DevOps Automation Guide for Streamlining Development and Operations

Time is the enemy of nearly every developer. Despite new, agile methodologies to speed up the development process without sacrificing quality, development teams still face the conundrum of how to new code updates to production faster and more efficiently. For these reasons, DevOps automation has resonated with development teams who are obsessed with going faster. This article will explore DevOps automation, how it’s changing software development and some of the benefits of automation in DevOps. We’ll also explore what challenges companies face when adopting DevOps automation services.

What is DevOps automation?

DevOps automation adds technology (AI, business intelligence, machine learning, etc.) to development. With a DevOps automation platform, developers and engineers can automate tasks that previously took months while also speeding up the number of updates they send to production and deployment.

However, even though the benefits of automation in DevOps are clear, it has yet to take over entirely. A survey of leading software companies found that only 36% had switched some manual processes to automation. But this figure represents an increase from 30% in the previous year.

The hesitancy of some developers over adopting DevOps automation comes from the flurry of challenges accompanying it. For example, one systematic literature review found that many critical success factors must be in place before DevOps infrastructure automation. Among the CSFs that companies need are:

• Integration - meaning successful integration with existing tools and infrastructure
• Organizational hierarchy - meaning communication is good between different teams and stakeholders
• Cultural shift - meaning the organization has already committed itself to DevOps principles and best practices

There are over a dozen more. Even within these categories, companies must address several sub-categories, such as strategic planning and performance engineering, before deciding which DevOps automation tasks best suit them. This analysis is essential for determining how and where to apply DevOps automation since one of the benefits of automation in DevOps is its versatility. You can use DevOps automation at various points during the development cycle.  But DevOps principles preach collaboration as a central tenet. This tenet means that the other side of the DevOps equation (Operations) also has a significant say in where and when to deploy DevOps automation services.

Ultimately, plurality and a multitude of voices are what DevOps culture demands, so this input from various sources is a strength of DevOps automation, not a hindrance. Given that there are so many stakeholders involved in how to employ DevOps workflow automation, deploying DevOps automation can be tricky. For all its benefits, it can be a laborious, resource-consuming process, so teams have to choose wisely where they use it. For this reason, we’ll look deeper at the categories where automation helps DevOps teams the most so you can better understand how this practice can transform your development process.

Core Areas for DevOps Automation

DevOps automation has become a critical enabler in modern software development. However, automation in DevOps spans various areas, including deployment pipelines, infrastructure management, and security controls. You can use DevOps automation software to manage and secure any one of these crucial aspects of development.

However, many practitioners have found that one of the most appealing assets of DevOps automation is how it improves efficiency by reducing the gap between development and operations through continuous feedback loops. With these loops in place, DevOps teams can better communicate with each other to ensure only quality builds make it to production.

To explore further what automation in DevOps can accomplish, we’ve outlined some of the main categories of DevOps automation and how they have affected various companies’ output and performance.

Continuous Integration and Continuous Deployment (CI/CD)

CI/CD is the heart of DevOps automation. Continuous Integration (CI) refers to frequently integrating code changes into a shared repository, where they are automatically tested. Continuous Deployment (CD) involves automatically deploying every change that passes the tests into production. Major companies like Google and Amazon rely on CI/CD to handle thousands of daily deployments. The benefit of DevOps workflow automation is evident—faster releases, higher-quality code, and a more reliable infrastructure.

Infrastructure as Code (IaC)

Infrastructure as Code (IaC) is a critical practice in DevOps automation that automates the provisioning and management of infrastructure. IaC allows you to define infrastructure configurations in code, which can be versioned and reused. Tools like Terraform and AWS CloudFormation lead the DevOps automation platform market, allowing businesses to scale infrastructure effortlessly.

Take the case of Netflix, which utilizes IaC to deploy infrastructure resources in a dynamic cloud environment. This automation enables Netflix to support billions of video streams, dynamically scaling their server capacity based on demand. With infrastructure automation in DevOps, teams can ensure consistency across environments, reduce human error, and manage complex architectures with minimal manual intervention.

