Speaker: Darlene Nerden, IBM
Overview: In this session will review the Maximo architecture and factors that influence performance. We will discuss some details for those factors regarding tuning for a performance impact. We will look at troubleshooting tools and Maximo settings to help identify and resolve a Maximo performance issue.
IBM Maximo Asset Management Training - Asset and Work Management for Chang Sh...Duane Aritonang
Work Management is designed to cover all of the applications that would be necessary for maintenance/asset management professionals in their work roles.
The applications covered include the MAXIMO 7 Environment, Navigation, Locations, Assets (Equipment), Work Orders (creation, planning and reporting of actual charges) and Failure Classifications.
In addition, the Work Planning components are included which focuses on the roles of Maintenance Craft Leads, Planners and Supervisors.
Rail, Metro and Monorail Networks
Industry Trends –Rolling Stock Challenges
IBM Maximo Solutions for Metro and Rail
Critical Capabilities of Maximo for Transportation
Maximo for Transportation 7.5 Features
Critical Capabilities of Maximo Asset Configuration Manager (ACM)
Maximo Asset Configuration Manager (ACM) 7.5 Features
Maximo integration to other systems by Bashar MahasenBashar Mahasen
The presentation shows Standard Maximo integration adapters along with well-established integration's implemented with Maximo.
It also goes through Maximo Integration framework (MIF) and available reports integration for Maximo 7.5
Speaker: Kim Woodbury, IBM
Overview: This session will provide insights into the strategic direction for Maximo, and the product roadmap. There will be a focus on the next years deliverables across the portfolio, including areas such as mobility and business intelligence. Also learn how to better interact with support and the tools and resources that are available as you look to troubleshoot and maintain Maximo.
In order to obtain the best performance possible out of your AEP server, the core architecture provides methods to reuse job processes multiple times. This talk will cover how the mechanism functions, what performance improvements you might expect as well as what potential problems you might encounter, how to use pooling in protocols and applications, and how the administrator or package developers can configure and debug specialized job pools for their particular applications
Grails has great performance characteristics but as with all full stack frameworks, attention must be paid to optimize performance. In this talk Lari will discuss common missteps that can easily be avoided and share tips and tricks which help profile and tune Grails applications.
IBM Maximo Asset Management Training - Asset and Work Management for Chang Sh...Duane Aritonang
Work Management is designed to cover all of the applications that would be necessary for maintenance/asset management professionals in their work roles.
The applications covered include the MAXIMO 7 Environment, Navigation, Locations, Assets (Equipment), Work Orders (creation, planning and reporting of actual charges) and Failure Classifications.
In addition, the Work Planning components are included which focuses on the roles of Maintenance Craft Leads, Planners and Supervisors.
Rail, Metro and Monorail Networks
Industry Trends –Rolling Stock Challenges
IBM Maximo Solutions for Metro and Rail
Critical Capabilities of Maximo for Transportation
Maximo for Transportation 7.5 Features
Critical Capabilities of Maximo Asset Configuration Manager (ACM)
Maximo Asset Configuration Manager (ACM) 7.5 Features
Maximo integration to other systems by Bashar MahasenBashar Mahasen
The presentation shows Standard Maximo integration adapters along with well-established integration's implemented with Maximo.
It also goes through Maximo Integration framework (MIF) and available reports integration for Maximo 7.5
Speaker: Kim Woodbury, IBM
Overview: This session will provide insights into the strategic direction for Maximo, and the product roadmap. There will be a focus on the next years deliverables across the portfolio, including areas such as mobility and business intelligence. Also learn how to better interact with support and the tools and resources that are available as you look to troubleshoot and maintain Maximo.
In order to obtain the best performance possible out of your AEP server, the core architecture provides methods to reuse job processes multiple times. This talk will cover how the mechanism functions, what performance improvements you might expect as well as what potential problems you might encounter, how to use pooling in protocols and applications, and how the administrator or package developers can configure and debug specialized job pools for their particular applications
Grails has great performance characteristics but as with all full stack frameworks, attention must be paid to optimize performance. In this talk Lari will discuss common missteps that can easily be avoided and share tips and tricks which help profile and tune Grails applications.
