DevOps Tutorial
Last updated on Jun 12, 2024
DevOps Tutorial - Table of Content
- What is Devops?
- Why is DevOps needed?
- History of Devops
- Devops Architecture
- DevOps Life cycle
- Devops Tools
- Applications of DevOps
- Benefits of DevOps
- Advantages and Disadvantages of Devops
- How to Become a DevOps Engineer:
- Roles and responsibilities of a DevOps professional
- Skills
- Conclusion
What is Devops?
DevOps is a software development practice that combines software development (Dev) and information technology operations (Ops). It aims at improving collaboration and communication between development and operations teams. DevOps has brought about a lot of change in the software development process and has helped in delivering software products faster.
The main aim of DevOps is to shorten the development cycle, known as the ‘time to market’, and improve the quality of products and services.
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Why is DevOps needed?
DevOps is an essential practice that revolutionizes the way development and operations teams collaborate, enhancing efficiency and driving successful outcomes. It aims to bridge the gap between these two integral teams within an organization, fostering a seamless connection that propels the entire software development lifecycle.
Kubernetes, a remarkable advancement, plays a pivotal role in enabling customers to effortlessly download distributed, highly accessible containerized workloads on a highly abstracted platform. Its architecture and collection of internal components may seem complex at first, but their strength, versatility, and robust feature set prove unparalleled in the open-source world. By understanding the interplay of these simple building blocks, developers can unlock the full potential of Kubernetes to run and manage workloads at scale.
However, this is where DevOps truly shines. DevOps not only empowers organizations to leverage the capabilities of Kubernetes but also ensures the effective collaboration and coordination between development and operations teams. It breaks down silos and facilitates direct interaction, eliminating delays and facilitating the timely delivery of high-quality data.
By embracing DevOps, development and operations teams can work together seamlessly, from code deployment to testing. This continuous connection enables uninterrupted monitoring and immediate feedback, leading to the best possible results. DevOps embodies the ethos of continuous integration and delivery, promoting iterative improvements and rapid response to changes and challenges.
Below is the list of a few key benefits that DevOps offers:
- The focus on the consumer is renewed. One of the main reasons for the shift to DevOps is that it puts the team back in the customer's shoes.
- Teams come together to accelerate product delivery.
- Focuses on growth in a more straightforward manner...
- The development process is made more automated.
- End-to-end accountability is supported.
History of Devops
In this DevOps tutorial, let us learn about the history of DevOps.
In recent years, several businesses have adopted DevOps ideas in order to better respond to their business problems. DevOps was once limited to IT services, but it has now spread throughout the firm, altering procedures and data flows as well as triggering significant organizational changes.
- The DevOps idea is not entirely new; it grew naturally from the Agile methodology.
- When IT operations and software development communities raised concerns about what they saw as a lethal degree of dysfunction in the industry during 2007 and 2008,
- The DevOps movement began to gather.
- Patrick Debois, one of the DevOp’s gurus, created the term "DevOps" in 2009.
- Alanna Brown of Puppet designed and published the State of DevOps study in 2012.
Devops Architecture
Build
Without DevOps, the cost of resource consumption was calculated using pre-determined individual utilization and set hardware allotment. And, with DevOps, the cloud is used, resources are shared, and the build is based on the needs of the user, which is a technique for controlling resource or capacity utilization.
Code
Many good practices, like Git, allow code to be utilized, ensuring that it is written for business, tracking modifications, being notified of the cause for the difference between the actual and expected output, and, if required, reverting to the original code generated. The code can be properly organized in files, folders, and so forth. They can also be reused.
Test
After testing, the application will be ready for production. Manual testing takes longer to complete since it requires more time to test and move the code to the output. Testing can be automated, which cuts down on testing time and hence cuts down on the time it takes to release code to production, as automating the execution of scripts eliminates numerous manual stages.
Plan
Agile technique is used by DevOps to plan development. When the operations and development teams work together, it is easier to organize the work and plan properly, resulting in increased productivity.
