JenniferSoft

Encouragement is Key to Success

2010-08-09T14:35:00.001-07:00

Quote about Business and Management...

Encouragement is Key to Success

“Flatter me, and I may not believe you. Criticize me, and I may not like you. Ignore me, and I may not forgive you. Encourage me, and I will not forget you. Love me and I may be forced to love you.”

William Ward

JenniferSoft becomes a sponsor of CMG'07 conference

2007-10-09T10:39:00.000-07:00

JenniferSoft, Inc. will attend ‘2007 CMG Conference which will be held on December 2nd through 7th in San Diego, California at the Manchester Grand Hyatt. The Computer Measurement Group (CMG), the association of system performance professionals responsible for planning, measuring and managing the world’s largest IT infrastructures, is a not for profit, worldwide organization of data processing professionals committed to the measurement and management of computer systems.

The CMG conference is annual international event which is held in December where many performance experts and global companies such as IBM, CA, BMC SOFTWARE, TeamQuest attend to exhibited their performance solutions and technology.

JenniferSoft also attended at ‘2007 JavaOne Conference’ in May and rejoiced a favorable notice in the press. It expects that CMG'07 will be another big opportunity to introduce Jennifer and its new product line worldwide.

For information about CMG Conference, please call Marketing Manager, YoonHee Kim, JenniferSoft (T +82-2-2027-0398, C +82-10-3167-7304, F +82-2-2027-0390). Thanks.

* CMG website: http://www.cmg.org/conference/
* Date: 2nd Dec, 2007~7th Dec, 2007
* Jennifer Booth # : booth # 215

CMG’07 Exhibitors

Alebra Technologies, Inc. • Aptitune Corporation • AQMSolutions, Inc. • BMC Software • CA, Inc. • Computer Management Sciences, Inc. • Compuware Corporation • CPT Global Limited • Demand Technology Software, Inc. • IBM Corporation • IntelliMagic • ISAM • ISM (the Information Systems Manager) • itSMF USA • JenniferSoft • Macro4 • Merrill Consultants • Metron-Athene, Inc. • OPNET Technologies, Inc. • OpTier, Inc. • PerfCap Corporation • SAS Institute Inc. • SeaNet Technologies • Software Diversified Services • Symmetricom • Sysload Software • TeamQuest Corporation • Trident Services, Inc. • Velocity Software, Inc. • z/Journal •

What is APM and why is it necessary?

2007-09-13T11:28:00.000-07:00

Are your WebSphere customers suffering from website performance issue such as system down or delayed transaction response time? Spending more than desirable time and resources troubleshooting web system performance issues? Traditional System Management Solution doesn’t provide adequate information for troubleshooting web system performance issues? Looking for additional ways to generate revenue through new and existing customer base?

Sounds like you need an Application Performance Management (APM) solution for web application servers.

My name is Jason Hong with JenniferSoft Inc, a company that provides WAS APM solution and services for enterprise businesses. I am contact you to share with you about our APM solution for application server, Jennifer® and about business partnership opportunity between Mainline Information System Inc. and JenniferSoft.

What is APM and why is it necessary?

Application Performance Management or APM is the discipline within system management that focuses on monitoring and managing the performance and availability of resources for software application. APM solution is software that provides Application Performance Management services. In the past decades, the Web Application Server (WAS) market has seen significant growth as use of internet in every aspect of our lives has increased exponentially. Until 3~4 years ago, website performance problem has not been so significant overall that a separate APM solution was needed besides the Traditional System Management Solution. Often the website performance issues were resolved by simply adding more hardware or system administrators checking the codes manually, sometimes with self-developed solutions based on tools. But as web traffic became more congested and web systems got more complicated, APM solutions became necessary since the web site performance was causing a big impact on revenue or service level for many companies. Indeed, a study by Infonetics Inc. have found that average medium size companies lose 1% (approx. $1,000,000) of their annual revenue due to downtime or performance problem. Web Systems today has reached a point where simply adding more hardware is not practical (and expensive) and administrators cannot devote all of their time and resources monitoring system for problem and checking massive amount of codes to find and resolve system bottlenecks. Concept of APM solution was born to find a practical and cost effective solution to WAS performance problems.

