By Alberto Da Anunciacao, Aptum
This year is trending to be significant for Edge Computing, as its popularity grows due to the vast computing demands of cloud users and massive data explosion through IoT. More businesses are using edge computing as an optimal solution to streamline IoT traffic and facilitate real-time, local data analysis. A Forrester Research report found that 57 percent of mobility decision makers surveyed stated they have edge computing on their roadmap for the next 12 months. The same annual predictions report also estimates the edge cloud service market will grow by at least 50 percent in 2020.
As organizations evolve and expand the size of their businesses, the need for on-site computing that supports low maintenance and high-speed capabilities grows as well, driving the demand for edge computing. As a result, edge computing is emerging as the latest solution for challenges businesses may face relating to scalability. The industries leading in this trend include healthcare, manufacturing, and retail. According to Gartner, by 2025 75 percent of enterprise-generated data will be created and processed outside of a traditional centralized data center or cloud, as the desire to process data faster to increase productivity continues to be a key KPI for many sectors.
In addition, companies are migrating to a hybrid IT approach to increase the speed of interaction between high volumes of data; time is saved, and decisions are made at a quicker pace.
As with every business decision, each technology solution has its advantages and disadvantages to factor in evaluating the way forward. But, with the explosive growth of IoT devices, this new generation of cellular technology is unable to deliver on its promises without ultra-low latency and high levels of connectivity – making edge computing a best practice. And, as a result, edge data centers are expected to become more commonplace. In fact, according to Global Market Insights, the edge data center market is expected to reach $16 billion by 2025.
Edge Computing, Explained
Stemming from the increased usage and reliance on interconnected devices, edge computing provides a solution for applications that require low latency, real-time computing power. Edge solutions rely on computing that is done at or near the source of the data, allowing for lower complexity in data communication by minimizing the length that data needs to travel. In turn, this results in less data being transmitted back to a central data center, increasing security, and reducing the amount of data that is at risk at a given time.
Edge computing considers the challenges incurred for clients and employees during a transition into a fully cloud-based storage system. Integrating an edge computing-based system allows for little downtime while contributing to resiliency not initially found in applications.
Artificial intelligence (AI) also plays a large role in edge solutions. AI found at the edge allows for critical, time-sensitive decisions to be made faster due to the real-time processing of the data within the device. AI algorithms based on the data generated on-site reduce the amount of network traffic flowing back to the cloud, cutting response times down to less than a few milliseconds. AI has given systems the power to use the data they receive where it is obtained, drastically reducing the need for storage.
Key Benefits Of Edge Computing
Various use cases and advantages to adopting an edge-based computing system are beginning to take shape as interconnectivity becomes top-of-mind for many organizations. Some of the benefits of integrating edge computing into a company’s system include boosting network performance, increasing speeds for end users, and providing a solution to scalability issues.
Edge solutions do not rely on network connectivity or human problem-solving to fix an issue, increasing the system’s independence and appeal to those who decide to move toward an edge data infrastructure. Compared to data stored on cloud architecture, local intelligence is a key benefit to edge computing. Consequently, data is distributed within the system redundantly, allowing for the infrastructure to self-heal and continue running applications as normal.
Issues surrounding scalability are mitigated through integrating an edge computing system. Traditionally, organizations have relied on purpose-built data centers and the manual management of systems. This conventional approach leads to increased difficulty in managing different locations as companies grow. Edge computing introduces the needed automation for many different locations of an organization to run smoothly through integrating a sealed system that automatically checks error rates, internal drive temperatures, and essential factors of the like.
How Edge Mitigates Security Concerns
As security breaches continue to escalate, organizations are scrambling to find easily adoptable solutions to avoid these threats, which can be extremely costly and time consuming for companies.
A key security risk businesses face is increased exposure to attacks resulting from the manipulation of devices within an edge network. Furthermore, with faster networking technologies becoming the foundation of many IT applications, the integrity and availability of those networks will become a major security challenge.
However, an edge solution’s infrastructure can reduce the amount of data exposed to cyberattacks. Edge computing can localize any data breaches to just one point on the network with the protection of data on local drives before being moved back to the microdata center. For example, affected areas resulting from a cyber breach can effectively isolate without shutting the whole network down. Edge computing allows organizations to avoid vulnerability through a single weak point.
Challenges Of Adopting Edge Computing
As each organization faces its challenges, customization is required to fulfill their specific needs to adopt edge solutions, because there is no standardized, one-size-fits-all approach. The use of edge computing requires a shift in network bandwidth, in turn creating a challenge for businesses in balancing more bandwidth across the network when moving IoT devices from the core to the periphery.
While these systems now exist on local infrastructure, they must still have the ability to be managed centrally to ensure all devices run smoothly. Traditional approaches cannot meet the autonomous operations that edge solutions demand.
Managing edge solutions is the biggest challenge for organizations despite the increased benefits they see when having a centrally focused system of local infrastructure. Shifting to a centrally managed and deployed system encourages businesses to escalate their management concerns to a selected partner with skills and expertise to supervise the edge networks. This partner supervision can, in turn, deliver the advantages of being closer to the edge and support long term business objectives.
The fact is digital business infrastructure is changing at a rapid pace. Current IT systems are struggling to meet the demands of growing IoT device popularity, falling behind in trying to generate localized computing power, along with continually finding limitations within centralized clouds or data centers. The rise of the next generation of network connectivity is prompting a boost in volume and speed of data, increasing inefficiencies when attempting to stream large quantities of data to a data center or cloud for processing. Some advantages to adopting edge computing will be more evident than others, but the benefits of edge solutions could be game-changing through its potential impact on organizational interconnectivity and efficiency.
About The Author
As Chief Infrastructure Officer (CIO), Alberto is responsible for building out and overseeing Aptum’s global IT infrastructure and managed IT capabilities, while supporting Aptum’s customers in 77 countries. As a member of Aptum’s executive leadership team, he plays an important role in establishing and executing Aptum’s corporate strategy. Alberto is a seasoned IT industry executive with more than 20 years of experience in the data center, telecommunications, and IT industries.