Monitor
Any risk of failure is identified by continuous monitoring. It also aids in correctly tracking the system so that the application's health may be assessed. Monitoring gets easier with services that allow log data to be watched through a variety of third-party tools, such as Splunk.
Deployment
The scheduler can be used by a variety of systems to automate deployment. By deploying dashboards, the cloud management platform allows users to capture accurate insights and examine the optimization scenario, as well as statistics on trends.
Operate
DevOps affects the way traditional development and testing are done individually. The teams work together in a collaborative manner, with both teams contributing actively throughout the service lifecycle. The operation team collaborates with developers to build a monitoring strategy that meets both IT and business needs.
Deployment
Automation can be used to deploy to a specific environment. When it comes to deploying to the production environment, however, manual triggering is used. Many release management processes are used to execute the deployment in the production environment manually to minimize the impact on customers.
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DevOps Life cycle
Now let us learn about the lifecycle of DevOps in this DevOps tutorial
Development
The Continuous Development phase concentrates on software planning and development. The project's vision is determined in the planning phase of the software. The programmers begin to work on the coding. Although the DevOps tools are not employed in planning, a number of solutions are available for code maintenance.
Testing
The resulting programme is rigorously tested for flaws at this stage. Continuous testing is carried out using automation testing tools such as TestNG, JUnit, Selenium, and others. These technologies allow QAs to test many code bases at the same time to ensure that the functionality is flawless. At this stage, Docker Containers can be utilized to emulate the test environment.
Integration
In the DevOps lifecycle, this is the most crucial stage. Continuous Integration is a software development technique employed by the developers which require committing source code changes more frequently. It's possible to do this once a day or once a week. Then each commit is produced, allowing for the early identification of any mistakes.
The developed code for the new feature is constantly mixed in with the existing code. Software is updated on a frequent basis as a result of this. The revised code must be seamlessly connected with the systems to reflect changes to end-users.
Deployment
At this point, the code is pushed to the production servers. It's also crucial to ensure that the code is implemented correctly on all servers.
New code is released on a regular basis, and configuration management software is essential for accomplishing jobs often and efficiently. Some of the most frequent tools used in this phase are Chef, Puppet, Ansible, and SaltStack.
Containerization tools are also important during the deployment phase. Vagrant and Docker are two popular tools for this. These technologies make it easier to maintain consistency throughout the development, staging, and testing environments. They also aid in the scaling up and down of instances in a delicate manner.
Containerization solutions ensure that an application's testing, development, and deployment environments are all consistent. There is no chance of mistakes or failure in the production environment because they package and duplicate the identical dependencies and packages used in the testing, development, and staging environments. It enables the application to run on a wide range of platforms.
Monitoring
This is a part of the DevOps process that incorporates all operational aspects and records and analyses critical details of the software's use to find trends and spot problem areas. Monitoring is usually included as part of the software application's operating features.
It may deliver large-scale data on the application parameters in the form of documentation files while it is in a continuous usage position. System difficulties like server not being reachable, insufficient memory, and so on are resolved at this stage. It ensures the security and availability of the service.
The next concept you would learn in this DevOps tutorial is the DevOps tools
Devops Tools
1. Version Control tools
Github: Github is widely considered as one of the largest and most advanced development platforms across the globe. a countless number of organizations, as well as DevOps professionals, use GitHub to design, ship and control their software.
Bitbucket: Bitbucket is a renowned platform with 10 million+ clients. It's not just a code hosting platform; it's also a code management platform. It congregates the complete software team to complete a project.
GitLab: GitLab is an ultimate DevOps solution that aids in the rapid delivery of software. It empowers teams to execute all tasks, including planning, supply chain management, delivery, and security.
