ISG Provider Lens™ Next-Gen Private/Hybrid Cloud - Data Center Services & Solutions - Archetype Report 2020
IT organizations in enterprises are under immense pressure to deliver secure applications along with faster time to market to stay ahead in the competition by leveraging new-age technologies. ISG has observed more enterprises embracing managed services providers for transformation and managing day-to-day infrastructure operations. This has allowed them to gain significant cost savings and focus on growing their core business. In addition, the shrinking IT budget and high costs incurred during a downtime have raised concerns among CIOs and CTOs, forcing enterprises to leverage managed services providers. These providers play a key role here as they have extensive experience in infrastructure management and are well equipped to support enterprises in their digital journey. They understand the requirement of the enterprise and define a problem statement so that the outputs can be quantified and measured. The deployments are efficient and quick due to the providers’ vast experience accumulated over the years, capabilities in leveraging new technologies, and their large workforce.
With the cloud infrastructure getting commoditized, enterprises have been increasingly adopting cloud technology into their digital journey, thus driving growth in the cloud sector. However, in the current situation, CTOs and CIOs are seeking rapid cloud adoption and are focused on moving severe to critical workloads to a hybrid cloud environment as quickly as possible. Enterprises now want to equip their mobile workforce with a highly secure work-from-home environment. Also, the implementation of lockdown measures across regions has caused a dearth of on-site IT personnel support. Enterprises have thus moved on to leveraging cloud capabilities to check, maintain and monitor their server and storage installations in data centers.
This year, ISG has observed more solutions leveraging artificial intelligence (AI)-based cognitive capabilities and/or machine learning (ML) tools and services to provide highquality outcomes, speed up service delivery, increase IT efficiency and deliver a superior user experience. Providers have developed tools that take data from various sources to predict downtime and implement self-healing measures to prevent such situations. AI for IT operations (AIOps) can monitor various elements of the entire hybrid environment and provide predictive analytics for incident management to aggregate events, reduce noise, auto-correlate and identify the probable root cause using ML technology. Also, running AI/ML-based applications requires significant processing capabilities and powerful servers, which were in limited quantity or considerably expensive until now. Currently, efficient infrastructures with specialized high computing equipment are being used to run AI-based cognitive capabilities and/or ML tools.
Over the past year, the hyperconverged infrastructure (HCI) industry has seen a major transition. Enterprises have realized that moving to a high-density environment allows them to improve cabinet space utilization by more than 100 percent. This can lead to a four-times increase in the processing performance and significant cost savings. The HCI industry has changed the integration of hardware and software technologies, with both software and hardware vendors working together to develop better HCI solutions. Hardware vendors are focused on improving their offerings to be more compliant with the standards of software-defined data centers (SDDCs), while virtualization vendors are working with their hardware counterparts to improve their software products and make them a best fit for their hardware. An HCI solution was initially used for multiple purposes and was deployed to respond to a dynamic change in infrastructure requirements. Nowadays, vendors position HCI as a dedicated, single purpose solution. IT managers are keen on the idea of having a single appliance that can manage this scale, streamline management, and deliver predictive and reliable performance. HCI solutions are also endorsed for SAP HANA as a dedicated appliance as clustering enables high availability and performance for a core business application. It is also recommended for highperformance compute requirements where clusters are dedicated to AI appliances. Clients can deploy high-performing TensorFlow appliances to run ML applications. Other use cases are for big data analytics and storage. However, due to the availability of other costeffective solutions in the market, they are not exclusively used for analytics and storage purposes.
Over the past couple of years, there has been an explosive growth of data generation. Data lakes are becoming data oceans. These large volumes of data have to be stored and managed in a secure environment, which posed a major challenge for enterprises. Also, data transfer in petabytes is expensive and should be fast. Providers have been addressing these challenges by developing expertise in managing large amounts of data efficiently. This has spurred growth in the managed data center services space. As data sets grow bigger, providers are leveraging various methods to overcome issues involving concentration and distribution of data. Some of these include data thinning, use of new technologies around networking for faster data transfer, and bringing data sources closer to applications instead of centralizing them and then sorting and moving them into the destination system.
The data center industry is facing a major shortage of talent. Employees with more than 20 years of experience are either moving toward retirement or management positions, while a small percentage of the workforce has less than five years of experience. It has been difficult to find qualified candidates in this domain. In addition, few women opt to join the data center business as they comprise a fraction of the entire workforce in the industry. The industry should focus on hiring and train new candidates to replace the highly experienced personnel who are moving out.