JenniferSoft and Jennifer

JenniferSoft is a successful software development company from Korea that took over the Korean APM market by storm over international competitions such as CA’s Wily and Symantec’s i3 and we currently hold # 1 APM market share in Korea. We are looking for enterprise software distributor, re-seller, or SI company that provides web application server and related middleware software sales and services, who are interested in establishing a mutually beneficial partnership with JenniferSoft to generate additional revenue and provide invaluable services to WAS customers who are experiencing web system performance problems.

Developed by industry's leading WAS experts, Jennifer is designed to work with many different WAS such as WebSphere, WebLogic, JBoss, Tomcat, any many other web application servers, providing valuable services such as performance monitoring, performance troubleshooting, load controlling, etc., for the web system to ensure 24x7 system stability and maximized system performance. Jennifer features eye-catching comprehensive Dashboard that shows relevant monitoring data and various tools such as "X-View" and "Problem Determination" that assist in finding the root cause and resolving the issue quickly and effectively in real-time. X-view, dashboard interface, and other features in Jennifer are unique and other competing solutions have not yet developed anything like it. X-View is one of the main features we promote heavily because it is great for monitoring and problem solving in practice and we have used it to resolve performance problems for many of our clients. We believe that these features are parts of our arsenal of advantages that will draw positive feedback from the customer.

What mutual benefits can be gained from a business partnership with JenniferSoft?

1) Customer Satisfaction – After spending a ton of money on hardware and software, if the customer’s web system experiences performance problem, how would the it effect the customers? Implementing a quality APM solution ensures that the web system is optimized to output maximum performance, ensuring customer satisfaction. A satisfied customer is likely to comeback for continual business, especially if their web system continues to expand to meet the increasing traffic needs.
2) Sell more hardware and Enterprise Solution – While Jennifer can optimized a web system performance, it cannot replace hardware. That mean a web system can be only optimized as far as the existing hardware will allow. Jennifer has comprehensive capacity planning capability that allows the administrators to see whether there is a need for additional hardware resource. Using Jennifer, our resellers have easily made case for their customers about the needs of additional resource to resolve the performance problem. Since Jennifer can provide clear evidence of needs for more hardware resources, selling additional hardware to customer who needs it gets that much easier. Also, satisfied customers tend to return for more business when their web system expands. Also, we recommend that Jennifer's server portion resides on its on its own machine. Yes, its only needs one and yes, it not a lot but it is still extra revenue.
3) Increase revenue through referral fee or revenue sharing – Jennifer Offers generous incentive for distributors, resellers, and SI companies who refer or sell Jennifer to their new and existing customer. Also, Jennifer is easy to install, support, and use and should only require minimal resources to implement the solution and provide support to ensure high customer satisfaction. Most of all, Jennifer is an awesome solution and customers will recognize the benefit of using Jennifer Immediately. Once customer recognizes Jennifer’s features and benefits, it should be easy to recommend and sell Jennifer to customers. For past success stories, please visit our website.

The APM market seems to be full of well known players such as Symantec i3, CA’s Wily, and Mercury. How do you folks position JenniferSoft against these players?

Currently, APM market has 3 giants that are well known (CA's Wily, Symantec i3, Mercury) and many other smaller companies. However, the APM market is still very new and even the well known APM products by the software giants such as CA and Symantec have not yet fully matured. The standards for the APM solutions has not been yet set; many design flaws and weaknesses exist in current APM solutions, and because of this, there are still debates happening amongst the tech communities today about the potential benefit or value received from implementing an APM solution. Many of today's APM solutions may look fancy and promise to do all kinds of stuff, but in practical use, it is often difficult to implement, cumbersome to use, and don’t offer much help in actually finding the bottleneck and resolution. In that respect, I think that we have a good opportunity to start setting the standard for the market. I believe that our product is on the right path in defining a standard for APM solution as a whole, and we are planning to do our best to promote our software so that people can try it out for themselves and decide on it.