2. Container Management tools
Docker: It is a lightweight solution that employs an integrated approach to streamline and expedite a variety of SDLC operations. It is a self-contained, executable source which contains all of the necessary components to run a programme.Kubernetes: One of the most extensively used container orchestration technologies is Kubernetes. It is a DevOps tool that automates the deployment and maintenance of the applications run in containers.
Apache Mesos: Mesos is a cluster management solution for DevOps. "Apache Mesos isolates CPU, storage, and other resources from physical and virtual machines, making it easy to build and manage fault-tolerant and flexible distributed systems."
3. Application Performance Monitoring tools
Prometheus: It is a community-driven open-source performance monitoring platform. You may also use it to keep track of containers and set alarms considering the time series data.
Dynatrace: Dynatrace allows you to monitor all aspects of your infrastructure. You can track information such as the traffic on your network, the CPU consumption, the response time of your processes, and more by performing log monitoring.
AppDynamics: AppDynamics gives you real-time information on how well your apps are doing. It keeps track of all transactions that travel through your apps and generates reports on them.
4. Deployment & Server Monitoring tools
Splunk: Splunk is a DevOps tool used for monitoring and exploration which can be used on-premises or as a SaaS.
Datadog: Datadog is a DevOps tool for monitoring servers and apps in hybrid cloud settings.
Sensu: Sensu is a DevOps tool for monitoring applications, servers, functions, containers and many more .
5. Configuration Management tools
Chef: Chef is an Erlang and Ruby-based DevOps tool to launch and manage servers and applications. It can be used combining with any cloud-based technology
Puppet: Puppet is in charge of simplifying the management and automation of your infrastructure and complex workflows.
Ansible: Ansible is an IT automation tool that eliminates repetitive chores and allows teams to focus on more strategic responsibilities.
6. Continuous Integration / Deployment Automation tools
Bamboo: It's a DevOps tool that takes you from coding to delivery or deployment through the complete Continuous Delivery process. It integrates automated builds, testing, and releases into a single workflow.
Jenkins: Jenkins is a Java-based open-source CI and CD platform that automates the end-to-end release management process. Jenkins has become one of the most crucial DevOps tools.
IBM UrbanCode: IBM® UrbanCode® Deploy simplifies and automates application deployment. It creates automated processes for deploying, upgrading, rolling back, and uninstalling apps using a pictorial flowchart tool.
7. Test Automation tools
Test.ai: Test.ai is an automation testing platform powered by AI that helps developers deploy products quickly and with higher quality.
Ranorex: Ranorex is a one-stop shop for automated testing of all types, including cross-browser and cross-device testing.
Selenium: Selenium is a tool for automating web browsers and applications for testing, but it can be applied to automate administrative tasks on the web.
8. Artifact Management tools
Sonatype's NEXUS: Sonatype, which bills itself as the "world's #1 repository management," successfully used for organizing, storing, and distributing development artifacts.
JFRog Artifactory: JFRog is an ultimate DevOps artifact that boosts productivity throughout your development ecosystem. It acts as a central repository for metadata and binaries. It also sup[ports all types of package formats.
CloudRepo: CloudRepo is a fully managed repository which enables you to share Maven repositories. CloudRepo empowers you to not worry about the maintenance of infrastructure and concentrate on the product.
9. Automated Codeless Testing tools
AcceIQ: Among DevOps tools, AcceIQ is the market leader in codefree test automation. It's a powerful code-free test automation tool that allows testers to design test logic easily, not considering the programming syntax:
Appvance: Appvance IQ is an AI-driven continuous testing solution. Appvance executed end-to-end autonomous tests and codeless script development.
Testim.io: Testim.io is an AI-based user interface testing platform that allows you to execute tests with quick scripting, better coverage and improved quality.
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Applications of DevOps
Below is the list of applications you would learn in this DevOps tutorial
1. Microservices
Microservices are an architectural style that can be used in conjunction with Devops to speed up the delivery of software. A microservice-based architecture breaks down an application into smaller, more manageable pieces called services. This allows for more flexibility and faster deployments.
