Scheduling Agents with Rules Engines

April 5, 2008

Paul Vincent of TIBCO talks about agents in his post, CEP and Agents…

At the core, TIBCO’s BusinessEvents is RETE-based rules engine and rules engines are well suited for scheduling problems.  This makes perfect sense, since many of TIBCO’s customers deploy BusinessEvents in scheduling-oriented, not detection-oriented, solutions.

It begs to be pointed out, however, that scheduling is only one component of a CEP architecture. 

Normally, the scheduling component of a distributed event processing architecture manages the intelligent scheduling of the sharing of data between distributed agents that are running a variety of analytics.

Simply stated, all agents are not rules engines; however, rules engines are often used to schedule the cooperation between analytical agents in a distributed agent-based architecture.

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Simple Event Processing != Complex Event Processing

December 16, 2007

One of the brillant minds in the CEP community, Claudio Paniagua Macia, recently posted, Event Stream Processing != Complex Event Processing.   In his post, Claudi draws a bold conclusion:

(1) SQL-based approaches to ESP might have a hard time doing CEP.

(2) No real CEP engine exists today in the marketplace, perhaps not even “off” the marketplace.

Friend, colleague, and co-chair Opher Etzion replied, On Event Stream Processing:

 “CEP engines do exist today, none is perfect, but probably sufficient for big majority of the existing applications today.”

Respectfully, I find it necessary to agree with Claudi and disagree with Opher.   Most of the so-called CEP engines today are solving quite simple event processing problems.   If the CEP engines on the market were truly solving a “majority of the exisiting applications today” then sales would be orders of magnitudes larger.

The fact-of-the-matter is that the current “simple rules-based approach” dominate in today’s marketplace are used to solve problems where rules-based approaches are useful.   Unfortunately, this is just a small fraction of the true potential of the CEP market.

For example (just one example of many), the vast majority of intrusion or fraud detection systems available today use rule-based approaches, and their detection capability, and the confidence in the detection, is quite elementary (poor quality).   If these systems worked well, cyberspace would be a very different and much safer place.  

Yes, it is useful to add another layer of rules, but rules alone will not solve the vast majority of CEP-domain classes of problems.   In addition, the CEP applications that have made the press recently are quite simple, certainly nothing scientifically earth shattering.

So, the sad truth of the matter, from an architectural, scientific and solutions perspective, is exactly as Claudi boldly offered, no real CEP engine exists today.    Furthermore, the vast majority, if not all, CEP applications sold today are used in very simple event processing (SEP) applications.  This is not very “advanced,” but it is a good start.  

What is holding the CEP market back is quite straight forward; the current “engines” are quite elementary (We should call them SEP engines.), relatively speaking, and SEP engines do not have the capability to solve difficult detection-oriented CEP problems in cyberspace.   These difficult problems compose the vast majority of the applications where “true complex event processing” is required.


CEP Center of Excellence for Cybersecurity at Software Park Thailand

December 16, 2007

In July 2007, at InformationSecurityAsia2007,  I unveiled an idea to create a cybersecurity CEP Center of Excellence (COE) in Thailand.  Under the collaborative guidance of Dr. Rom Hiranpruk, Deputy Director, Technology Management Center, National Science and Technology Development Agency (NSTDA), Dr. Prinya Hom-anek, President and Founder, ACIS Professional Center, and Dr. Komain Pipulyarojana, Chief National Security Section, National Electronics and Computer Technology Center (NECTEC), this idea continues to move forward.

Today, in a meeting with Mrs. Suwipa Wanasathop, Director, Software Park Thailand, and her executive team, we reached a tentative agreement to host the CEP COE at Software Park.   

The mission of Software Park Thailand is to be the region’s premier agency supporting entrepreneurs to help create a strong world-class software industry that will enhance the strength and competitiveness of the Thai economy.

Since 2001, Thailand’s software industry has experienced approximately 20% year-over-year (YOY) growth.  Presently, Software Parks Thailand supports a business-technology ecosystem with over 300 active participants employing over 40,000 qualified software engineers across a wide range of technology domains.