If you are interested in learning more about APM, Jennifer and how partnership with JenniferSoft can benefit your company, please contact me. My contact information can be found below.

Thanks

Jason Hong

TheTrue Value - Customer Satisfaction, Jennifer - The New Paradigm

2007-08-18T14:53:00.000-07:00

Web site visitor is an important target for every internet enabled companies and even public organizations. Just as a nation cannot exist without citizens, the market cannot exist without customers. As we are living in the information era flooded with data, the most promising market is definitely the internet-web market. The size of web market is increasing constantly and customer diversity is also expanding exponentially in the web market.

Then, what object should be pursued by web service industry? This is a quite difficult question but at the same tine, many fresh, original ideas are born daily. For example, meeting consumer needs and increasing customer appeal by providing attractive web site would be one possible answer. However these are not the best idea in terms of business critical issues such as web system performance management. According to Boston Consulting Group, four out of five internet shopping customers have experienced website performance problem while they purchased products through e-commerce website. Among them, 25% never bought the same product again through an online shopping mall and 23% never used the site where they experience performance problem. This means that popular e-shopping malls cannot survive if it has performance problem with their website. Therefore, performance management must be one of main objective for web companies.

However, most web system administrators don’t think about APM solutions carefully in spite of its effectiveness. Meta Group research indicates that only 5-7% among IT companies monitors web site performance and response time using APM solutions. The report from Meta Group, emphasizes that companies need to focus more on web system performance management. According them, “company’s sales, productivity and brand image can be damaged by badly performing web application.” and “IT companies need to set a unified monitoring plan of web application to avoid difference between process and technology that give negative impacts on distributed system environment.” IT companies agree that customer satisfaction is their ultimate aims and APM solution is an important tool to meet consumer satisfaction. However, they sit back and just stick to existing business practices because of fear of possible failure while using APM solution. Web companies are like a herd of Zebras crossing the river full of crocodile, they are all waiting for someone to cross the river first, so that they can make sure it’s safe to cross first.

Unfortunately, APM solutions have not established a solid foundation yet even though it is considered as a new paradigm of web service. It’s because APM market is still in the developing stage and need more time to fully mature. Nevertheless, APM will serve as a new standard to provide valuable web services to many. As web service is more commercialized and become more sophisticated, “performance guarantee” will be a requirement for customer satisfaction. Now is time to run across the river for customer like a heard zebras crossing river for grassy field.

Sun Ho Kim

Response Time Scatter Graph (X-View)

2007-08-18T12:54:00.000-07:00

Service response time is one of most important factor in determining website visitor’s satisfaction level. While it is important to prevent system downtime, preventing system crashes alone isn’t enough for today’s web system management and administration. Website visitors must be able to surf through the site with ease and visitor waiting time and site loading time must be minimized. Website with slow response time tends to frustrate website visitors and it is one of leading cause of deterioration in customer satisfaction level, and ultimately, loss of the customers. Thus, service response time must be considered in customer satisfaction and website administrator much continually work to improve service response time, prioritizing services that are most frequently accessed.
The traditional graph used for monitoring respone time has been the line graph of avaerage reponsetime over time.

However, the traditional line graph cannot convey any more information than the response time itself. Line graph cannot show if there is a specific performance problem, or if there is overall increase in response time (ex: due to network issue) or if only certain services are receiving overwhelming requests, etc… furthermore, line graph is ineffective in discovering which service is experiencing problem, or the root cause of the crawling response time.

Monitoring Response Time with Scatter Graph...
Thus, response time must be monitored in a single graph while individual service transactions plotted serparately. In order to express individual service transactions in a single graph, line graph is not appropriate but scatter graph must be used.

Response Time Monitoring

We call this type of graph Response Time Scatter Graph, aka X-View. The entire history of service transaction can be monitored in a single graph and if any one or group of service transaction is selected, detailed information concerning selected transaction (Method Call Path, SQL, Socket, File etc…), is displayed in a separate window.

