DevOps Engineer Full Course 2026 | Learn DevOps In 24 Hours | DevOps Tutorial | Simplilearn

Welcome to SimplyLearns YouTube channel. In today's fastmoving digital economy, organizations are expected to release software updates quickly, reliable, and also minimal downtime. However, in traditional development environments, development and operations team often work independently. This separation created communication gaps, slower release cycles, and increased the chances of deployment failures. DevOps emerged as a modern approach to solve this challenge by bringing development and operations teams together. It focuses on collaboration, automation, and continuous improvement to accelerate software delivery while maintaining system stability and reliability. DevOps are not just tools. its culture and a set of practices that enable teams to build, test, deploy, and monitor applications more efficiently. Companies across industry now rely on DevOps engineers to design automated pipelines, manage cloud infrastructure, and ensure seamless application deployment. In this complete DevOps engineer course, you will earn a key concepts and technologies that power modern software delivery pipelines. We will begin with the fundamentals of DevOps and gradually explore essential topics such as Linux version control, continuous integration, containerization, infrastructure as code, cloud computing, monitoring and dev sec op practices. Throughout the course, you will also gain exposure to industry standard tools used by DevOps professionals including Git, Jenkins, Docker, Kubernetes, Terraform, and popular cloud platforms like Amazon Web Services, Microsoft Azure, and Google Cloud Platforms. By the end of this course, you'll have a strong understanding of how DevOps practices help organization to automate workflows, improve deployment speed, and build scalable, reliable systems. Whether you're a beginner exploring DevOps or a developer looking to expand your skill set or an IT professional aiming to transition into DevOps role, this course will provide the practical knowledge and confidence needed to start your DevOps journey. Having said that, let's take a look at today's agenda. We will start off with module one which is introduction to DevOps and DevOps culture. Module two is DevOps life cycle and key principles. Module three is Linux fundamentals for DevOps engineers. Module four is version control with Git and GitHub. Module five is software development life cycle. Module six is continuous integration concepts. Module seven is CI/CD pipelines with Jenkins. Module 8 is containerization with Docker. Module 9 is container orchestration with Kubernetes. Module 10 is infrastructure as code with Terraform. Module 11 is configuration management with Ansible. Module 12 is cloud computing for DevOps. Module 13 is monitoring and logging. Module 14 is dev sec ops and security DevOps. Module 15 is DevOps automation and real world projects. Module 16 is DevOps engineer interview question and answers. That said, if these are the type of videos you'd like to watch, then hit that subscribe button with the bell icon to get notified whenever we host. Also just so that you know if you want to upskill yourself, master cloud computing and DevOps skills and land your dream job or grow in your career then you must explore Simply Learn's cohort of various cloud computing and DevOps programs. Simply learn offers a variety of masters certification and post-graduate programs in collaboration with some of the world's leading universities. Through our courses, you will gain knowledge and work ready expertise in skills like application migration, autoscaling, continuous integration, BI, microservices, database management, and over a couple of dozen others. And that's not all. You also get an opportunity to work on multiple projects led by industry experts working in top tier data and product companies. After completing these courses, thousands of learners have transitioned into cloud computing and DevOps role as a fresher or moved on to higher paying job and profile. If you're passionate about making your career in this field, then make sure to check out the link in the pin comments and in the description box to find DevOps and cloud computing program that fits your experience and areas of interest. So, let's get started with a small quiz. What is the primary goal of DevOps? building website, improving collaboration between development and operations team, designing computer hardware, or is it creating databases? Please let us know your answers in the comment section below. Now, over to our training experts. Right from the start, software development comprise two different departments. The development team that develops the plan, designs, and builds the system from scratch and the operation team for testing and implementation of whatever is developed. The operations team gave the development team feedback on any bugs that needed fixing and any rework required. Invariably, the development team would be idle awaiting feedback from the operations team. This undoubtedly extended timelines and delayed the entire software development cycle. There would be instances where the development team moves on to the next project while the operations team continues to provide feedback for the previous code. This meant weeks or even months for the project to be closed and final code to be developed. Now what if the two departments came together and worked in collaboration with each other? What if the wall of confusion was broken? And this is called the DevOps approach. The DevOps symbol resembles an infinity sign suggesting that it is a continuous process of improving efficiency and constant activity. The DevOps approach makes companies adapt faster to updates and development changes. The teams can now deliver quickly and the deployments are more consistent and smooth. Though there may be communication challenges, DevOps manages a streamlined flow between the teams and makes the software development process successful. The DevOps culture is implemented in several phases with the help of several tools. Let's have a look at these phases. The first phase is the planning phase where the development team puts down a plan keeping in mind the application objectives that are to be delivered to the customer. Once the plan is made, the coding begins. The development team works on the same code and different versions of the code are stored into a repository with the help of tools like git and merged when required. This process is called version control. The code is then made executable with tools like Maven and Gradal in the build stage. After the code is successfully built, it is then tested for any bugs or errors. The most popular tool for automation testing is Selenium. Once the code has passed several manual and automated tests, we can say that it is ready for deployment and is sent to the operations team. The operations team now deploys the code to the working environment. The most prominent tools used to automate these phases are anible, Docker, and Kubernetes. After the deployment, the product is continuously monitored and Nagios is one of the top tools used to automate this phase. The feedback received after this phase is sent back to the planning phase and this is what forms the core of the DevOps life cycle that is the integration phase. Jenkins is the tool that sends the code for building and testing. If the code passes the test, it is sent for deployment and this is referred to as continuous integration. There are many tech giants and organizations that have opted for the DevOps approach. For example, Amazon, Netflix, Walmart, Facebook, and Adobe. Netflix introduced its online streaming service in 2007. In 2014, it was estimated that a downtime for about an hour would cost Netflix $200,000. However, now Netflix can cope with such issues. They opted for DevOps in the most fantastic way. Netflix developed a tool called the Simeon army that continuously created bugs in the environment without affecting the users. This chaos motivated the developers to build a system that does not fall apart when any such thing happens. So on this note, here is a quiz for you. Match the DevOps tool with the phase it is used in. A, B, C, D. None of the above. Today, more and more companies lean towards automation with the aim of reducing its delivery time and the gap between its development and operations teams. To attain all of these, there's just one gateway, DevOps. Meet Tim. Tim builds a robot in his lab, a climate controlled and pollutionfree environment. Once he's done, he drops the robot off at his project partner, Mia's house. Mia takes it out to her backyard to ensure that the robot meets the requirements. But here is where the problem arises. The change in the environment causes the robot to malfunction. Mia is now really annoyed and she has a lot to correct and it seems to her as though Tim didn't really do much. This wall between them leaves a poor robot to bite the dust. Well, what if we broke this wall? Tim and Mia now work together in a common space. Tim develops each block of functionality of the robot which is then immediately checked by Mia. Both are now working simultaneously instead of waiting on the other to finish their task. As and when a feature is ready for use, they are put together to build the final product. They develop a common mindset and share ideas. To further speed up the process, they use several tools which can automate every stage. This means that the robot is now ready sooner with less iterations and manual work. From an organization perspective, Tim would be the developer while Mia the operations. Their union is the core of the DevOps approach. DevOps has several stages and set of tools to automate each of these stages. Let's have a look at these. Tim first puts down a plan. In terms of a software, this could mean deciding on the modules and the algorithms to use. Once he has the plan, he now codes the plan. With tools such as Git, Tim has a repository for storing all the codes and their different versions. This is called version control. Next, this code is fetched and made executable. This is the build stage. Tools such as Gradel and Maven will sort this out. Now, before deployment, the product is tested to catch any bugs. The most popular tool automating testing is Selenium. Once the products are tested, MIA must deploy it. The deploy product is then continuously configured to the desired state. Anible, Puppet and Docker are some of the most common tools used that automate these stages. Now, every product is continuously monitored in its working environment. Nagios is one such tool that automates this phase and the feedback is fed back to the planning stage. And finally we have the core of the DevOps life cycle. The integration stage tools such as Jenkins is responsible for sending the code for build and test. If the code passes the tests, it's further sent for deployment. This is called continuous integration. Let's now have a look at an organization that has adopted the DevOps approach. Which of the below sequence of steps would they follow to develop a software? Leave your answers in the comment section. Keep an eye out for the right answer on the comment section or our YouTube community. Giants such as Amazon, Netflix, Target, Etsy, and Walmart have all adopted DevOps and seen a considerable increase in delivery and quality. In 2014, an hour of downtime for Netflix would cost it $200,000. It became absolutely crucial that Netflix prepared themselves for any sort of failure. And so they took to the DevOps approach and implemented it in the most unique way. They developed a tool called Simeon Army. This tool created failures and automatically deployed them in an environment that