2. Use of DevOps in Networking
Networking is a critical part of any organization, but it can be difficult to manage and maintain.DevOps can be used in networking to improve the process of software changes and to improve the communication between network engineers and developers. By using DevOps, networking teams can automate their processes, improve their collaboration, and deliver better software faster.
3. DevOps in Data Science
By using DevOps in data science, you can speed up the process of data analysis and get results more quickly. Additionally, DevOps can help to ensure the quality of your data.
4. DevOps in Testing
Testing is an important part of software development, and it can be difficult to ensure that all aspects of the system are tested thoroughly and effectively. DevOps is a methodology that can help with testing by improving communication and collaboration between developers and operations staff. DevOps can help to speed up the testing process by making it easier to identify and fix problems early in the development cycle. It can also help to improve the quality of testing by providing more accurate and timely information about the state of the system.
DevOps in the cloud
Cloud computing being centralized and scalable offers a common platform for deployment, testing, and production, as well as integration, for DevOps applications. DevOps empowers teams to easily grow and adapt to changing requirements.
Automated testing in virtual environments that are indistinguishable from live environments is also possible because of the cloud. This frees up DevOps team members to focus on the work that only humans can do while also removing them from mundane chores that are prone to human error.
Benefits of DevOps
List of the Technical Benefits of DevOps:
- Reliability
- Efficiency
- Reduced danger
- The development cycle is shorter
- Stability
List of the Business Benefits of DevOps:
- Faster updates
- Improved user experience
- Less flaws.
- High-quality,
- Faster-delivery products
- Cost reduction
Advantages and Disadvantages of Devops
Below is the list of advantages of DevOps:
- Access to a DevOps Expert Pool
- There will be no internal challenges.
- Development Cycles are Shorter
- Quality and flexibility have both improved.
- Cost-effectiveness
- Risks and Recoveries are better managed.
- Improved Security Procedures
Below is the list of disadvantages of DevOps:
- Workplace Culture Restructuring
- Demands expertise in Software Engineering
- Demands strong teamwork.
- Devops takes some time at first
- Speed and security are challenging
How to Become a DevOps Engineer:
This DevOps tutorial will now take you through the roles and responsibilities and skills required to become a DevOps Engineer.
Roles and responsibilities of a DevOps professional:
Below are the list of different job roles of DevOps and the responsibilities associated with it.
DevOps Release Manager:
- Control the software development process.
- Manage team members' project planning and documentation. Perform quality assurance tests considering the client’s feedback.
- By properly planning, you may manage and mitigate risk.
- Ensure that technical and managerial employees are in constant contact.
DevOps Lead
- Work on the CI/CD pipeline.
- Observe the entire process, as well as the infrastructure for continuous integration and deployment.
- Have experience implementing CI/CD pipelines utilizing tools such as Jenkins, Chef, Puppet, and Git.
- Have experience with monitoring software such as NAGIOS, Zabbix, and others.
- Responsible for ensuring that production and non-production infrastructure are always available.
- Understanding of various cloud computing platforms such as IaaS, PaaS, and SaaS
- Have extensive experience with AWS, Azure, OpenShift, and other cloud platforms.
DevOps Automation Expert
- Create CI/CD pipelines that are fully automated.
- Have experience with GIT, SVN, and Jenkins
- Have a strong understanding of Unix
- Know how to use Shell scripts, Perl, and Python.
- Have experience with Gitlab, Jenkins, Chef, Ansible, and Puppet to create automated CI/CD pipelines.
- Know how to use containerization tools like Docker to deploy containers.
DevOps Testing Professional
- Have a thorough understanding of software testing
- Creating automated test pipelines is a skill.
- Have a thorough understanding of unit testing
- Python and Java are two languages that you should be able to code in.
- Have a crystal-clear DevOps visions.
DevOps Software Developer
- Experience with commercial IDEs such as IntelliJ Idea, Komodo, and others.
