Tips to choose Hadoop, kubernetes and Jenkins

# Tips to choose Hadoop, kubernetes and Jenkins Hadoop is a highly scalable data storage platform used as the foundation for many Big Data projects and products. By the 2000s, Hadoop had become standardized for creating data lakes, allowing local clusters to be built with commodity hardware to store and process this new data cheaply. Until not long ago, mounting a Data Lake on Hadoop was a widely used option for the following reasons: <ul> <li>Greater familiarity among the technical team.</li> <li>Easy to climb.</li> <li>The locality of the data allows for faster computation.</li> </ul> But the Open Source world has continued to evolve. With Hadoop, it can be challenging to achieve the elasticity, simplicity and agility in provisioning that other Kubernetes-based solutions offer. This article explains <a href="https://kuberty.io/blog/kubernetes-vs-hadoop-yarn/">Kubernetes Vs Hadoop</a>.  <img src="http://justpaste.me/upload/20221124/e40d-1f696ad3c51b1a429c2d76339ed3//Best-OS-for-Docker.jpg" alt="" width="320" height="300" /> What is Kubernetes? It is an open-source platform to manage Linux containers in private, public, and hybrid cloud environments. Enterprises can also use Kubernetes to manage microservices architectures. Containers and Kubernetes can be deployed on most cloud providers.   Application developers, IT system administrators, and DevOps engineers use Kubernetes to deploy automatically, scale, maintain, schedule, and operate multiple application containers on group nodes. Containers run on top of a common shared operating system (OS) on the host machines but are isolated from each other unless a user chooses to connect them. See the difference between <a href="https://kuberty.io/blog/kubernetes-vs-jenkins/">Kubernetes Vs Jenkins</a>.   Jenkins is a Java-based DevOps solution for continuous integration/continuous delivery (CI/CD) automation. Pipelines make combining various code branches into a single main branch easier by automating testing and reporting on isolated changes in a more extensive code base in real time. They also build the software, automate testing of their builds, prepare the code base for deployment (delivery), and ultimately deploy the code to containers, virtual machines, bare metal servers, and cloud servers. They also quickly find bugs in code bases.     What Is Network Convergence?  The next evolution of wireless network architecture is the densification of 4G/LTE and 5G wireless technology, which will bring a convergence of physical fixed network assets and wireless access points. The issue, as consumer demand for data increases, will be capacity.   Wireless capacity can be increased in several ways: better modulation techniques, more spectrum, or spatially. 4G/LTE densification and potentially 5G mobility create more spatial capacity. Smaller cells close to each other (250 meters) mean fewer users at each access point, which means more bandwidth per square meter. The promise of fixed wireless 5G in the sub 6 GHz range and millimetre wave (28 GHz) band also creates more bandwidth with additional spectrum.   Network requirements for convergence A converged network requires three main aspects: Power, wireless access points and other peripheral devices. The power requirement at each wireless access point is essential but is often assumed to be available or even forgotten until the completion of network planning.   FTTH PON networks do not have this power access other than installing a drop cable and a meter. While the latter can be purchased at a reasonable cost and within a reasonable timeframe, installation on hundreds or thousands of access points will quickly become a project hurdle.