did not affect the users. The team would troubleshoot these failures and this gave them enough experience to deal with any degree of collapse. With everything being automated and happening simultaneously, organizations can now deliver at a much faster pace. So considering the benefits of DevOps and its divergence from the traditional methods, would DevOps be the future? Let us know what you think in the comment section below. So DevOps is is an evolution of the agile model. The agile model really is great for gathering requirements and for developing and testing out your solutions. And what we want to be able to do is kind of address that challenge and that gap between the ops team and the dev team. And so with DevOps, what we're doing is bringing together the operations team and the development team into a single team. and they are able to then work more seamlessly together because they are integrated to be able to build out solutions that are being tested in a production-like environment so that when we actually deploy we know that the code itself will work. The operations team is then able to focus on what they're really good at which is analyzing the production environment and being able to provide feedback to the developers on what is being successful. So we're able to make adjustments in our code that is based on data. So let's step through the different phases of a DevOps team. So typically you'll see that the DevOps team will actually have eight phases. Now this is somewhat similar to agile. And what I'd like to point out at time is that again agile and DevOps are very closely related that agile and DevOps are closely related delivery models that you can use. With DevOps, it's really just extending that model with the key phases that we have here. So let's step through each of these key phases. So the first phase is planning and this is where we actually sit down with a business team and we go through and understand what their goals are. The second stage is as you can imagine and this is where it's all very similar to agile is that the coders actually start coding but they typically they'll start using tools such as git which is a distributed version control software. It makes it easier for developers to all be working on the same code base rather than bits of the code that is rather than them working on bits of the code that they are responsible for. So the goal with using tools such as git is that each developer always has the current and latest version of the code. You then use tools such as Maven and Gradal as a way to consistently build out your environment. And then we also use tools to actually automate our testing. Now what's interesting is when we use tools like Selenium and JUnit is that we're moving into a world where our testing is scripted the same as our build environment and the same as using our Git environment. We can start scripting out these environments. And so we actually have scripted production environments that we're moving towards. Jenkins is the integration phase that we use for our tools. And another point here is that the tools that we're listing here, these are all open-source tools. These are tools that any team can start using. We want to have tools that control and manage the deployment of code into the production environments. And then finally, tools such as Anible and Chef will actually operate and manage those production environments so that when code comes to them, that that code is compliant with the production environment. So that when the code is then deployed to the many different production servers that the expected results of those servers which is you want them to continue running is received. And then finally you monitor the entire environment. So you can actually zero in on spikes and issues that are relevant to either the code or changing consumer habits on the site. So let's step through some of those tools that we have in the DevOps environment. So here we have is a breakdown of the DevOps tools that we have. And again, one of the things I want to point out is that these tools are open-source tools. There are also many other tools. This is just really a selection of some of the more popular tools that are being used, but there's quite likely that you're already using some of these tools today. You may already be using Jenkins. You may already be using Git. But some of the other tools really help you create a fully scriptable environment so that you can actually start scripting out your entire DevOps tool set. This really helps when it comes to speeding up your delivery because the more you can actually script out the work that you're doing, the more effective you can be at running automation against those scripts and the more effective you can be at having a consistent experience. So let's step through this DevOps process. So we go through and we have our continuous delivery which is our plan code build and test environment. So what happens if you want to make a release? Well, the first thing you want to do is send out your files to the build environment. And you want to be able to test the code that you've been created because we're scripting everything in our code from the actual unit testing being done to the all the way through to the production environment. Because we're testing all of that, we can very quickly identify whether or not there are any defects within the code. If there are defects, we can send that code right back to the developer with a message saying what the defect is. And the developer can then fix that with information that is real on the either the code or the production environment. If however your code passes the the scripting test it can then be deployed and once it's out to deployment you can then start monitoring that environment. What this provides you is the opportunity to speed up your delivery. So you go from the waterfall model which is weeks, months or even years between releases to agile which is 2 weeks or 4 weeks depending on your sprint cadence to where you are today with DevOps where you can actually be doing multiple releases every single day. So there are some significant advantages and there are companies out there that are really zeroing in on those advantages. If we take any one of these companies such as Google, Google any given day will actually process 50 to 100 new releases on their website through their DevOps teams. In fact, they have some great videos on YouTube that you can find out on how their DevOps teams work. Netflix is also a similar environment. Now what's interesting with Netflix is that Netflix have really fully embraced DevOps within their development team and so they have a DevOps team and Netflix is a completely digital company. So they have software on phones, on smart TVs, on computers and on websites. Interestingly though, the DevOps team for Netflix is only 70 people. And when you consider that a third of all internet traffic on any given day is from Netflix, it's really a reflection on how effective DevOps can be when you can actually manage that entire business with just 70 people. So there are some key advantages that DevOps has. It's the actual time to create and deliver a software is dramatically reduced particularly compared to waterfall. Complexity and maintenance is also reduced because you're automating and scripting out your entire environment. Uh you're improving the communication between all your teams. So teams don't feel like they're in separate silos, but that are actually working cohesively together and that there is continuous integration and continuous delivery so that your consumer, your customer is constantly being delighted. Hey there and welcome to our video on DevOps engineer roles and responsibilities. If you're into the tech industry or just curious about the role of DevOps in software development, you have come to the right place. So what exactly is DevOps? In simple terms, it's a set of practices and tools that help developers and operational team work better together, releasing software faster with higher quality. At its core, DevOps is about breaking down barriers between development and operations, and creating a culture of collaboration that focuses on delivering value to customers as quickly and efficiently as possible. Of course, this is a vast oversimplification and there are many different aspects of DevOps that we could spend hours diving into. But for now, let's focus on some of the key responsibilities of a DevOps engineer. Who is the person responsible for implementing and overseeing DevOps practices and processes. But before we begin, if you're new to the channel and haven't subscribed already, consider getting subscribed to Simply Learn to stay updated with all the latest technologies and hit that bell icon to never miss an update from us. So without any further ado, let's get started with today's topic. Firstly, let us understand what is DevOps. Now, DevOps is a software development approach that emphasizes collaboration, automation, and communication between development and operations team. It aims to streamline the entire software development life cycle by integrating and optimizing processes, tools, and methodologies. It encourages a culture of shared responsibility where developers and operations team work together closely throughout the entire software development life cycle from planning and coding to testing, deployment and monitoring. Now the question is who is a DevOps engineer? Well, you got it right. A DevOps engineer is a professional who combines software development expertise with operations knowledge to facilitate collaboration, streamline processes and improve software delivery and infrastructure management within an organization. A DevOps engineer role is to bridge the gap between development and operations team enabling efficient and reliable software development and deployment practices. But the question is how to become a DevOps engineer? What are the skills that you need to possess to become a good DevOps engineer? Well, a DevOps engineer possess a wide range of skills including proficiency in scripting and programming languages. Knowledge of various tools and technologies, expertise in system administration, cloud platforms and containerization technologies as well as strong problem solving and communication skills are necessary. Firstly, having a good coding knowledge. Well, tools like Confluence, Jira, Git, these tools can support and enhance collaboration and project management within a DevOps environment. Next, having a good knowledge on deployment tools are also necessary. Now, tools like DCOS provides orchestralization capabilities for distributed applications. Docker enables containerization for consistent and scalable deployments. And AWS offers a broad range of cloud services for infrastructure provisioning, scalability, and manage services. Next, you need to have a good knowledge on operations tools as well. Now, Chef and Anible focus on infrastructure automation and configuration management while cubernet specializes in container orchestration and management. These tools are utilized in DevOps to automate various aspects of software development life cycles including infrastructure provisioning, configuration, management, application deployment and scaling. Moving ahead, you need to have a strong grip on monitoring tools. Nagios, Splunk and Data Dog are three commonly used tools in the field of monitoring and observability. Now each tool serves a specific purpose in monitoring and managing system and applications. Nagio specializes in infrastructure and application monitoring. Splunk focuses on log analysis and data visualization. Data dog provides comprehensive monitoring and analytic capabilities in cloud environments. These tools play a