DevOps Automation

DevOps Automation

A revolutionizing technology, DevOps has captured the attention of the IT world and become the most sought-after software engineering methodology today. It is considered the driving force responsible for improving the efficiency and productivity of Information Technology and establishing a more unified and collaborative workflow that helps deliver sophisticated, innovative, and high performing applications.

However, meeting the fast-growing consumer demand for quality products and agile services was not only possible through collaborative efforts and practices. It required technology-driven solutions to cater to their changing needs. Hence, DevOps incorporated automation to effectively meet these requirements, trigger enhanced productivity through reduced manual labor and eliminating communication delays, and effectively tackle various SDLC issues.

This led to the introduction of one of the most promising principles of DevOps implementation, DevOps Automation.

What is DevOps Automation?

A critical component for accelerating DevOps implementation, Automation in DevOps helps organizations establish consistency, speed, higher accuracy, efficiency, and reliability by enabling teams to identify and troubleshoot problems. Implemented to increase the process' efficiency, DevOps Automation involves automating a wide range of relatively slow and complex processes in software development and infrastructure maintenance, which further ensures and promotes continuous deployment and delivery.

Automation is a crucial need for DevOps practices as it fundamentally automates everything from build and code generation to infrastructure setup and configuration, software deployment, and monitoring.

To achieve DevOps automation, organizations repackage systems, platforms, and applications into reusable building blocks through technologies like virtual machines and containerization. Moreover, they use various tools for automation implementation that should cover the following areas of SDLC:

• Infrastructure as Code
• CI/CD
• Test automation
• Containerization
• Orchestration
• Software Deployment
• Software Measurement

In short, with the help of DevOps Automation organizations can facilitate feedback loops between operations and development teams and ensure iterative updates are deployed faster to applications in production. Moreover, it will allow the DevOps team to get effective insights that help them move in the right direction and better serve the end-users.

DevOps Automation Best Practices:

DevOps Automation is continuously evolving to help organizations in the pursuit of continuous application development and delivery. However, to ensure this, teams need to put great efforts to eliminate bottlenecks, improve product features, fix issues, and swiftly respond to customer requirements.

Moreover, businesses will have to reduce friction between ideas, adopt common, open standards for packaging, runtime, configuration, networking, and storage, and use dynamic variables and flexible tools.

That's not all!

The team will need to follow certain best practices that help them reach their goals, without being restricted by the toolchain. Divided into the following four categories, these practices of DevOps Automation will get the teams moving in the right direction:

• Continuous Integration, Continuous Delivery, & Continuous Deployment (CI/CD): Core components of DevOps Automation, CI/CD creates a collaborative process through shared ownership and unified goals and allows the team to maintain quality control through automation. Moreover, Continuous deployment ensures all successful changes are automatically deployed to production and helps deliver new features to users effectively.
• Change Management: To succeed with DevOps automation, organizations need to implement effective change management plans that allow the development and operations team to create consistency. This involves the following practices:
  1. Version Control: Also known as Source code is the practice that helps the team to track changes and learn from past decisions. It promotes team collaboration and offers them a common workflow and codebase to work with.
  2. Change Control: Another important element of change management, change control helps maintain code's version history, coordinates and facilitates changes to maintain product direction, reduces harmful code changes, and promotes collaborative processes.
  3. Configuration Management: An automated process that helps manage complex deployments using templates. Moreover, it uses proper controls and approvals to successfully manage changes at scale.
• ‘X' as Code: ‘X' as a Code encompasses various models that are crucial for DevOps automation, as they offer a declarative framework for seamless operating environment management and help create a consistent, reliable, and testable process for resource deployment. These models are:
  1. Infrastructure as Code (IaC): IaC helps the team create a production-like environment using the versioning and workflow used by developers for source code, which is utilized to test applications early in the development cycle. This prevents common deployment issues and helps the team deliver a stable environment rapidly, reliably, and at scale.
  2. Platform as Code (PaC): Implemented through abstraction, PaC offers a framework for the recreation of the same infrastructure and allows the team to deploy services or changes to the existing infrastructure rapidly. It promotes collaboration between Development and Operations teams and enables them to repeatedly and consistently deliver efficient enterprise applications.
  3. Configuration as Code (CaC): CaC defines the application configuration as versioned resources and helps save time, increase flexibility, and improve system uptime. It is another important model of the process, that helps migrate the configurations to the release pipeline, alongside application code, while backing it with the version control system.
  4. Policy as Code: This model helps bring DevOps workflow and versioning to security and policy management, which helps enhance application security, improves compliance, ensures efficient deployment, establishes control over infrastructure, and allows effective use of Cloud-native resources.
• Continuous Monitoring: The critical aspect of DevOps Automation, Continuous Monitoring is used to monitor applications and infrastructure performance and stability throughout the software lifecycle, as well as to understand software behavior to ensure maximum security and quality. This helps collect necessary the data required for troubleshooting and debugging and allows the team to prevent interruptions, outages, and system crashes.
  1. Logging: Offer a continuous stream of data about your business' critical components, which is used to learn and improve products.
  2. Monitoring: Offers insights into the raw data provided in logs and metrics, which is used to enhance the quality of the product.
  3. Alerting: Offers proactive alerts and notifications to let the team know when something goes wrong in the software and provides them with needed debugging information for quick problem resolution.
  4. Tracking: Offers a deeper insight into application performance and behavior and identifies issues that may impact application stability and scalability in the production environment.

These DevOps Automation practices, along with some necessary DevOps automation needs evaluation, are an effective way of accomplishing your goals and ensuring the efficiency of your end product. These not only help save time, cost, and efforts but also allow you to deliver a quality, reliable, and scalable application consistently.

