The Core Principles Of DevOps And How It Works?

As we saw, both methods in the opening example would achieve the same outcome, but the second follows DRY practices. At the same time, this might not seem critical in simple programs. More code means larger files, and larger files mean more load time.

Regarding DevOps, principles also serve as signposts for a DevOps team in the same way DRY guides developers' decisions. Without these central practices to orient us, the various technical and operations aspects of DevOps could quickly overwhelm us. In other words, we lose the forest for the trees.

However, by using DevOps principles as a framework, we can evaluate decisions based on their operational value (e.g., faster turnaround times) and if they move the team closer to these practices (e.g., automation). This judgment calls and the principles behind them help form your team's best practices.

  • Collaboration
    In its purest form, DevOps is the Integration of the development (Dev) and operations (Ops) teams. This means that collaboration is central to the foundation of DevOps. By working together, development can better configure the software for the operations phase, and operations can test it earlier to ensure it meets requirements.
    Collaboration also depends on good information-sharing practices. An issue discovered while the application is deployed should be adequately logged so the development team can account for this in future builds. In the same vein, feedback should also be shared across the team.
    Positive feedback bolsters morale and reminds the team why its work is important. Negative feedback is even more important to continue improving software deliveries.
  • Data-Based Decision Making
    Another central principle of DevOps is informing your decisions with data. Whether selecting the right tech stack or tools to streamline your pipeline, you should always collect data around each decision to ensure your choice agrees with your team's metrics and historical data.
    For example, a key performance indicator (KPI) for many teams is the time it takes to resolve an issue. The longer a defect exists, the more damage it can cause.
    Knowing your average resolution time will help you make informed decisions when introducing new tools or procedures to your pipeline. You can compare their results against your benchmark average and get a good idea of whether or not the new addition will ultimately help or hurt your team.
  • Customer-Centric Decision Making
    The customer should be a central focus in a DevOps lifecycle. Equally as important as data, decisions should be weighed with the question, "Will this benefit the customer?" Collecting feedback from the customer on the existing product will guide future optimization.
    DevOps teams also use live monitoring strategies to address problems before they become an issue for the customer. Other tools allow the team to measure how end users interact with the application in real-time to see if they are encountering areas of friction.
    The speed of the DevOps lifecycle allows the team to push out updates to remove these pain points.
  • Constant Improvement
    Continuous improvement, or the idea that the team should continuously focus on new features and updates, is the central tenet of DevOps. Another key idea is to adhere to the incremental release methodology of agile.
    Prior software development approaches aimed to deliver the ideal product all at once. Although this sounded like the perfect solution, in reality, it usually led to protracted software delivery delays while issues were resolved. Instead, incremental releases allow the team to focus on swiftly developing a minimal viable product (MVP) to meet the customer's primary use case.
    After the MVP has been provided, the team develops features to boost the product's value and advances toward the perfect software. The customer can start using the tool earlier and learn new features as they are delivered rather than having to master the entire platform at the end of a waterfall delivery cycle.
  • Responsibility throughout the Lifecycle
    According to conventional software development approaches, the development team creates the application through coding. They then give it to the operations team for testing, deployment, and client delivery. The operations team, not the engineers who built the code, is in charge of fixing any bugs found in the second phase.
    A more sensible strategy is demonstrated by DevOps: accountability throughout the lifetime. From conception to final disposal, the entire crew controls the product. The development and operations teams collaborate to update the software and fix problems.
    The developers who are currently working to enhance and include new features are also those who are most familiar with the source code. This puts a new emphasis on writing high-quality code and finding defects early, which improves the client experience.
  • Automation
    The speed of software delivery, updates, and fixes is a fundamental advantage of the DevOps method. Automation is used to achieve this momentum. Every step of the process, including code reviews, handoffs, provisioning, and deployment, is intended to be automated by DevOps teams.
    This enables the pipeline to move more quickly and increases team members' job happiness. They are no longer required to complete laborious manual jobs. Instead, they can concentrate on more complex activities like developing future enhancement plans and learning about cuttingedge technology to incorporate into the product.
    Through purpose-made DevOps technologies, automation may be accomplished most easily.
  • Failure as a Learning Opportunity
    A flexible approach to development is DevOps. Just as the software is continually improving, processes are also being adjusted regularly. Keeping this flexibility requires accepting failure as a chance to grow and learn. Encourage risk-taking in the appropriate circumstances rather than striving to avoid failure at all costs.
    Risks include the potential for failure but can also result in success. No matter what happens in an experiment, you will have a deeper understanding of what works and what doesn't. You can use this experience as additional data to inform your decision-making and to help you plan future tactics.
    Early testing will allow you to fail quickly, where the failure won't affect the client. Issues should be encountered now rather than failing after deployment. This tactic is a component of the idea of "shifting left," which we'll look at next.

