Q&A: Edge computing move services to the point of processing Special Decentralized IoT networks and edge computing can help businesses to tighten data security and to reduce costs by moving services closer to the point of processing. Adi Hirschtein of Iguazio looks at the technology and its application. The company Iguazio is aware of the importance of edge computing when modernizing industries such as telecom or transportation to adapt to new IoT technologies. It has demonstrated how moving services closer to the point of processing – to the edge – can be highly advantageous when considering data security and connectivity costs. Iguazio has assisted multiple companies in moving closer to the edge in order to take on and master the challenges presented by the growing IoT sector. To understand more about edge computing, Digital Journal spoke with Adi Hirschtein, Director of Product at Iguazio. Digital Journal: How important is digital transformation becoming for businesses?Adi Hirschtein: Around the world, businesses are turning to data to improve operational efficiency and provide more personalized customer experiences. Extracting business value from data in real-time is critical for companies across most industries; whether it be telecoms, finance, mobility, or any other industry working with data. By undergoing this digital transformation, companies empower themselves to remain competitive and relevant in their markets. In practice, that means streamlining data from multiple sources to a singular place, enriching data with external sources, coupling it with historical data and using AI to get new business insights. The result? Rapid delivery of new services and optimization of existing business processes. DJ: What part does edge computing play in this? Hirschtein: With the rise of IoT, intelligent edge computing is becoming a priority. An effective edge computing solution allows companies to move many of its services closer to the point of processing- otherwise known as the edge – which is highly advantageous when considering performance, data security and connectivity costs. Operating certain services at the edge allows enterprises to dramatically accelerate time to insights by processing data closer to its source. This does not mean, that the cloud is going anywhere. If anything, this only stresses the importance of working with hybrid platforms. Companies can then deploy machine learning models and ingest data at the edge for faster and smarter decisions while leveraging high connectivity to public clouds for historical data, elastic computing and edge provisioning and monitoring. Let’s face it, IoT is forcing companies to analyze vast amounts of data in record times to ensure efficient operations. Companies must find ways to eliminate the need to send all their data to the cloud for processing as this will only create vulnerabilities, delays, and high costs. Why not process and analyze time-sensitive data locally to boost response times and ensure security, while sending less costly data to the cloud for processing? At the end of the day, operating at the edge is essential for companies that want, or more importantly need to digitally transform. DJ: How would you define ‘edge computing’? Hirschtein: The best way to understand edge computing is to contrast it to using the cloud. When a company utilizes the cloud (publicly or privately) for processing all its data, it must send every bit of information away from its source – to the cloud itself. This can be risky, especially for industries dependent on time-sensitive data to keep operations running smoothly. Edge computing removes the step of sending all data to the cloud and processes more essential information closer to its source, allowing for faster reaction times. As mentioned before, this does not mean that edge computing replaces the cloud, but instead, offers an effective alternative for certain data points. The Intelligent edge takes it a step further by enabling analytics and AI for a complete mini-cloud near the sources of data. DJ: Which industries will edge computing have the greatest impact upon? Hirschtein: Edge computing is already impacting multiple industries, not just one. At Iguazio we see this from our experience working with businesses utilizing time-sensitive data to make accurate predictions. In industrial IoT, factories are processing much of their data at the edge to enable immediate response times in the case of equipment failure and to ensure employee safety. Equipment failure can also be predicted with edge computing, heading off accidents at the pass. Telecommunication companies predict network health to eliminate outages. This is achieved by processing high message throughput from multiple streams correlated with historical data at the edge. For the physical security industry, local processing can quickly and effectively understand the images that security cameras capture, which is crucial in time sensitive use cases where decisions must be made instantaneously to prevent or stop criminal activity as soon as it occurs. DJ: How is data security impacted? Hirschtein: By keeping the most time-sensitive data right at its source and not sending it to the cloud for processing, a company is essentially getting rid of any intermediary that could prevent a secure data transmission. Of course, this method does not entirely remove the need to secure connected devices, but it is a step in a secure direction for a company’s most essential data points. Since industrial devices can be located in sensitive environments, controlling vital systems or sending private data, companies must still apply fine-grained policies to control access, service levels, multitenancy and data lifecycles. DJ: Can businesses cost be lowered? Hirschtein: Business costs are significantly reduced when utilizing edge analytics. Processing data at the edge, or even prefiltering prior to sending it to the cloud, can cut bandwidth costs dramatically for an enterprise. Finding an effective solution that specializes in edge computing can make a major difference in a company’s operational budget. Iguazio’s platform, for instance, is designed to enable simultaneous access for several types of data in real-time, thereby reducing cloud costs with data reduction and accelerating data processing. DJ: What services does Iguazio provide? Hirschtein: Iguazio simplifies the development and deployment of high-volume, real-time, intelligent applications by ingesting, enriching and analyzing multivariate data in one solution. Iguazio’s fully managed platform combines a high performance scalable database and open source tools for AI and serverless. Iguazio runs anywhere; on-premises, at the edge, in public clouds or in hybrid environments. DJ: Which types of companies have you worked with? Hirschtein: Iguazio’s key audiences span multiple, data heavy industries seeking increased efficiency. We use data to assist telcos to detect and prevent network outages, combine streaming feeds to assist major stock exchanges in leveraging their data, and offer real-time heatmaps so smart mobility companies can manage supply and demand. We are in productive partnerships with industry leaders including Microsoft, Google and Equinix and have successfully deployed our solution across a broad range of verticals.