In recent years, DevOps has become an important concept that integrates software development (Dev) with system operation and maintenance (Ops). DevOps aims to shorten the development lifecycle and provide continuous delivery of high software quality. DevOps is one of the hottest career fields in the IT industry today, but DevOps is a "golden collection" of multi-domain interweaving. To become a qualified DevOps Engineer (Dev, Ops), you must be proficient in a range of DevOps skills. Here, Worm provides you with the tools and technologies that DevOps professionals must master, which are the most popular tools in the free and open source industry, covering a range of requirements from programming, continuous integration and delivery (CI CD) to infrastructure i.e., IAC, monitoring, etc., to ensure that they can cope with a variety of DevOps roles and scenarios. If you want to enter the DevOps industry, you can follow the list to learn by yourself, and veterans who have already entered the industry can also use this to check and fill in the gaps and enrich their knowledge and toolbox.
DevOps is a set of practices and methods that bring together teams of development (people who create software) and operations (people who deploy and maintain software). Rather than working in separate silos, these teams work closely together throughout the software lifecycle, from design to the development process to production support.
In a traditional setting, these teams may work separately, leading to miscommunication, delays, and an imperfect end product. DevOps ensures that everyone is working together, sharing responsibilities, and constantly communicating from the start to solve problems faster and more efficiently. It is the bridge that connects the creation and operation of software into a cohesive, efficient, and productive workflow.
In other words, DevOps is the practice of ensuring that teams work together and use the same playbook. The ultimate goal is to improve software quality and reliability, and to accelerate the time it takes to deliver software to end users.
In DevOps practice, it is necessary to ensure the consistency and reliability of software delivery, so the unified management of configurations and libraries is the core of DevOps thinking. Store and track configuration changes with centralized configuration management through version control, configuration management, automation, and infrastructure.
Continuous Integration (CI):Developers involved often incorporate their changes into a repository where they run automated builds and tests. The ultimate goal is to quickly catch and fix integration errors.
Continuous Delivery (CD):Following CI, continuous delivery automates the delivery of applications to selected infrastructure environments. This ensures that the software can be deployed at any time without human intervention.
Automation:Automation is at the heart of DevOps. Suitable for testing, deployment, and even infrastructure configuration, it helps reduce manual effort, minimize errors, and speed up processes.
Monitoring & Feedback:Continuous monitoring of application and infrastructure performance is critical. It helps to identify and resolve issues quickly. The feedback loop allows for continuous improvement based on the real user experience.
Mastering the various stages of the DevOps lifecycle is key to fully understanding the essence of DevOps. The following diagram covers the various phases of the DevOps lifecycle and the methods and tools involved.
Plan:In this initial phase, the team decides on the features and functionality of the software, the timeline of project development, the main features, the operating environment, etc.
Development:Once the plan is in place, the developer writes ** to develop the software. This stage involves the use of programming languages and tools to turn ideas into tangible products, and version control of **, which requires collaboration between developers, and involves version control tools such as git, etc.
Build:After coding, the next step is to compile the source into a runnable application, which involves converting the source into an executable program, involving automation tools (CIs) such as automated builds.
Testing:Testing is essential to ensure the quality and reliability of your software. In this phase, automated tests are run to find and fix bugs or issues before releasing the software to users. Tools (CI) such as automated testing and quality management are involved.
Deploy and run:Once the software has passed all the tests, it's time to release it and run it into a production environment that users can access. Deployments should be automated for frequent and reliable releases and require minimal human intervention. It involves automation tools, CI CD tools, IOCs, configuration management tools, etc.
Monitoring:Monitoring involves collecting, analyzing, and using data about the performance and usage of software to identify problems, trends, or areas for improvement, involving monitoring tools.
Improvement to the lower level start:The final phase forms a closed loop, where feedback from monitoring and end-user experience is used to make informed decisions about future improvements or changes.
However, in order to achieve this, specific software tools are required. The good news is that there are top-level open source systems in the DevOps ecosystem that can help us implement some or all of the processes.
