Automation is a fundamental part of DevOps as it allows to standardize operations and processes while providing higher efficiency in all parts of the software development. It is an incredibly beneficial practice that can streamline software development and release, which is a must in a highly competitive and ever-changing contemporary environment.
This article covers the DevOps automation fundamentals, core concepts, tools, and best practices.
So, What is DevOps Automation?
DevOps automation is an approach to software development, deployment, and operations that eliminates inefficient manual labor with various tools and technologies. Although it can be very technical, in a nutshell it is also a mindset. It requires a deep understanding of all the processes to evaluate potential automation opportunities and how important they are.
For instance, it is often easy to automate manual tasks like testing or monitoring, and alerting. However, tasks that require creativity are complex to automate. It might change with time and the development of AI technology. But so far, it is not one of the processes DevOps would be concerned with.
As an analogy, one can compare the academic writing process. With the newest tools, it is incredibly easy to automate the proofreading of the text. Modern tools allow one to easily find any errors and mistakes and correct them almost instantly.
However, when it comes to formulating a thesis and building an argument, human creativity has no competition, so one might think, “I want to seek a college essay writing service like EssayPro to create a unique and insightful text without any generative tools.” It is a fair request, as no tool is yet advanced enough to replace human creativity.
Professionals must evaluate what to automate and how to do it so that the result is beneficial and valuable. The goal is to increase speed of development and release along with maintaining consistency, reliability, and easy scalability.
Core Concepts and Principles for Automation in DevOps
To put it simply, DevOps and Automation go hand in hand in software development. They share the same goal – to increase efficiency, reduce time, and conduct repetitive manual tasks without human interference.
Automation can cover every stage of the software development process, including:
- Development
- Testing
- Deployment
- Maintenance
- Monitoring, etc.
The main purpose is to optimize what can and should be optimized and streamline the workload. As a result, all the processes happen by standard protocols, which increases speed and efficiency. Customers get the product and any updates earlier, and any error is found and fixed almost instantly.
Overall, automation is here to reduce the workload of the team and free more human resources for more advanced and challenging tasks. At the same time, it is crucial to know what is worth automating and what will create unnecessary overhead. That’s why all DevOps consulting companies start with research and evaluation before using any tools or scripts.
The DevOps team uses different tools to create an efficient and productive lifecycle. There are plenty of fantastic solutions ready to use that will be covered in the next sections. But, before that, it is imperative to learn about core principles of automation in DevOps.
Often, people think that automation is essentially building a continuous integration(CI) and continuous deployment (CD) pipeline; however, it is more than that. There are tools and practices outside this pipeline that can significantly increase efficiency and production speed.
Three Core Components of DevOps Automation
In the best practices of DevOps, there is a structured approach to understanding the main components of the process. They can be separated by three factors as follows:
1. Technology. It is a collection of tools necessary for the automation of various parts of the CI/CD pipeline and more. They also include configuration management tools, monitoring and alerting tools, cloud platforms, containerization, etc.
2. Processes. Those are operations and activities the DevOps team is aiming to automate. This segment includes CI, CD, IaC (Infrastructure as Code), and collaboration between different departments and teams.
3. Feedback loops. There are two main concepts here – monitoring and improvements. Both of them require consistency.
As for principles, they all represent the DevOps mindset – collaboration, integration, continuity, and reliability.
Common Areas of Automation in DevOps
Automation covers all the areas that can benefit from scripts, templates, code, and pipelines. Although every case is different, there are common areas that are usually a subject of automation, namely:
- Building artifacts/Docker containers – including scanning and uploading processes;
- Testing from units to security testing;
- Cloud infrastructure – the creation of an environment with IaC;
- Configuration of cloud environments;
- Alerting and monitoring with a constant feedback loop;
- Deployment of new versions of updates;
- Backups and recovery.
All of these processes can hugely benefit from DevOps automation tools that increase the speed and effectiveness of delivery.
CI/CD Pipelines and Automation
It would not be an exaggeration to say that CI/CD pipeline is one of the most important concepts in DevOps. That’s why people often assume it is the whole part of the automation in DevOps. However, it is not the only pipeline out there.
CI/CD pipeline incorporates several steps that can happen consequently or simultaneously. The main point is that with each step the reliability of the product is growing.
Automation and standardization ensure not only faster development and deployment cycles but also error reduction. The less humans are involved in manual and repetitive tasks, the less prone to human error the code is.
Consistent procedures and scripts provide consistency within the whole product and its performance. It also ensures that the team is ready for any type of bugs or errors that can occur. Some things cannot be prevented, so the best idea is to be ready to respond quickly and appropriately.
Essential DevOps Automation Tools
Here are eight crucial tools used in DevOps automation, along with their specifics, pros, and cons.
1. Jenkins
It is a powerful and versatile CI/CD pipeline automation tool with a massive ecosystem of existing plugins. It can be used as a CI server or a CD hub. One of the main benefits of it is the ease of installation and configuration. The plugin architecture makes the app very easy to scale up and extend.
The programmers use it for code deployment, task automation, testing, increasing code coverage, and a simpler audit.
