The Hybrid IT Evolution – What’s Next?
In the early days of computing, a prominent CEO, Thomas J. Watson at IBM, said publicly that the world only needs maybe five computers. The evolution couldn’t be more different. IT users have been using multiple platforms for computing for decades—from the abacus and simple code breaking machines, to mainframes, desktops, iPhones, cloud computing and now “edge computing.” Most enterprises today are using all three of the top major public cloud platforms (AWS, MS and Google). For many, a hybrid IT strategy may seem obvious, but managing and being successful at it is another story.
Today, we walk around with more horsepower in our pocket than we ever imagined with some of the most innovative, high performance, dense sensor technology at our fingertips.
Currently…
- 92% of companies have a multi-cloud strategy (Flexera, 2021)
- 80% plan on implementing a hybrid cloud strategy (Flexera, 2021)
- 50% of enterprise workloads are on public cloud (Flexera, 2021)
- Companies use an average of 13 XaaS vendors, growing to 18 by the end of 2022 (Omdia, 2021)
- Network traffic more than doubled since 2018 – 107 EB to 219 EB (Telegraphy Report, 2021)
- Over 4.2 billion people are using the internet—more than half the world’s population—and there are over 1.9 billion websites (Telegraphy Report, 2021)
Hybrid IT or cloud is an evolution from multi-platform or cloud usage. It emphasizes some important themes, like improved coordination of resources, better control, governance and synchronization that result in better optimized usage, better agility and reliability. These attributes contribute to better cost management, less sprawl of resources, more security, and allow companies to use the best technology for the job versus being stuck on a less than optimal platform. Combined with new customer requirements for resiliency and uptime, there’s little room for mistakes while evolving IT.
In December 2020, Andy Jassy, soon to be CEO of Amazon and the leader of AWS, estimated that only 4% of workloads were in the cloud. More applications are being written as cloud-native, virtualized or with containers like Kubernetes. As the customer experience becomes more sensitive and competitive, applications will need service layers or to be edge-enabled. More IoT data sources will require more processing and to be more distributed to meet demands—at the edge and integrated with core and cloud data services.
So, what’s next?
- More Distribution: IDC predicts by 2023, half of all infrastructure deployments will happen at the edge, up from 10% today. Distributed technologies will be augmented with blockchain to help manage SLAs, commitments and security.
- Container Ready: Software containers like Docker and Kubernetes are on the rise in most environments and will become a default choice for cloud-native deployments.
- AI Everywhere: AI and machine learning are easier to implement every day and are being embedded in Software-as-a-Service (SaaS) applications regularly, helping to manage the growing deluge of data.
Hybrid will evolve to meet new demands and having flexibility to implement will be key. Often, just-in-time decisions to deploy new services may make sense for the cloud—fast and easy to deploy. As applications mature, so can the deployment models, offering new choices to better optimize, like scale-out colocation or private cloud. Ultimately, hybrid IT allows for these services and technologies to be used together, held together by strong security and network enabled capabilities.
Look for our upcoming white paper on hybrid architecture and the most important attributes to consider, including:
- Connectivity: Data centers, 5G, clouds, servers, end users, branches, edge, IoT
- Control: Multi-cloud capable, DevOps, management servers, portals
- Observability: Transparency, monitoring, response time, feedback response
- Governance: Application portfolio rationalization, cost management, GRC
- Security (or more broadly, Assurance): Service Resilience, Physical to logical security, privacy, standards, controls, regulatory data, trust