We often hear how different IT companies look at the whole world of Analytics and Computing through their narrowed lenses of anxiety and stifled opportunities. In the fast changing world of Cloud Computing for IT and ITES, we hear lot of noise related to how the traditional Cloud set ups would vanish from the face of the Earth—as if they were dinosaurs! New IT designers and engineers discuss Cloud Computing topics with a sense of fear.
Because, they realize that Edge Computing is just round the corner and it’s time to buck up to the hyper-personalization of the Cloud ecosystem. Edge and Cloud Analytics are discussed as if they were mutually exclusive technologies. Well, let me clarify at the very beginning.
Both, Cloud and Edge Computing are part of the same ecosystem that we are working in. For professionals admitting into Analytics Training Institute, it’s a matter of hard fact learning. You are going to learn about management of both technologies anyway, buddy!
Sounds unrealistic! Not anymore.
If you plan to dive into the Edge of Cloud Analytics and Computing, here are some contriving facts and “assumptions” that you must keep a tab on.
What is Edge Computing and How it Equates in Cloud Infrastructure?
Edge Computing, as the name suggest, is dealt from the ‘edge’ of any networking framework. It is a scientific specialization in Networking and IT Management where data is processed at the edge, instead of happening in a centralized data processing warehouse.
With edge computing coming into force, most Cloud Analytics vendors are moving to distributed open network IT architecture for a decentralized management. This switch to Edge is driving the growth of Mobile Commerce, and Internet of Things, as it makes light of every data processing unit that were traditionally deployed to manage Cloud services in the past.
If you are to distinguish between Cloud and Edge Technology today, you will have to think about school grades. If Cloud Analytics is 4th grade, Edge is the graduation. All the mid-level promotion of Cloud Computing eventually qualify themselves to achieve same capabilities as that foreseen in an Edge platform. If you are learning Analytics for Cloud, you should anyway aim to apply it to Edge IoT and IIoT services.
Simply because that’s where big Cloud companies are placing their money on.
According to Cisco’s recent Global Cloud Index report, Cloud traffic will grow four times over by 2020, putting enormous pressure on existing Cloud infrastructure, and raising operational costs. Add to it the cost of risk analytics, security management and data processing. Edge Computing not only allows for divide and conquer approach for Data Processing, it also allows companies to explore opportunities within low connectivity costs and heightened security practices.
Where are we heading in Cloud?
As leading Cloud companies begin to explore more realistic solutions within their marketplaces and inside their organizations, we expect IT professionals will move to the ‘Edge’ of technology advancement. If few months back it was AI and Data Science taking your breath away, it’s going to be Cloud AI DevOps and Edge Computing Analytics now.
Leading players like Cisco, HP, Dell EMC, Google Cloud, AWS and IBM are already discussing and investing into Edge Computing development. What Cloud lacks in agility and security, Edge Computing fills that gap with sheer scale of flexibility, agility, cost effectiveness and power of viability into the future.
The most common applications for Edge would be IoT, no doubt! But, enterprise mobility platforms and digital transformation enablers can also look at Edge to move out of centralized Cloud repository.
For businesses working with Big Data, Edge may not be a great option. But, add an element of filtered analytic and intelligence powered by AI and ML models, you have a killer infrastructure that can manage any activity in the IT and IoT industry, all within itself.
By 2022, we will find most companies switching to best of two worlds. While storage concerns would continue to haunt these big data companies, most will prefer moving to a more secured collocated IT infrastructures that save the logistical nightmare of working with data warehouses.
Ask any Cloud expert, and s/he is most likely to tell you that it’s a tempestuous future to predict. With new frameworks evolving every day around Edge, Micro Data Centers, and Machine Learning algorithms, only one thing will remain constant here— Mobility Talent. A company that can hire best talent for best roles will survive the onslaught of coming of age within technologies. Are you a mobility talent?