In recent times, businesses around the world have been enthusiastically adopting cloud services, with a global expenditure of almost $230 billion on public cloud services last year, a significant jump from the less than $100 billion spent in 2019. The leading players in this cloud revolution—Amazon Web Services (AWS), Google Cloud Platform, and Microsoft Azure—are witnessing remarkable annual revenue growth of over 30%.
What is interesting is that these tech giants are now rolling out advanced artificial intelligence tools, leveraging their substantial resources. This shift hints at the possible decline of traditional on-site company data centers.
Let’s Understand First What is In-House Data Center
An in-house data center refers to a setup where a company stores its servers, networking hardware, and essential IT equipment in a facility owned and operated by the company, often located within its corporate office. This approach was widely adopted for a long time.
The primary advantage of an in-house data center lies in the complete control it provides to companies. They maintain constant access to their data and have the freedom to modify or expand on their terms as needed. With all hardware nearby and directly managed by the business, troubleshooting and operational tasks can be efficiently carried out on-site.
Are Companies Rolling Back?
Despite the shift towards cloud spending surpassing in-house investments in data centers a couple of years ago, companies are still actively putting money into their own hardware and tools. According to Synergy Research Group, a team of analysts, these expenditures crossed the $100 billion mark for the first time last year.
Particularly, many businesses are discovering the advantages of on-premises computing. Notably, a significant portion of the data generated by their increasingly connected factories and products, expected to surpass data from broadcast media or internet services soon will remain on their own premises.
While the public cloud offers convenience and cost savings due to its scale, there are drawbacks. The data centers of major cloud providers are frequently located far from their customers' data sources. Moving this data to where it's processed, sometimes halfway around the world, and then sending it back takes time. While this is not always crucial, as not all business data requires millisecond precision, there are instances where timing is critical.
What Technology Global Companies Are Adopting?
Manufacturers are creating "digital twins" of their factories for better efficiency and problem detection. They analyze critical data in real-time, often facing challenges like data transfer inconsistencies in the public cloud. To address this, some companies maintain their own data centers for essential tasks while utilizing hyperscalers for less time-sensitive information.
Industrial giants like Volkswagen, Caterpillar, and Fanuc follow this approach.
Businesses can either build their own data centers or rent server space from specialists. Factors like rising costs, construction delays, and the increasing demand for AI-capable servers impact these decisions. Hyperscalers are expanding to new locations to reduce latency, and they're also providing prefabricated data centers. Despite the cloud's appeal, many large firms prefer a dual approach, maintaining control over critical data.