Simon Crosby
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Articles by Simon Crosby
Analyze Then Store? You’re Kidding Right?
If I bumped into Zuck’s avatar at the virtual water cooler I’d quit on the spot. But the recent name change at Facebook, Microsoft’s enthusiasm, Nvidia’s Omniverse and broader industry support mean we should at least peel back the lid on the “metaverse” to see what the fuss is about. Spoiler alert: It’s not VR. Collaboration with your colleagues’ avatars may yet become a thing, but you’d be right to point to Microsoft’s Hololens or Meta’s AR glasses and say “We’ve seen this (train wreck) before”.
Using Swim with Apache Kafka
by Simon Crosby, on May 11, 2021 9:15:00 AM (Tune in to my presentation to the Apache Kafka EU Summit on Wednesday 12 May, to learn how to build a Swim app in 10 minutes!) Organizations want to derive continuous intelligence from their data streams for competitive advantage. Streams of events from their “always on” infrastructure, products and applications hold the clues they need, but most fail to find them in time.
Coherence vs Consistency for Continuous Intelligence Applications
by Simon Crosby, on May 6, 2021 9:30:00 AM Applications that deliver continuous intelligence from streaming data must analyze a boundless stream of updates that can’t be stored or delayed, even during a network partition. The “fire and forget” nature of real-world events means updates could be lost, causing apps to fall out of sync and making automation risky.
Comparing Swim & Akka
by Simon Crosby, on May 4, 2021 8:00:00 AM Recently several developers have asked me to compare Swim (OSS SwimOS) with other well known Actor Systems and especially Akka, which is a widely used Actor based language.
Continuous Intelligence Fills in Where Smarter Databases Can’t Help
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.
Continuous Intelligence for 4G/5G Mobile Edge Computing
Combining compute, connectivity, and low latency communication to endpoints lets MEC-hosted applications analyze streaming data on-the-fly and respond before storing it. Next-gen mobile networks can deliver powerful services that take advantage of low-latency, high bandwidth, and edge computing. This article describes a software architecture for continuous intelligence applications that operate in 4G/5G Mobile Edge Computing (MEC) environments.
Continuous Intelligence Is The Way To Smaller Data
Simon is CTO at SWIM.AI. He also co-founded Bromium, was CTO at Citrix, Founder & CTO of XenSource, and a Principal Engineer at Intel. Getty Continuous intelligence is becoming accepted as the preferred way to deal with never-ending streams of big data because the "store then analyze" approach is expensive in storage, bandwidth and processing, and it forces applications to be batch-oriented.
Thinking Beyond the Database: Continuous Intelligence
Thinking Beyond the Database: Continuous Intelligence The speed and volume of modern data demands continuous intelligence to create business impact. By Simon Crosby August 18, 2020 The use of databases is deeply embedded in our enterprise application architectures. There are scores of database types, open source projects, and massively scalable cloud data lakes and databases.
The Journey to Continuous Intelligence
by Simon Crosby, on Jul 15, 2020 7:15:00 AM A Technical Blog Series for Data Architects This multi-part blog series is intended for data architects and anyone else interested in learning how to design modern real-time data analytics solutions.
Continuous Intelligence - Apps That Always Have The Answer
Continuous prediction of traffic flow in major US cities via Cubic TidalWave. Source: traffic.swim.ai Continuous Intelligence — Apps That Always Have The Answer Enterprises have to adapt on a dime to stay competitive. But they are overwhelmed by streams of live data from products, assets, partners, people, cloud services, apps & IT infrastructure. Over 2M smart devices are connected per hour, and there are a billion mobile devices in our hands. Networks are flooded with streaming data.
Isolation And The Unknown
Photo: Getty You are probably working in isolation due to the novel coronavirus, against which we have no countermeasures. Though its DNA was sequenced early and vaccines are in development, they will likely take months to test and distribute — a long time relative to the rate at which the virus is transmitted. It would appear that isolation is the only way to avoid disaster. Comparisons can be made between the current pandemic and the cybersecurity world of malware.
Article Series: Edge Cloud
Is edge computing the next frontier? Possibly. Once you get past the inevitable hype, you can see the value of processing data streams across distributed compute pools. If you view edge as an evolution of both infrastructure and application architecture, you recognize that our existing practices need an upgrade. How should we design systems that run in a disconnected state? How do we deploy changes to hundreds or thousands of locations? Should management be centralized or distributed?
Is Edge Computing a Thing?
Key Takeaways "Edge" is not a place, but rather, a new way to compute on streaming data. Real-time analysis of streaming data demands that we kick the REST + Database habit. Cloud computing is built on stateless microservices and stateful databases, whereas edge requires stateful "things", boundless data streams, and dynamic context.
Everybody Has Big Data - Deal With It
Enterprises are awash in data, and though many are tempted to save it all for later analysis – after all it worked for Google for many years – the store then analyze approach is poorly suited to environments with data sources that never stop. Storing all data is costly if you have a vast amount of it or it is boundless in nature. On top of that, getting the data to the storage infrastructure then processing it fast enough become major challenges.
