Jeff uses the example, “Smart Order Routing” as an example of taking an event and routing the resulting market order match based on some simple rules.    Routing a order kicked off by a simple order match against a deep liquidity pool (or other market factor) does not define complex event processing nor detecting a complex event - the core idea behind CEP.   Order routing based on simple rules is BPM, plain and simple.

Let’s take another example, fraud.  In this example, there is some complex neural network monitoring for credit card fraud and a potential fraud is detected - this is CEP, detecting a complex event based on some sophisticated analytics.   

After a possible fraud has been detected, a process looks into a database and the routes the incident to someone in the company who is a (1) specialist in credit card fraud, (2) working at the same time of the discovered threat, and (3) immediately available to act on this type of task.   Routing the incident is not CEP, it is BPM.

Jeff makes the argument that it is OK to call an event-driven BPM task CEP because “it fits the EPTS definition” in the CEP glossary.   He also avoids the discussion of detection accuracy, and instead insists that latency is a ”very important” factor in a CEP application.

If you read the various post by vendors in the blog-o-sphere, it is obvious that they are continually defining CEP as BAM, BPM, BRE, BRMS, SOA and just about every other related processing activity that is complimentary to the event correlation and analysis required to detect an opportunity or threat to your business.

I’m not picking on Aleri.  TIBCO has been doing the same thing recently in their CEP blog, continually attempting to redefine CEP as BRMS.    Detecting business opportunities and threats with high confidence requires sophisticated analytics, and their tools have not yet evolved to “real CEP” capabilities.  Instead, vendors are attempting to redefine BPM, BRMS, BRE, and even SOA to some degree, as CEP. 

CEP is Not BPM, BAM, BRE, BRMS or SOA.

At the moment, event correlation and event analysis is Gartner’s closest magic quadrant (MQ)  that relates directly to complex event processing (and event processing in general).    

A number of our friends and colleagues would like to position CEP as BRE, BRMS, BPM, SOA, algo trading and just about every other technology under the sun, except event correlation!

In a nutshell, the state-of-the-state of CEP/EP is that a number of firms in the software industry have found some “uncharted magic quadrant waters” and are positioning themselves to be “chart worthy”. Instead of competing head on with the experienced players (event correlation and analysis) that have been in the event processing field for many years.   

As I have mentioned a few times here on The CEP Blog, if the current generation self-described CEP engines were leading the industry in event correlation and analysis (CEP’s core technology domain) they would be either be on Gartner’s Magic Quadrant for IT Event Correlation and Analysis, or possibly acquired by a one of these large giants in event processing to solve complex event processing and event correlation problems that remain, for the most part, still unsolved!

The convergence of voice and video traffic are quickly transforming the growing complexity of networks at a torrid pace. IDC estimates that the skills gap in VOIP should grow to 19% by 2011.

This changing profile in the role of the network plays a key role in the skills shortage. Network enabled collaboration tools such as social networking apps and the Webex conferencing/collaboration solutions we use in our business each and every day are demanding a new set of IT skills to deliver business value.

My perspective is two-fold on this issue; the first is what I have seen in the resources we have attempted to hire! We give a very straightforward quick written/oral test to all new technical hires. This requires basic networking knowledge and some Unix commands. On average, (after filters from reputable recruiting firms, some with 5-10 years experience) less than 10% pass muster for the first filter we use in our hiring process. This is a troubling fact, which has cost us considerable time and effort to secure the right resources with competent skills. So I can say from our market assessment in a very strong technological job skills market, core Unix and networking foundation skills are slipping.

The second is that we as an IT Operations Management (ITOM) industry need to keep pushing hard to build better proactive and intuitive solutions to aggregate instrumentation from all Data Center tools, including more work around VOIP, video streaming, and collaboration so that we can ease this transition. If ITOM solutions become more proactive across the typical Cisco infrastructure that is commonly installed in the Data Center, we can free up some additional time for advanced “emerging technologies” training where existing IT workers can enhance their core skills and re-invigorate their careers. We have to do a much better job of getting our existing IT professionals trained on emerging technologies!