How to get the maximum performance from your AEP server. This will discuss ways to improve execution time of short running jobs and how to properly configure the server depending on the expected number of users as well as the average size and duration of individual jobs. Included will be examples of making use of job pooling, Database connection sharing, and parallel subprotocol tuning. Determining when to make use of cluster, grid, or load balanced configurations along with memory and CPU sizing guidelines will also be discussed.
Work with hundred of hot terabytes in JVMsMalin Weiss
Third-party updates to the database can cause Hazelcast applications to work with data which is out-of-date.
By synchronizing with an underlying database using an SQL Reflector, the Hazelcast Maps will be “alive” and change whenever the underlying data changes. The solution can also automatically derive domain models directly from the database schemas, so that you can start using the solution very quickly and handle extreme volumes of data.
Java one2015 - Work With Hundreds of Hot Terabytes in JVMsSpeedment, Inc.
Presentation Summary: By leveraging on memory mapped files, the Chronicle Engine supports large maps that easily can exceed the size of your server’s RAM, thus allowing application developers to create huge JVM:s where data can be obtained quickly and with predictable latency. The Chronicle Engine can be synchronized with an underlying database using Speedment so that your in-memory maps will be “alive” and change whenever data changes in the underlying database. Speedment can also automatically derive domain models directly from the database so that you can start using the solution very quickly. Because the Java Maps are mapped onto files, the maps can also be shared instantly between several JVM:s and when you restart a JVM, it may start very quickly without having to reload data from the underlying database. The mapped files can be hundreds of terabytes which has been done in real world deployment cases.
How to Integrate Hyperconverged Systems with Existing SANsDataCore Software
Hyperconverged systems offer a great deal of promise and yet come with a set of limitations.
While they allow enterprises to re-integrate system components into a single enclosure and reduce the physical complexity, floor space and cost of supporting a workload in the data center, they also often will not support existing storage in local SANs or offered by cloud service providers.
However, there are solutions available to address these challenges and allow hyperconverged systems to realize their promise. Sign up to discover:
• What are hyperconverged systems?
• What challenges do they pose?
• What should the ideal solution to those challenges look like?
• A solution that helps integrate hyperconverged systems with existing SANs
This technical presentation by EDB Dave Thomas, Systems Engineer provides an overview of:
1) BGWriter/Writer Process
2) Wall Writer Process
3) Stats Collector Process
4) Autovacuum Launch Process
5) Syslogger Process/Logger process
6) Archiver Process
7) WAL Send/Receive Processes
Hadoop Summit SJ 2016: Next Gen Big Data Analytics with Apache ApexApache Apex
This is an overview of architecture with use cases for Apache Apex, a big data analytics platform. It comes with a powerful stream processing engine, rich set of functional building blocks and an easy to use API for the developer to build real-time and batch applications. Apex runs natively on YARN and HDFS and is used in production in various industries. You will learn more about two use cases: A leading Ad Tech company serves billions of advertising impressions and collects terabytes of data from several data centers across the world every day. Apex was used to implement rapid actionable insights, for real-time reporting and allocation, utilizing Kafka and files as source, dimensional computation and low latency visualization. A customer in the IoT space uses Apex for Time Series service, including efficient storage of time series data, data indexing for quick retrieval and queries at high scale and precision. The platform leverages the high availability, horizontal scalability and operability of Apex.
Intro to Apache Apex - Next Gen Platform for Ingest and TransformApache Apex
Introduction to Apache Apex - The next generation native Hadoop platform. This talk will cover details about how Apache Apex can be used as a powerful and versatile platform for big data processing. Common usage of Apache Apex includes big data ingestion, streaming analytics, ETL, fast batch alerts, real-time actions, threat detection, etc.
