Back in early days software was developed as a single unit constructed from a mishmash of custom technologies that were clubbed together. As can be imagined, with the addition of more features, it started becoming more complicated with a codebase that steadily grew bigger and harder to work with. Microservices break apart this model into a set of small, discrete and most importantly, independent processes, helping developers improve the software faster and more efficiently.
The Internet of Things or IoT has opened various new avenues for the intersection of technology, connectivity, and everything in between. It has extended internet connectivity to physical devices and everyday objects, giving you the power to control them remotely. It relies on the principles of electronics and communication and uses hardware such as sensors to enable connectivity and interaction over the internet. Apple, Amazon, Google, and a number of organizations around the world are using IoT to bring forth innovative changes. At the same time, there are many organizations that are looking to deploy IoT in their products and services.
As a data science technique that permits predictive analysis, machine learning has brought about a major change in the way most organizations function. It has streamlined a wide array of computing processes and operations by employing data as the basic foundation upon which the success of various production systems can be built. Be it the evaluation of patterns, the discovery of trends, the measurement of outcomes, or the forecast of behaviors - machine learning has allowed business apps and devices to become smarter, without being limited by the need for extensive technical programming.
The systems, applications, and products in data processing software, commonly known as SAP, has brought about a complete transformation in the way most organizations manage their ERP ecosystems. By providing an efficient platform to integrate various business processes and information flows, SAP has permitted collaborative management, enhanced productivity, and effective resource use within its comprehensive framework.
A lot of organizations today look to provide disaster recovery capabilities towards smooth business operations.
Because of the availability of various options for remote recovery in the event of a disaster, there has been a dramatic rise in the number of service providers offering IaaS (Infrastructure as a Service).
Quite rightly described by Microsoft, the multitude of offerings at Microsoft Graph’s disposal do justice to the statement, “The fabric for all your data.” In plain English, Microsoft Graph acts as a gateway that brings together the services, intelligence, and data offered by a company. It gives developers the luxury of using a unified programming model that harnesses the power of MS Cloud services like Intune, Office 365, Azure Active Directory, SharePoint, One Drive, and many more.
If you're a digital marketer, you must have heard about Azure managed hosting services.
Blockchain can be thought of as an open distributed ledger that can hold transaction records between multiple parties in a transparent and immutable way offering security and integrity to online transactions. Blockchain is now widely implemented in finance, supply chain, retail, digital media and various other industries.
Azure is one of the most popular cloud service providers today offering capabilities in three major categories - IaaS (Infrastructure as a Service), PaaS (Platform as a Service) & SaaS (Software as a Service). Migrating to a cloud platform such as Azure is in the IT road map of most if not all enterprises. Moving the software and workloads to Azure helps in driving productivity, reducing cost of operations, increasing scalability and ensuring high service availability. So how does an organization move to cloud? It does seem like a daunting process but with proper planning and strategy success can be ensured.
Be it in the financial services industry or other digitally-enabled verticals, organizations in the USA are readily implementing Azure, AI and Office 365 to achieve the next level of success. Most of them are in the transformational stages of migrating their in-house IT infrastructural capabilities to the cloud with the help of AI.