While there’s less that ScienceLogic can do around training, we certainly strive to do our part to enhance a day in the life of the networking engineers who use our solutions to simplify monitoring of increasingly complex networking, Wireless, VOIP, and collaboration needs.

adaptive process management (n.) an element of resource and business process management, adaptive search and event processing. Sometimes referred to as “Level 4” event processing or process refinement.

application concept (n.) a definition of a set of properties that represent the data fields of an application entity. An application concept can describe relationships among themselves. For example, an order concept might have a parent/child relationship with an item concept. A department concept might be related to a purchase requisition concept based on the shared property, department_id. Application concepts can include an application state model.

application state modeler (n.) a UML-compliant application that allows you to model the life cycle of a concept instance — that is, for each instance of a given concept, you can define which states it will pass through and how it will transition from state to state. States have entry actions, exit actions, and conditions, providing precision control over the behavior of an event processing agent. Transitions between states also may have rules. Multiple types of states and transitions maximize the versatility and power of the application state modeler.

derived event (n.) an event that is created as a result of processing one or more other events.

complex event (n.) an event that is a situation-entity abstraction of two or more simple, derived or other complex events.

complex event processing (n.) CEP is a technology for extracting information from message-based systems. CEP is primarily an event processing concept that deals with the task of processing multiple events from an event cloud with the goal of identifying the meaningful events within the event cloud. CEP employs techniques such as detection of complex patterns of many events, event correlation and abstraction, event hierarchies, and relationships between events such as causality, membership, and timing, and event-driven processes.

event (n.) a instance of an event definition. It is an immutable object that represents a business activity that happened at a single point in time. Just as one cannot change the fact that a given activity occurred, one cannot change an event — events are immutable.

event aggregation (n.) the aggregation of simple, derived or complex events into higher levels of event abstractions.

event definition (n.) a set of properties related to a given activity that represents an important or interesting change of state in a human, system or computational activity. An event definition includes event properties such as event priority, event time to live (TTL), and a description of the payload, which is comprehensive information related to the activity that occurred. Events expire when the TTL has elapsed, unless the event processing agent has instructions to consume them prior to that time.

event channel (n.) a communications channel in which events are transmitted from event source to event receivers, typically received as electronic messages. Each channel can have multiple destination and. events can be configured to transmit to a default destination. JMS is an example of an event channel.

event cloud (n.) a partially ordered set of events (poset), either bounded or unbounded, where the partial orderings are imposed by the causal, timing and other relationships between the events. Typically an event cloud is created by the events produced by one or more distributed systems. An event cloud may contain many event types, event streams and event channels. The difference between a cloud and a stream is that there is no event relationship that totally orders the events in a cloud.

event-driven (n.) the behavior of a human, system or computational entity whose execution or actuation is in response to events, typically received as electronic messages.

event-driven architecture (n.) an architectural style for distributed computing applications in which some of the components are event-driven and communicate by means of events.

event processing (n.) computing that performs operations on events, including modifying, creating and destroying events.

event-object (n.) an software object that represents an event, generally for the purpose of computer processing, that exhibits both encapsulation, inheritance and polymorphism.

event prediction (n.) computational activity where the impact of events, complex events, and situations caused by events identified, including both opportunity or threat. Sometimes referred to as “Level 2” event processing, impact assessment or predictive analytics.

event pre-processing (n.) computational activity where events are cleansed or normalized to produce semantically understandable data. Sometimes referred to as “Level 0” event processing.

event processing (n.) computational activities on events dealing with the association, correlation, and combination of event data and information from single and multiple event sources to achieve refined identity and situation estimates for observed event objects, and to achieve complete and timely assessments of opportunities, threats, and their significance. Event processing is characterized by continuous refinements of event estimates and assessments and by evaluation of the need for additional sources, or modification of the process itself, to achieve improved results.

event processing agent (n.) an EPA is a computational entity that performs event processing.

event processing network (n.) a set of event processing agents and a set of event channels connecting them.

event properties (n.) data representation of an event, typically by name-value pairs of type string, integer, real, boolean or a complex data type.

