By: Jeffrey Ricker, co-founder and CEO of Hivecell
Now more than ever, audio and visual security systems create massive amounts of raw data every second. As companies embrace technologies such as the Internet of Things (IoT) and machine learning, these systems are pushing hours upon hours’ worth of data―most of which provide little or no value―to the cloud for analysis, wasting bandwidth, overspending, and putting sensitive data at risk.
Recent breakthroughs in technology designed for cloud infrastructures, such as containerization (Kubernetes), high availability, and continuous integration/deployment, have created a better cloud environment. However, the cloud is still not a practical option alone due to its complicated nature and costliness, which is why more companies are looking to edge computing to scale infinitely and save massive amounts of resources in their management and processing of big data.
What is edge computing
Edge computing is a new type of compute power that exists between smart technologies (think Internet-connected appliances, cameras, sensors, etc.) and the cloud. This solution allows companies using IoT and machine learning to harness the power of business relevant data, cut costs and manage their data remotely. Each enterprise must find the balance between edge and cloud computing that meets its unique circumstances.
Why the cloud isn’t viable on its own
The amount of bandwidth required for security software is too large for the cloud. Data produced at one location under security surveillance can often be so large that moving it to the cloud could take several days. And this data is often going unused and providing little or no value. Historically, only one percent of data is actually used for decision making.
Moving massive amounts of data across the Internet and storing it in the cloud is also expensive. Companies relying on the cloud are spending drastic amounts of money to store raw data that provides no value to the business. Why would you pay to transfer raw video from hundreds or thousands of camera feeds when you could simply use edge computing to identify events (such as unsafe operations or inventory changes) and push just those to the cloud instead?
Additionally, adopting edge solution technology, such as Hivecell, is easy to install, remotely managed and scalable for future expansions. For contrast, deploying and maintaining Kubernetes on-premise is a harrowing process that takes at least half a day for an expert to install – now imagine that process at 2,000 locations.
Finally, there are a host of security risks that come with moving data to the cloud. Some data is considered too sensitive to move across the internet, even if encrypted and in a virtual private cloud. In this case, relying on the cloud is not a viable option. For larger companies, there may be issues on certain sensitive information crossing state and country lines.
Companies need compute power for advanced analytics at the source of the data―or as close to it as possible―and the answer is to adopt an edge computing solution. To be clear, edge computing does not replace cloud computing; it does not even compete against cloud computing. Edge computing complements it.
What edge computing can provide
Customers can efficiently manage thousands of remote locations without the use of a huge IT team and send business relevant data to the cloud at a fraction of the cost of using the cloud alone.
For many organizations, the cloud is already full of other AI and Machine Learning applications that are relevant to other pieces of the business. Organizations need a solution that’s outside the data closet at the true edge that can be security-centric. And they need the ability to provision, monitor and update complex distributed frameworks (such as Kubernetes, Kafka and VMware) remotely.
Additionally, servers can run outside the data closet and be secured in much smaller spaces. By adopting an edge solution to analyze mass amounts of data, only the business-relevant metrics will be pushed to the cloud, saving time and providing more valuable insights.
Cloud computing cannot meet every computing need, but edge computing is now a real and pressing requirement for many enterprises allowing them to lower costs, increase reliability, and keep pace with technology.
Hivecell is a complete edge solution that offers the ease of the cloud at 50 percent less cost and is extremely small, energy-efficient, and scalable.
Jeffrey Ricker is the Co-Founder and CEO of Hivecell, the Edge-as-a-Service company. Jeffrey is an experienced technology leader, a hands-on senior software developer, and an entrepreneur. He has a 30-year career working with the financial industry, start-up companies, and the Defense Department.