Various prospect for defining the problem statement in modern DevOps approach

Introduction

For a long time, development and operations were isolated modules. Developers wrote code; the system administrators were responsible for its deployment and integration. As there was limited communication between these two silos, specialists worked mostly separately within a project.

Today, DevOps is one of the hottest trends in the software industry and successful DevOps implementation is the goal of most progressive IT organizations (see chart below, courtesy of Google Trends). DevOps (short for development and operations) is a set of automated software practices that combine software development (Dev), testing and IT operations (Ops) to shorten the software development life cycle while delivering features, fixes, and updates frequently in alignment with the business’ objectives.

DevOps is applied in Facebook, Netflix, Amazon, Etsy, and many other industry-leading companies. So, if you are considering embracing DevOps for the sake of better performance, business success, and competitiveness, you take the first step and hire a DevOps engineer. But first, let’s look at what DevOps is all about and how it helps improve product delivery.

12 New DevOps Features in Modern Trends of Technology

What is DevOps?

DevOps stands for development and operations. It’s a practice that aims at merging development, quality assurance, and operations (deployment and integration) into a single, continuous set of processes. This methodology is a natural extension of Agile and continuous delivery approaches.

By adopting DevOps companies gain three core advantages that cover technical, business, and cultural aspects of development.

Higher speed and quality of product releases. DevOps speeds up product release by introducing continuous delivery, encouraging faster feedback, and allowing developers to fix bugs in the system in the early stages. Practicing DevOps, the team can focus on the quality of the product and automate a number of processes.

Faster responsiveness to customer needs. With DevOps, a team can react to change requests from customers faster, adding new and updating existing features. As a result, the time-to-market and value-delivery rates increase.

Better working environment. DevOps principles and practices lead to better communication between team members, and increased productivity and agility. Teams that practice DevOps are considered to be more productive and cross-skilled. Members of a DevOps team, both those who develop and those who operate, act in concert.

These benefits come only with the understanding that DevOps isn’t merely a set of actions, but rather a philosophy that fosters cross-functional team communication. More importantly, it doesn’t require substantial technical changes as the main focus is put on altering the way people work. The whole success depends on adhering to DevOps principles.

DevOps principles

Culture

DevOps is initially the culture and mindset forging strong collaborative bonds between software development and infrastructure operations teams. This culture is built upon the following pillars.

• Constant collaboration and communication. These have been the building blocks of DevOps since its dawn. Your team should work cohesively with the understanding of the needs and expectations of all members.
• Gradual changes. The implementation of gradual rollouts allows delivery teams to release a product to users while having an opportunity to make updates and roll back if something goes wrong.
• Shared end-to-end responsibility. When every member of a team moves towards one goal and is equally responsible for a project from beginning to end, they work cohesively and look for ways of facilitating other members’ tasks
• Early problem-solving. DevOps requires that tasks be performed as early in the project lifecycle as possible. So, in case of any issues, they will be addressed more quickly.

Automation of processes

Automating as many development, testing, configuration, and deployment procedures as possible is the golden rule of DevOps. It allows specialists to get rid of time-consuming repetitive work and focus on other important activities that can’t be automated by their nature.

Measurement of KPIs (Key Performance Indicators)

Decision-making should be powered by factual information in the first place. To get optimal performance, it is necessary to keep track of the progress of activities composing the DevOps flow. Measuring various metrics of a system allows for understanding what works well and what can be improved.

Sharing

Sharing is caring. This phrase explains the DevOps philosophy better than anything else as it highlights the importance of collaboration. It is crucial to share feedback, best practices, and knowledge among teams since this promotes transparency, creates collective intelligence and eliminates constraints. You don’t want to put the whole development process on pause just because the only person who knows how to handle certain tasks went on a vacation or quitted.

How does DevOps work?

DevOps is a methodology meant to improve work throughout the software development lifecycle. You can visualize a DevOps process as an infinite loop, comprising these steps: plan, code, build, test, release, deploy, operate, monitor and -- through feedback -- plan, which resets the loop. Figure 2 shows how DevOps work.

Ideally, DevOps means that an IT team writes software that perfectly meets user requirements, deploys without any wasted time and runs optimally on the first try. Organizations use a combination of culture and technology to pursue this goal.

To align software to expectations, developers and stakeholders communicate about the project, and developers work on small updates that go live independently of each other.

To avoid wait times, IT teams use Continuous Integration/Continuous Deployment (CI/CD) pipelines and other automation to move code from one step of development and deployment to another. Teams review changes immediately and can enforce policies to ensure releases meet standards.