crucial role in maintaining the health and performance of systems and applications. Moving ahead, you need to have a good knowledge on Genkins and code ship. Now genin and code chips are both essential tools in devop practices. Genkins is a flexible and extensible automation server that supports continuous integration, testing, and deployment. On the other hand, Core Ship is a cloud-based CI/CD platform that offers simplicity and ease of use, particularly for cloudnative applications. Both these tools contribute to improving development productivity and code quality. And finally, having a good knowledge on testing tools like Selenium, JUnit are necessary for a DevOps engineer. JUnit is primarily focused on unit testing and automated testing of Java code while Selenium is geared towards functional testing and automation of web applications. Both these tools play critical roles in DevOps workflow contributing to faster feedback cycles, improved code quality and reliable software releases. So these are some of the main and important skills that you need to possess as a DevOps engineer. Well, now comes the main part. What exactly are the day-to-day roles and responsibilities of a DevOps engineer? Now a DevOps engineer play a crucial role in bridging the gap between development and operations team as we discussed earlier. So here are some of the top five roles and responsibilities of a DevOps engineer in detail. First on the list we have collaboration and communication. Now DeOps engineer facilate effective communication and collaboration with development and operations team. They actively participate in meetings and discussions to align goals and expectations. Now as a DevOps engineer you need to engage in regular meetings and discussions. Regular engagement ensures that they are up to date with ongoing projects, challenges, and goals, enabling them to better align their efforts and contribute effectively. Regular engagement ensures that they are up to date with ongoing projects, challenges, and goals, enabling them to better align their efforts and contribute effectively. Actively listen and understand the requirement, concerns, and feedback. Now, when engaging with development and operations team, DeOps engineers practice active listening. They pay close attention to the requirements, concerns and feedback expressed by team members from both the sides. By understanding their perspectives, pain points and suggestions, DevOps engineers can better assess the needs of their teams and collaborate to find suitable solutions. Facilitate effective communication channels. Now, DeOps engineers take the initiative to establish and maintain effective communication within the organization. This often involves setting up dedicated chat platforms like Slack, Microsoft Teams or collaboration tools like Jira to foster better collaboration and ensure that information flows smoothly between the teams. And finally, encourage cross functional collaboration. Now, DevOps engineers recognize the value of crossunctional collaboration and knowledge sharing among the team members. They actively encourage them from development and operations team to collaborate, exchange ideas and share their expertise. Second on the list we have infrastructure automation and configuration management. Now DevOps engineers focus on automating infrastructure provisioning and managing configurations using certain tools. They define infrastructure as code enabling efficient deployment and scaling of resources. Now as a DevOps engineer you have to identify the infrastructure requirements effectively. Now DevOps engineers work closely with development teams to understand the infrastructure requirements of the application. This involves analyzing the needs of applications in terms of computer resources, storage, security, networking and scalability. By gathering all these requirements, DevOps engineer can ensure that infrastructure is provisioned and configured to meet the application specific need and future growth. Write infrastructure automation scripts and templates. Now once the infrastructure requirements are identified, DevOps engineers use automation tools and techniques to define the desired state of infrastructure components. They write scripts and templates that specify how the infrastructure should be provisioned, configured and managed. Automate the provisioning, configuration and management of servers. Well, DevOps engineers leverage infrastructure as code or in short IA principles to automate the provisioning, configuration and management of servers, networks and other infrastructure resources. They use tools like an symbol, chef or puppet to automate the deployment and configuration of infrastructure components. And finally, regularly update infrastructure code. Now, DevOps engineer uses version control systems like Git to track changes, collaborate with team members, and manage different versions of infrastructure code by regularly updating and versioning infrastructure code. DevOps engineers can easily track and revert changes whenever necessary. Now, third on the list, we have continuous integration and continuous deployment or CI/CD in short. Now DevOps engineers are responsible for establishing and maintaining CI/CD pipelines which enable developers to integrate code changes seamlessly and deploy applications rapidly. So for that they have to set up a version control system. Now version control system like Git play a crucial role in DevOps by providing a centralized repository for managing code and tracking changes. Setting up a version control system involves creating a repository, initializing it with the code, and defining branching and merging strategies. Configure a build server. Now, a build server automates the process of compiling, testing, and packaging application code. Tools like Genkins and GitLab, CI/CD allows you to define build pipelines that specify the steps to be executed. These pipelines typically involve tasks such as pulling code from repository, compiling source code, generating artifacts, and packaging the application. Next, automate the deployment process. Now, automation of the deployment process is crucial for achieving rapid and consistent software releases. Containerization tools like Docker provide a lightweight and portable way to package application and the dependencies. Docker containers can be created and deployed consistently across different environments, ensuring consistency between development, testing, and production. Define and enforce quality gates and monitor CI/CD KPIs. Quality gates ensure that the code meets predefined quality standards before it is promoted to the next stage of the CI/CD pipeline. Automated testing including unit test, integrated test, and end toend test. Integration test and end to-end test help catch bugs and validate the functionality of the managing applications. And finally, measuring KPIs of the CI/CD pipeline provide insights into its performance and help identify areas for improvement. Well, next we have monitoring and performance optimization. Now, DevOps engineers monitor system performance, identify and optimize the infrastructure and application stacks whenever necessary. They implement monitoring tools to collect and analyze metrics, logs and traces. So for that select and configure monitoring tools. Now monitoring tools like Prometheus or Graphina can be used to collect and visualize these metrics allowing teams to identify bottlenecks or optimize processes and enhance the overall efficiency of the CI/CD pipeline. Also they have to collaborate with development and operations team to fine-tune application performance. So continuously optimizing the infrastructure which will ensure high availability, scalability and reliability of that application. And finally we have security and compliance. Now do engineers play a critical role in in implementing security measures and ensuring compliance with industry standards and regulations. They work closely with security teams to define and implement security controls throughout the software delivery pipeline. So they have to continuously collaborate with the security teams to identify and define security requirements and controls and implement security measures such as vulnerability scanning, access management and secure configuration. They have to continuously integrate security testing and code analysis into the CI/CD pipeline and monitor for any sort of potential security risks or breaches and respond promptly to mitigate any identified vulnerabilities. So these were some of the main or top five roles and responsibilities of a DevOps engineer. I hope you understood that DevOps engineers are one of the highest paid professionals in the tech industry today. And if you are watching this video, most likely you are someone who wants to get into DevOps or want to learn DevOps. But with so many different tools and technologies like Terraform, Ansible, Linux, AWS, genkins, Docker, Kubernetes and so much more, learning DevOps can be very timeconuming and confusing. And that is why in this video I'm going to share with you a complete DevOps road map that you can follow to learn DevOps from scratch and also an excellent resource you can use to learn all these DevOps tools at one place. So watch this video till the end. Before we start with the video and look into the DevOps road map, let me introduce myself. My name is Nasula Chri also goes by Cloud Champ on YouTube and I work as a freelance DevOps engineer for multiple companies. The road map shared in this video is the exact road map I followed to learn DevOps from scratch and I'm pretty sure if you watch this video till the end, you will have a clear idea on what things to learn and what not to learn and get jobs faster. A DevOps engineer is responsible for deploying application and automating the manual process. But how can you automate a manual process if you don't know how is an application created? So first thing you need to know is to understand the concepts of software development. What is a build? What is software deployment? So generally try to understand the whole software development life cycle from idea to code and to releasing the application to end users. After you understand the software developer life cycle and now you have an idea of how is an application created. Second thing you need to know is Linux. Linux is very very very important. A DeOps engineer should have a good hands-on knowledge with Linux. Need to know all the important commands because every DevOps tools you look at let's say an Terapform, Kubernetes, Docker, all of them work on commands and you can only manage to work with them when you have good hands-on knowledge with Linux. So learn Linux. In the next you can learn things like shell commands, direct file systems and permissions, SSH key management, virtualization, some part of networking like load balancers, how to set up firewalls, how IP addresses work and much more. Linux is very important. So it's also called as operating system of the cloud. So spend time learning Linux. Now most of you might be confused and you might ask I want to learn all these tools but where should I find the resources? You can learn this from YouTube, some of these from blogs, some from documentation, but they are all scattered which will waste your time. So rather than that, I would suggest you checking out an excellent DevOps program by simply learn. This post-graduate DevOps program by simply learn is in collaboration with IBM which will teach you all the important DevOps tools that you require in order to become a DevOps engineer like Terapform, Maven, Anible, Genkins, Docker, Kubernetes, Git and lot more along with industry projects that will provide you hands-on experience and can help you become