While, the concept of using scatter graph to display service transaction, and drag-and-drop feature to see the individual transaction detail is revolutionary, this is not the only advantage that the X-View offers to the users. While monitoring, if there are any performance problem in the WAS or related systems, the problem typically is expressed as a specific pattern in the X-View. The pattern found in the scatter graph provides important information about the monitored WAS
system to the user.

Please see below for the examples of scatter graph pattern typically encountered and their descriptions.

Vertical Streaming Pattern

As if slowly pouring water from a kettle, the service transactions line up vertically.

This phenomenon describes situation where transactions called by different service requests experience delayed response time due to shortage of the same system resource. For example, when many different transactions are effected by single database lock, a vertical streaming pattern is formed.
Finding the common factor within this pattern is relatively easy. If the plotted dots in this pattern are from multiple different WAS instances, it is usually due to problem with a system resource outside of the WAS, and if the plotted dots are from a single WAS instance, then it is due to system resource within the WAS. Also, if the plotted dots are from the same service request, the shared resource within the application (usually DB) is the problem.

During web system tuning, administrator should give priority to transactions in vertical streaming pattern than any one plotted dot with extremely high response time. A single dot with delayed response time may have its own specific issues, but a group of lined up transactions may indicate significant problem within the entire system.

Layered Cake Pattern

As throughput increases, horizontal lines may form in X-View. If there is no relationship between increase in throughput and increase in number of horizontal lines, then this pattern is not applicable. Multiple applications with frequent service request may also form a horizontal line, but in this case, even if the throughput increases, the number of horizontal line will not increase along with it.

Layered Cake pattern is a phenomenon that can be seen when many transactions are forced to wait for same amount of time until a shared resource becomes available. As throughput increases, the probability of waiting becomes higher and the response time becomes longer; the response time becomes longer uniformly across all transaction that uses shared resource thus the horizontal lines form in X-View. In this case, just investigating whether the transactions in the line come from the same WAS instance, can provide important clue in finding the root cause of the problem. In addition, looking for resources with parameter that indicate wait time (the time difference between one layer and the next) is also necessary.

Matrix Pattern

Named after the opening scene of the movie Matrix, this phenomenon describes pattern where many short vertical (and sometimes horizontal) lines are spread all over the screen.

It can be seen when a resource bottleneck causes problem only for some of the application, and when it happens evenly spread out over time.

An example is while DirtyRead is not allowed in the DB, there exists lock that is higher level than READ_COMMITTED at least. Matrix pattern does not happen due to just a single resource issue, it is not associated with typical H/W resource problem; it’s been observed in environment with Sybase or MS-SQL database. Once Matrix pattern is observed, the problem cannot be resolved without adjusting the LOCK LEVEL of the entire database. Fundamental adjustment of LOCK LEVEL and consequential adjustment of application is inevitable.

Waterfall Pattern

The plotted dots resemble series of water falls. Waterfall pattern can be seen when a specific resource experience shortage or lock suddenly then becomes normal again, and then the pattern repeats multiple times.

There seems to be no indication that the throughput or response time suddenly increase at the time when Waterfall pattern appears. But the requests that call on the problem resource must have been increased. In this case, the applicable resource usage is not proportionate to the overall response time until the resource is depleted; the Waterfall pattern occurs when at the point when the resource is depleted. Another characteristic is that while amidst of the pattern, short transactions less than 3 seconds can be seen. This means that the problem resource responsible for the Waterfall pattern is not one that is used by the entire application.

Waterfall patterns, as seen in second screenshot, share fixed height as one of its characteristic. Waterfall pattern occurs when resources that are used for a short time is depleted suddenly (Full, Overflow), and the services are suspended temporarily until the necessary resource is refreshed and suspension is released.

Conclusion

Response Time Scatter Graph is direct and powerful. User will feel that using Response Time Scatter Graph is more effective than using several line graph combined.

Lastly, screenshots below are two type of graph captured from same production system at the same time.

Do you feel that the red box indicate some sort of performance problem? Do they make you want to investigate them?