Steps to Prioritize in DevOps Automation:

DevOps Development Cycle encompasses numerous processes and practices, which might vary from one project or organization to another. However, one cannot automate this process entirely, as it can lead to increased dependency on tools and make the process costly and prone to issues. Hence, before implementing DevOps automation, the team needs to choose and prioritize what needs to be automated to ensure seamless execution as well as to maintain the speed of the entire process.

Therefore, listed below are some critical phases of the process that ought to be automated and considered while making this decision:

• CI/CD: Without automating Continuous Integration and Continuous Delivery cannot ensure rapid development, deployment, and delivery of the software application, which makes it essential to automate this process.
• Software Testing: Testing is one of the most important phases of SDLC that helps ensure the performance, functionality, reliability, quality, and accuracy of the software. However, manual testing limits the process as it is dependent on the number of team members dedicated to the project. Hence, by automating software testing through various tools, the organization can increase the thoroughness of testing.
• Monitoring: By automation software monitoring, you can continuously evaluate and monitor the availability, performance, or security problems of your application and generate alerts based on them.
• Log Management: Another task that can benefit from automation is log management. As the DevOps environment generates a vast amount of data, collecting and analyzing this data manually can be difficult. Hence, with log management solutions teams can automatically aggregate and analyze log data and save time and efforts.

Now that we have a comprehensive understanding of what to automate during DevOps automation, let's move on to the tools that are used for DevOps Automation.

DevOps Automation Tools:

There are a variety of automation tools available in the market to cater to the specific requirements of each DevOps project. However, deciding on the right tools has become an ever-challenge for enterprises worldwide. Hence, here is a list of the best DevOps tools, categorized as per their major functions, to help find the suitable tool:

• Infrastructure Automation:
  • Amazon Web Services (AWS): With Amazon's AWS you can effortlessly automate manual tasks and manage complex environments at scale. It is one of the best tools for automating infrastructure provisioning and management and monitoring infrastructure performance. Moreover, it simplifies application code deployment, automates release processes, etc.
  • Terraform: An open-source Infrastructure as Code software tool, Terraform, enables teams to safely create, change, and improve infrastructure. Terraform works with both Public and Private Cloud and allows safe and convenient infrastructure management and improvement.
• Configuration Management:
  • Chef: A Ruby-based DevOps configuration management tool, Chef is a prominent choice of teams that want to automate their development and deployment infrastructure. This tool improves risk management and offers optimal speed, scale, and consistency by simplifying complex tasks and configuration management. Moreover, it automates infrastructure, which allows the teams to respond and adapt to the changing business landscape.
  • Puppet: Puppet is one of the most powerful Configuration Management tools that is used for server deployment, configuration, and management. It uses a Master-Slave architecture and performs functions like dynamic scaling up and down of machines, providing control over all configured machines, and more.
  • Ansible: Another important open-source software provisioning, configuration management, and application-deployment tool, Ansible enables infrastructure code and offers powerful automation for cross-platform computer support. This free tool is extremely easy to set up and use and can model even highly complex IT workflows.
• Deployment Automation:
  • Jenkins: A free and open-source automation server, Jenkins reliably software build, testing, and deployment and facilitates continuous integration and delivery. It provides hundreds of plugins that can be integrated with any tool.
  • IBM UrbanCode: An important deployment tool, UrbanCode Deploy, by IBM automates application deployment through environments and facilitates rapid feedback, continuous delivery, and offers audit trails versioning and production approvals.
• Performance Management:
  • App Dynamic: AppDynamics is an application performance management company that helps improve performance by detecting issues with real-time monitoring and drives business results to improve end-user impact. Moreover, it manages the performance and availability of applications across cloud computing environments and ensures robust security.
• Log Management:
  • Splunk: Splunk is a free tool for real-time monitoring of logs. It is an effective tool that searches and analyzes all the data logs and troubleshoots application outages, investigates security incidents, and demonstrates compliance.
  • PaperTrail: Another important log management tool, Papertrail helps organizations search, live tail, access, and analyze log data. It integrates with communications platforms like PagerDuty and Slack to track down customer problems, debug app requests, or troubleshoot slow database queries.
• Monitoring:
  • Nagios: An enterprise-class free, open-source application monitoring tool used for monitoring and alerting services for servers, switches, apps, and more. Nagios runs periodic checks on critical parameters of application, network, and server resources and offers alerts when issues are identified or resolved.
  • Prometheus: Prometheus is a free metrics-based monitoring system used for event monitoring and alerting. Designed with various support tools, Prometheus records real-time metrics in a time-series database and analyzes the performance of applications and infrastructure.

For a comprehensive list of the best DevOps Automation Tools, click here.

DevOps Automation Benefits:

From facilitating speed, consistency, and scalability to enhancing developers' productivity by minimizing manual burden, reducing chances of failure, and ensuring compliance with standards, DevOps Automation offers a range of benefits to both DevOps teams and the organization, a few of which are listed below:

• Ensures faster time to market.
• Automates workflow.
• Increases deployment rate for new software releases.
• Reduces operational cost.
• Eliminates recurring actions, enabling the team to focus on value addition.
• Reduces dependency on a single source, teams, or tools.
• Decreases risks through continuous monitoring, tracking, and automation.

Conclusion:

Automation, though, is an essential part of DevOps, it is not what the technology is all about. It relies on automation to accomplish various tasks between the teams effectively while saving on time, efforts, and cost, which are dedicated to the critical tasks and processes that cannot be automated.

In short, by automating otherwise manual processes, organizations not only improve the accuracy and speed of the workflow but also manage tasks across the cross-project requirements, reduce associated risks, maintain standards, and allow organizations to effectively meet the raised customer expectations for application performance, reliability, and quality.