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Why DevOps recommend shifting left testing principles

A critical way that DevOps differs from traditional software development strategies is its emphasis on testing. DevOps uses the "shift left" strategy, which places testing before developing and creating the software. Shifting left entails moving to test as far left as feasible in the direction of the process' beginning if the development process were to be visualized as a straight line.

Testing has many benefits while the DevOps lifecycle is still in the development phase. First, finding errors early in the process before adding extra code is more straightforward, quicker, and less expensive. The probability that fixing one section of the code may break another increase as dependencies and complexity increase.

Another benefit of a shift-left testing strategy is that the development team is now focused on writing high-quality code right away rather than waiting until afterward to identify defects. The consumer receives the goods more quickly and with fewer (if any) bugs. Everyone benefits from this strategy.

Implementing DevOps Principles

These seven principles of DevOps are meant to serve as your north star as you fine-tune your pipeline. It's important to recall that DevOps is as much a culture as a development strategy, and collaboration is the bedrock of your culture and development practices.

The main takeaway is that you should practice a collaborative approach as you work to embrace these DevOps principles within your team. After all, your team comprises individual stakeholders with perspectives, skills, and ideas to contribute. Beyond that, center your motivation on serving the customer and prioritize quality at every stage.


It is crucial to understand the history of DevOps before we can understand what it is. Agile and waterfall software development methodologies existed prior to DevOps. The waterfall model is what we will now examine.

Waterfall Model

A top-down, sequential development process for software or systems is known as the waterfall model. Clearly defined and linear, this model. There were six stages in the waterfall model: requirement definition, software design, implementation, testing, deployment, and maintenance.

Software development companies that used the waterfall model approach had to spend a lot of time getting their product right. That is because you must complete a particular phase to proceed to the next one. Also, the working software was delivered only after the final phase of this model. This model was only suitable for projects which had stable requirements. By stable, I mean that requirements will not change with time. But in today's world, this is very unlikely because requirements keep changing from time to time. These were a few drawbacks of the waterfall model.

DevOps Life Cycle

Continuous software development, integration, testing, deployment, and monitoring are all parts of the DevOps lifecycle. A competent DevOps lifecycle is required for the DevOps methodology to be fully utilized.

To create, test, use, and evolve software products, the DevOps approach supports continuous innovation, agility, and scalability. It encourages a mindset of ongoing learning, experimenting, and feedback to reinvent products, services, and processes. However, a thorough understanding of the many phases of the DevOps lifecycle is essential for implementation.

Developers need to thoroughly understand every phase of the DevOps lifecycle to produce results more quickly. If not, the entire development process may be difficult and timeconsuming. Here is a detailed breakdown and analysis of every component of the DevOps lifecycle.


DevOps Lifecycle: Key Components

The DevOps lifecycle engages the enterprise in continuous development and optimizes development processes from beginning to end, leading to quicker delivery timeframes. The following seven stages make up the majority of this process.