- Capable of producing high-quality code
- Have a better knowledge of how algorithms work and how data is organized.
- Strong command of C, Ruby, Java, and several other programming languages.
DevOps System Engineer
- Infrastructure maintenance is the responsibility of this position.
- Have a thorough understanding of UNIX and Linux, as well as Shell scripting, Python, Perl, and other scripting languages.
- Have a deep understanding of AWS, Azure, OpenShift, and other cloud platforms.
- MySQL expertise is required.
DevOps Security Professional
- Understands the importance of system and network security.
- Can analyze risks and devise a plan to mitigate them.
- Have a thorough understanding of firewalls, intrusion detection systems, and operating systems.
- Have a solid grasp on penetration testing
- Metasploit, Nmap, Wireshark, Snort, and other tools have been utilized.
- Have a thorough understanding of cloud security.
Skills
Let us try understanding the various prerequisites of learning DevOps.
Programming skills:
You should have a basic understanding of coding. You do not have to be a pro in coding. However, you should not be a novice. A thorough understanding of several programming languages like Java, Python, Perl and more would help you master the concepts of DevOps.
Linux:
Possessing a comprehensive understanding of Linux and its commands would help you learn DevOps at a faster pace.
Automation skills:
A Basic understanding of Automation, automation pipelines, and automation process knowledge would also be a great aid in learning DevOps.
Besides the above mentioned, a good understanding of various operating systems, familiarity with AWS and Azure would benefit you in understanding the core technical concepts of DevOps.
Apart from that, good communication skills and analytical understanding also play a key role in helping you become a successful DevOps Engineer.
Conclusion
DevOps is a hot topic in the tech world right now. If you want to pursue a career in DevOps, there is no better time than this. We believe that this DevOps tutorial helped you learn several interesting concepts of Devops and how to get started with DevOps.
What is Kubernetes?
At its simplest level, Kubernetes is a framework for running and coordinating containerized applications across a cluster of machines. It is a framework designed to fully manage the life cycle of containerized software and services using approaches that provide stability, usability and data integrity.
As a Kubernetes user, you will decide what your applications should run and how they ought to be able to communicate with other applications or the outside world. They can reduce operational costs of your services, make seamless roll-up upgrades, and move traffic across various versions of the frameworks to test functionality or roll-back troublesome deployments. Kubernetes provides an interface and configurable platform primitives that enable developers to identify and handle your applications with a high degree of flexibility and interoperability.
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Tasks performed by the Kubernetes:
Kubernetes is the Linux kernel used by embedded environments. It allows you to isolate the hardware resources of the nodes(servers) and maintain a reliable interface for apps that access a common pool of resources.
Reasons for using Kubernetes:
Here are some of the benefits of using Kubernetes. They are:
- Kubernetes will run on-site bare metal, OpenStack, Google, Azure, AWS, etc.
- Helps you prevent vendor lock issues as you can use any vendor-specific APIs or services except where Kubernetes offers an abstraction, e.g. load balancing and storage.
- Containerization using Kubernetes enables package applications to achieve these objectives. It will allow applications that need to be published and modified without any downtime.
- Kubernetes helps to make sure that certain containerized frameworks run where and when you want to and lets you find the resources and tools you want to work with.
Features of using Kubernetes:
Some of the essential features of the Kubernetes are:
- It performs automated scheduling
- Self-healing powers
- Automated rollouts & rollbacks
- Horizontal Size & Load Balancing
- Provides continuity of the environment for development, testing, and production
- Infrastructure is loosely coupled to each part that can function as a separate entity.
- Provides a higher resource use density
- Offers business-ready features
- Application-centered management
- Self-scalable infrastructure
- You can construct a predictable infrastructure
Kubernetes basics:
Here are the basics of the Kubernetes. They are:
- Cluster: It's a list of hosts (servers) that lets you aggregate your available resources. This includes the ram, the Processor, the ram, the disc, and their computers in an accessible pool.