Configuration Management

Configuration management automates the setup and maintenance of system configurations, ensuring that infrastructure components are deployed with the correct settings. DevOps automation is essential in maintaining the reliability of servers, databases, and application settings across different environments. Puppet and Chef are popular tools in this category, allowing for automated and consistent configuration management. By integrating configuration management into your DevOps automation framework, you can ensure consistency and speed, which translates into higher operational efficiency.

Security Automation

Security automation is no longer an option but a necessity in software development. Security automation integrates security controls directly into the DevOps workflow automation, ensuring vulnerabilities are detected early in development. Tools such as Snyk and Aqua Security scan code repositories, containers, and dependencies for vulnerabilities, allowing teams to address security risks before they reach production.

For instance, Adobe adopted Snyk’s DevSecOps tools to monitor their open-source dependencies, preventing security vulnerabilities from impacting their applications. The integration of automated security testing reduced their vulnerability exposure. Automating security checks within the development cycle ensures that your applications are secure without slowing down the release process, making DevOps automation an essential strategy for modern software development.

Monitoring and Logging

Monitoring and logging are crucial for maintaining the health of your applications and infrastructure. Automation allows teams to detect and respond to incidents in real time. Tools like Datadog, Prometheus, and Elasticsearch provide robust monitoring capabilities that automatically generate alerts based on predefined thresholds.

For example, Airbnb uses Prometheus to monitor its microservices, allowing its engineers to detect performance bottlenecks before they affect customers. Automated monitoring can significantly reduce mean time to recovery (MTTR) in the event of an incident, allowing for faster resolution and less downtime. By implementing DevOps workflow automation in monitoring, you ensure your system remains operational even when faced with unexpected issues.

Automated Testing

Automated testing is integral to DevOps automation, ensuring that code is thoroughly tested before being released into production. Automated testing can include unit, integration, performance, and security tests, which are triggered every time a new code is pushed. This process eliminates the need for manual testing, reducing human error and improving code quality.

Microsoft adopted automated testing to streamline its DevOps practices. With over 100,000 developers contributing to its Azure platform, automated testing ensures that every code change is verified before it goes live. By automating testing, Microsoft reduced testing time by allowing faster delivery of new features and patches. Automated testing will enable you to maintain high-quality software, even in fast-paced development cycles. Integrating computerized tests within your DevOps automation framework ensures you catch bugs early, reduce technical debt, and stabilize your software.

Top 10 DevOps Automation Tools

There are dozens of quality DevOps automation tools. However, savvy DevOps practitioners would be best prepared to confront the challenges associated with implementing DevOps automation by adopting several toolkits. As we’ll see with this summary, each tool uniquely enhances the DevOps automation process, offering distinct benefits that contribute to more efficient and reliable development and operations - exactly what DevOps teams seek.

Integrating these tools into your DevOps workflow automation allows you to streamline processes, improve consistency, and achieve greater control over your infrastructure. From containerization with Docker to configuration management with Puppet and Chef, these tools provide a broad solution for modern DevOps practices. We’ll talk about their main highlights and give a few reasons why each tool is an irrevocable part of streamlining development and operations.

Jenkins

Jenkins is a popular (probably the most popular) DevOps automation tool known for its high-performing capabilities in continuous integration and continuous delivery (CI/CD). By automating the build, test, and deployment processes, Jenkins helps you maintain consistent code quality and accelerate release cycles. Its extensive plugin ecosystem allows for customization and integration with various tools, making it adaptable to different DevOps automation frameworks. For example, Jenkins can automate the deployment of applications to a Kubernetes cluster, facilitating smoother updates and rollbacks.

Docker

Docker revolutionizes how you package and deploy applications by using containerization. It simplifies the creation, deployment, and running of applications through lightweight, portable containers that encapsulate everything the application needs to run. This approach enhances consistency across different environments and reduces conflicts between dependencies. Docker’s role in infrastructure automation in DevOps is crucial as it allows you to scale applications and efficiently manage complex deployments. For instance, Docker can package an application with all its dependencies, ensuring it runs the same way in both development and production environments.

Kubernetes

Kubernetes is a powerful container orchestration tool that automates containerized applications' deployment, scaling, and management. It works seamlessly with Docker and other container technologies to efficiently manage complex applications. Kubernetes provides features like automated scaling, load balancing, and self-healing, which enhance the reliability and efficiency of your deployments. For example, Kubernetes can automatically adjust the number of running instances of an application based on current traffic, ensuring optimal performance and resource utilization.