I am very pleased that Software Park Thailand is excited about the potential benefits of CEP in the area of cybersecurity and detection-oriented approaches to cyberdefense. The COE will be working with best-of-breed CEP vendors to build, test and refine rule-based (RBS), neural network (NN) based and Bayesian network (BN) based approaches (as well as other detection methods) for cybersecurity.

I will be announcing more details in the future, so stay tuned.  Please feel free to contact me if you have any questions.


Bankers Voice Scepticism Over New Event Processing Technologies

November 28, 2007

This week I completed a presentation on complex event processing at Wealth Management Asia 2007 where I had a chance to field some tough questions from risk management experts working for some of the top banks in the region.

In particular, one of the meeting attendees voiced strong scepticism over emerging event processing technologies.   The basis for his scepticism was, in his words, that the other “65 systems” the bank had deployed to detect fraud and money laundering (AML) simply did not work.  In particular, he referenced Mantas as one of the expensive systems that did not meet the banks requirements. 

My reply was that one of the advantages of emerging event processing platforms is the “white box” ability to add new rules, or other analytics, “on the fly” without the need to go back to the vendor for another expensive upgrade. 

Our friend the banker also mentioned the huge problem of “garbage-in, garbage-out” where the data for real-time analytics is not “clean enough” to provide confidence in the processing results. 

I replied that this is always the problem with stand-alone detection-oriented systems that do not integrate with each other, for example his “65 systems problem.”    Event processing solutions must be based on standards-based distributed communications, for example a high speed messaging backbone or distributed object caching architecture, so enterprises may correlate the output of different detection platforms to increase confidence.   Increasing confidence, in this case, means lowering false alarms while, at the same time, increasing detection sensitivity.

As I have learned over a long 20 year career of IT consulting, the enemy of the right approach to solving a critical IT problem is the trail of previous failed solutions.   In this case, a long history of expensive systems that do not work as promised is creating scepticism over the benefits of CEP.


COTS Software Versus (Hard) Coding in EP Applications

November 21, 2007

Opher Etzion has kindly asked me to write a paragraph or two on commercial-off-the-shelf  (COTS) software versus (hard) coding software in event processing applications. 

My thoughts on this topic are similar to my earlier blog musings, Latency Takes a Back Seat to Accuracy in CEP Applications.

If you buy a EP engine (today) because it permits you run some quick-and-dirty (rule-based) analytics against a stream of incoming events, and you can do this quickly without spending considerable software development costs, and the learning curve and implementation curve for the COTS is relatively low, this could be a good business decision, obviously.   Having a software license for an EP engine that permits you to quickly develop and change analytics, variables and parameters on-the-fly is useful. 

On the other hand, the current state of many CEP platforms, and their declarative programming modelling capabilities, is that they focus on If-Then-Else, Event-Condition-Action (ECA), rule-based analytics.  Sophisticated processing requires more functionality that just ECA rules, because most advanced detection-oriented applications are not just ECA solutions.

For many classes of EP applications today, writing code may still be the best way to achieve the results (accuracy, confidence) you are looking for, because CEP software platforms have not yet evolved to plug-and-play analytical platforms, providing a wide range of sophisticated analytics in combination with quality modelling tools for the all business users and their advanced detection requirements.

For this reason, and others which I don’t have time to write about today, I don’t think that we can say blanket statements that “CEP is about using engines versus writing programs or hard coding procedures.”   Event processing, in context to specific business problems, is the “what” and using a CEP/EP modelling tool and execution engine is only one of the possible “hows” in an event processing architecture.  

As we know, CEP/EP engines, and the marketplace for using them, are still evolving and maturing; hence, there are many CEP/EP applications, today, and in the foreseeable future, that require hard coding to meet performance objectives, when performance is measured by actual business-decision results (accuracy). 

Furthermore, as many of our friends point out, if you truely want the fastest, lowest latency possible, you need to be as close to the “metal” as possible, so C and C++ will always be faster than Java byte code running in a sandbox written in C or C++.   

