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VMblog Expert Interview: Simon Crosby Talks Continuous Intelligence and Swim Continuum 4.0

interview swim simon crosby 

Applications that can analyze, learn and predict on-the-fly belong in an exciting category, called "continuous intelligence".  To find out what's happening and hear what makes continuous intelligence so powerful, VMblog recently caught up with Simon Crosby, CTO of Swim to learn more about Version 4.0 of their product Swim Continuum, that lets businesses focus on insights and applications rather than infrastructure and integration.

VMblog:  The last time we spoke with you was in March, and now you're announcing Swim Continuum 4.0.  Could you tell us a bit about the vision for the product and how it streamlines data analysis?

Simon Crosby:  Sure. Today, continuous streams of events from "always on" infrastructure, applications and "things" hold the clues organizations need to achieve a competitive advantage, but most fail to find them in time. And, it's not getting easier: There are a billion mobile devices in our hands with over two million more connecting every hour. Networks are flooded with streaming data. Most is only useful for a short time, but the streams never stop. So big data architectures with a "store then analyze" approach don't work well.

We developed Continuum to bridge this gap. Continuum is a continuous intelligence platform that makes it easy for developers to create applications that continuously analyze, learn and predict from streaming data on-the-fly with an "analyze, react - and then store" architecture. As a result, with Continuum, insights are continually available - enabling always-on situational awareness and real -time responses.

The Swim Continuum architecture reduces data volumes, delivers continuous analysis and predictions, while offering an application speedup of over 95% using less than 10% of the infrastructure typically used by traditional big data architectures.

VMblog:  Continuous intelligence is not a term we hear a lot of talk about in the industry.  Can you explain more about it and how the concept is different than other technologies in the market?

Crosby:  Continuous Intelligence is an evolution of the traditional "store-analyze-act" process used in legacy data analytics architecture where raw batch data is stored for long periods of time in centralized locations. Streaming analytics changed this process to an extent, expanding the number of data sources but not necessarily changing the way data is analyzed. Continuous intelligence instead uses a different paradigm for deriving value from streaming data, analyzing contextual information close to the edge and only storing what's useful.

As a result, applications that deliver continuous intelligence are able to always have an answer from the latest data, continuously adapting, analyzing, and predicting data patterns without supervision. Unlike traditional data architecture, their ability to analyze information is driven by arriving data, rather than UIs or user queries.

Continuous Intelligence applications statefully analyze each new event in memory, in real-time, to deliver a million-fold performance boost compared to legacy database access. Insights and predictions are analyzed in context, forming a real-time data stream with historical references and well-mapped relationships between data sources - such as containment, proximity, or computed relationships. These are critical when deriving deep insights that result from the joint meaning of events over time, where each new event would otherwise require immediate re-evaluation and response.

VMblog:  What industries do you see benefiting the most from Swim Continuum?

Crosby:  A variety of industries can benefit, but the biggest gains come from those that need to rapidly respond to network and infrastructure changes such as telecom, smart city, manufacturing and energy - or any organization that operates at large scale. Developer teams using Continuous Intelligence to augment both enterprise and consumer applications can respond to network-wide events like outages in seconds, rather than hours, and easily predict data patterns and trends.

Here are some examples -

Industrial Automation: Continuous intelligence applications can help predict equipment failures, detect problems, optimize supply chains, manage inventory, and customize production.

Telecom: These deployments typically revolve around network management and operations, where Continuous Intelligence can help dynamically maximize connection quality, accurately assign resources to network slices, identify faults, deliver quality of service guarantees, ensure privacy, and enhance security.

Retail: Continuous Intelligence can deliver immersive in-store environments allowing retailers to offer new customer experiences that can only be achieved with low latency, proximity and personalization. Rapidly analyzing data at the edge can also assist with deployment of new services, such as alternative forms of payment or customizable loyalty programs.

Security and Safety: Continuous Intelligence works particularly well for security and safety applications, where mobile device location of one or more users can give emergency teams new tools to improve response time to emergencies. In these use cases, rapid response to changing environments is critical and understanding complex data can often mean the difference between life and death.

Smart Cities: Continuous Intelligence applications are a gateway to deploying larger smart city technology due to their ability to dynamically predict infrastructure patterns in traffic loads or changing public transit needs. Information from sensors in utility infrastructure, fused with information from mobile devices, can help predict energy demands and control user environments based on personal preferences.

VMblog:  What else can we expect to see from Swim in the coming months?

Crosby:  This year's events, including COVID-19, have shown us that the cycle of continuous disruption is increasing and organizations now - more than ever - need business adaptability in order to survive. The companies we work with want to take advantage of the disruption around them and become proactive at seizing advantages from insights derived on the fly - faster than their competitors can react.

Swim Continuum 4.0 offers a range of contextual analytics capabilities and the single pane of glass management features are the first part of this, but we will continue to focus our R&D efforts on allowing companies to access data at the speed of change. 2020 has proven that change can be unexpected, but not impossible to successfully navigate.


About Simon Crosby

Simon Crosby is CTO at Swim, a continuous intelligence software vendor that focuses on edge-based learning for fast data. He co-founded Bromium in 2010 and now serves as a strategic advisor. Previously, he was the CTO of the Data Center and Cloud Division at Citrix Systems; founder, CTO, and vice president of strategy and corporate development at XenSource; and a principal engineer at Intel, as well as a faculty member at Cambridge University, where he led the research on network performance and control and multimedia operating systems. Simon is an equity partner at DCVC, serves on the board of Cambridge in America, and is an investor in and advisor to numerous startups. He’s the author of 35 research papers and patents on a number of data center and networking topics, including security, network and server virtualization, and resource optimization and performance. He holds a PhD in computer science from the University of Cambridge, an MSc from the University of Stellenbosch, South Africa, and a BSc (with honors) in computer science and mathematics from the University of Cape Town, South Africa.

Published Wednesday, October 07, 2020 12:03 PM by David Marshall
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