Ansible

Ansible is an open-source automation tool that simplifies configuration management and application deployment. It uses declarative language to define the desired state of your systems, making it easy to automate tasks such as provisioning servers and deploying applications. Ansible’s agentless architecture reduces overhead, allowing faster and more straightforward automation. In the context of DevOps automation, Ansible can manage configurations across multiple servers, ensuring consistency and reducing manual intervention. For instance, you can use Ansible to automatically configure a new server to meet your application's requirements, including installing necessary software and setting up user permissions.

Git

Git is a distributed version control system that is fundamental to DevOps automation. It allows you to track changes in your source code and collaborate with other developers efficiently. By integrating Git with CI/CD tools like Jenkins, you can automate the process of building and testing code changes, leading to faster and more reliable software releases. Git’s branching and merging capabilities facilitate parallel development and enable you to manage multiple features or fixes simultaneously. For example, you can use Git to create feature branches for new development and merge those changes into the main branch after passing automated tests.

Puppet

Puppet is a configuration management tool that automates the deployment and management of your infrastructure. It uses declarative language to define the desired state of your systems and ensures that your infrastructure remains consistent and up-to-date. Puppet’s ability to manage complex configurations across multiple servers makes it a valuable asset in infrastructure automation in DevOps. For instance, Puppet can automatically apply security patches to all servers in your environment, protecting them against known vulnerabilities.

Bamboo

Bamboo is a continuous integration and deployment tool developed by Atlassian. It integrates well with other Atlassian products like Jira and Bitbucket, offering an all-encompassing solution for managing your build and release processes. Bamboo’s user-friendly interface and powerful features help streamline the DevOps automation process by letting you look under the hood of your build and deployment pipelines. For example, you can configure Bamboo to automatically trigger builds and deployments based on changes in your Git repository, ensuring that your latest code changes are quickly tested and deployed.

Nagios

Nagios is a monitoring tool that helps you keep track of the performance and availability of your IT infrastructure. It provides comprehensive monitoring and alerting capabilities, allowing you to identify and address issues before they impact your operations. In DevOps automation, Nagios can be integrated with other tools to provide real-time insights into the health of your systems and applications. For example, Nagios can monitor the performance of your servers and alert you if they are approaching resource limits, enabling proactive management and reducing the risk of downtime.

Chef

Chef is a configuration management tool that automates the provisioning and management of your infrastructure. It uses declarative language and a set of predefined recipes to define and apply configurations across your servers. Chef’s ability to manage complex environments and integrate with other DevOps automation tools make it a valuable asset in streamlining your development and operations processes. For instance, you can use Chef to automate the installation and configuration of software across a fleet of servers, ensuring that all systems are configured consistently and according to your specifications.

Challenges in DevOps Automation and Solutions

DevOps automation brings efficiency and agility to software development processes, but several challenges can arise when trying to implement it. These challenges include overcoming team mentality issues, transitioning from legacy systems, avoiding overreliance on tools, managing resistance to change, and resolving clashes between Dev and Ops toolsets. Each challenge requires careful planning and strategic solutions to ensure a smooth transition toward DevOps integration. Below, you’ll find an elaboration on these challenges and practical solutions based on actual studies and practices.

Eliminating the “Dev vs. Ops Mentality”

One of the most significant hurdles in DevOps automation is overcoming the traditional divide between development (Dev) and operations (Ops) teams. Historically, Dev teams focused on rapid code changes, while Ops prioritized stability and system reliability, often leading to conflicting goals. This mentality persists in many organizations, making implementing a collaborative DevOps culture difficult. This issue is exacerbated in larger organizations, where the hierarchical structure may reinforce the separation between Dev and Ops teams.

Fulfilling a culture of collaboration and shared responsibility is vital to overcome this challenge. As noted by Nasreen Azad and Sami Hyrynsalmi, organizational size, and management support play critical roles in adopting DevOps practices: "Our findings also suggest that the size of the organization and management support also plays a significant role in critical decision-making for DevOps adoption for CSFs". Top-down management support helps break down silos and encourage teamwork. You can bridge the gap between Dev and Ops by implementing cross-functional teams where both groups work closely together from the outset of a project, sharing responsibilities and objectives. This shared accountability helps foster a more collaborative mindset that is essential for successful DevOps automation.