And, as you (Opher) correctly point out, along with most of the end users we talk to, they do not process megaevents per second on a single platform, so this is a marketing red herring.  This brings us back to our discussions on the future of distributed object caching, grid computing and virtualization – so I’ll stop and go out for some fried rice and shrimp, and some cold Singha beer.


Clustered Databases Versus Virtualization for CEP Applications

November 16, 2007

In my earlier post, A Model For Distributed Event Processing, I promised to address grid computing, distributed object caching and virtualization, and how these technologies relate to complex event processing.   Some of my readers might forget my earlier roots in networking if I continue to talk about higher level abstractions!  So, in this follow-up post I will discuss virtualization relative to database clustering.

In typical clustered database environments there are quite a few major performance constraints.  These constraints limit our capability to architect and design solutions for distributed, complex, cooperative event processing problems and scenarios.  Socket-based interprocess communications (IPCs) within database clusters create a performance limitation contrained by low bandwidth, high latency, and processing overhead.

In addition, the communications performance between the application layer and the database layer can be limited by both TCP and operating system overhead.  To make matter worse, hardware input-output constraints limits scalability for connecting database servers to disk storage.   These are standard distributed computing constraints.

The physical architecture to address scalability in emerging distributed CEP solutions require a low-latency network communications infrastructure (sometimes called a fabric).  This simple means that event processing agents (EPAs) require virtualization technologies such as Remote Direct Memory Access (RDMA).  CEP agents (often called CEP engines) should have the capability to write data directly to the memory spaces of a CEP agent fabric (sometimes called an event processing network, EPN).   This is similar to the concept of shared memory as an IPC in UNIX-based systems applied to distributed computing, so all “old hat” UNIX systems engineers will easily grok these concepts.

RDMA virtualization helps improve performance by bypassing operating-system and TCP overhead resulting in significantly higher bandwidth and lower latency in the EPF (Event Processing Fabric – I just minted a new three letter acronym, sorry!).  This, in turn, improves the communication speed between event processing agents in an event processing network (EPN), or EPF (depending on your taste in acronyms).

Scheduling tasks such as a distributed semaphore checking and lock management can also operate more efficiently and with higher performance.    Distributed tables scans, decision tree searches, rule-engine evaluations, Bayesian and neural analytics can all be performed in parallel,  dramatically improving both performance and scalability of distributed event processing applications.

In addition, by adopting transparent protocols with existing socket APIs, the CEP architect can bypass both operating-system and TCP protocol overhead.   In other words, communications infrastructures for CEP that optimize networking, interprocess communications, and storage, provide architects with the underlying tools to build better solutions to computational complex problems.

Many of the communications constraints of earlier distributed architectures for solving complex problems, such as blackboard architectures,  can be mitigated with advances in virtualization.  So, in a nutshell, virtualization technologies, are one of the most important underlying capabilities required for distributed, high performance CEP applications, in my opinion.

The article, Virtualization hot; ITIL, IPv6 not,  appears to indicate that some of the top IT managers at Interop New York might agree with me.  

Unfortunately for a few software vendors, virtualization threatens to dilute their market share for ESB and message bus sale.  (OBTW, SOA is DOA.)   “Old hat” UNIX system programmers will recall how the UNIX IPC called “message queues” lost favor to sockets, pipes and shared memory.   A similar trend is happening in the virtualization world with RDMA as a distributed shared memory technology versus message-based communications technologies.  I will opine more on this topic later.


Event Cloud Computing – IBM Turning Data Centers Into ‘Computing Cloud’

November 15, 2007

 I predict we may experience less debates on the use of the term “event cloud” related to CEP in the future, now that both IBM and Google  have made announcements about “cloud computing” and “computing cloud”, IBM Turning Data Centers Into ‘Computing Cloud’

“The initiative also builds on IBM’s announcement with Google last  month that they are developing cloud computing environments for  academic use.  But today’s announcement is aimed more widely at corporations and government users that want the extreme scale made possibly by lashing together pools of computers.”

This also furthers the notion and architecture we have been advocating, that event processing will move toward a distributed, cooperative computing model..