How The Cloud Made ‘Data-Driven Culture’ Possible | Part 3: Cloud Solutions
This is a three-part story (Part 1, Part 2). Previous blogs covered cloud innovations and cloud adoption. Now, to cloud solutions.
Popular Cloud Computing Solutions
Cloud solution is a broad topic. Cloud infrastructure, as discussed in the previous blog, is quite vast. Cloud solutions can be broadly classified into four components: Public, Private, Multi-Cloud and Hybrid cloud solutions. For every company, this is a very important starting step.
Public Cloud Infrastructure
The cloud infrastructure consists of shared resources, deployed on a self-service basis over the Internet. It is hosted by public cloud providers such as AWS or Azure and are the most popular of the lot.
Disadvantages: Number of security challenges, lack of freedom to a certain extent
Private Cloud Infrastructure
A single customer, typically large MNCs have the privilege of a cloud computing environment that is exclusive only to them. The hardware and software tools in this environment are accessible only by this particular player. IBM is one of the leaders in providing such an infrastructure.
Advantages: High levels of security, efficiency and control
Disadvantages: High Costs
Community Cloud Infrastructure
Certain companies unite and build a shared infrastructure accessible only by them and no other party.
Advantages: Better utilization of resources
Disadvantages: Entry and exit is challenging task
Hybrid Cloud Solution
This model has recently garnered a lot of attention. Under this model, the strategy is to make use of both private (for highly confidential data) and public cloud infrastructure for cost and performance optimization. A well-calculated combination can do miracles for cost saving without compromising on data security.
Single Cloud Strategy
Not relying on more than one cloud network. The questions typically asked here are which cloud provider’s services best align with their needs and requirements? This is especially popular for SMEs and smaller enterprises who work with limited amounts of data. Every cloud solution is scalable but with such companies need not go through the trouble of going multicloud when a single cloud fulfills all their needs.
A combination and integration of multiple public clouds. Business problems and business needs are getting more complex. Here, the question changes to which applications would be best suited for the organization’s long term strategy. Many organizations leverage multiple cloud platforms strategically for multiple reasons. It may vary from cost-cutting, best of different worlds to emergency backup options.
Container workload and Microservices
Kubernetes, considered one of the best innovations in recent times, is responsible for enabling containerized workloads in its platform. The system introduced cluster architecture to enterprises that can massively simplify certain applications. Kubernetes is an open-source system used to automate deployment, scaling, and management of containerized applications. It organizes the containers that constitute an application into logical units to facilitate management and discovery. The workload is one such application. A company runs several applications and workloads on Kubernetes using containers over a cluster of nodes. Containers isolate applications from the host infrastructure.and each container that is run is repeatable. Fintech services and neo-banks who need to always be online, activate multiple active kubernetes clusters, on thousands of nodes. Refer to other industry examples in this wonderful article.
Edge computing is a distributed computing concept that moves compute and storage closer to data sources. The technology was introduced as a bet on a future where data generation could blow up in leaps. So much that even centralized systems cannot handle it without high costs, bandwidth and latency issues.
Edge computing comes as a boon for industries that depend on IoT like logistics and telecommunications. Ericsson believes that the future of IoT has the potential to be limitless. Various forecasts project a growth of over 5 billion IoT devices by 2025. Imagine connecting IoT devices especially in tens of thousands if not millions for data generation in real-time. Rigorous computing will be time consuming when the results need to be almost near-real time. Edge computing is here and as discussed in the first blog, Azure and AWS are constantly innovating to tap into this paradigm.
Edge computing moves computation and storage closer to the data sources. Fog computing finds a middle-ground between the cloud and the sources that produce the data. So as to cut latency and optimize the cloud storage system. it is inefficient to store all data into the cloud for analysis. Not all the data stored on the cloud is used for analysis. Companies store it anyway for potential use-cases at a later stage as tech keeps innovating. Fog computing enables data-filtering, so only certain type data need to be stored in the cloud.
Both these innovations come as a boon to industries such as logistics, healthcare, utilities, and manufacturing.
Industries where Cloud adoption has been aggressive in the past decade
According to the Web Tribunal, 94% of enterprises already use a cloud service and organizations leverage almost 5 different cloud platforms on average. The increasing popularity of remote work adds to the need for cloud adoption. The easy adoption and development of AI/ML (Machine Learning)/DL (Deep Learning) applications on cloud is another factor that is promoting the adoption of cloud.
Managing cloud solutions is no easy task and there are multiple challenges involved right from discovery, like, migrating to cloud, platform-related hiring and retention, handling cloud security, and cost optimization.
Technology companies, streaming platforms, retail & e-commerce platforms, logistics, and financial services industries are the most proactive in leveraging the cloud opportunities. The healthcare industry is anticipated to swiftly follow suit in this space.
The Future of Cloud Computing: All The Hype
In the likely event of large complex tasks that need powerful processing power, a network of computers can be made to run as a cluster. You now have something that is nothing short of a virtual supercomputer. The cloud can be used to build vast computer grids for meeting a common objective. Using the cloud ensures that the processing time is significantly reduced, expenses are minimal and efficiency is higher.
Or High Performance Computing (HPC), it is no surprise that its a requirement for some organizations. The cloud is currently storing over 100 Zettabytes (for imaginative purposes, it is 1 billion terabytes)
Cloud and Metaverse
Blockchain-as-a-service is difficult to digest and now, metaverse-as-a-service? Some say it might be a big thing soon.
To sum up all 3 blogs, please leverage the cloud and keep an eye out for all the innovations taking place in this space.
And let us know in the comments if we have missed out on something important. Check out the BizAcuity website if you are looking for cloud services.