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Best Practices
Edge calculation is one of the top areas for IT investment,
especially in light of enterprise digital transformation initiatives such as
the Internet of Things (IoT). Computing technologies that ensure the timely
delivery and analysis of data and resources to people and objects are
collectively referred to as edge computing. Edge computing is about moving
computation to where data is generated, and therefore helps to shorten the
“time to time”, which is the insight gained.
At first glance, edge computing looks very homogeneous and
includes all activities that take place outside the "core", which may
be the location of the IT infrastructure (information technology) in the
enterprise. In fact, edge computing is a combination of multiple layers of
assets organized in a use case and workload-oriented manner. The “smart” edge
is the critical link between the core and the endpoints, providing distributed
computing, data persistence and network aggregation, and serving as
intermediate analytics for the collected data. For OT (Operational
Technologies) use cases, the control and execution equipment is located at the
edge, and for CT (Communications Technologies) use cases, it can even interface
with communication equipment such as auxiliary and relay equipment. The lack of
industry standards and architectural approaches to edge computing
infrastructure means that most edge device deployments today are highly
customizable in nature (although the introduction of architectural overlay
concepts such as fog computing may eventually lead to ratification of the proposed
standards.)
CIOs and other CIOs must prepare their organization and key
stakeholders for the steps required to successfully deploy and manage an edge
computing infrastructure. Companies that regard edge computing as a long-term
investment generally fall into two categories:
Companies that adopted Edge Computing from the start. They
have invested in bespoke or semi-custom approaches and are confidently moving
towards realizing the business benefits of moving compute closer to data. Many
early adopters of the Internet of Things fall into this category or
Companies that are still not ready to use Edge Computing.
They assess how they can deploy edge computing in a production environment,
what changes need to be made to their IT processes, and how they can generate
long-term business benefits. These companies often take an approach that
includes industry-standard infrastructure.
(Note: This categorization does not include
"traditional" Edge deployments such as remote and branch offices.
Instead, it examines Edge deployments for new use cases such as the Internet of
Things, as well as telecoms, oil, energy, and retailers. ..)
For companies that fall into the second area, I recommend
the following areas of due diligence - areas that will dramatically improve the
value that organizations get from their edge computing infrastructure.
Abandoning any of these practices can result in the loss of money for an
incomplete and sub-optimal solution or in the loss of income and additional
costs to overcome crises arising from an incomplete or poorly implemented
infrastructure.
Asset and application management requires asset sprawl
control and cataloged deployment of IT, OT and CT management applications.
Deploy a software-defined infrastructure solution that sees Edge as the cloud
Data management and governance includes lifecycle management
of data created or collected on Edge. Ephemeral data must be analyzed and then
discarded, and persistent data must be protected. Organizations must define a
Core-Edge-Endpoint data management paradigm that manages data according to its
value.
Infrastructure security requires the management of devices,
users, applications, and data security. Requires edge devices to be managed in
accordance with corporate governance, risk and compliance policies. This is
where organizations can use the multifaceted "always active"