOps advantages based on the minimum knowledge provided with this.

Particular traits of any given company do matter on the way to DevOps, of course. Infrastructural characteristics, staff composition, business segments, and many other individual aspects can determine a practical step-by-step plan for DevOps adoption. Contacting an experienced advisor will never hurt—and will in fact help you make no mistakes in such a situation. Contact our experts, who are always ready to share their vast hands-on experience in DevOps transformation with anyone interested.

Dmitry Danchuk
Dmitry Danchuk Head of DevOps Department

Dmitry has 15+ years of experience developing server and cloud architectures for all-sized businesses. Now, he leads a team of 100+ qualified engineers who help companies design, build, and maintain IT infrastructures worldwide.


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