At present, container cloud technology has become the foundation of the DevOp system. They have revolutionized the way developers build, publish, and run applications, closing the gap between deployment and deployment like never before.
Containers allow developers to package together an application and all the parts it needs, such as libraries and other dependencies, and publish it as a package. This consistency improves the ease of deployment of complex systems, reduces the variety of problems due to differences in development and production environments, and simplifies the DevOps lifecycle to increase productivity.
At the same time, docker containers can be started and stopped in seconds, making it easier to manage peak loads. This flexibility is critical in today's agile development processes and continuous delivery cycles, enabling teams to push updates into production faster and more reliably.
Containers also provide isolation between programs, ensuring that each application and its runtime environment can be protected individually. This helps minimize conflicts between running applications and enhances security by limiting the scope of potential attacks.
Although containers existed before Docker existed, it made them popular and set them as a key standard widely used in the IT industry. Today, Docker is still the go-to choice for working with containers, making it an essential skill for all DevOps professionals.
In the container-based container cloud ecosystem, this tool is used to manage (orchestrate) this complex cluster. In the DevOps ecosystem, this is called a "coordinator". While there are other widely used alternatives in the container space, such as Swarm, Podman, LXC, etc., when talking about container orchestration, there is one name that stands out as the ultimate solution, and that is K8s (Kubernetes).
As a powerful open-source platform for automating the deployment, scaling, and management of containerized applications, K8S fundamentally transforms the way development and operations teams collaborate, delivering applications quickly and efficiently by automatically allocating applications across clusters of machines.
K8S also supports seamless application scaling to respond to changing needs, ensuring optimal resource utilization and performance. K8S abstracts away the complexity of managing infrastructure, freeing developers to focus on writing and operations teams to focus on governance and automation.
In addition, K8S is user-friendly with the CI CD pipeline, automating the check-in to deployment process, enabling teams to release new features and fixes quickly and reliably on an ongoing basis.
In simple terms, knowing how to use K8s is essential for every professional in the DevOps space. If you are in this industry, learning K8S is a must.
At the heart of DevOps is the need for automation. The simple syntax of Python and Golang and an extensive library ecosystem allow DevOps engineers to write scripts to automate deployments, manage configurations, and simplify the software development lifecycle. Both languages are supported by modules and tools of the dedicated DevOps ecosystem and process stack system, and they complement each other's advantages and are the two indispensable pillars of the DevOps development system.
Whether it's Ansible (Python) for configuration management, Saltstack, and Python as the glue language, glue integrates various CICD stack tools to enable a continuous DevOps workflow that enables seamless operations across different platforms and environments.
Python is also crucial in the IAC (Infrastructure as a Thing) paradigm, allowing teams to define and configure infrastructure through Python. Libraries such as Terraform and CloudFormation are often used with Python scripts to automate the setup and management of servers, networks, and other cloud resources.
Python's data analysis and visualization capabilities are invaluable for monitoring performance, analyzing logs, and identifying bottlenecks. Tools such as Prometheus and Grafana are often integrated with Python to enable DevOps teams to maintain high availability and performance.
Python is also widely supported in the popular human field, and DevOps and data intelligence are indispensable to access AI, which makes it even more dependent on this language.
The vast majority of tools in the DevOps ecosystem include Docker, K8S, CoreOS, InfluxDB, Traefik, Hugo, Terraform, OpenTof, and Gitlab Runner and many cloud-native tools are developed using Golang, so Golang is a natural big brother in DevOps development, and in order to make achievements in the DevOps ecosystem, you must learn Golang development well.
Git, a distributed version control system developed by Linus for three months, has dominated the world of software development, version management and collaborative development, and is an integral part of the DevOps system. Git provides a comprehensive history of project changes, making it easier to track progress, recover errors, and understand the evolution of the library. This feature is essential to maintain the speed and quality of development that DevOps is looking for. Git integrates seamlessly with the Continuous Integration Continuous Deployment (CI CD) pipeline, creating a de facto DevOps stack that acts as the source of the stack (** and configuration management repositories) and is triggered by streams (modifying push, pull, and triggering subsequent CI CD actions with various git hooks).