DevOps engineer faster and also a certification by Caltech which will validate your learning in DevOps. So you can check out the learning path here and the reviews by previous learner. Wow, all of them are five-star reviews. So click on the link in the description and click on apply now. For this program, you don't require any prior work experience. You require a bachelor degree with an average of 50% or higher marks. You can be from programming or non-programming background which makes this program for everyone. So click on the link in the description. Click on apply now. Fill in all your details and proceed to start learning DevOps with simply learn. Next important thing after learning Lux is going to be Git because every company is going to store their code online on Git repositories like GitHub, GitLab or Bitbucket. So our DevOps engineers need to know how to work with Git to clone and push the code from local machine to Git repositories or from Git repositories to local machine. also understand what is branching, how does branching works, what is merge request, what is pull request and a lot more. So deops engineer should have a good understanding of git and also know all the most used git commands. Once you have cleared your basics, now is the time to learn cloud because devops engineers need to know how to create servers, databases, storage, virtual APCs and lot more on the cloud. You can choose any cloud like AWS, Azure, GCP, IBM, Oracle or anything. But DevOps infrastructure to deploy their applications and software on the cloud. Once you have learned how to create infrastructure and deploy applications on the cloud manually, you need to automate this because DeOps is all about automation. So you can automate this using infrastructure as code tools like Terraform, Anible, Chef, Puppet and a lot more. But I would suggest you learning only these two tools which are Terapform and Anible that are highly used in the industry today. Learning Anible and Terapform can provide you with so many job opportunities. So start with learning Terapform and Anible after you have mastered creating an application on the cloud manually. Due to rise in demand and application stability, companies are shifting from servers to containers. Which is why you need to learn Docker and Kubernetes. For Docker, you need to understand the concepts of virtualization and concept of containerization. Also you need to know how to containerize our application and run it on a server or a kubernetes cluster. You need to know the commands on how to create docker file, how to create docker image, how to run containers, networking in docker and some of the parts for kubernetes. You need to understand the Kubernetes architecture, what is deployment, what is replica set, what is pod, what is node and how to properly manage your containerized application using kubernetes cluster either on EKS, AKS or GKE which is going Kubernetes engine. So it is very important for you to understand and know the commands to properly work through containization which is a leading and a popular tool right now in the market. Next very important thing for a DevOps engineer to learn is going to be CICD or continuous integration and continuous deployment because every company wants to deploy their application automatically. In DevOps, all code changes like new features or bug fixes should be integrated in the existing application and provided to the end user in an automated fashion and you can only do this by using CI/CD. So adoption engineer should know how to set up CI/CD server. How to integrate code repositories to trigger pipeline automatically when there is a change and to fix bug faster and to provide better quality software to the end user very fast in automated fashion. Some popular CI/CD tool includes Genkins, GitLab, CircleCI, Travis CI. So learning CI/CD will help you land your job very very fast and it's very important also known as heart of DevOps. So you should master CI/CD. All the tools that we have mentioned till now will help you deploy your application on the cloud or on containers anywhere. But once the software or your application is in production, it is very important for you to monitor it to track performance to see if there are any issues, check system resources like CPU or RAM or anything. So one of the responsibilities of DOPS engineer is to set up software monitoring, infrastructure monitoring, collect logs and to visualize data to check if there are any issues or if system has necessary resources or not. So you need to learn tools like Prometheus, graphana also logging tools like cloudatch or elk stack which is very important to make sure that your application is running without any issues and without any problems. Congratulations. Now you know all the tools and technologies you require to become a DevOps engineer. But DevOps is all about automation and there is always going to be something that you can automate. So to automate this you will require scripting language. And some of you might argue that scripting is not required or you don't need any programming language in DevOps. Coding is not a thing in DevOps. But that's not actually true. you will require knowledge of one programming language or a scripting language because you need to automate the manual process. So some popular scripting language can be bash, powershell which are all OS related. So you can use bash in Linux in PowerShell and Windows and nonOS related are Python, Go, Ruby uh which is what I would suggest. I would suggest you trying to learn Python which will help you automate all the manual process like uh rotating passwords of your databases like starting a deployment starting a build or or clearing c anything that you are doing manually can be automated through scripting languages using this Python or go or bash my suggestion would be to start with Python and if you love Python you will be unstoppable and you will have more value as a DevOps engineer and you don't need to learn any programming language at a software engineer level you just need to know enough Python or enough go just to write scripts which can automate your things. You don't need to go deep in uh DSA and all those things which are very common questions that I get. So just focus on learning Python in a way where you can automate things by writing scripts. So just the basics not too advanced only to automate stuff. So there you have it a complete DevOps road map to learn things from scratch. Along with this, make sure you have your LinkedIn perfect, you attend meetups and also enroll to the simply learn DevOps program. Thank you and have a good day. Today we are diving deep into DevOps, one of the most exciting and rapidly growing fields in tech. But what exactly is DevOps and why is everyone talking about it? DevOps at its core is a blend of development and operations. It's a culture, a mindset, and a set of practices that bridge the gap between software developers and IT operations team. And the goal to deliver software faster, more efficiently, and with higher reliability. So, in today's fast-paced digital world, businesses are racing to release new features, improve user experiences, and stay ahead of their competition. And DevOps is the secret source enabling them to do just that. So by automating processes, improving collaboration, and integrating cuttingedge tools, DevOps has become the backbone of modern software delivery. And here's the exciting part. As we approach 2025, the demand for skilled DevOps engineers is skyrocketing. It's one of the hottest career opportunities in tech right now, offering not just great salaries, but also the chance to work on innovative projects that shape the future. So in this video, I will guide you through the ultimate DevOps engineer road map for 2025. So whether you are a beginner or looking to level up, stick around. This road map could be your gateway to rewarding career. But before we begin, make sure to check out the quiz linked in the description below. Take a few minutes to answer it and don't forget to share your thoughts in the comments. And we have more tricky and interesting quizzes lined up for you. So let's get started. So the first month is about choosing a programming language. So when you're diving into the world of DevOps, picking up a programming language is a gamecher. It helps you automate tasks, integrate systems, and troubleshoot those tricky issues that pop up. So now the language you pick up can depend on the project you're working on. But the key skills you learn are going to be applied everywhere. So for beginners, I highly recommend starting with languages like Python or Go. Why? Because both are super easy to learn, have clean syntax, and are widely used across the IT industry. So now let's break down what all you have to learn under each of these languages. So in Python you'll start with introduction to Python. So you'll start with the basics like understanding how Python works, its syntax and how to write clean readable code. Then comes data types and variables. So here you will learn the fundamental building blocks like strings, integers and lists. Then comes conditionals and loops. So get comfortable with if else statements and loops. So these control the flow of your code. Then comes functions and modules. So organize your code into reusable functions and modules for clean maintainable projects. Now next on the list is oops or object oriented programming. So here you'll dive into classes and objects. This is key for structuring your code effectively. And finally you can go through some advanced concepts to explore things like exception handling, file input, output, rejects, collections and more to level up your Python game. Now in Golang again you can start with introduction to Golang like Python. Go syntax is simple but it's powerful for handling large scale systems. After the introduction you can move on to variables and constants. So here you can learn how to declare variables and constants essential for clean code. Then comes arrays and slices. Now these are go's way of handling collections of data. After this comes concurrency and go routines. So go's real strength lies in handling multiple tasks at once. So you can get comfortable with Go routines for parallel processing. And finally, you can learn interfaces and methods. So Go is all about simplicity, but interfaces and methods let you write more flexible and reusable code. Now once you have completed this modules, you'll be going to the second month where you'll be dealing with operating systems. So basically operating systems are like the backbone of any computing environment. So they connect the hardware with the software. So as a DevOps engineer, you need a solid understanding of operating system to effectively manage applications, optimize infrastructure and streamline deployment pipelines. So let's go through some of the key operating system concepts you'll need to know. First one is OS basics. So this is the foundation understanding what an operating system does and how it works. Then comes processes and threads. So you can get familiar with the process life cycle and how threads are managed within processes. Then next comes CPU scheduling. So learn how tasks are assigned to CPU resources and how time is allocated for different processes. Process synchronization. This ensures that processes don't clash with each other while running. Now next comes deadlock. So sometimes processes get stuck in a loop. So understanding how to identify and resolve these situations is crucial. And then there is memory management. So how does the operating system manage memory? So learning memory allocation strategies will make your systems run smoother. And finally, you'll learn about disk management and scheduling. So