event refinement (n.) filter, identify and track events & make initial processing decisions based on association, correlation and state estimation. Sometimes referred to as “Level 1” event, or event-object, track and trace.

event stream (n.) a time-ordered sequence of events. An event stream may be bounded by a certain time interval or other contextual dimension (content, space, source, certainty), or be open ended and unbounded.

event stream processing (n.) a time-ordered sequence of events. An event stream may be bounded by a certain time interval or other contextual dimension (content, space, source, certainty), or be open ended and unbounded.

rule (n.) defines what triggers unusual, suspicious, problematic, or advantageous activity within an event processing agent and what the EPA does when it discovers these types of activities. Rules execute actions based on certain conditions on events, instances, or a combination of both. A rule includes a group of condition-rule statements and action-rule statements. The condition statements instruct the EPA what to look for in events, and action statements instruct the EPA how to respond when conditions are met. If all the conditions in a rule are satisfied by events or instances or both, the EPA fires the actions. The action might be to execute tasks, create an event instance, modify property values in an event instance, create and send an event, or something else.

rules engine (n.) a type of event processing agent that uses a declarative programming model to process events. Formally described as “an abstract structure that describes a formal language precisely, i.e., a set of rules that mathematically delineates a (usually infinite) set of finite-length strings over a (usually finite) alphabet“. Informally, it can be any system that uses rules, in any form, that can be applied to data to produce outcomes.

rule language (n.) is an artificial language that is used to control the behavior of an event processing agent. Rules languages, like human languages, have syntactic and semantic rules to define meaning.

situation refinement (n.) identify situations, or complex events, based on event clustering, event-event relationships and relationship analysis and context. Sometimes referred to as “Level 2” event processing.

simple event (n.) an event that is not an abstraction or composition of other events.

virtual event (n.) an event that is imagined, modeled or simulated.

To kick off our celebration of our first five years, we asked ScienceLogic founders Dave Link, Richard Chart and Chris Cordray for their thoughts and memories on events leading to today’s milestone. How and why did they set out on this venture? What happened along the way – expected and unexpected? Why were they successful in times when other new (and established) businesses have come and gone?

How did you three put together this team?

We all worked together at a large Managed Service Provider for a couple of years before leaving to start ScienceLogic, so we all knew each other and knew our collective strengths. More importantly, each of us had worked with network management tools on some level (sales and marketing, engineering and product development), and knew first-hand all of the customer pain points, from every perspective. So we left and began rapidly figuring out how to build a better network management solution based upon our real world operational experience..

Dave: One interesting aspect is that our areas of expertise don’t overlap, which has contributed to our success. Chris is excellent with developing the product front-end and interface, Richard handled the backend architecture and engineering and I focused on the technical business side of sales and marketing. Our roles have been to build a product that works well and that provides real value to operations teams that experience the same day to day frustrations that we felt.

Whose idea was it to start the company?

Dave: It was really a collective effort. We were all passionate about “getting it right” and not just starting a company. We knew the industry need and between us, we had the knowledge and skill sets to address all of the right aspects of developing a product and a building a business around it.

What process did you go through to get started?

Richard: From the beginning we knew the type of solution the market needed and we knew that we wanted to build it as an appliance. From different vantage points, we had each experienced the effects of long, difficult and expensive installations that still exist with traditional network tools. Every install has unique variations: there are always different server types, varying hardware and software versions, different patches installed, and on and on. Every installation was time consuming and unpredictable. We knew that an appliance model would address all of these variables and save a lot of time on how quickly customers could achieve immediate value.

The harder decisions were around actually starting the business, assessing the market and of course determining the product pricing.

EM7 completely flips the traditional model of complex, lengthy and expensive deployments. How did you convince others that the EM7 Meta-Appliance product was valid?

Dave: Yes, EM7 totally disrupts the traditional model for network management. While others take a narrow approach, we intentionally designed EM7 to focus on the broad problem – managing the data center. How do you cover a variety of technologies and make sure they work seamlessly together? The vision was to make it easier, not harder, for customers.