- Master: The master is a set of components that make up the Kubernetes control panel. These components are used in all cluster decisions. This involves both arranging and reacting to cluster events.
- Node: It is a unified host designed to operate on a physical or virtual machine. The node can run both Kube-proxy, minikube, and kubelet which are considered to be part of the cluster.
- Namespace: It's a logical cluster or setting. It is a commonly used tool used to calculate the access or division of a cluster.
Kubernetes Architecture:
Master Node:
The master node is perhaps the most vital part capable of controlling the Kubernetes cluster. It is a point of entry for all sorts of managerial functions. There could be more than one master node in the cluster to search for fault tolerance.
The master node has numerous components, such as API Server, Controller Manager, Scheduler, and Etcd. Let's see both of them.
API Server: The API server serves as an entry point for all REST commands used to manage the cluster.
Scheduler:
The scheduler sets the tasks for the slave node. It stores information on the use of resources for every slave node. It is responsible for the allocation of the workload.
It also lets you monitor how the working load is used on cluster nodes. It allows you to put the workload on the resources that are available and to embrace the workload.
Etcd:
etcd store configuration information and wright values. It interacts with most of the components to receive commands and function. It also handles network rules and port forwarding operations.
Node worker/slave :
Worker nodes are another important component that includes all the services you need to handle networking between containers, and communicate with the master node, which enables you to allocate resources to the scheduled containers.
- Kubelet: Gets the specification of the Pod from the API server and ensures that the containers listed are up and running.
- Docker Container: Docker Container is running on each of the worker nodes running the configured pods.
- Kube-proxy: Kube-proxy serves as a load balancing agent and a network proxy to support a single worker node.
- Pods: A pod is a mixture of single or multiple containers that logically run on nodes together.
Key terminologies associated to kubernetes:
Replication controllers:
The replication controller is an entity that determines a pod template. It also regulates variables to scale similar Pod prototypes horizontally by raising or lowering the amount of operating versions.
The replication controller is essential for securing that the quantity of pods distributed in the network corresponds to the amount of pods in its setup. If a pod or underlying host fails, new pods will be started by the controller to compensate. If the number of replicas in the configuration of the controller changes, the controller either starts up or destroys the containers to fit the desired number. Replication controllers can also make automatic changes to roll over a set of pods to a new version one by one, minimizing the impact on application availability.
Replication Sets:
Replication sets are an interaction on the replication controller architecture with versatility in the way the controller understands the pods it is supposed to handle. It replaces replication controllers due to their higher replicate selection capability.
Like pods, both replication controllers and replication sets are usually the units in which you operate directly. Although they build on the pod architecture to incorporate horizontal scaling and reliability assurances, some of the fine grained life-cycle management capabilities found in more complex artefacts are lacking.
Deployments:
Deployment is a typical workload that can be directly generated and handled. Deployment uses a replication collection as a building block that adds a life cycle management feature.
Although deployments designed with replication sets may appear to duplicate the functionality provided by replication controllers, deployments address several of the pain points that existed in the implementation of rolling updates. When upgrading applications with replication controllers, users are forced to request a proposal for a new replication controller to replace the existing controller.While using replication controllers, tasks such as monitoring history, recovering from network failures during upgrade, and reversing bad changes are either difficult or left to the responsibility of the user.
Deployments are a high-level object designed to help control the life cycle of replicated pods. Deployments can be easily changed by modifying the configuration, and Kubernetes updates the replica sets, handles changes between various versions of the programme, and optionally automatically preserves event history and undo capabilities. Due to these features, deployments are likely to be the type of Kubernet object for which you operate most frequently.
Stateful Sets :
It's a specialized pod control that provides ordering and uniqueness. It is mainly used for fine-grained control that you need in particular with regard to deployment order, stable networking, and persistent data.
