Introduction
Edge computing is the next big thing in cloud infrastructure. The concept of edge computing was first conceived by IBM in 2002, and it has been gaining traction ever since. Edge computing refers to using one or more processing functions as close as possible to where data is generated, as opposed to centralizing all computation at a single location. This approach has many benefits, including lower latency, reduced network costs and better overall performance of applications that run on edge systems versus traditional cloud offerings.
Edge Computing
Edge computing is a new approach to computing that involves running applications, data and other services closer to the end user. It’s a subset of cloud computing–the same concept but applied differently. Edge computing is used for real-time analytics, IoT and other applications that require low latency and high bandwidth connections (such as video streaming).
Windows Server 2019, Windows 10 and Azure Stack
Windows Server 2019 is a cloud-ready operating system that provides a foundation for building and running applications, services, and workloads in the datacenter. Windows Server 2019 also enables you to run Azure Stack on your own premises, so you can take advantage of hybrid cloud solutions like Azure Analysis Services and Power BI Embedded.
Windows 10 is the most popular OS in the world with over 500 million computers running it. It’s an operating system designed for people who want more out of their devices than just basic functionality–it offers immersive experiences as well as innovative ways to work across multiple devices (including virtual reality).
Google Cloud Platform
Google Cloud Platform is a cloud computing service that provides infrastructure for building, testing, deploying, and managing applications on the internet. Google Cloud Platform is a platform as a service (PaaS) that provides developers with a set of cloud-based tools. This allows them to build their own apps without worrying about the underlying hardware or operating systems.
IBM Cloud Private
IBM Cloud Private is a private cloud that can be deployed on-premises, in a hybrid cloud or in the public cloud. It’s based on the Kubernetes container orchestration tool and is aimed at DevOps teams.
IBM Cloud Private offers features such as:
- A secure, configurable environment for development and testing of applications before they go into production
- Integration with IBM Bluemix services, including Watson IoT Platform, MobileHub and Security Intelligence
Amazon Web Services, Microsoft Azure and Google Cloud Platform are the top three players in the Edge Computing market
Amazon Web Services (AWS), Microsoft Azure and Google Cloud Platform are the top three players in the Edge Computing market. AWS and Azure are leaders in this space with a combined share of over 60{6f258d09c8f40db517fd593714b0f1e1849617172a4381e4955c3e4e87edc1af} of total market revenues, while Google is a new entrant in this field. IBM Cloud has also entered into an agreement with Apple to develop edge computing solutions for iPhones and iPads using IBM’s Bluemix platform as well as its cloud services infrastructure, analytics capabilities and cognitive computing technologies such as Watson AI-powered IoT solutions or Watson Digital Assistant service which will help Apple build more intelligent devices using advanced technology features like voice recognition support etc..
Conclusion
The edge computing market is expected to grow at a high CAGR during the forecast period. The demand for edge computing is increasing due to its benefits like high speed processing, better security, easy maintenance and scalability. The major players in this market include Amazon Web Services (AWS), Microsoft Azure and Google Cloud Platform (GCP). These companies offer different types of services like infrastructure as a service (IaaS), platform as a service (PaaS) and software as a service (SaaS).
More Stories
What Is Edge To Cloud Computing & What Are The Benefits?
What Edge Network Vpn Is & Why You Should Have An Account
Edge Computing: The Future Of Data Processing