Chris: I have to give it to Dave – very early on, he realized the power of a demo. If Dave could get in front of someone, he’d make them a believer. He’d use the Peter Falk/Columbo technique of “let me show you one more thing.” It was very effective. It’s getting easier, but even today people sometimes have to see EM7 in action before they become believers.

Can you describe the early days of running a new business?

Dave: ScienceLogic is a classic case of entrepreneurship. For the first year we worked out of our basements. We kept the costs low in every conceivable way and spent the first year developing the product before we even made a sale.

Chris: We stayed at lots of odd places when we were on the road, took cheap flights with multiple layovers and purchased lots of our first test equipment on eBay. This was during the dot-com bust so there was lots of equipment for sale on eBay, really cheap!

Richard: The amount of equipment I had in my house was absolutely crazy. Back then, servers were huge – I had a Cisco 6509 Catalyst, a Compaq Proliant DL380, Brocade switch, IBM Netfinity 4500R, and tons of other machines.

Chris: I had to install a new circuit box at home because I was blowing breakers. I remember when that 6509 crashed, we revived it and it died again. The second death was final.

So you started in your houses – what was your first office space?

Dave: My friend, the CEO at Ernst & Young Technology had a few extra cubes and a data center in their office that they graciously allowed us to use. Their help was an important step in helping us really formalize the business. We started doing well and adding people, but ironically, their company was downsizing. Before long, many of their original YET people were gone and the ScienceLogic team kept growing in to the open cubes.

Our first leased space was converted warehouse space in Chantilly, VA that once housed an internet radio station. It was cool – it had a large salt water fish tank, a loft, a spiral staircase and a Star Trek door that retracted into the walls with the customary lights and “whooshing” sound.

We outgrew the Chantilly space, leading to our current office in Reston, VA.

Who was the first ScienceLogic customer?

Our first paying customer was Martins Point Health Care. We deployed there in July 2004 and are pleased to say they continue to be a ScienceLogic customer. Other early (and still) EM7 customers include Navy Knowledge Online and the Department of Transportation. Nearly all of our customers are still actively using EM7 and renewing their maintenance.

Where do you see the company in the next 5, 10 or 15 years?

Well, our revenue has doubled year-over-year in each of the last three years, so of course we’d like to continue to grow like that or even faster. In five years we’ve gone from three founders to the point where Dave does not know everyone’s fondest childhood memory. We’ll continue to scale our growth to cover the demands of our growing customer base.

Where do you see the industry going over the coming years?

Chris: IT is always moving and gaining in complexity, so network management is also becoming more complicated. There’s increasing diversity, new standards, virtualization and cloud computing. All of these are today’s technologies. Customers have a mix of the old and the new, so EM7 has to accommodate and support both.

Richard: Each generation of products has a new set of ways to monitor, but the “old” doesn’t go away. Even when a new, hot technology comes along, the old technologies still need to be supported. We work to ensure EM7 keeps up with both.

Dave: After five years we’re just hitting our stride and we’re just now reaching the tipping point in awareness of ScienceLogic and EM7. We’re all still passionate about the product and as Chris and Rich said, there’s still a lot do. We’ll continue disrupting the market with EM7. Our vision hasn’t changed, and with the increasing levels of automation that customers demand, the market needs are greater than ever. Our future is as bright, or brighter, than ever and we’ll continue to be looking for smart ways to automate traditionally manual IT Operations processes.

What’s your advice for someone interested in starting their own business?

Chris: Be passionate. That’s what has gotten me through the tough times. I didn’t really appreciate this thought when I heard others say it before. But it’s very true.

Richard: I agree. We met and talked with lots of people who told us, “That’s been done before.” But we kept going because we truly believed in what we were doing and we knew that while our approach was different, that it would be successful.

Richard: Be fearless. You can’t be too nervous and you need to be able to expect and handle the stress because it will be there. You have to learn to accept the stressful times as a necessary part of the process of starting out on your own.

Dave: Know your niche from the beginning and give potential customers a compelling reason to trust you and really benefit from your solution. You have to know the problem, see the gap and have a clear and consistent vision of how to solve the problem. Then you have to execute. If you don’t build your team with “doers” you won’t make it.