Moving from Legacy Infrastructure to Microservices

Another common challenge is transitioning from legacy infrastructure to microservices. Many organizations still rely on older monolithic applications, which can be difficult to modify, scale, or integrate into modern DevOps automation frameworks. Legacy systems are often rigid, with tightly coupled components that make minor changes risky and time-consuming. The shift to microservices—where applications are broken down into smaller, independently deployable components—promises greater flexibility and scalability, but migrating to this architecture can be complex and resource-intensive.

To ease this transition, adopting Infrastructure-as-Code (IaC) can help automate the provisioning and management of your infrastructure, making it easier to manage complex microservices architectures. Using tools like Ansible, Terraform, or Chef, you can define your infrastructure in code and automate its deployment. This approach reduces human error and ensures consistency across environments. Additionally, implementing microservices gradually, starting with less critical applications, allows your teams to gain familiarity with the architecture and minimize disruptions to your operations. This way, you can make the transition smoother and more manageable while continuing to innovate with your DevOps automation platform.

Too Much Focus on Tools

While tools are essential for DevOps workflow automation, putting too much emphasis on them can create problems. With so many tools available for version control, CI/CD, infrastructure management, monitoring, and more, it’s easy to become overwhelmed by the complexity of managing and integrating them. The use of multiple tools often leads to fragmented processes, where different teams rely on different toolsets, resulting in a lack of uniformity and difficulties in maintaining and troubleshooting the system.

The solution to this problem lies in adopting a holistic approach that focuses on processes and collaboration, rather than just the tools themselves. Instead of trying to use every available tool, you should prioritize adopting a cohesive set of tools that integrate seamlessly into your DevOps automation framework. For example, tools like Jenkins, Kubernetes, and Docker can be integrated to provide a unified pipeline for building, testing, and deploying applications. Additionally, ensuring that your teams are properly trained in using the chosen tools will reduce integration issues and make it easier to maintain the system over time.

Resistance to Change

Resistance to change is a common obstacle when introducing new processes like DevOps. Many team members and stakeholders may feel threatened by the shift, particularly if they perceive DevOps as a complete overhaul of existing practices. This fear can result in a reluctance to adopt new tools or workflows, leading to delays or outright failure in implementing DevOps automation.

It’s helpful to position DevOps as an evolution of your current development practices, rather than a radical revolution. Highlight the benefits of infrastructure automation in DevOps, such as faster release cycles, improved collaboration, and more reliable systems, to demonstrate how DevOps can enhance the way your teams work without requiring them to abandon what they already know. Training and ongoing support can also help ease the transition, ensuring team members feel confident in adopting new practices. Additionally, involving key stakeholders early in the process allows you to address concerns and gain buy-in from those who are most affected by the changes.

Dev and Ops Toolset Clashes

Another challenge is the clash between the different toolsets used by Dev and Ops teams. Development teams often use tools geared toward rapid iteration and flexibility, while operations teams prioritize stability and reliability. This divergence can lead to incompatible workflows and conflicting metrics, making it challenging to integrate DevOps effectively.

To resolve this issue, it’s important to establish a unified toolchain that supports both development and operations needs. Using an end-to-end DevOps automation platform like GitLab or Bamboo can help provide a familiar interface for both teams, reducing the friction caused by incompatible toolsets. Standardizing common metrics, such as deployment frequency or mean time to recovery, allows both teams to align their goals and measure success using the same benchmarks. This alignment ensures that your chosen tools and processes contribute to a cohesive DevOps workflow automation.

Conclusion

With a deep understanding of continuous integration and continuous deployment (CI/CD) pipelines, VodWorks can help you achieve faster delivery cycles while maintaining high-quality standards. Our expertise in DevOps automation platforms and infrastructure automation in DevOps allows your organization to scale operations, reduce manual errors, and enhance overall productivity. Contact us today to learn more about what our DevOps automation experts can do for your business.