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While software product development companies are massively implementing DevOps practices – in particular, in 2022, the DevOps market size crossed 8 billion USD and will grow with a 20% CAGR from 2023 to 2032. Many companies are still failing to reach their full potential due to not utilizing DevOps capabilities. For example, many enterprises didn’t fully realize from the outset the scale and the obligatory nature of innovations associated with the introduction of DevOps practices. Below we will talk about one such innovation—DevOps automation—and consider specific DevOps automation examples.
First, let’s recall what DevOps is. In essence, it’s a set of practices for organizing the software development process aimed at reducing and optimizing the development life cycle, as well as the introduction of such methods as continuous integration, continuous delivery, and continuous deployment (CI/CD).
In turn, DevOps automation involves the use of specialized software solutions and methodologies to automate repetitive tasks throughout the software development life cycle. Thus, DevOps automation simplifies, speeds up, and makes development processes more efficient, allowing teams to build, test, deploy in the cloud, and maintain code faster and better than when using manual approaches. The most popular tasks for automation are code analysis, unit testing, functionality testing, performance, and other processes, as well as phased deployment and release management. That’s why, thanks to the benefits of DevOps automation, your IT staff will be able to spend more time on highly intelligent tasks that require a non-trivial approach and will be able to avoid human error.
Let’s look at key benefits of DevOps.
The consistency of the development process usually means the smooth transfer of the project from one stage of development by one type of specialist to another stage and other specialists (for example, developers and testers). And automation can handle this, reducing the likelihood of errors—this means that narrowly focused teams will have more time to discuss the work done and the details that are critical to the successful completion of the project.
Automation in DevOps is always aimed at speeding up the execution of tasks for infrastructure provisioning and configuration by using Infrastructure as Code best practices. This means that with the introduction of DevOps automation tools, your team will be able to develop more applications or services in less time. Thus, your digital solutions will be released more often and faster than your competitors.
However, this is not all the benefits that DevOps automation can provide. The fact is that some bugs in software are often discovered after its release, and to keep the bar high, developers must fix them as soon as possible. Actually, in these situations, automation will also bring its advantages.
Despite all the advantages that conventional DevOps provides, after the introduction of automation, the possibilities for scaling workflows associated with the software life cycle are significantly expanded. This means that you won’t need to hire new IT specialists or overload the existing ones with new routine tasks.
Changing market trends and the needs of the target audience can be very fast, and automation will be the measure that will help companies quickly adapt to these changes.
In particular, thanks to DevOps automation tools, your IT team will be able to adapt to changing development conditions faster and less resource-intensive than ever before. This, in turn, enhances the competitiveness of companies at the lowest resource costs.
When key processes are automated, they become predictable. Indeed, automation implies the use of a clear algorithm of actions that will always do the same thing until it’s changed to perform other actions and tasks. With manual processes, such consistency is not achievable, as any action may be subject to human error.
In fact, the list of tasks for automation in DevOps for each company may be different. If we talk about special cases, this can be database backup, historical data import, version control integration, changing access policies, restarting microservices, managing abnormal activity on the network, and much more. However, all these tasks have some common characteristics:
Now let’s look at the stages of the software development life cycle where automation is used most often and explain why it’s needed there.
DevOps automation of testing is needed to find bugs and vulnerabilities in a software solution in the early stages of the continuous integration and continuous delivery (CI/CD) pipeline. Thus, bringing the product to optimal quality begins early, allowing the teams to get competitive solutions that the target audience will accept positively.
CI/CD automation development allows teams to implement continuous deployment of software solutions by streamlining (i.e., speeding up, reducing costs, and getting rid of human error) the processes of making changes to product configurations as well as their global updates.
The resource-intensive activities of teams, associated with non-standard and creative thinking, can also be subjected to partial automation. Specifically, your teams can use tools like Git, Microsoft Teams, JIRA, and more to make communicating with each other from a distance easier.
This type of DevOps automation provides teams with on-demand access to the computing resources they need, eliminating the need to reconfigure the network infrastructure regularly. For example, they can use containers implemented with the Kubernetes tool to be able to quickly and efficiently provision network resources to deploy applications in new environments.
Finally, teams can take advantage of DevOps automation tools to simplify the tasks of monitoring applications and services to minimize downtime, ensure that issues and errors are quickly resolved, provide a better quality of service, and so on. In the long term, this approach can reduce the mean time to repair (MTTR).
It’s time to gradually move from theory to practice, so we decided to share a selection of tools that will help you with automation in DevOps.
Docker is an open platform for developing, delivering, and operating applications. With Docker, you can decouple your application from your network infrastructure and treat your infrastructure as a managed application.
In this way, Docker helps teams test and deploy applications faster, reducing the time between writing and running code. In particular, this tool makes it possible with a lightweight container virtualization platform, using processes and utilities that provide end-to-end pipeline management.
Kubernetes is a portable, extensible, and open-source platform for managing containerized workloads and services that facilitates both declarative configuration and automation. To be more precise, this tool automates the following tasks:
In this way, Kubernetes ensures consistency across development, testing, and production environments.
Jenkins is an open-source Java-based system that provides continuous software integration. Along with this, the tool acts as a free CI server compatible with Windows, macOS, and a number of Unix-based operating systems. Thus, Jenkins covers both CI and CD processes.
Currently, the library of this tool contains more than one and a half thousand plugins that automate individual functions responsible for developing, testing, and deploying software.