Chris: It helps to have friends. ScienceLogic was built on friendships and relationships, starting with the three of us. If you look at our team, most of our hires are referrals – people who developed and maintained great connections with other great people throughout their careers. Maintain your connections and keep in touch with your network of friends.

A good place to being to look for clues to an answer is Wikipedia, where the opinion of the author there is,

 ”A simple and practical definition, however, would be how an entity (i.e., business) arrives at an optimal or realistic decision based on existing data.”

Quoting the Wikipedia author(s) further,

“Common applications of Analytics include the study of business data using statistical analysis in order to discover and understand historical patterns with an eye to predicting and improving business performance in the future. Also, some people use the term to denote the use of mathematics in business. Others hold that field of analytics include the use of Operations Research, Statistics and Probability. However, it would be erroneous to limit the field of analytics to only statistics and mathematics.”

The Wikipedia author(s) continue their discussion of analytics, as follows;

“Analytics closely resembles statistical analysis and data mining, but tends to be based on modeling involving extensive computation. Some fields within the area of analytics are enterprise decision management, marketing analytics, predictive science, strategy science, credit risk analysis and fraud analytics.”

All of these topics above are CEP-related areas involving complex events and situations based on the need for optimal and reliable real-time capabilities to make meaningful (business) decisions. 

Simple pattern matching, event mediation and routing, and basic mathematical calculations do not really fall into the realm of complex event processing.  Instead, CEP is real-time decision support based on modeling and “extensive” computation.  In a nutshell, complex events and situations require analytical models that are non-trivial and that is why without analytics, there is no true “complex event processing.”

See also:

WIkipedia on Predictive Analytics

You can not process complex events in some very simple way and expect to get accurate results.  You need knowledge, represented by one or more situational models, to process complex events.

Some folks, like to say that a “complex event” is simply an event which is an aggregation of two more more event objects.    If you follow this (flawed) logic, then counting integers is complex event processing; because 1 plus 1 is 2, and 2 is an aggregation of 1 and 1, so 2 is a complex event (not!).  

Since we know that counting is not a complex processing operation, then some folks would say that you can process complex events with very simple operations because you are processing complex events , in the case adding 1 to the previous number (counting), enriching an event object.

This is simply nonsense.

The logic flaw is that the basic definition of a “complex event” (used by many people) is wrong.   A complex event is not simply an event object with two more more events as sub-components. 

A complex event is when two event objects are combined (processed) to form a complex object with a higher degree of inference, or situational knowledge.   One plus one equals more than two in complex event processing, because the combination of event objects requires knowledge (e.g. a situational model).

A Complex Event = Sum (EventsObjects) + Situational Knowledge

Let there be no mistake about it.    Complex event processing is the complex processing of complex events.   You cannot accurately process complex events with simple event processing models.

The simple processing of complex events is not CEP, it is simple event processing (event track-and-trace, simple event object enrichment, simple event object aggregation, and so forth).
 

Today, allow me to update you on FAIR and the movement towards a formal, open standard.  There’s a couple of cool things going on in our little risk-world.

First, The Open Group Security Forum continues to move towards a formal adoption of FAIR.

WHAT DO YOU MEAN “WE” - YOU GOT A STANDARDS BODY IN YOUR POCKET OR SOMETHING?

Our meeting in Chicago a few weeks ago was great, but also slightly disturbing for me. I got pronoun-confusion syndrome.   I’m used to using the “we” pronoun to refer to RMI, or Jack and myself as we vet the models.  So without even thinking I would said “we have been looking at how loss occurs, and may want to change the model some” and The Open Group Members freaked out (rightfully so).  Adrian Seccombe gently reminded me that the “we” was now the Security Forum, and that “we” didn’t go changing things at will without vetting against each other.  Man I love this stuff.  I get to run our thoughts and ideas past some great folks now - you know, those smart people who tend to have really complex problems and are trying hard to solve them.

