The global pandemic of 2020 permanently changed our working dynamics. What is easily missed is how much the workplace has changed too. Whether and how much work will return to the workplace (versus work from home) is a matter for a different blog. Here, we want to talk about how the workplace has changed forever: especially the distributed enterprise.
To be fair, the distributed enterprise is not a new concept at all. From an IT/networking perspective, distributed enterprises always moved away from a centralized IT infrastructure to connected islands to maximize convenience, networking and efficiency, faster access, and localized control.
In a borderless economy, where businesses fiercely compete for resources and market share, it is fair to expect re-architecting systems and networks to maximize customer benefits and increase employee flexibility.
How will you make the Distributed Enterprise future-ready?
Here are our top 5 tech picks:
Computing is moving to an Edge near you!
Powered by a significant increase in computing power and ubiquitous bandwidth, suddenly, it is possible to move the computing power to where it needs to be, rather than where it always was. Be it in a user’s hands, PoS (Point of Sale) at a retail counter, manufacturing assembly line, or CSP (cellular service provider), the edge has moved closest to the point where it needs to be. This comes with advantages such as faster response times, localized approvals saving a round trip to the central server, increased privacy, security, and reduced cloud costs.
Daihen, a Japanese manufacturer of industrial electronics equipment, realized that their Osaka plant could not handle data from dozens of sensors. The data was being processed remotely by a cloud server, and response time was slow. The solution came in the form of an Intelligent Edge solution from FogHorn that makes complex machine learning modules run on highly constrained devices. The results were almost immediate: improved speed, higher accuracy, drop-in defect count, all of which encouraged them to increase investment in the Edge in the following year.
The Cloud is going hybrid
While the transition from an on-premises server to the cloud has been a work in progress, the cloud itself has metamorphosed entirely. The distributed enterprise can now have a mix of premise, public and private cloud, as required based on business needs.
The enterprise must be careful not to get locked into a hyper-scaler vendor’s vision of the future but keep options open to realize their own. Since many of these paths are evolving, the enterprise needs to engage deeply and tread carefully while committing to future road maps.
The CSP (cellular service provider) is also evolving and is now a major cloud provider with advanced capabilities in Service Edge and SD-WAN (software-defined Wide Area Network). CSPs have blurred the line between enterprise and carrier cloud with their offerings. With upcoming 5G rollouts, massive IoT networks, mmWave, and network slicing requirements, their cloud and edge capabilities will be of an entirely different scale. Enterprises will need to understand how to best harness offerings from each vendor without compromising their requirements.
Enterprise software also has disaggregated from a monolithic form split into microservices (via containers) where code, debugger, utilities, and algorithms may be contained within the container and control routed appropriately to the parent code block as required. Containers make decoupling of applications convenient by abstracting them from the runtime environment. This way, they are deployed agnostic to the target environment. These smaller services can be highly efficient and lend themselves to high scalability, but not without loading DevOps teams with the additional pressure of housekeeping.
When Ducati, a global automotive giant, undertook a data center modernization project, they expected gains, but that was not how it turned out. The hybrid cloud dramatically changed their perspective of what is possible. The data awareness, speed, and minimal footprint across departments brought a new level of productivity that was not planned.
Currently, an emerging trend but likely will become mainstream as many of the required elements are already falling in place. Hyper Automation refers to the coming together of systems, processes, software, and networking to automate most known processes with zero-touch human intervention resulting in ‘robotic process automation’ sequences.
This advanced state of automation will require stable AI, ML modules, and integrating IT and OT (operation technologies in the IIoT world), where machines will make decisions and keep routine systems running. Real-time monitoring and analytics are logged for a supervisor to check and intervene if necessary.
Understanding documents through OCR (optical character recognition), emails using NLP (natural language processing), and enhancing automation using AI / ML data flows are increasingly common. Banking and healthcare have seen successful deployments of OCR and NLP.
Data will soon be everywhere, but how about Security?
Security will become such an essential parameter for business success that the CISO (Chief Information Security Officer) might well, if not already, be the most important executive in the economy. With billions of IoT devices from airplane tires to connected cars and heating systems at offices and production lines going online, the opportunities for a security breach just went up a notch. And every incident will only dilute human trust delaying further progress and slowing down growth.
With geopolitical scenarios going worse, cyber warfare being a reality, there is no telling when some of these will start impacting enterprise system security. This is an ongoing new reality – almost as real as the pandemic.
Quantum computing, the emerging innovation in high-speed computing, will be a threat too. It is believed that current-day data breaches are being tapped and data being stored for analysis and targeting after quantum computing power becomes available (because current computing could take years to decipher this data). Some cyber experts believe the advanced planning and methods of cybercriminals are years ahead of the capabilities of corporate IT security teams. And that can be a cause for worry.
When Gartner coined the term AIOps, it meant Artificial Intelligence for IT Operations (or Algorithmic IT operations). They referred to a “method of combining big data and machine learning to automate IT operations and processes, including event correlation, anomaly detection, and causality determination.”
AIOps is a set of methods or practices that makes rapid data processing possible for vast volumes of data, which then feed into an ML engine to predict issues. AIOps will be very much a requirement for the DevOps teams. They try catching up with data and problems across hybrid environments to support agile processes in ever-changing platforms and networked silos.
US infrastructure provider Ensono provides infrastructure support to mission-critical processes of many top enterprises. As its volumes started growing, it became important for Ensono to invest in AIops to ensure its ability to monitor client hardware and software would not be compromised. Investing in TrueSight AIops helped Ensono decrease its trouble ticket numbers from over 10,000 to a few hundred per month. This is the power of AI ops.
In conclusion, remember no one has a crystal ball into the future. But going by current technology trends in the distributed enterprise, some things are clear: growth, chaos, and churn are predicted. It helps to have a trusted consulting team of experts on your side to learn from, seek advice from, and leverage from experience.
At Trigent, our domain experts have delivered solutions, charted digitization route maps, and provided distributed enterprise workflow design and architecture for future growth to global leaders in every sector.