How about the next graph? Do you want to find out which transaction is represented by each plotted dots?

This the strength of the Response Time Scatter Graph.

Response Time & Performance

2007-08-18T12:42:00.000-07:00

Why Monitor Service Response Time?

In Web Application Server, service response time can be expressed as measurement of customer satisfaction. Even if there exist some bugs in a system, if the bug does not cause any problem in service response time or site’s functionality, it cannot be seen as a problem. As such, even if there is no bug found in the system, if the service response time is not fast enough to fulfill customer satisfaction, the system itself has a problem and cannot be considered normal.
Service response time is an important information source in measuring system’s stability and diagnosing system problems. Following documentation describes using service response time to resolve system performance issues and why monitoring the system resource alone is correct approach.

Resource Usage Cannot Exceed 100%

System resource usage cannot exceed 100%. This means that system resource usage cannot be used to diagnosis system capacity. Let’s take look at a situation where vmstat is being used to monitor CPU usage. CPU usage is constantly very high, 95~100%. Is this a problem? Most system administrators cannot determine if this is a problem. All they can say is that the CPU is being used heavily. The administrators cannot determine whether the number of incoming requests exceed system capacity just by monitoring the system resources alone. For example, lets say that it takes 20 concurrent request to max out the CPU usage of a WAS server. What if there are 30 concurrent requests? Whether there are 20 or 30 requests, the CPU usage will 100% in both cases. Of course administrator usually cannot tell how many concurrent incoming requests will max out system resource.

Monitoring all system resources is an inefficient.

Another limitation of resource monitoring is that there are too many things to monitor.
In any given system, there exist many H/W and S/W related resources such as CPU, Memory, NET, HEAP, Connection Pool, etc…; it is inefficient (also probably impossible) to monitored all these system resources individually and its is not really necessary neither.

Incoming requests exceeding system capacity results in delayed response time.

In order to overcome the limitations of system resource monitoring, service response time must be monitored. As the incoming requests exceed system capacity, service response time is increased indefinitely, letting administrators know that resource shortage exists within the system. Since response time increases if any system resource is lacking, response time can be used to monitor system resource.

Response time must be measured per transaction.

Then how should service response time be measured? Before discussing this point, let’s look at the relationship between service and the resource. In a web system, service may interact with many different components such as class, DB, LDAP, file, etc… and when the different system resources that are tied to each component is combine, that number can be very large. Also, resources are only used by specific requests while others may be used by many different services. To conclude, the relationship between resource and service is N:M relation and it cannot be clearly defined. The N:M relationship between services and resources are only expressible as average response time grouped by service name or functional category in a line graph. Instead the individual transaction must be plotted separately.

There are a few reasons why Jennifer monitors service response time individually rather than in groups.

First, when identical services are executed multiple times, the response time may be delayed for specific transactions only. No matter how the grouping is done, the individual service response time will be diluted if it is averaged out with other services in the group. Secondly, there is mapping issue between response time and profiling. If the grouping is done by service name, the mapping would somewhat make sense, but if the mapping is done by business object, the mapping will be too complicated to be used effectively. Thirdly, Service cannot be classified easily by name. Since service name is determined by the initial request that called it, it does not capture the internal changes that occur during its process. Grouping different services with that has changes dynamically during its process simply because they share the same service name is not very effective way to group the services.

Jennifer can show response time per individual transaction in a single view

Jennifer’s X-View offers direct and powerful way to monitor performance issue. The ability to see all services’ individual response time and its detail in one view is more effective than using many different views or graphs combined. Resource shortage is shown as delay in response time in X-View, and the plotted dots form patterns depending on the issue at hands thus users can benefit from this view compared to other solutions.

User can also feel the benefit that Jennifer offers in its speed. Tasks that may hours/minutes with other solutions take only minutes/seconds in with Jennifer’s X-View.