Formal Adoption:  Soon, Very Soon Now

Formal Adoption basically means we’ve made this document, everyone is close to saying that they generally like it, and once that finally happens then “bam”, we’re ready to move onward and upward with better things (see Cookbooks, below).  We’ve got a couple of changes to the current document that have been requested that aren’t a big deal.  For example, one request is that we make some statement about general applicability of FAIR to risk domains outside of the IT realm.   But once additions like that and others are done, this long process should be complete.

New Document Moving Towards Public Release:

We’ve got a basic document that should be public in the next few weeks on “What Makes a Good Risk Assessment Methodology” - written by yours truly and Jack.  It’s a very high-level document, and serves two purposes:

• For novices it helps parse out what is important in any undertaking to understand corporate risk (the repeated discussions on the ISO 27001 mailing list make me think it would be a place ripe for such a document).
• For those who “know” risk, it helps to re-establish some fundamental principles like the use of scales (ratio, please), the implications of dealing in probabilities, what attributes like consistency and defensibility mean, how “risk” should be reported to the business (something you know, meaningful) and so on.

When this doc is deemed ready for public consumption I’ll be sure to post on this blog here.

COOKBOOKS, EUROPEAN AGENCIES, AND, IRON CHEF “RISK” - WHOSE CUISINE WILL REIGN SUPREME?

One interesting thing that came up in the Chicago meeting was that ENISA (The European Network and Information Security Agency) developed a very nice document that reviewed something like 18 different risk assessment methodologies against their Criteria for Goodness.  FAIR was one of the ones they reviewed, and we (the royal “we” used there to include all us FAIR-Folk) did awfully well.  Things of interest:

1. They based their work on the current introduction paper which is not at all a step-by-step guide towards an organizational risk assessment (what ENISA really wanted) and we did pretty well.  Well enough that if we had developed a paper along the lines of NIST 800-30 or OCTAVE for the use of FAIR in a formal process, we could have done really, really well.  Like won-the-bake-off kind of well.
2. FAIR is actually not at all incongruous to many of the risk assessment methodologies offered, and in fact compliments many of them by letting those methodologies develop real, structured probabilities.  Think OCTAVE, where they basically say “math is (probabilities are) hard, so if you want to do them for reals, good luck!  But here’s a nonsensical way to do things if you want to believe in magic-fairy risk“.  FAIR fits right in there by stomping on the magic-fairy risk with the jack-boots of rationality.  FAIR similarly helps other risk standards that might lack structured probability development.

So The Open Group Security Forum decided that though we could create a new document and totally p0wn any future ENISA bake-off, there wasn’t much demand for the development of that documentation by the membership  - a point which was made quite apparent at the beginning of the discussion when one large European company CISO asked “What’s ENISA?”  Relevancy is everything, I suppose.

But that second item up there - the one about helping rather than competing with other “risk assessment methodologies” - really struck a chord.  So “we” (The Security Forum) are going to develop some “Cookbooks” that basically are high-level documents that say “If you want to use FAIR with (OCTAVE/COSO/CoBIT/Whatever) here’s how it fits, makes it better, and improves your life.  I’m pretty excited about these, and our first document looks like it’s going to be COSO integration.

THE OPEN GROUP SECURITY FORUM - THEY’RE A TRUSTING BUNCH (WITH QUALIFICATION, OF COURSE)

Finally, many people have asked me “Why work with The Open Group?”  There are many reasons, to be sure, but I will give you one example.  Members of the Security Forum there are not only great at vetting the model and getting consensus on risk and risk factors - but they’re quick to start applying.  So in Chicago, I thought I’d be talking about FAIR and the standard and fighting groupthink.  Nope.  Not at all.  In fact, the forum members spent more time suddenly discussing use of FAIR in a new Trust Model they’re developing.  So all of the sudden, I’m part of a new and exciting project to develop a Trust Model - how cool is that?  While formal adoption of the Trust Model will be necessarily long and deliberate - the collaboration and development is happening much faster than I can keep up with.  But if you all will allow me, it will help me get my head around it all by blogging about it later this week.  So be prepared to read about me dealing in “Trust” a little bit.