Understanding Git enables DevOps professionals to effectively implement and manage branching strategies, such as popular Git processes.
A lot of the work done by DevOps teams starts with simple git commands. As a switch triggered by the DevOps flow, it directly initiates a series of steps in the CI CD process, culminating in a complete software product, a functioning service, or a stable IT infrastructure.
In short, for industry professionals, commands such as "pull", "push", "commit", etc., are the DevOps alphabet. Therefore, getting better and succeeding in this field depends on proficiency in using git.
Automation tools such as Ansible, Saltstack, Puppet, and Chef are at the core of our DevOps practices and play a key role in infrastructure, configuration management, and application deployment as open source automation tools. It is becoming increasingly important for professionals in the DevOps field to master the skills of automated execution tools.
These tools allow teams to automate software configuration, configuration management, and application deployment processes. This automation reduces the potential for human error and significantly increases efficiency, allowing teams to focus on more strategic tasks rather than repetitive manual work.
While this is not mandatory for DevOps engineers, just like containers, Kubernetes, and Git, any position in a DevOps role requires proficiency in the use of automation tools.
Jenkins is an open-source automation server that facilitates continuous integration and continuous delivery (CI CD) practices, enabling teams to build, test, and deploy applications faster and more reliably.
Jenkins works by monitoring changes to the version control system, automatically running tests against new ones, and facilitating the deployment of builds to production.
Because of these qualities, just as Kubernetes is the preferred tool for container orchestration, Jenkins is also the tool of choice for the CI CD process, automating the repetitive tasks involved in the software development lifecycle, such as building**, running tests, and deploying to production.
By integrating with multiple development, testing, and deployment tools, Jenkins is the backbone of a streamlined CI CD pipeline. It enables developers to integrate changes into projects and makes it easier for teams to spot issues early.
Proficient Jenkins is highly sought after in the DevOps space. As organizations increasingly adopt DevOps practices, the demand for professionals who are proficient in Jenkins and similar technologies continues to grow.
Mastering it opens the door to many opportunities, from roles focused on building and maintaining CI CD pipelines to DevOps operations development roles.
GitLab is currently the only full-stack, full-process complete Dev (SEC) Ops platform delivered as a single application, fundamentally changing the way development, security, and operations teams collaborate and build software. From design to development, GitLab helps teams reduce cycle time from weeks to minutes, reducing development costs and time-to-market while increasing developer productivity.
With Jenkins building block scripts and plug-ins for CI CD implementation, GitLab implements a complete DevOps system on a single platform: one interface, one conversation thread, one data store, and one stack for security and design management.
Continuous iterative development and continuous rapid rollout. Empower all teams to work together efficiently with CI CD. Gitlab enables powerful, scalable, end-to-end automation. Gitlab is also a model of agile development and continuous iteration, with a major version a year, a medium version a month, and several patched versions, which can quickly achieve feature updates and iterations, and its Dev(SEC)Ops design concept and features are also the most advanced and fastest in the industry, far ahead of other (such as Jenkins) tools.
Gitlab also comes with built-in security automation required for DevSecOps (advanced features are only supported in Enterprise Premium Editions), *quality, and vulnerability management. Through strict data and security management and compliance checks, the entire stack of security iteration management from production development to delivery is eliminated.
If an enterprise can't adopt a Gitlab one-stack DevOps solution on-premises. For example, if you are using a third-party Git repository (GitHub), you can choose to use the Argo CD.
Essentially, Argo CD is a declarative Gitops continuous delivery tool for Kubernetes, with a Git repository acting as a de facto that defines the application and its environment.
When a developer pushes changes to the repository, Argo CD automatically detects those updates and synchronizes the changes to the specified environment, ensuring that the actual state in the cluster matches the desired state stored in Git, reducing the potential for human error.