  • Continuous development
    The program undergoes continual development and is planned and coded. In this case, the entire development process is split into smaller development cycles. This method makes accelerating the software development process more accessible for the DevOps team. During this phase, the vision of the overall development cycle is laid out, allowing developers to understand the project's specifications fully. As a result, the group starts to visualize its ultimate goal.
    No DevOps tools are required for planning, even though different version control systems are utilized to manage the code. The phrase for this type of code maintenance is source code maintenance. Standard technologies for maintaining source code include JIRA, Git, Mercurial, and SVN. Other tools are also available for packaging the codes into executable files, including Ant, Gradle, and Maven. These executable files are delivered to the next stage of the DevOps lifecycle.
  • Continuous integration
    Various processes linked to the execution of the test process are included in continuous integration (CI). Clients also contribute information that is used to expand the application's functionality. During this stage, the source code gets changed the most. On a daily or monthly basis, CI becomes the center for resolving these frequent changes. Unit and integration testing, code review, and packaging are all steps in software development. Since developers frequently make changes, they can rapidly identify issues and address them before they become more serious.
    New code functionalities are continuously integrated with the source code throughout this phase. The system's upgraded code integrates seamlessly because of continual development. One of the most well-liked tools for continuous integration is Jenkins. It assists in retrieving the most recent code and creating executable builds.
  • Continuous testing
    The testing phase, which comes next in the DevOps lifecycle, involves checking the developed code for faults and defects that may have crept in. Quality analysis (QA) is crucial in determining whether the generated software is usable. The program must pass the QA process to ensure it complies with the client's requirements.
    Continuous testing uses automation tools like JUnit, Selenium, and TestNG to simultaneously let the QA team examine various code bases. By doing this, it is ensured that the generated program functions flawlessly.
    Additionally, continuous testing takes advantage of Docker containers to simulate the entire test environment. A Docker container is a standalone, compact executable package that includes all the necessary system tools, libraries, runtime code, and settings to run an app.
    Automation tools like Selenium are used for automated testing, and then additional automation tools, like TestNG, are used to produce the results. With the use of Jenkins, a continuous integration platform, the entire testing procedure can also be automated. Testing automation is essential for reducing time, labor, and effort expenses.
  • Continuous deployment
    The application's performance is not harmed by continuous deployment (CD), which guarantees hassle-free product deployment. During this stage, it is crucial to ensure the code is accurately deployed across all accessible servers. This method eliminates scheduled releases and speeds up the feedback system, enabling programmers to fix problems more efficiently and precisely.
    Through configuration management, containerization solutions assist with continuous deployment. The consistency between test, development, staging, and production environments can be achieved using a containerization tool like Vagrant. Containerization focuses on raising virtualization to an operating system level.
    Once you have a solid automated testing infrastructure, continuous deployment is undoubtedly advantageous for your company. In the continuous deployment stage, configuration management is quite valuable. It entails setting up and upholding uniformity in the app's functional requirements. Ansible, Puppet, and Chef are well-known DevOps technologies for configuration management that aid in the speedy deployment of new code.
  • Continuous monitoring
    Performance monitoring is crucial to assess the effectiveness of a software product's output. This stage handles necessary app-related data processing. Continuous monitoring allows developers to spot broad trends and ambiguous spots in the program that need additional work.
    Continuous monitoring, a phase of operations, aims to increase the software application's overall effectiveness. Additionally, it keeps track of the app's functionality. As a result, it is among the DevOps lifecycle's most important stages.
    In the continuous monitoring phase, many system faults, such as "server not reachable," "low memory," etc., are fixed. It also keeps the services secure and readily available. When they are discovered, network difficulties and other issues are automatically rectified during this phase.
    The operations team uses tools including Nagios, Splunk, Sensu, ELK Stack, and NewRelic to monitor user activity for improper conduct. As a result, engineers can proactively assess the system's general health during continuous monitoring.
    Preventative maintenance lowers maintenance costs while increasing system productivity and reliability. Additionally, significant problems are immediately communicated to the development team so they can be fixed in the beginning. As a result, problems are resolved more quickly.
  • Continuous feedback
    It's imperative to have ongoing feedback to assess and evaluate the application's final result. It establishes the framework for enhancing and rolling out a new version in response to stakeholder feedback.
    Analyzing the outcomes of the software operations is the only way to improve the development process of apps. Information obtained from the client's side is all that feedback is. Information is vital since it contains all the information about the software's performance and any problems that may be associated with it. Additionally, it includes recommendations made by the software's users.
  • Continuous operations
    The DevOps lifecycle's final stage is the quickest and most straightforward to understand. Continuity is the cornerstone of all DevOps operations, which enables developers to identify problems and create better iterations of software products immediately. It is crucial to move forward to remove detours and other additional steps that impede progress.
    Continuous operations have shorter development cycles, enabling businesses to advertise continuously and hasten the product's overall time to market. DevOps raises its value and draws in new customers by making software products better and more effective.

Next Article

DevOps Culture And How It Helps


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