Price: Free
Pros: It supports various control tools and can be distributed across multiple machines. It is a free and open-source solution with easy installation and usage. Moreover, it is adaptable and platform-independent.
Cons: The single-server architecture is not ideal for huge environments and multiple teams. If there are too many tasks at one moment, the server can easily get overwhelmed. It slows all the processes down and can even result in a server crash. Also, the program was created before container architecture became the new norm. So it is not inherently aligned with the container building principles. Among other cons, there are difficulties with implementation in the product environment and complex plugin management.
2. GitLab CI/CD
It is another popular tool for a CI/CD pipeline. It supports parallel job configuration and keeps the code management with CI in the same place. Also, the tool supports a container environment and horizontal scalability. It comes with a large ecosystem of users and pre-made solutions, along with reporting and auditing.
Price: Free for the basic version or $19 per month for a premium one
Pros: Great testing features, strong version control, and easy installation and configuration. It also supports Jekyll plugins. Also, the tool comes with auto-scaling of CI runners and Milestone setting (monitoring, tracking, and reporting issues). Overall, it is an efficient tool with a multitude of useful features like reliable security and privacy, merge request integration, and easy scalability.
Cons: One must define and upload artifacts for every job, which adds to the overall timeline. The testing of the merge state can happen only after the merge is done. There is also no support for stages within phases.
3. Docker
It is one of the most popular containerization tools currently. This application offers an opportunity to package an application into containers. They are lightweight and easily manageable. The main reason why programmers use such architecture is that it makes any application consistent and reliable across various environments.
Price: Personal use is free; professional costs $11 per month and $16 per month for a team.
Pros: Containers can run across any environment, which makes them remarkably consistent and portable. Thanks to OS kernels, they are very lightweight, which means lower operational costs, faster start, and less storage space. Containers also create isolated and secure systems with strong version control and streamlined development and deployment.
Cons: Container systems are not suitable for apps that require different OS for the same host – they cannot replace virtual machines. Isolation is not as secure as virtual machines. Moreover, containers are not always as efficient as native apps. Also, the tool requires a decent learning curve to be used properly.
4. Terraform
https://developer.hashicorp.com/terraform
It is an IaC tool that covers low-level and high-level components (from storage and networking to SaaS features). Terraform is the most widespread open-source solution for cloud management so far. It is quite effective for multiple cloud deployment, SDN, and for multi-tier architecture of an application. The tool is portable across various platforms, which is always an advantage.
Price: Free for up to 500 resources per month.
Pros: Cross-platform programming, very detailed documentation, multi-language support. It is easy to use in terms of automation, and there is a large community of programmers behind it. It supports modules (they act like containers) for streamlined IaC management.
Cons: It requires a complex learning curve. Also, there is a limited number of official plugins. Programmers can also use third-party plugins. However, it comes with a dependency on the said third party. Also, state file management comes with a set of difficulties and risks of discrepancies.
5. Prometheus
Prometheus is a neat tool for monitoring. It is designed to work with dynamic containers with very detailed documentation. The main advantage of the tool is its operational simplicity.
Price: $0.9 for the first 2 billion samples, $0.35 for 250 billion samples, and $0.16 for over 252 billion samples.
Pros: It is an open-source program based on time series data. It offers flexible querying and easy integration. It works with Docker, Kubernetes, and many other tools. It is horizontally scalable and has a functional alerting system. The pull-based model means better collection of metrics data and better control. Also, the custom metrics support is very useful.
Cons: The scalability with large deployments is quite tricky. The tool is also not for log support. Another downside is that there is no anomaly detection and no durable storage.
6. SonarQube
https://www.sonarsource.com/products/sonarqube
It is a security tool by SonarSource. It is an open-source platform used for quality assurance of continuous code. The primary goal is to make the codebase maintainable and reliable. Generally, it is a handy program to detect and eliminate various bugs and potential vulnerabilities.
Price: There is a free functionality, but overall, it costs 30 euros per month with up to 100k LOC.
Pros: It is a good tool to improve the quality of the code. The tool easily finds and highlights issues and errors. The tool is great for detecting security vulnerabilities as well. It supports multiple programming languages and integration with various other tools like Jenkins, GitLab, and Azure DevOps.
Cons: As a static code analysis tool, it will produce false-positive results sometimes. Also, the program takes up a decent amount of resources, which can be an issue with a large code base. The feedback is not always as fast as one might want – the more complex the project is, the more time feedback takes. Also, the tool requires a learning curve along with some maintenance (updating and upgrading).
7. Kubernetes
This is an alternative solution for the containerization of an application. It works similarly to Jenkins. It is a powerful tool with great scalability functionality (dynamic and in real-time).
Price: It is a free solution, but one has to pay for storage, virtual machines, and services. Droplet nodes cost $12 per month per node. The block storage starts with $10 per month.
Pros: Open-source solution with pay-as-you-use model for storage and nodes. It is robust, scalable, and flexible. Kubernetes offers excellent container orchestration possibilities. The program can automate deployment, scaling, and management of containers. Another great advantage is the high reliability and availability of applications it offers. It is efficient in terms of resources, has a great ecosystem, and supports CDs.