Mastering ARGO CD enables professionals to effectively manage complex deployments at scale. This level of proficiency comes with several key benefits, chief among which is enhanced automation.
By tying deployments to version control configurations in Git, Argo CD ensures consistency across environments. In addition, it automates the deployment process, reduces human error, and frees up valuable time for DevOps teams to focus on more strategic tasks.
In addition, as applications and infrastructure grow, Argo CD's capabilities enable teams to easily manage deployments across multiple Kubernetes clusters, supporting scalable operations without compromising control or security.
For professionals in the DevOps space, mastering Argo CD means being at the forefront of the industry's move towards a more automated, reliable, and efficient deployment process. Last but not least, putting in the effort to master the Argo CD can advance the career path.
In recent years, Terraform has become a cornerstone for DevOps professionals, defining and configuring infrastructure – "infrastructure as a matter (IAC)".
Terraform allows developers and IT professionals to define their infrastructure using a high-level configuration language, enabling them to script the setup and configuration of servers, databases, networks, and other IT resources. In doing so, Terraform brings automation, repeatability, and consistency to the often complex infrastructure management process. Make infrastructure management more reliable, scalable, and transparent by automating and integrating it into the development process.
With Terraform, DevOps professionals can seamlessly manage multiple cloud services and providers, deploying the entire infrastructure with a single command. This capability is critical in today's multi-cloud environment because it ensures flexibility, avoids vendor lock-in, and saves time and resources.
In addition, it integrates well with distributed version control systems such as Git, allowing teams to track and review changes to the infrastructure in the same way that they manage applications.
In light of the fact that Terraform's developers have opted for closed sources, Linux ** is launching its open-source compatibility tool, OpenTofu, which is fully compatible and production-ready fork of Terraform. It is strongly recommended that you replace the existing terraform with opentofu or use opentofu from scratch.
Prometheus is an open-source monitoring and alerting toolkit that has gained widespread adoption due to its powerful dynamic service monitoring capabilities. At its core, metrics are collected and stored in real-time as time-series data that allows users to query this data using the PromQL language, allowing DevOps teams to track everything from CPU usage and memory to user-definable custom metrics to gain insight into the health and performance of the system.
Prometheus works by scraping metrics from configured targets at specified intervals, evaluating rule expressions, displaying results, and triggering alerts when certain conditions are met. This design makes it ideal for environments with complex monitoring and alerting requirements.
Overall, Prometheus is a critical skill for anyone in the DevOps space. It provides detailed, real-time insights into system performance and health, making it an integral part of modern, dynamic infrastructure management. As systems become complex, the need for skilled professionals who can effectively leverage Prometheus will only increase, making it a critical competency for any DevOps career path.
Grafana serves as an enterprise monitoring data middle-end interface, helping user teams visualize and analyze metrics from a variety of ** (e.g., Prometheus, Elasticsearch, Loki, etc.) in a comprehensive and easy-to-understand dashboard.
By transforming this digital data into visually compelling graphs and charts, Grafana enables teams to monitor their IT infrastructure and services, providing real-time insights into application performance, system health, and more.
Grafana enables DevOps professionals to be vigilant about the system, identify and resolve issues before they escalate, ensuring smoother operations and better service reliability.
In addition, Grafana enables data from a variety of systems to be aggregated and visualized in a single dashboard, making it a monitoring location for all systems.
On top of that, Grafana's wide range of customization options allows DevOps professionals to tailor the dashboard to their specific needs. This flexibility is essential in areas where the needs of one project may differ significantly from another.
In conclusion, mastering Grafana equips DevOps professionals with the skills to effectively monitor, analyze, and optimize systems. As a result, the ability to harness the power of Grafana will continue to be a valuable asset in any DevOps professional's toolkit. **10,000 Fans Incentive Plan
Summary
The DevOps tools and methodologies listed in this article cover a range of scenarios from programming, automation, version control, continuous integration and delivery (CI CD) to infrastructure i.e., IAC), monitoring, and show best practices in the DevOps industry, whether you're a newbie or a seasoned professional looking to improve your skills.