Git is a distributed version control system that helps teams share code and collaborate on testing and deploying projects. It provides end-to-end tracking and management of all changes in the program code. It’s noteworthy that, unlike centralized alternatives, this tool is suitable for working with inconsistent projects with a common repository.
Ansible is an open-source Infrastructure as Code tool for configuring, orchestrating, and automating infrastructure provisioning and configuration tasks. It can help DevOps teams significantly speed up the software development process by integrating projects into production environments.
Chef is a cloud-based network configuration management system that allows DevOps specialists to provide dozens or hundreds of server instances. In terms of functionality, it is similar to Ansible but has a special, skeuomorphic approach.
In general, this network configuration system is sharpened for culinary topics. These scripts are placed in the “Bookshelf” (storage), where the current configurations are retrieved and installed on client machines automatically. All operations are performed using a console tool called “Knife.”
Ganglia is an open-source distributed system for monitoring clusters of parallel and distributed computing and cloud systems with a hierarchical structure. With Ganglia, DevOps teams can monitor statistics and history (processor and network load) in real time. It works separately for each observed node and can scale their management to thousands of units.
Splunk is a platform for collecting, storing, processing, and analyzing logs (up to hundreds of terabytes per day). One of the platform’s main features is that it can work in real time with data from almost any source, and therefore the list of its possible applications is very wide. The comprehensive monitoring provided by this tool allows teams to run high-quality code faster than with manual practices.
Since automation is a rather abstract task that can be adapted to any process within a pipeline, it would be nice to have a list of general guidelines to point you in the right direction. Actually, now we will bring you these guidelines.
Performing tasks related to the development, testing, cloud deployment, updating, and troubleshooting of applications and services with a manual approach has always been complicated due to the need to ensure end-to-end interaction between individual hardware settings, operating systems, and environments. To simplify these tasks, teams must resort to containerization (for example, with Docker).
Cloud containerization provides strong process isolation and enhances system security. Applications and services that run inside a container don’t have access to the main OS and cannot influence it. Thus, with containers, you can automate the deployment of applications and services and their updates across different hosts, run container autotests in CI/CD pipelines, and speed up container hosting in a central registry.
Big Bang releases (the approach when the application/service is deployed completely in one go, not in stages, by separate modules) often cause many problems, from data loss to incorrect operation of some functions and incompatibility with individual machines. In turn, it would be much safer and more rational to separately transfer the program code to the production environment and separately launch the update. And the more autonomous these two processes are, the better—ideally, the code should be tested in test production first.
Thanks to this, your team can disable individual broken (or incorrectly working) modules and eliminate errors before they get into the user environment.
As mentioned, test automation should be implemented as early as possible; however, there are several more precise tips that will make the testing process more efficient. For example, we recommend the following (using automation tools for each of the processes):
By automating all of these tasks, you can ensure high-quality code without needing independent code review, which is time-consuming.
Observability is the measurement of the state of a network infrastructure through analysis of its output data. Thus, teams can identify bottlenecks and errors as long as they cause the program code to work incorrectly. Manually doing this is very difficult and time-consuming, so some software tools for DevOps automation will cope with this task more quickly and without human participation.
Moreover, this way, you can prioritize fixing bugs and vulnerabilities early and gradually eliminate them without slowing down the delivery of your software to end users.
Elasticity is determined by the system’s propensity to instantly adapt to rising and falling loads without downtime and unforeseen costs. To provide the necessary level of elasticity, you can resort to autoscaling, one of the key concepts of DevOps, which allows dynamic scaling of workloads.
Usually, cloud providers offer autoscaling services, however, your team will also need to additionally set up individual settings that will trigger the allocation of new computing power or the reduction of those that are not used for a certain time period.
As your network infrastructure becomes more complex, automating testing, deployment, and updates can only partially relieve your team of manual tasks, as container management ones will still be present in this list. To overcome this challenge, you can use container orchestration tools (like Kubernetes) that make distributing, planning, deploying, scaling, monitoring, and configuring containers easier and faster.
Finally, we invite you to consider specific DevOps automation examples in some business verticals. In general, disparate software development teams can communicate more effectively with each other, build, test, and deploy applications and services in new environments faster, and deliver them to the target audience earlier than your competitors can.
DevOps automation will also be useful for businesses specializing in online financial trading. Specifically, using DevOps automation tools to replace specific manual tasks can speed up the development and testing processes.
With DevOps automation, companies can deploy and perform end-to-end testing for new network cycles with minimal overhead. This opens up new opportunities for eliminating vulnerabilities and improving the security and safety of user data.
In regards to the banking industry, it especially needs increased security of financial operations and, particularly, those that use private user data. As for the benefits of DevOps automation, the tools that ensure them can provide companies in the banking sector with rapid testing and delivery of security policies dictated by local legislation.
The last one from our list of DevOps automation examples is the automobile industry. Like any other industry, this one requires early detection of defects and errors in manufactured products. DevOps automation allows companies to achieve this with the least resource costs. Moreover, implementing DevOps automation solutions allows these companies to scale their activities quickly and cost-effectively.
Summarizing the above, we can conclude that DevOps automation in business:
We hope that we helped you discover the benefits of DevOps automation and also understand whether you need it (or, rather, why you need it). At the same time, determining which processes need to be automated, as well as their automation is a rather difficult thing, and to implement it correctly, you may need help from professionals. NIX experts have experience and extensive DevOps skills to enhance your business. If you want to fully justify your expenses on DevOps implementation, we can take care of this task. We have effectively implemented DevOps automation in dozens of companies of various sizes and are ready to help you get the most out of it. Contact us right now to discuss the details of our further cooperation.
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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