this is all about efficiently handling disk usage and optimizing readr operations which are key to keeping things running faster. And also in the second month you'll be dealing with virtualization. So DevOp engineers should also be familiar with different types of virtualization to manage resources efficiently. So some of the virtualizations that you can get familiar with are application virtualization, network virtualization, desktop virtualization, storage virtualization, server virtualization and data virtualization. Now let's move on to the third month. So if you want to be a top tire DevOps engineer, mastering the command line interface or CLI is a must. So it gives you advanced control over systems and access to powerful features that go beyond the limitations of a graphical user interface or GU. So being proficient in the CLI means you can manage, you can troubleshoot and configure systems more efficiently. So whether you're working locally or remotely, this is especially crucial when it comes to infrastructure management and automating tasks across different environments and operating systems. So let's look at some key CLI skills to master. So number one is scripting. This is for automating repetitive tasks and creating custom scripts to make your work more efficient. Then next you can learn about editors. So learn CLI based editors like Vim or Nano for editing files directly from the terminal. Then you can learn about networking tools. So get comfortable with tools like Bing, netstat and curl to troubleshoot network issues and manage network configurations. Next is process monitoring. So here you have to learn how to use tools like PS top or edgetop to monitor processes and system performance in real time. After process monitoring comes performance monitoring where tools like SAR and IOTA help you keep track of system performance and resource usage. And finally comes text manipulation. So you can master text processing tools like AWK sed and grip to handle and analyze large data sets directly from the terminal. So by becoming proficient in the CLI, you'll be able to solve problems faster, gain deeper insights into system behavior, and effectively manage infrastructure with confidence. Now moving on to the fourth month. If you're diving into DevOps, version control and hosting are non-negotiable. So they play a crucial role in collaboration, code management, and version tracking, especially if you're looking to implement GitOps or streamline your DevOps life cycle. So when it comes to version control, Git is the go-to tool. It is the most widely used distributed version control system. So, Git lets you create repositories to store your code, work with branches to make and test changes without affecting the main code base, make commits to save your progress and merge changes with others works and track every change made which makes collaboration easy. And next comes hosting platforms. So once your code is neatly tracked with git, it's time to host it. So hosting platforms let you make your code public or share it with your organization. So popular options are number one, GitHub. So this is the most popular platform for opensource projects with tons of collaboration features. And then you have Bitbucket. So this is a great choice especially for teams already using atlation tools like Jira. And finally there is GitLab. It is a featurerich platform with integrated CI/CD pipelines for better DevOps workflow. So with Git and these hosting platforms you'll have all the tools needed to manage your code base, collaborate smoothly with your team and keep track of every change. So now let's move on to the fifth month. So in the fifth month you are supposed to learn about cloud providers. So in a DevOps journey understanding cloud computing is a game changer. So ultimately all the applications you work on will be hosted somewhere right and that somewhere could be either on a cloud or onremise. So there are a few big players in the cloud space that you'll want to get familiar with. Number one is of course AWS Amazon Web Services. So AWS is one of the most popular cloud platforms offering a ton of services. So whether it's EC2 for virtual machines, S3 for storage or Lambda for serverless computing, AWS has a service for almost every need. And next you have Azure. So Azure is Microsoft's cloud platform and offers a wide range of services similar to AWS. However, the standout for DevOps professionals is Azure DevOps. It's a suite of integrated tools that covers everything from CI/CD pipelines to version control and project management. And then comes GCP or Google Cloud Platform. So Google Cloud offers many of the same services as AWS and Azure but with a unique touch. So whether you're working with Kubernetes or looking for storage options, GCP brings Google's power and reliability to the table. So now that we have completed the plan till the fifth month, you can take a moment to answer the next quiz in the description box. So I hope you have answered the quiz. So in the sixth month, you'll be dealing with containerization with Docker. So if you're serious about DevOps, Docker is a tool you can't afford to skip. So before Docker came, deploying applications involved packaging the app, downloading all necessary dependencies into the server and manually configuring everything. So the scaling was a nightmare. But with Docker, packaging and deploying the app is a breeze and it makes scaling super easy too. So here's what you have to concentrate while learning Docker. Number one is running containers. So learn how to run containers, essentially lightweight standalone applications on any system. Next, inspect active containers. So get comfortable with checking which containers are running, their status and any issues that might pop up. And then you have docker networking. So understand how containers communicate with each other and the outside world which is key to a well architected system. Then you'll move on to persist data with docker volumes. So by default containers are ephemeral meaning the data disappears when they stop. So learn how to use volumes to persist data beyond the life of a container. Next, you can learn about dockerizing apps with Docker files. So, master writing Docker files, simple text files that define how to build a Docker image for your app. Next, run multiple containers with Docker Compose. So, learn how to manage multicontainer apps using Docker Compose, which simplifies complex setups. And finally, there is Docker repositories. So, learn how to work with Docker Hub or private repositories to store and share Docker images with others. So with Docker deploying apps becomes faster, easier and more scalable making it an essential tool for any DevOps engineer. Also in the sixth month you'll be dealing with container orchestration. So we have covered containers right and how they make scaling a breeze. But what if you need to manage lots of containers at once. So that's where container orchestration tools come in. So these tools let you automate the management of containers like creating multiple replicas and scaling them as needed. So the two main players in this space are Kubernetes and Docker Swam. So in the seventh month, you'll be moving on to networking and security protocols. So networking and security are the backbone of any DevOps process, especially since most of your work will be on servers and in production environments. So understanding networking concepts helps you manage and troubleshoot infrastructure, deploy microservices, handle containerized application, automate network tasks. So here are some of the key concepts you have to learn in network and security. The first one is FTP, SFTP. So these are protocols for transferring files securely over the network. Then there is HTTP and HTTPS. So the foundation for web communication and you should know the difference and when to use each of these. Then comes SSLTS. So these are the encryption protocols that secure the web traffic keeping data safe. Then next you have DNS. So the system that helps convert domain names into IP addresses. Basically the address book of the internet. Then you'll be dealing with SSH which is a secure protocol used for remote server management and communication. Then you will move on to other protocols such as TCP IP and UDP which are also crucial. So with this knowledge you'll have the tools to keep your network secure and your infrastructure running smoothly. Now in the eighth month you must concentrate in understanding serverless computing. So this is a cloud computing model where you don't have to worry about managing or provisioning servers. So instead cloud providers dynamically allocate resources as needed allowing you to focus purely on writing and deploying your code. So as a DevOps engineer here are the key tools and platforms you should dive into. First one is Cloudflare. So Cloudflare offers a suite of services including CDN and security but also enables serverless computing for edge functions speeding up your applications globally. Next is AWS Lambda. So AWS Lambda is Amazon serverless platform allowing you to run code without provisioning or managing servers. So you can get it to trigger in response to events making it highly scalable and efficient. And then comes some Azure functions. So Azure functions from Microsoft offers similar serverless capabilities enabling you to run small pieces of code in the cloud. And finally there is Versel. So Versel is a cloud platform that focuses on serverless deployment for modern web apps particularly for front-end applications. So by mastering these serverless computing you'll be able to streamline your app development process, reduce costs and let cloud providers handle the heavy lifting for you. Also in the eighth month you'll be dealing with infrastructure provisioning. So as a DevOps engineer you'll need to manage and set up infrastructure. But using traditional methods like click ops can be timeconuming and hard to scale. So luckily things have gotten a lot easier. So infrastructure provisioning is all about automating the setup of your infrastructure. So some of the key tools in this area are terraform, pulley and AWS CDK. And then you have got configuration management. So basically configuration management is all about keeping track of and controlling the configuration of your infrastructure software and systems. So imagine in any organization you will often need to manage multiple servers and imagine doing this manually for hundreds or even thousands of servers. It's not only time consuming but also prone to errors, right? So that's where configuration management tools comes in. So here are some essential tools to master in configuration management. Number one is Ansible. Uh so Ansible is a simple and powerful automation that lets you configure servers, deploy apps and manage tasks. So next is Chef. This is another automation tool. So it's great for larger environments where scalability and flexibility is needed. And then you have Puppet. So Puppet allows you to manage infrastructure with the declarative language. So it's widely used for managing large scale infrastructure and automating repetitive tasks across systems. Now moving on to the ninth month, you'll be dealing with infrastructure monitoring. Uh so infrastructure monitoring is all about keeping an eye on the health and performance of your infrastructure and tracking its availability, checking for issues and predicting future problems before they occur. So you collect data from system logs, metrics and other streams and use that data to spot any potential issues. So here are some top tools you should learn for infrastructure monitoring. So first one is Graphfana. So, Graphan is a powerful open-source tool that lets you visualize