In a recent session at VMware Explore Las Vegas, a trio of industry insiders shared valuable insights into the rapidly evolving edge market. Modern enterprises need an edge data strategy so they can make real-time decisions, react swiftly to changing situations, and give their consumers a better user experience by processing data closer to the source. But how do you choose the best tools for that job? The session, titled “Edging Ahead Data-Driven Decisions for Edge AI with RabbitMQ and OpenVINO,” proposed using those tools with VMware Edge Compute Stack™ to unlock customer and business value using data at the edge.
To delve deeper into these insights and understand the practical applications of these tools, watch the full session video.
The future of data processing is happening at the edge
The rapidly growing edge market is projected by Gartner to soar to $206 billion by year’s end, reaching an astounding $317 billion by the end of 2026. This forecast aligns with the mounting importance placed on emerging applications, AI/ML workloads, and virtualizing operational workloads. All of these fall under the umbrella of edge applications.
It’s worth noting that by 2025, Gartner predicts a significant shift in where enterprises are running data analysis and inferencing. They forecast that 55% of all data analysis by deep neural networks will occur at the point of capture in an edge system.
However, seamless data processing at the edge is not without its challenges. These include limited bandwidth, data silos, and the necessity for common APIs and event standards. To overcome these hurdles, the session proposed a comprehensive solution: Use VMware Edge Compute Stack combined with RabbitMQ as a common data substrate for services to exchange data, and OpenVINO for hardware abstraction and running AI/ML workloads on Intel-based hardware.
Solutions for the challenge: Edge Compute Stack, Tanzu RabbitMQ and OpenVINO
VMware Edge Compute Stack is a notable solution for navigating the challenges of deploying workloads at the edge. It is tailored to low-latency applications, provides GPU passthrough, and facilitates support for VM and container workloads.
At the core of the solution is OpenVINO, an open-source developer toolkit for executing inferencing and optimizing models on Intel platforms. Complementing this is Tanzu RabbitMQ, an efficient and flexible open source solution for capturing, storing, and serving data on the edge. It stands out with support for multiple protocols, languages, and scalability.
In today’s data-intensive era, the significance of a common data platform and secure communication on the edge cannot be overstated. With the advent of powerful tools like RabbitMQ and OpenVINO and the right strategies in place, businesses can unlock new opportunities and harness the power of data in the most efficient way.