Jennifer

2007-08-14T23:26:00.000-07:00

Application Performance Management Solution

JENNIFER

Enterprise Web Business Monitoring

THE MOST EXCELLENT CHOICE

FOR J2EE PERFORMANCE MANAGEMENT

The tremendous growth in e-business sector over the past decade

has induced the IT infrastructures of many companies to become

increasingly complex. The increasing complexity in IT infrastructure

has resulted in diminishing marginal return of IT investment for many

companies due to the often inefficient and incompatible integration

of different system components in a multi-tiered system environment.

Result is frequent server downtimes, inefficient use of IT

resources, deteriorating system performance, and a general inability to

forecast future system usage to timely adjust for ever changing volume of

incoming data. While companies are spending significant amount of

monetary and human resources for development of their IT

infrastructure, they are often unable to redeem equitable return for

their investments due to these issues. Ever-increasing data and

system complexity, combined with server performance problems are

causing significant delays in customer service response times,

resulting in reduced customer satisfaction and missed opportunity

in revenue generation. Finding the root causes of these problems are also

not an easy task because of the complexity of today’s multi-tier

system environments which may include many different types
of web servers such as

WAS (web application server), databases, and various other

integrated applications.

JenniferSoft’s newest Application Performance

Management (APM) solution,

JENNIFER has been specifically

developed to provide a unified

management for today’s complex e-business system

by applying its methodology to the life cycle of targeted

infrastructure. Jennifer can diagnose and recommend

solutions for system performance problem as well as

prevent future system problems.

JENNIFER is capable of real-time

WAS performance monitoring,

cause-analysis and resolution recommendation for existing

performance issues, application SQL query optimization/tuning,

intelligent load-balancing for connection counts and system

resource requirements, system capacity estimation and forecast of

future usage quantified with evidentiary data, user customizable

menu, intuitive dashboard for accessible display of data, automatic

alert system to provide effective status updates to end-user, and

business data monitoring for overall business analysis.

J2EE/WAS SYSTEM MONITORING

Jennifer is capable of real-time monitoring for J2EE (Java2

Enterprise Edition)/WAS systems, expeditious diagnosis of

performance barriers, integration system control and end-to-end

service monitoring.

INTEGRATED IT SERVICES DASHBOARD

Beyond providing application performance data, Jennifer is also

able to provide end-to-end comprehensive monitoring of systems,

networks, databases, WAS servers, and TP (transactional process)

using optional adaptors based on “Adaptable Framework Technology”.

Furthermore, Jennifer is capable of monitoring all types of

data needed for overall business analysis and can also provide

core infrastructure for ITSM integrated dashboard and AMS

system.

REAL-TIME PERFORMANCE MONITORING

Jennifer’s intuitive monitoring screen combines different types of

information into one easily accessible display. When Jennifer

identifies any performance issue, featured automatic alert

system is used to communicate the system issue to system

administrators and other end-users. Jennifer is also capable of

communicating with back-end systems (CICS, TUXEDO) and

interpreting DBMS SQL query history to identify the exact location and

cause of the issue encountered down to the exact

class/method.

PERFORMANCE PROBLEM DETERMINATION

Possessing vast library of system performance issues and

solutions collected over many years by our system performance

analysts and consultants, Jennifer can utilize this knowledge to

provide relevant clues and recommendations to the system

administrators, so that they can accurately and timely determine

the cause of the issues encountered and provide counter-measures
to correct the problems.

APPLICATION / SQL QUERY TUNING

Jennifer can track response times, CPU usage, and others system

critical information for active applications per each class/method,

thus identifies which specific module is experiencing the

performance problems.

CONFIGURABLE DASHBOARD

The dashboard can be customized by drag & drop feature,

moving desirable topic/category into the integrated monitoring screen.

The customized dashboard can be saved as templates per user or

user type (i.e. manager, administrator, team leader).

CUSTOMIZABLE REPORTS

Jennifer can provide statistical data for service information such as

number of connections, response times, system resource usage,

service call records, SQL transaction history, back-end transaction

history, etc... Stored data can be used for second level processing

and displayed in visually effective charts, diagrams,

and graphs in a separate screen. Using user customizable optional

report templates, Jennifer can output various informative

performance reports in Rich Formatted report files.