metrics and logs from multiple sources. Then you have data dog. So, again, data dog is a cloud-based platform that offers comprehensive monitoring of infrastructure performance and logs. And then you have Prometheus. So, Promeththeus is an open source monitoring tool designed for reliability and scalability. So, it's perfect for tracking time series data and it can easily integrate with Graphana to give rich visualizations. Now, finally, we have to learn about application monitoring. So application monitoring is crucial especially when deploying updates or bug fixes. So a new change could unexpectedly take the app down. But with continuous monitoring you can track, measure and analyze the app's performance in real time to prevent issues from escalating. So here are some key tools for application monitoring. So number one is data dog itself. So just like your infrastructure monitoring, data dog is a great tool for application monitoring also providing deep insights into your app's performance logs and other metrics. So it's perfect for real-time visibility. And then you have New Relic, you have Yagger, and then there is open telemetry and app dynamics. Now in your final month of DevOps learning, focus on hands-on projects that put your knowledge into practice. Work on building pipelines, managing infrastructure, and monitoring systems. So this is the time to apply what you have learned and showcase your skills to real world experience. So the main question is what fuels this DevOps revolution? Now it's a powerful collection of tools specifically designed to support and amplify its principles. So these tools acts as a catalyst empowering teams to automate task manage infrastructure efficiently and monitor application performs effectively. So without any further delay let us directly jump into the top nine noteworthy tools highlighting their features, benefits and significance that have become synonymous with the DevOps ecosystem in no particular order. So first on the list we have Jenkins. Now, Jenkins is an open-source automation server known for its extensive plug-in ecosystem, making it highly versatile and customizable. It facilitates continuous integration and continuous delivery or in short CI/CD pipelines, automating the build, test and deployment processes. Jenkins enables team to integrate code frequently, ensuring early detection of issues and faster software releases. So, let us now look at some of the key features of the Genkins. Firstly, easy installation and configuration. Genkins has a user-friendly web interface that simplifies installation, configuration, and management of build jobs and pipelines. Distributed builds for scalability. Now, it supports for a vast ecosystem of plugins for seamless integration. And it can distribute build tasks across multiple nodes, which helps in parallelizing builds and reducing overall build time, especially in large projects. And finally, extensible through scripting languages like Groovy. Now Jenkins provides extensibility through scripting languages like Groovy which is a powerful and versatile language that runs on a Java virtual machines or in short JVM. So by leveraging Groovy scripting capabilities, Genkins becomes highly adaptable and customizable to meet the specific requirements of different development teams and projects. So those are some of the key features of Genkins. Let us now move ahead and discuss some of the benefits or advantages of using Genkins. So firstly we have enables faster feedback and quicker time to market. Now, Genkins continuous integration capabilities enable developers to merge their code changes into a shared repository regularly. By doing so, Genkins automatically triggers built and testing processes to validate any kind of changes. This automates feedback loop allows developers to receive quick feedback on the quality of their code. So, as a result, issues and bugs can be identified early in the development cycle, preventing the accumulation of defects and reducing the time required to fix them. As discussed earlier, it also facilitates early issue detection and reduce bug turnaround time. Now with Genkins running automated builds and test every time new code is committed, potential issues and bugs are caught early in the development process. So by detecting issues at an early stage, developers can address them promptly before they propagate further into the code base. And finally, automates repetitive task save time and effort. Now, Jenkins automates various tasks involved in the software development life cycle. This includes tasks such as building the code, running tests, and deploying applications. By automating these repetitive and time-conuming task, Genkins saves developers and operations team significant amount of time and efforts. So that is what Genkins is all about. It's a widely adopted in the DevOps landscape due to its flexibility and extensive plug-in support and learning it will add a great value to your array of skills. So its ability to automate CI/CD processes and integrate with various tools makes it a crucial component of modern software development and delivery pipelines. Second on the list, we have Docker. Docker has revolutionized application deployment with its containerization approach. It allows developers to package applications and their dependencies into lightweight isolated containers. Docker contains provides consistency across different environments ensuring that applications run consistently regardless of the underlying infrastructure. This portability along with the rapid startup times and efficient resource utilization has made Docker a foundational tool in DeOs practices. So let us now some discuss some of the key features of Docker. First one is packaging applications and dependencies into containers. Now Dockers allows developer to package their applications and all their dependencies into a self-contained units called containers and the process is known as containerization. Now these containers encapsulate the application code, its runtime, various libraries and system tools required to run the application. By doing so, Docker ensures consistency across different environments. Secondly, efficient resource utilization through containerization. Now, this lightweight nature of containers allows for more efficient resource utilization. Multiple containers can run on a single physical machine without the need for individual OS instances. It means that you can host more applications and services on the same hardware, reducing the number of servers needed. And finally, easy scaling and management of containers. Now, containerization simplifies application scaling and management. So when you need to handle increased application load, you can quickly scale by running more instances on the containerized application on additional servers or within a container orchestration platform like Kubernetes. So let us now talk about some of the benefits of the docker tool. Now firstly rapid deployment and scalability. Docker enables rapid deployment of applications due to its lightweight and containerized approach. When using Dockers, developers package their applications and dependencies into containers which encapsulate everything needed to run the application. So these containers are portable and can be easily moved from one environment to the other. And next we have the isolation of applications and dependencies for improved security. Docker utilizes cauterization to isolate applications and the dependencies from the ecosystem and other containers. Each containers operate in its own user space separate from other containers providing a strong level of isolation. This isolation prevents applications from affecting each other and helps contain potential security breaches within the confines of the container. And finally, simplify development to production workflow. Now, Docker streamlines the relevant to production workflow by providing consistency between different environments. With Docker, developers can create containers that run the same way in development, testing, and production environments, thereby reducing the chances of unexpected issues arising during the deployment. So Docker has become a cornerstone of modern day of practices. It's updated to streamline application deployment and improved resource utilization, has transformed software development and operations enabling faster and more reliable application delivery. So that was all about Docker. So let us now move ahead and discuss the next tool which is Cubernetes. So next on the list we have Cubernetes. Kubernetes is an open-source container orchestration platform that automates the deployment, scaling, and management of containerized applications. It provides a robust infrastructure for running and coordinating containers across clusters of machine making it easier to manage large scale deployments. DevOps teams can easily deploy, update and scale applications, facilitating faster and more reliable software delivery while promoting collaboration and consistency across development and operations life cycle through cubernetes. So let us look at some of the key features of it. Automatic container deployment and scaling. Now container orchestration platforms like Kubernetes provide automatic container deployment and scaling capabilities. When deploying applications on cubernetes, you can define the desired state of your application using YL files on declarative configuration. Kubernetes then take carees of this ensuring that specified number of container replicas is running at all times. Service discovery and load balancing. Now, Cubanet enables faster feedback and quicker time to market. In a containerized environment, multiple instances of an application may be running across different containers, making it challenging for clients or other services to know the IP addresses of all the running instances and detecting and keeping tracking of the locations of various services within the container cluster. And cubernetes, for example, provides a built-in service discovery mechanism. Next, we have self-healing and auto reset of containers. Now container orchestration platform provides self-healing capabilities to ensure that applications are always available and responsive. If a container fails due to an application crash or any other issues, the orchestration platform detects the failure and automatically restarts the failed container. So let us now move ahead and discuss some of the benefits of using Kubernetes tool. Firstly, it is scalable and highly available application and it provides a seeming repeat and provides a seamless scaling of resources based on demand. Next, it has a simplified management of containerization applications across various clusters and finally automated deployment and updates reducing manual intervention which further improves resource utilization and optimization. Overall, Kubernetes has emerged as the industry standard for container orchestration. Its ability to automate application deployment, scaling and management simplifies the complexities of running containerized applications at scale making it a crucial tool for DevOps practitioners. Moving ahead, let us discuss our next tool which is Ansible. Ansible is a powerful automation tool that simplifies configuration management, application deployment and orchestration. It employs a declarative language to define desire state configuration making it easy to manage and automate infrastructure task. Ansible follows an agentless architecture allowing it to work efficiently across a wide range of systems and environments. So let us now look look at it some of its features. Firstly, it's a declarative language for defining infrastructure configuration and it is also an agentless architecture for