Stateful sets include a secure communication indicator by generating a special, number-based name for a pod that survives even if the pod has to be transferred to another node. Persistent storage volumes can also be moved with a pod when rescheduling is required. Volumes remain even after the pod has been removed to avoid unintended data loss.
When deploying or modifying the scale, stateful sets conduct operations on the basis of the numbered identifier in their name. This provides greater predictability and control over the execution order, which may be useful in certain situations.
Daemon Sets:
Daemon sets are just another specialized type of pod controller which runs a pod copy on every node in the cluster. This form of pod controller is an effective way for distributing pods that are able to perform updates and provide node services on your own.
For example, gathering and distributing logs, compiling statistics, and operating services that enhance the ability of the node itself are common candidates for daemon sets. Since daemon sets also provide basic services and are required across the fleet, they may circumvent pod scheduling restrictions that prohibit other controllers from assigning pods to certain hosts. As an example, for its job tasks, the master server is often designed to be inaccessible for regular pod scheduling, but daemon sets have the ability to circumvent the pod-by-pod restriction to ensure that critical services are running.
Kubernetes VS Docker Swarm:
- Kubernetes supports auto-scaling when compared with the docker swarm.
- In Kubernetes, you can manually configure the load balancing settings whereas in docker it will be done automatically.
- Kubernetes helps in sharing the storage volumes between the multiple containers in the same pod whereas docker shares storage volumes with any other containers.
- It comes with a switch built-in tool for logging and monitoring whereas docker uses third-party tools for logging and monitoring.
- Kubernetes is complicated, time-consuming whereas docker is easy and fast.
- Kubernetes comes with GUL whereas docker there is no GUI support.
- Scaling up is very low when compared with docker.
Disadvantages of kubernetes:
Some of the disadvantages of kubernetes are:
- The Kubenetes dashboard is not as useful as it should be.
- Kubernetes is a little confusing and unnecessary in environments where all development is performed locally.
- Protection is not very good at all.
What are the drawbacks of the Waterfall Method?
The Waterfall Method has several drawbacks that need to be taken into consideration:
1. Inflexibility: One major drawback of the Waterfall Method is that once a stage is completed, it cannot be changed. This lack of flexibility can be problematic if changes or updates are needed throughout the project.
2. Not suitable for large projects: The Waterfall Method is not recommended for large-sized projects that have complex requirements and dependencies. Its linear and sequential nature makes it difficult to manage and adapt as the project becomes more intricate.
3. High risk of customer dissatisfaction: Since the Waterfall Method lacks early feedback and customer involvement until the later stages, there is a high risk of customer dissatisfaction. The end result may not align with the customer's expectations or requirements, leading to wasted efforts and potential conflicts.
4. Limited collaboration and communication: This methodology often follows a top-down approach, where communication and collaboration among team members, stakeholders, and customers are limited. This can hinder the exchange of ideas, problem-solving, and the overall success of the project.
5. Lack of early feedback: Unlike iterative or Agile methodologies, the Waterfall Method lacks early feedback loops, making it challenging to identify and address issues or make necessary adjustments during the development process. This can result in increased costs and time if problems are discovered late in the project cycle.
What are the applications of DevOps?
Conclusion:
Kubernetes is an amazing development that enables customers to download distributed, highly accessible containerized workloads on a highly abstracted platform. Although Kubernetes architecture and collection of internal components can at first seem overwhelming, their strength, versatility, and robust feature set are unparalleled in the open-source world. By learning how simple building blocks fit together you can start developing frameworks that completely utilise the functionality of the framework to run and manage your workloads at scale.
About Author
Ishan is an IT graduate who has always been passionate about writing and storytelling. He is a tech-savvy and literary fanatic since his college days. Proficient in Data Science, Cloud Computing, and DevOps he is looking forward to spreading his words to the maximum audience to make them feel the adrenaline he feels when he pens down about the technological advancements. Apart from being tech-savvy and writing technical blogs, he is an entertainment writer, a blogger, and a traveler.
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