HIGHLIGHTS

● Real-time WAS system performance monitoring

● Performance barrier root-cause analysis

● Application and SQL query tuning

● Elapsed time and CPU usage tracing per class/method

● Automatic load-balancing for sudden change in service level

● Web, WAS, TP, DB integration monitoring via single display

● Reporting capability based on user defined templates

● CICS/TUXEDO and other TP monitoring support

● Database monitoring support

● Quantified data for capacity planning

● User customizable displays

● Customizable menu and configurable dashboard per user type

BENEFITS

Jennifer can ensure stability of client system servers by providing

real-time monitoring in all aspects of IT service operations via single

unified view. Jennifer can minimize downtime and provide

progressive monitoring through prevention of performance barriers,

thus ensures minimized operational risk. Through continual
collection and analysis of quantified performance data, Jennifer can
assist in allocating sufficient resources to critical systems as preventive measure,
rather than merely adjusting to rectify already transpired system performance failures.
Jennifer can reduce TCO via advanced
performance optimization, preventing misusage of system resources.

Minimizing System Downtime
When a system performance problem occurs, Jennifer immediately
and speedily determines the root cause and recommends a
solution. That contributes to minimize system downtime and ensures
operational stability.

Automatic Alert System
Through intuitive system monitoring, Jennifer can predict potential
system performance problems that may occur in the future and
automatically alert system users appropriately to prevent such
problems from ever happening.

Quantified System Performance Data
By collecting information such as connection counts, user counts,
system resource usage, and other statistical performance data,
Jennifer can provide quantified evidentiary data needed for planning
system expansion and application tuning.

Satisfactory Customer Service
Jennifer provides peerless service to customers, achieving consistent
and stable system operational environment by minimizing
system downtime, enabling immediate response to system
performance issues, and load-balancing to prevent service level
deterioration due to sudden flux of system usage.

Integrated Performance Management
Services such as WAS system performance monitoring,
TUXEDO/CICS including TPM monitoring, system resource, and other
user defined business data monitoring is available to users through
simple, efficient, integrated dashboard by providing user collective
control over system performance.

Minimizing TCO

TCO can be reduced by minimizing system downtime, preventing
future performance issues, maximizing system performance via
application tuning, and optimizing usage of IT infrastructure and
human resources.

TECHNICAL SPECIFICATIONS

Application Servers

● BEA WebLogic 5.1, 6.x, 8.x, 9.x

● IBM WebSphere Application Server 3.5, 4.x, 5.x, 6.x

● Tmaxsoft JEUS 3.x, 4.x , 5.x

● Oracle Application Server 9iAS, 10gAS, OC4J, ERP

● SUN Application Server 7.x, 8.x

● Fujitsu Interstage 5.x, 6.x, 7.x

● Hitachi Cosminexus 7

● Sybase EAServer 4.x, 5.x

● Macromedia JRun 4.x

● Apache Jakarta Tomcat 3.x, 4.x, 5.x

● Caucho Technology Resin 2.x, 3.x

● Evermind JBoss Application Server 3.x, 4.x

● Apache Jserv

Operating Systems

● AIX 4.3.3, 5.x 32bit, 64bit

● HP-UX 11.x 32bit, 64bit, HP-UX Itanium 64bit

● Sun Solaris 2.8, 2.9 32bit, 64bit,x68

● Intel Linux 32bit, Redhat AS Itanium 64bit

● Compaq Tru64 UNIX OSF1

● Microsoft Windows NT 4.0, 2000, XP, 2003, Vista

● IBM iSeries(AS400) for WebSphere

● IBM z/OS for WebSphere,

● Linux

Why Jennifer?

2007-08-13T11:20:00.000-07:00

Why does everyone talk about Jennifer? Out of many Java application monitoring solutions in existence, the reason why Jennifer stands out is because it utilizes its own unique and revolutionary concept. Jennifer, created by the field engineers with years of performance tuning experience, has something that no other solutions have.