easy deployment and management as we discussed earlier. Now, this is done through a playbook-driven automation for orchestration where extensive library of modules for a wide range of task are employed. So, let's now discuss some of its benefits. So firstly it's simplified infrastructure management through automation which increases the operational efficiency with reduced manual task and its ident nature ensures that it has consistently and predictability overall and finally it supports a wide range of infrastructure automation use cases and with its agentless architecture it allows easy integration with various systems and environments. So in a nutshell, Ansible simplicity, flexibility and ease of use have made it a popular choice for automating infrastructure and application deployment task. Dev approach and agentless architecture contribute to efficient and streamlined development workforce. So moving ahead, the next tool on our list is git is a distributed version control system that has become a fundamental tool for modern software development practices. It allows developers to track changes, collaborate effectively and manage codebase efficiently. Git's decentralized architecture ensures that developers can work offline and merge changes seamlessly across branches. Let us now discuss it some of its key features. Now its distributed version control system has efficient collaboration with various uh tools within the management of the ecosystem of DevOps and it also has an integration with various code hosting platforms which is the branching and merging capabilities for concurrent development and finally it support for code reviews and collaboration workflows which also gives a commit based tracking of changes. So these are some of the key features of git. So let us now discuss some of the advantages or like benefits of using git. So firstly its easy tracking and management of code changes which ensures efficient collaboration and concurrent development within the resource files and its ability to work offline and merge changes seamlessly will benefit a lot of DevOps engineers. And finally, its easy integration with other DevOps tools makes it a wonderful to use to manage code versions, track changes, and enable efficient collaboration, which has revolutionizes software development. So, it has become a essential tool for version control, facilitating effective collaboration, and enabling streamlined DevOps workflows. So, moving ahead, the next tool on our list is Terraform. Now, Terraform is an infrastructure as code or in short IA tool that allows teams to define and provision infrastructure resources in a declarative manner. It supports multiple cloud providers and enables consistent and reproducible infrastructure deployment. Terraform's declarative syntax and state management capabilities, simplify infrastructure provisioning and configuration. Let us now look at some of its key features. Firstly, it provides multi cloud support for provisioning resources across different providers. Its infrastructure as code approach for consistent and reproducible deployments makes it a declarative syntax for defining infrastructure configurations. And finally, automated resource provisioning and dependency management. So some of its benefits or the advantages of using Terraform is its simplified resource provisioning and dependency management. Now, Terraform's infrastructure as code approach supports for multiple cloud providers makes it an essential tool for managing infrastructure codes and collaboration and version control for infrastructure configurations as well. And finally, it state management for tracking infrastructure changes which makes it a beneficial tool for DevOps engineers. Now, Nigos is used to monitor and manage the health and performance of the infrastructure application and network resources. It's a comprehensive monitoring solution to identify and resolve issues proactively ensuring high availability and reliability of systems. So let us look some of its key features. Firstly, its monitoring capabilities. Secondly, it's centralized configure management and finally its event handling and escalation tool. So learning Nagios is also crucial and beneficial if you are just starting on DevOps journey. So moving ahead, let us now discuss our next tool on our list which is ELK stack. Now, Elkstack offers a comprehensive solution for centralizing logs from various applications and systems, making it easier for deops teams to monitor, troubleshoot and gain valuable insights from their log data. The ELK stack comprising elastic search, log statch and kibbana provides a comprehensive log management and analysis platform. It acts as a distribution search and analytics engine while log stack collects, processes and transform logs. And finally, Kibano offers a user-friendly interface for visualizing and exploring data. So, some of its key features including real-time monitoring and alerting, scalable and efficient log storage and retrieval, and distributed search and analytics to data visualization and exploration with Cabana. Let us look at some of its benefits. So firstly, it's realtime monitoring for proactive dete. Realtime log monitoring for proactive issue detection with the help of centralized log management and analysis. Advanced log analytics for troubleshooting and performance optimization making it a scalable architecture for handling large scale volumes of data. And finally, efficient log storage and retrieval for compliance and auditing purposes. In a nutshell, ELK stack has gained immense popularity for its ability to handle log management and analysis at scale. It empowers DevOps teams with real-time insights into application and infrastructure logs. facilitating effective optimization. Well, finally on the list we have Jira software. Jira is a widely used project management tool that supports agile development methodologies. It offers robust features for planning, tracking and managing task issues and workflows. Jira's customizable boards, backlogs, and workflows empire teams to collaborate effectively, visualize and progress to gain transparency into project statuses. With integration to various DevOps tools, Jira facilitates seamless tracking of development activities, enabling continuous improvement and efficient project management. Some of its key features are customizable boards, workflows for project management, agile planning and estimation features, issue tracking and management capabilities. And some of its benefits include efficient task management and tracking, enhanced collaboration and visibility across various teams and integration with various DevOps tools for streamlined workflows. It also helps in reporting and analytics for project insights and performance measurement. Finally, Jira has become a go-to tool for agile project management in the DevOps ecosystem. Its ability to support agile methodologies, track task and integrate with other DevOps tools makes it a valuable assets for teams seeking efficient project management and continuous improvement. So learning it will add a great value to your area of skills again. So these were some of the top nine DevOps rules that you must know which will help you enhance and accelerate your career in DevOps. So today we will be talking about one of the booming technologies used which is DevOps. We will first look into what is DevOps. Then we are going to dive deep and understand the top 10 reasons why you should learn DevOps. So what is DevOps? DevOps is a collaboration between the development and operation teams which enables continuous delivery of applications and services to our end users. Before DevOps, there was a lot of communication gap between the development and operation teams. The code that used to work fine on the development side would create a lot of errors on the operation side. This in fact led to a lot of issues. The biggest issue was the delay in project delivery. The solution to this was DevOps. In DevOps, the operation and development engineers participate together in the entire life cycle from the design through the development process to the delivery of the software to the end users. It enhances the process to deliver the software faster and a software of high quality. If there is any bug or error, it is fixed at the right time rather than dragging it to the last phase. Let's now look into the 10 reasons why you should learn DevOps. So at number 10 we have technical, cultural and business benefits of DevOps. Let me explain each benefit one by one. So first we have the technical benefits. Continuous software delivery is the most important process of delivering the software in smaller increments to ensure that the software can be released at any time. With this approach of DevOps, the team will always be ready on delivering any time. It has the benefit of having less complex problems to fix. The code is tested at every stage and both the development and operation teams make sure that the complexity is reduced to a great extent. DevOps also has the benefit of faster and easier resolution to every problem. If any bug or error is found at an earlier stage, it is fixed and then moved on to the next stage. Hence, this way at the final stage, there will be zero or minimum number of bugs. Moving forward, let's look into the cultural benefits of DevOps. The workload is divided equally between all the employees. So no individual is under the pressure to code, test, debug an entire software. This results in a team that is happy and more productive. Since DevOps is a collaboration between the development and operation teams, if any issue arises on one side, the team is always ready to help and the employees are engaged to make sure that the software is as the end user requires and hence is delivered at the set date. DevOps helps in increasing the professional development opportunities. Finally, let's look into the business benefits of DevOps. The basic principles of DevOps that is automation, continuous delivery and quick feedback cycle aim to make the software development process faster and more efficient. Being an extended version of agile methodology, DevOps ensures that the complete software development life cycle goes smoothly. By promoting collaboration between the teams, DevOps offers continuous feedback so that the errors are fixed in time and the releases are done faster. These days the development teams need to break down the interdep departmental constraints and collaborate as well as communicate in a dynamic roundthe-clock environment. DevOps gives a way to improve the business agility by providing an environment of mutual collaboration, communication and integration across the various teams in an IT organization. All the team members are responsible for meeting the quality and timeline of the software deliverables. With DevOps, organizations can improve the deployment frequency, recovery rates, and hence result in a lower failure rate. With every new release, it is possible to ensure the reliability and stability of an application. When applications perform flawlessly in the market, organizations reap the benefits of greater customer satisfaction. At the ninth position, we have work with good developers. Per code is all too common. Sadly, users arrive at the realization when it's too late. The fact is some developers are good at what they do while others have poor coding skills. A team of software developers consists of excellent, good, average and poor developers. It is important that the bad codes generated by many developers need to be stopped else it may increase the production time. DevOps helps in reducing the bad code limits as the bad code cannot go to the next phase until it is fixed. Also a team member who is terrible at coding could be