Cons: It is a complex tool with a decent learning curve. It also requires significant hardware resources to operate fully. And it has the same security vulnerabilities as Jenkins when it comes to container networks and isolation. Kubernetes requires constant updates and maintenance. Also, it is not suitable for monolithic architectures and legacy apps.
8. Reflect
It is a great no-code automation tool for testing. This is its main selling point – customers do not need to write code to automate testing of web apps. Among unique features it has generative AI that helps tests adapt to your application and its changes.
Price: Free trial period for 14 days and 30 minutes of free testing. $212 per month for a team package, $530 per month for a professional package.
Pros: Very user-friendly and requires no coding for automation. It supports visual testing with screenshots. Also, it can run tests on different browsers. The functionality includes API testing and backend validation. Overall, a powerful tool with CI/CD integration.
Cons: In terms of mobile testing, the tool is quite limited in functionality. It is best for web applications. Also, the price is relatively high. There could be more customizations in terms of test configurations.
Overall, all DevOps automation tools come with a set of benefits and limitations. To understand which to use for a specific case, one needs to evaluate all the factors from budget to app architecture and potential scalability.
DevOps Automation Best Practices
Automation in DevOps has its own set of best practices that one needs to keep in mind.
- Automate Everything Possible: Identify and automate repetitive, error-prone, and time-consuming tasks. It takes time and expertise to find the processes that require automation and would benefit from it.
- Build Robust CI/CD Pipelines: This covers the automation of code integration, testing, and deployment. All of that comes with a faster delivery, higher reliability, and a continuous feedback loop.
- Implement Infrastructure as Code (IaC): DevOps professionals use code to manage and provision infrastructure for consistency and repeatability. IaC’s strong point is that it offers much faster deployment and development, along with easy configuration.
- Automate Testing: The integration of automated tests at every stage is imperative. It allows the team to catch issues early and ensure reliability of the app. A constant feedback loop provides reliable error detection. It improves the code base quality and reliability.
- Monitor and Log Extensively: DevOps practices include automated monitoring and alerting to find and resolve any issues asap.
- Plan for Failures: There has to be a rollback and recovery mechanism; DevOps often uses deployment strategies like blue/green and canary releases to ensure they are covered for potential failures. When it is impossible to eliminate risks, the best practice is to come prepared for various situations. So, if the inevitable happens, the team knows how to act fast.
- Integrate Security: Automation of security checks and compliance as part of the pipeline. It crosses with DevSecOps in terms of importance and purpose.
- Foster Collaboration and Continuous Improvement: DevOps methodology is not only about software and hardware. It is a mindset principle and communication point. Professionals encourage open communication, feedback loops, and incremental enhancements to ensure proficient collaboration between teams.
Common Challenges in DevOps Automation and Future Trends
DevOps aims to create a collaborative environment where all members of the software development process can efficiently work together and create reliable and scalable products quickly. Automation is a huge part of it as it reduces mundane and repetitive tasks while freeing human resources.
Naturally, automation is very desirable because it comes with a multitude of benefits like reliable performance, fast delivery, and higher security. However, automation has its limitations and challenges. Here are some of the most common ones.
1. Mindset shift
One of the main challenges comes not from software but from cultural resistance. The shift to a new methodology and mindset can be complicated for teams. When a company decides to shift, it is important to address the decision to the team members and communicate the shared goal and motivation for doing so.
2. Tool integration
A DevOps environment is created with a set of various tools and programs. All of them have their specifics and limitations. As a result, the integration process can be complex and daunting. All of the various tools must work seamlessly together; that’s why the choice of particular programs is so important.
3. Development speed vs. security and compliance
As the speed of all processes grows, it becomes more challenging to keep up with security risks and issues along with compliance. Also, the usage of third-party tools and plugins increases the number of potential vulnerabilities.
To overcome it, DevOps professionals put an extra focus on security tools and risks along with proper documentation. It is all about being proactive with continuous testing, monitoring, and alerting. The integration of security tools into pipelines is a must (it is often referred to as DevSecOps methodology).
4. Manual processes
No matter how much automation one introduces into the process, there will still be manual operations. For instance, manual testing is still incredibly relevant, no matter how many automatic tests the system runs. Each manual process adds time to the whole project and opens a door for inconsistencies and errors.
There is a need for a balanced approach. All that can be effectively automated should be automated. On the other hand, tasks that require human creativity or expertise should remain manual. Automation would be too complicated and unreliable in the current state of technology.
The goal is to investigate which is what and create a standardized system of integration for these tasks.
To Sum Up
DevOps automation is an incredible set of principles and tools for increasing the speed and reliability of any application. With the right and holistic approach, it can transform the whole process and the collaboration between teams.
At the same time, it comes with a lot of responsibility and choices, which means experts must do everything correctly, from identifying processes that should be automated to selecting specific tools and programs. It is a developing field that requires constant learning and adapting to new findings and environments.