1. Real-Time Monitoring

Then how is Jennifer’s real-time monitoring better than that of other solutions? Jennifer is a better solution because it offers real-time data on categories that other solutions do not offer.

Jennifer provides service status, visit users and concurrent user count, throughput, resource status, and other important information in real-time.

One item that really stands out is the real-time active service data. The change in number of active service and its status is very significant. When the number of active services increase, it typically means that the number of service that are processing requests from users have increased; typically this mean that the service response time has become longer, thus more services are need to process the same number of incoming requests, rather than the number of incoming requests have increased. Even if request increases, if the service response speed approaches to 0, the number of active services approaches close to 0, and even if the number of request are low, if the response time is relatively low, the number of active services becomes close the number of concurrent users. As you can see, the active service status is one of important data that can be used to analyze system status.

Jennifer can directly monitor services during its progress instead of monitoring them after they end. In that respect, Jennifer is more effective than other solutions.
Important factor in real-time monitoring is its analysis capability. Just because a monitoring solution displays tens or hundreds of monitoring data in real-time doesn’t mean that the user will use the given information correctly or effectively. The data must be organized and presented to the user in a meaningful way and with minimum number of clicks (or time to display the data) for it to be effective. Jennifer dashboard’s Engineer’s View is setup to show all monitoring data needed to directly analyze the web system within 3 mouse clicks. The dashboard can be customized according to customer preference if needed.

2. Response Time Scatter Graph

System performance issue should be analyzed through response time. When monitoring service response time, service profiling must also be monitored. One of the characteristic of Jennifer concerning service response time is that all the service response time is monitored individually. In other competing solutions, response time is typically grouped by service type or time (ex: 30 sec or more).

There are a few reasons why Jennifer monitors service response time individually rather than in groups.

First, when identical services are executed multiple times, the response time may be delayed for specific transactions only. No matter how the grouping is done, the individual service response time will be diluted if it is averaged out with other services in the group.
Secondly, there is mapping issue between response time and profiling. If the grouping is done by service name, the mapping would somewhat make sense, but if the mapping is done by business object, the mapping will be too complicated to be used effectively
Thirdly, Service cannot be classified easily by name. Since service name is determined by the initial request that called it, it does not capture the internal changes that occur during its process. Grouping different services with that has changes dynamically during its process simply because they share the same service name is not very effective way to group the services.

3. Enterprise Point of View (User, File,Socket, SQL param etc…) Monitoring Concept

System Monitoring
In enterprise system, tracking the system user related information is important. What is the website visitor count? How many people are using the site currently? What is the concurrent user count and the throughput? These information need to be quantified and analyzed in order to find the system capacity and tune the system to its optimal point of usage. Jennifer is the perfect tool in answering above questions and concerns. Jennifer’s strength lies in that it doesn’t just evaluate above information in java system point of view, but also in enterprise system point of view.
Transaction Profiling
Enterprise information system is different in many aspect compared to PC game or application. The number of user is much greater and the speed or stability of system is important and most of the data processed are Critical to operation. To monitor enterprise system, the focus must not the service transaction flow instead of the website code. Jennifer puts its monitoring focus on file, socket, SQL, and others instead of the site code.

4. Easy & Powerful

EASY

Monitoring solution must be easy to use. This point obviously applies to all types of software, but it is especially important for monitoring solutions. Because system administrator must have expert knowledge on many different S/W and H/W, spending additional time learning to use a monitoring solution is not realistic. Jennifer is a tool designed to be used by both administrator and developer, and it is currently being used by both party. Even a notice user can learn to use Jennifer with just a few minutes of instruction.
POWERFUL

A monitoring solution cannot be just easy to use; it must also provide applicable information in a effective fashion. The monitoring solution must be easy enough to use for a novice user and it must be able to provide detailed information to expert user as well. Jennifer provides advanced data that was not considered to be important by other APM solution such as Socket OPEN, File usage, JDBC resource, etc… Jennifer allows user to customize the monitoring categories via monitoring framework (ADF), and administrator can utilize these function to effectively monitor and troubleshoot their system.

by Sung Jo kim