good at any other different roles and vice versa. Retasking team members earlier in the process prevent wastage of time and resources. So in this way DevOps eliminates bad developers and ensures that the team comprises of good developers. Next at eighth position we have increased efficiency. Due to increment in efficiency level it results in speeding up the process of development and also makes it error-free. DevOps can also increase efficiency through automation. There are many ways to automate tasks in DevOps. DevOps allows engineers to focus on those tasks which are not automated. There are certain tools of acceleration that increase the efficiency. They are the cloud-based platforms or other scalable infrastructure which help in increasing the access of the team to the hardware resources and hence speeds up the process of testing and deployment operations. With the use of build acceleration tools, the code compiles faster. There may be a process that helps in embedding parallel workflows into the continuous delivery chain so that the delays are avoided. Moving on, at seventh position, we have a better organizational culture. With the help of DevOps, there has been an improvement in software development. The development and operation teams are more focused on performing together rather than having separate goals. The team is more focused on production. If both the teams are combined, it will result in innovative ideas in a very efficient and effective manner. There is improved collaboration and communication between the team members. DevOps facilitates better understanding among the team members and this understanding increases worker morale. Next, at the sixth position, there is faster release of software. It is true that DevOps makes the process of software development agile. Hence, it leads to the timely release of the software. Companies can quickly study the behavior of users and incorporate the changes to come up with a better product. This in turn helps the organization to stay competitive. There is a reduction in roll backs and failure rates regarding deployment and the time that is taken to recover with better products. DevOps reduces the time for cycles of development and also ensures a faster rate of innovation. At position five, we have better knowledge of software delivery life cycle. Once you get to know about DevOps, you will get a lot of information about the software delivery life cycle. It is divided into main phases like planning, analysis, design, implementation, testing and integration and maintenance. In the plan phase, initially there should be a plan for the type of application that needs to be developed. Getting a rough picture of a development process is always a good idea. In analysis, a detailed study of requirements is done to check whether all the requirements are available or not. The list of all the requirements like human resources, hardware, software required to accomplish this project successfully will be clearly analyzed and listed out here. In the design phase, the whole project is divided into modules. Each module into subm modules by drawing some diagrams using unified modeling language. A pseudo code will be prepared at this phase. In the implementation phase, the application is coded as per the end user requirements. Coder now has the task to do the coding. Developers will develop the actual source code by using the pseudo code and following the coding standards. The testing and integration phase is the most important step of the application development. Here the application is tested and rebuilt if necessary. The multiple modules of codes from different programmers are finally integrated into one. Then finally the application is developed and delivered to the end users. The final phase is maintenance. Once the client starts using the developed software, then the real issues start coming up. In this stage, the team is required to fix the issues, roll out new features and refine the functionalities as required. At the fourth position, we have boost product quality. The concept of DevOps does not allow mistakes in the stage of methodology. When both the operation and development stages are done correctly with no errors, then it will result in a release of better and improved product qualities. This leads to a cleaner, more efficient code and hence increases the software quality with each release. The DevOps process brings better quality to the development process and reduces the chances of unplanned work. At the third position, we have exposure to trending technologies and advanced tools. Deops works with a variety of tools. Few of them are Nagios, Chef, Docker, Git, Selenium, Puppet, Kubernetes, Anible and many more. You will get a chance to understand and use all these tools and learn how to design, develop, deploy and maintain an app or software with the help of these tools. Apart from that, by knowing all things about such software and tools, you can increase your chances of getting hired by the best companies. At the second position, we have increase your professional credibility. By obtaining a DevOps certification, you can increase your professional credibility. This certification will help you to let the others know that you have sufficient skills in monitoring a software's performance, easily write and code with scripts, enhancing the software security to a greater extent, providing the best IT hardware, you will be able to troubleshoot various issues in the software, and finally you will be able to connect softwares, databases, and much more to ensure effective functionality. 42% of companies are now preferring open-source jobs and want candidates with DevOps skills. So if you want to become a part of developing the DevOps job market, then this is the perfect time to start getting DevOps training. And finally, the top reason to learn DevOps is to get a perfect job and increase your salary. DevOps is a very popular career choice. Now, researchers have also shown that in the coming years, DevOps will be the main hiring criteria for 46% of the IT companies. However, they are not sufficient experts who can match the requirements. That's why they are massive opportunities for a candidate seeking DevOps jobs. Besides, when it comes to salary, you can earn a lot of money. On an average, a divorce professional gets a pay of $99,64 perom in the United States. And a divorce professional in India gets an average salary of 6 lakhs 2,000 rupees perom. Now let me recap and call out all the 10 reasons for learning DevOps. Once again at number 10 we had the technical, DevOps. At number nine we had work with good developers. At number eight we had increased efficiency. At number seven we had a better organizational culture. At number six we had faster release of software. Then at fifth position we had better knowledge of the software delivery life cycle. At the fourth position, we had boost product quality. And at third position, we had exposure to trending technologies and advanced tools. At the second position, we had increase your professional credibility. And finally, at the top position, we had get a perfect job and increase your salary. Without any further delay, let's get started with the topic cloud engineer versus DevOps engineer. Engineer specializes in designing, implementing, and managing cloud infrastructure and services. Cloud engineers main responsibility is collaborating with cloud providers like Amazon web services, Microsoft Azure or Google cloud platforms to design scalable and dependable solution for application and services. Whereas a DevOps engineer focuses on the interaction of development and operation. Their role is to bridge the gap between software development team and IT operation to improve collaboration, automation and efficiency in the software delivery process. Cloud engineers typically deeply understand cloud computing concepts, visualization, networking, and security. They may work on tasks such as provisioning and managing cloud resources, configuring networking and storage, fine-tuning performance, and ensuring high availability and disaster recovery measures. Whereas DevOps engineer commonly poses a solid software development and system administration foundation leveraging their expertise in this domain. They work to streamline and automate process such as building and deploying applications, managing infrastructure as code and implementing delivery pipelines. Some roles and responsibility of a cloud engineer include cloud infrastructure design, cloud resource provisioning, cloud administration, security and complaints, cloud cost optimization and cloud migration. DevOps engineer have diverse roles and responsibility which encompasses key areas such as continuous integration and continuous delivery practices, infrastructure as code implementation, configuration management, deployment and release management, monitoring and logging and DevOps tool chain. Cloud engineers requires a diverse skill set in composing various technical and non-technical areas such as Linux, database skills, programming, networking, security and recovery understanding, visualization and cloud service providers. So here are some of the skills of cloud engineers. First cloud platforms proficiency in specific cloud platforms like AWS, Azure or GCP. Next cloud infrastructure designing, implementing and managing cloud infrastructures. Then we have networking understanding cloud networking concepts including virtual networks, subnets and security groups. And then security and complaints implementing security measures and ensuring complaints within the cloud environment. And then we have automation using infrastructure as core tools like terraform or cloud formation to automate provisioning and management. And then storage confering and optimizing cloud storage solutions and then high availability and disaster recovery designing and implementing cloud solutions for high availability and disaster recovery. Now that you are aware of cloud engineer skills, this simply lens postgraduate program will equip you with all the necessary skills including cloud provider selection, application migration, performance testing, cloud workloads, web services and API, database management, multicloud deployment, storage services and many more. And now let's see the skills of DevOps engineers. First we have CI/CD pipelines. Setting up and managing continuous integration and deployment pipelines. Then infrastructure as code automating infrastructure provisioning and configuration using tools like Enible, PET or CHF. Then containerization working with containerization platforms like Docker and tools like Cubernetes. And then we have scripting and programming. Proficiency in scripting languages like Python, Bash or PowerShell as well as programming languages, config management, managing and optimizing the configuration of systems and applications. And then we have monitoring and logging implementing monitoring and logging solutions to ensure applications and infrastructure performance. And finally, collaboration and communication, working effectively with crossf functional teams and facilitating cooperations between development and operations. Now that you know DevOps engineering skills, this simply lens post-graduate program will including DevOps methodologies, continuous integration, continuous delivery, deployment, automation, cloud platforms and many more. Along with the skills, it also covers tools such as Terraform, Maven, Enible, Denkins, Kubernetes, Docker and many more. In the upcoming years, there will be higher demand for cloud engineers due to the growing usage of DevOps practices and cloud computing technologies. Some career opportunities available for cloud…

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