Why You Should Rent Instead Of Buy ML Solutions
An enterprise (which shall remain nameless) invested heavily in the purchase a machine learning solution to optimize one of its key processes. It worked with a vendor of “best in class” machine learning (ML) software (which shall also remain nameless) that had served many customers with similar processes. The solution worked superbly for a while. Then the wheels fell off. The failure took some time to unwind — far longer than it ought to have. Why?
Democratizing Insights From Fast Data
Organizations are overwhelmed by boundless streams of data from suppliers, products, assets, apps, IT infrastructure, employees and customers. If they could quickly make sense of it all, they could respond faster, cut costs, improve service and find new sources of revenue. But they struggle for many reasons. Big-data analytics (on-prem or in the cloud) demands hard-to-find developer, data science and IT skill sets.
Open-Source Machine Learning Is Free, As In Beer
Machine learning (ML) continues to amaze us with its abilities and is set to transform the economic structure of many industries -- from producers of widgets to financial analysts and health care providers. But many IT and operations practitioners are struggling to put the rapid advances in ML to work for their organizations.
Simon Crosby: Takeaways from the O'Reilly AI Conference
Last week I presented SWIM.AI Edge Intelligence at the O’Reilly AI conference in San Francisco. It was a terrific opportunity to learn from real users about their challenges delivering value from their AI projects. My pitch was simple and well received: SWIM makes delivering edge intelligence easy because it lets streaming data build the model on-the-fly – at the edge, avoiding a ton of complexity and infrastructure cost for traditional solutions.
Who Will Build The Intelligent Edge?
The number of “smart” edge devices in circulation is enormous. Business Insider estimates that "5.6 billion IoT devices owned by enterprises and governments will utilize edge computing for data collection and processing by 2020." The volume of data that these devices will produce is growing just as rapidly. But there’s a problem: Who will make these edge devices smart?
Edge Learning is Enhanced With Digital Twins
The tech industry is aflutter at the thought of applying machine learning (ML) at the edge to streams of city and industrial data and to new IoT devices. Edge-based smarts enable quick, local decision making, cut the cost of data transport and storage, and ease concerns over data custody, confidentiality, and privacy. As pioneers of machine learning, major cloud vendors have developed powerful services that enable developers to deliver ML-derived insights more easily.
Citrix: Lesson from Wikileaks
What do Virtualization and Cloud executives think about 2011? Find out in this VMblog.com series exclusive. Wikileaks ought to have you sitting bolt upright in your black leather CIO chair. Independent of your views of the legitimacy or otherwise of Wikileaks, the last month has given us a shocking demonstration of the results of weak IT control over enterprise data and applications, and the incredible resilience of cloud based apps to both government-initiated take-downs and organized attacks.
Separating Fact From Fiction: The Role Of Artificial Intelligence In Cybersecurity
Artificial intelligence (AI) has become such a buzzword that it’s at risk of becoming no more than tech marketing pixie dust. Just sprinkle a little here and suddenly, your solution inherits the foresight of a self-driving Tesla and the simplicity of an Amazon Echo. As more solutions crowd the cybersecurity market touting the benefits of AI, it’s important to read through the hype. Machine learning (ML) can deliver transformative insights in some domains, but it has limitations.
Hunting the Snark with Machine Learning, Artificial Intelligence, and Cognitive Computing
How do you find the unknown unknown that may have breached your perimeter defenses and might be doing something you cannot see? Answer: you move from deterministic solutions to a probabilistic approach and let your computer do the work. This is the purpose of new developments in machine learning (ML), artificial intelligence (AI), and cognitive computing (CC) within cyber security.
Cybersecurity is the Sputnik of Our Day
Simon Crosby is the chief technology officer and co-founder of Bromium. From the U.S. election to the French and German elections, data from breached organizations, personal email and web apps is being used to sway the political debate—and to sow the seeds of an alternative narrative. The play: circulate “plausible” stories or allegations with scant evidence by taking advantage of a press whose business model has become reliant on clicks and sensational revelations.
What The Election Can Teach Us About Cybersecurity
It is rare for a U.S. president to face a major political stand-off before his own inauguration. But that was the history-making environment we saw playing out as president-elect Donald Trump, members of the U.S. intelligence community and Congress scuffled over the degree to which a Russian influence campaign, played out through cyber activity, shaped an election for the ages.
Dear Washington – My Advice on Making America (Cyber) Safe Again
HP Threat Research Blog • Dear Washington – My Advice on Making America (Cyber) Safe Again • Category: Uncategorized • By: • In part one, I shared my story of giving advice to the Trump Transition Team. My bottom line advice, “Move everything to the cloud. Fast.” Then use virtualization to protect what matters most. First, some clarity on the term “cloud”. I’m heavily biased toward the adoption ofpublic cloud services wherever regulations permit.