It's easy to write software quickly; writing software that works is another story. To deploy good code to production, DevOps adherents use containers or other methods to make the software behave the same way from development through testing and into production. They deploy changes individually so that problems are traceable. Teams rely on configuration management for consistent deployment and hosting environments. Problems they discover in live operations lead to code improvements, often through a blameless post-mortem investigation and continuous feedback channels.

Developers might support the live software, which puts the onus on them to address runtime considerations. IT operations administrators might be involved in the software design meetings, offering guidance on how to use resources efficiently and securely. Anyone can contribute to blameless post-mortems. The more these specialists collaborate and share skills, the more they can foster a DevOps culture.

What problems does DevOps solve?

DevOps promises speed: delivering value to customers, reducing cycle time, faster time to market, shorter mean-time-to-resolution.

• DevOps minimizes the time it takes to deliver value to customers.
• Getting more satisfaction from internal users.
• make customers lives simpler and easier
• The greatest value realized through DevOps is that it allows IT organizations to focus on their “core” business activities
• DevOps drives app dev teams towards continuous improvement and faster release cycles.
• DevOps and the many related ideas surrounding it are all used by enterprises to accelerate the delivery of modern applications. The benefits are many: By introducing new digital capabilities faster enterprises can respond more quickly to customers, partners, and internal users. Businesses can greatly enhance their agility to decrease time to market, increase customer satisfaction, and gain competitive advantage. Reducing cycle times can also speed innovation. New ideas can manifest more quickly. Those that fail can be sorted from those that flourish sooner, bringing more focus to the most successful innovations faster. Multiplying this effect over many interactions of experimentation and discovery can dramatically increase the ROI on advanced research and development. The process automation that underpins DevOps and enables rapid delivery at scale also improves the bottom line. Automation improves productivity, reduces errors, and greatly enhances operational efficiency.
• The most important problem being solved is the reduction of the complexity of the process -- whether it's configuring a new cluster for existing applications or provisioning the environment for a new application. This contributes significantly to our business success by shortening our time to market, giving us fast feedback on features, and making us more responsive to our customers' needs.
• The greatest value of DevOps is not wasting time. Aligning an organization’s people and resources enables rapid deployments and updates which allows DevOps programs to fix problems before they become disasters. DevOps creates a culture of transparency that fosters focus and collaboration among development, operations, and security teams.
• The two biggest benefits of DevOps are bringing people together, which is at the center of DevOps, and automating labor-intensive activities that reduce creativity and productivity. Both are essential for increasing software quality, getting it to market faster, and driving up business value.
• Eliminate human error. The more you automate a well-defined process you will see the greatest value.

DevOps benefits and challenges

DevOps benefits include the following:

1. Continuous delivery of software
2. Better collaboration between teams
3. Easy deployment
4. Better efficiency and scalability
5. Errors are fixed at the initial stage
6. More security
7. Less manual intervention (which means fewer chances of error)
8. Less downtime
9. Less menial work, thanks to automation

DevOps adoption

Why DevOps in the first place?

Before DevOps, there were two development models: Waterfall and Agile Method.

1. Waterfall Model

The waterfall model is the first model to be introduced in software development. It is a sequential process and very easy to understand. In this approach, software development is divided into several phases, and the output of one phase becomes the input for the next phase. This model is similar to a waterfall when the water flows off from the cliff; it cannot go back to its previous state.

The phases are: Requirements, Design, Implementation, Verification, and Maintenance.

Drawbacks of the waterfall model:

• It’s difficult to make changes to the previous stage
• Not recommended for large-sized projects
• Developers and testers don’t work together (which can result in a lot of bugs at the end) 
• Not recommended for projects that will likely have changing requirements

2. Agile Model

Agile is an approach in software development where each project splits into multiple iterations. As a result, at the end of each iteration, a software product is delivered. Each iteration lasts about one to three weeks. Every iteration involves functional teams working simultaneously on various areas, such as:

Using the agile method, the code that works for the developer may not work for the operations team.

With DevOps, there is continuous integration between deployment of code and the testing of it. Near real-time monitoring and immediate feedback through a DevOps continuous monitoring tool enables both the developer and operations team work together. The figure 5 shows how well the software is handled using DevOps.