Fixing “the Cybers” in Washington DC
• Category: Uncategorized • By: • The challenge: collapse fifteen years of experience into a one-page recommendation. Keeping the government safe from cyber villains is a shared responsibility. This is part one of two parts about my experience. Read part two here. I was recently asked to provide guidance to the Trump transition team to help prioritize their IT strategy to improve the resilience of the US government (USG) to cyber-attacks. On a single page.
Endpoint Security Wars: Is Peace Breaking Out?
In May 2016 VirusTotal (VT) changed its rules. Any vendor wishing to receive antivirus results via the VT API would in future be required to integrate its own detection scanner into the public VT interface. Furthermore, such vendors would need to be certified by The Anti-Malware Testing Standards Organization (AMTSO).
Crypto Malware: Responding To Machine-Timescale Breaches
Thethousand-foldincrease in crypto-malware highlights a profound change in the cyber-landscape: Previously, an attacker seeking to steal intellectual property, personal identifiable information or payment card information would need to successfully breach and persist on one or more endpoints, carefully research the network, stealthily exfiltrate data, and finally process it in order to sell it on the dark web – a lot of effort for an uncertain payout.
How Cybersecurity Techniques Can Avoid Security Theater
Metadata is the key to a more comprehensive and less reactionary approach to cybersecurity.
HTML5 Won't Stop Malvertising, Brings New Threats
Flash is one of the most abused pieces of software in use. Flexera Software's Vulnerability Review 2016 counts 457 vulnerabilities in 2014 and 2015 (second only to Chrome with 516 vulnerabilities). But Flash is the attacker's tool of choice. For example, as recently as late May 2016 Malwarebytes reported on a malvertising campaign exploiting Flash and redirecting users to the Angler exploit kit. Such abuse is behind current browser campaigns to deprecate the use of Flash while browsing.
What Keeps Security Professionals Up at Night? Their Users
You might believe that the expensive network security hardware you installed will protect you from bad actors — until a single employee undoes all that good work when he doesn’t realize the attachment he just opened carries dangerous malware. It’s hard keeping criminals from infiltrating networks, much less worrying that users will simply open the door to bad guys by letting their guard down.
Cybersecurity Predictions 2016: Luck or Leadership?
Unfortunately, in most respects, 2016 won’t change much: Users will still unknowingly click on malicious links; IT departments will still be bad at staying up to date with patching; the bad guys will continue to attack; and the tide of misery from breaches will persist. What matters most is whether your organization will be a victim or not. Of course you could do nothing, and be lucky.
What’s The Half Life Of A Unicorn?
“Cybercorns” are companies that have surpassed the magical $1 billion valuation. Several of these extraordinary ventures are Okta, Sophos, Tanium, Palantir, FireEye, Splunk, Zscaler, Lookout, CloudFlare, Illumio and AVAST. Each has attained an enviable position as a valued solution to an important set of customer security pains. The entrepreneurs who built these companies (many of which are privately held) and the investors that backed them deserve their success.
What’s The Half Life Of A Unicorn?
Posted on 01 gennaio 2016 Cybercorns are companies that have surpassed the magical $1 billion valuation. Several of these extraordinary ventures are Okta, Sophos, Tanium, Palantir, FireEye, Splunk, Zscaler, Lookout, CloudFlare, Illumio and AVAST. But in a world where technology is changing rapidly, and in which attackers are agile and focused, which of these unicorns will survive? What is the half-life, perhaps measured… Read More
Choosing Leadership Over Luck
Cybersecurity issues are never going to be resolved if organizations don't start holding vendors responsible.
Machine Learning Is Cybersecurity’s Latest Pipe Dream
Is machine learning the answer to the security problem? Again, this is an imprecise statement of the problem and the potential set of solutions. In this piece I want to focus on attack detection. In this domain we need to ask two questions: Can an algorithm reliably find the needle in the haystack (the tiny differences from “normal” behavior that might be indicative of an attack)?
Changing the Economics of Cybersecurity
It’s almost a cliche to talk about how often breaches occur—in 2015 alone, we’ve seen high-profile breaches from everyone from Anthem, the popular work collaboration tool Slack, and even the federal government thanks to the recent US Office of Personnel Management attack.
The Psychology Of Insecurity
The recent Ashley Madison hack isn’t the only high-profile one to make headlines this summer. The personal and private information of more than 21.5 million current and former federal employees and over a million unique fingerprint scans were leaked in an attack on the Office of Personnel Management (OPM) that is believed to be the work of the Chinese. Government officials said longtime security lapses left the OPM vulnerable to hackers.
The Psychology Of Insecurity
The latest data breach victim to make the headlines is a big one — deeply personal and private information of more than 21.5 million current and former federal employees and over a million unique fingerprint scans, were leaked in an attack on the Office of Personnel Management (OPM) that is believed to be the work of the Chinese. Government officials said longtime security lapses left… Read More
The Virtualization Reality
A number of important challenges are associated with the deployment and configuration of contemporary computing infrastructure. Given the variety of operating systems and their many versions—including the often-specific configurations required to accommodate the wide range of popular applications—it has become quite a conundrum to establish and manage such systems.
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