DevOps tools

• DevOps is a mindset, not a tool set. But it's hard to do anything in an IT team without the right tools. In general, DevOps practitioners rely on a CI/CD pipeline, containers and cloud hosting. Tools can be open source, proprietary or supported distributions of opensource technology. 
• Code repositories: Version-controlled source code repositories enable multiple developers to work on code. Developers check code out and in, and they can revert to a previous version of code if needed. These tools keep a record of modifications made to the source code. Without tracking, developers may struggle to follow which changes are recent and which versions of the code are available to end users.
• In a CI/CD pipeline, a code change committed in the version-control repository automatically triggers next steps, such as a static code analysis or build and unit tests. Tools for source code management include Git and GitHub.
• Artifact repositories: Source code is compiled into an artifact for testing. Artifact repositories enable version-controlled, object-based outputs. Artifact management is a good practice for the same reasons as version-controlled source code management. Examples of artifact repositories include JFrog Artifactory and Nexus Repository.
• CI/CD pipeline engines: CI/CD enables DevOps teams to frequently validate and deliver applications to the end user through automation during the development lifecycle. The continuous integration tool initializes processes so that developers can create, test and validate code in a shared repository as often as needed without manual work. Continuous delivery extends these automatic steps through production-level tests and configuration setups for release management. Continuous deployment goes a step further, invoking tests, configuration and provisioning, as well as monitoring and potential rollback capabilities. Common tools for CI, CD or both include Jenkins, GitLab and CircleCI. 
• Containers: Containers are isolated runtimes for software on a shared OS. Containers provide abstraction that enables code to work the same on different underlying infrastructure from development to testing and staging, and then to production. Docker is the most well-known containerization software, while Microsoft offers specific Windows container options. Container orchestrators -- such as Kubernetes and commercial Kubernetes distributions Red Hat OpenShift and Amazon Elastic Kubernetes Service -- deploy, scale and maintain containers automatically.
• Configuration management: Configuration management systems enable IT to provision and configure software, middleware and infrastructure based on a script or template. The DevOps team can set up deployment environments for software code releases and enforce policies on servers, containers and VMs through a configuration management tool. Changes to the deployment environment can be version controlled and tested, so DevOps teams can manage infrastructure as code. Configuration management tools include Puppet and Chef.
• Cloud environments: DevOps organizations often concurrently adopt cloud infrastructure because they can automate its deployment, scaling and other management tasks. AWS and Microsoft Azure are among the most used cloud providers. Many cloud vendors also offer CI/CD services.
• Monitoring: Additionally, monitoring tools enable DevOps professionals to observe the performance and security of code releases on systems, networks and infrastructure. They can combine monitoring with analytics tools that provide operational intelligence. DevOps teams use these tools together to analyze how changes to code affect the overall environment. Choices are wide-ranging, but include New Relic One, Dynatrace, Prometheus, Datadog and Splunk.
• Cloud-based DevOps pipelines: Public cloud providers offer native DevOps tool sets to use with workloads on their platforms. An incomplete list includes AWS CodePipeline and CloudFormation, Azure DevOps and Pipelines, and Google Cloud Deployment Manager. Cloud adopters have the option to use these pre-integrated services or run third-party tools. For example, an organization can use HashiCorp Terraform or CloudFormation to make infrastructure-as-code templates for its AWS workloads. 
• As-a-service models: Lastly, DevOps as a service is a delivery model for a set of tools that facilitates collaboration between an organization's software development team and the IT operations team. In this delivery model, the provider assembles a suite of tools and handles the integrations to seamlessly cover the overall process of code creation, delivery and maintenance.

The Future of DevOps: Possibilities and Challenges

There are many possibilities for the future of DevOps, but many challenges also need to be addressed.

The following are three potential areas of growth for DevOps:

Improved collaboration between development and operations teams: One of the most significant benefits of DevOps is that it fosters enhanced collaboration between development and operations teams in an enterprise. This collaboration can lead to faster and more efficient development processes and better support for customer needs. Collaboration at this level, however, requires overcoming several obstacles. For example, operations teams may need more training in software development processes to be able to work effectively with developers. Effective communication between teams can also be problematic when diverse cultures are involved.

Increased automation of processes: Automation is another critical aspect of DevOps. Automation reduces the time it takes to complete tasks and increases efficiency. Despite its benefits, automation also comes with some challenges. For example, effective automation requires a good understanding of how software is developed, which can be difficult for your teams. In addition, automation requires a reliable platform and a monitoring and management system that is effective. If these factors are not in place, automation can lead to the unintended consequences of increased workloads for development teams and reduced efficiency for operations teams.

Better use of machine learning and artificial intelligence: Machine Learning and Artificial intelligence will see a surge in popularity and become more prevalent in DevOps. These technologies can help automate tasks and improve the accuracy of processes. However, effective machine learning requires large data sets that can be difficult to collect and store. Additionally, artificial intelligence is often sensitive to human bias, so it can be challenging to ensure correct and accurate processes. 

That said, the future of DevOps is promising. However, while there are many potential growth areas, there are also many challenges you should address. Cloud, Edge, and IoT are all intertwined and essential for the future of DevOps. In order for companies to take full advantage of these technologies, they need to understand how these technologies work together. Doing so will enable them to deploy applications faster and more securely while meeting customer demands.

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