Bio:
Pramod Immaneni is Apache Apex PMC member and senior architect at DataTorrent, where he works on Apache Apex and specializes in big data platform and applications. Prior to DataTorrent, he was a co-founder and CTO of Leaf Networks LLC, eventually acquired by Netgear Inc, where he built products in core networking space and was granted patents in peer-to-peer VPNs.
Datadog: a Real-Time Metrics Database for One Quadrillion Points/DayC4Media
Video and slides synchronized, mp3 and slide download available at URL http://bit.ly/2mAKgJi.
Ian Nowland and Joel Barciauskas talk about the challenges Datadog faces as the company has grown its real-time metrics systems that collect, process, and visualize data to the point they now handle trillions of points per day. They also talk about how the architecture has evolved, and what they are looking to in the future as they architect for a quadrillion points per day. Filmed at qconnewyork.com.
Ian Nowland is the VP Engineering Metrics and Alerting at Datadog. Joel Barciauskas currently leads Datadog's distribution metrics team, providing accurate, low latency percentile measures for customers across their infrastructure.
There are many computational paradigms that could be used to harness the power of the herd of computers. In financial services, a share-nothing approach could be used to speed up CPU intensive calculations while the hierarchal nature of rollups requires tight synchronization. Some interesting use cases are:
In Wealth Management, the SQL approach is traditionally used, but it lacks efficient support of hierarchal structures, iterative calculation, and provides limited scalability. Unlike traditional, centralized scale-up enterprise systems, an in-memory-based architecture scales out and takes advantage of cost-effective high volume commodity hardware that maximizes compute power efficiently. It makes the user experience better by speeding up response time utilizing distributed implementation of calculation algorithms. OData enables DaaS to expose financial data and calculation capabilities.
In the insurance industry, in-memory computing was used for Monte-Carlo to estimate the value of life insurance policies. This is a very CPU-intensive task, which requires 2000 cores to build ~1 million simulated policies in 30 minutes (about 25 trillion numbers or 100TB of data), which then aggregates and compresses into 40GB of data for analysis.
To speed up CPU-intensive iterative financial calculations, we use a share-nothing approach while the hierarchal nature of rollups requires tight synchronization. Several algorithms that are typical for the financial industry, different approaches on distribution and synchronization, and the benefits of in-memory data grid technologies will be discussed.
IBM BIM and Maximo: Values for Owners and OperatorsFMMUG
Speakers: Kawan Park and Derek Fu, IBM
Overview: With rapid worldwide BIM (Building Information Modelling) adoption, more owners and operators are taking advantage of the BIM data in operation and maintenance cycle of their assets. This session will cover an overview of how Maximo leverages BIM to create additional values for the owners and operators.
Introduction to IBM Watson IoT for Predictive Maintenance and Optimization with Maximo
Speaker: Andrew Condos, IBM
Overview: Optimizing asset performance is crucial to the cost effective and efficient operation of asset-intensive organizations. Scheduled maintenance procedures help to achieve this goal, but the key to unlocking real productivity improvements is in predicting how an asset operates over its entire life-cycle.
This session will introduce you to how companies are using IBM Watson IoT Predictive Maintenance and Optimization with Maximo to identify and manage asset reliability risks that could adversely affect plant or business operations. IBM PMO with Maximo applies machine learning to prescribe actions based on predictive scoring, identifies factors that positively and negatively influence asset health and delivers a detailed comparison of historical factors affecting asset performance.
How Recreation Management Software Can Streamline Your Operations.pptxwottaspaceseo
Recreation management software streamlines operations by automating key tasks such as scheduling, registration, and payment processing, reducing manual workload and errors. It provides centralized management of facilities, classes, and events, ensuring efficient resource allocation and facility usage. The software offers user-friendly online portals for easy access to bookings and program information, enhancing customer experience. Real-time reporting and data analytics deliver insights into attendance and preferences, aiding in strategic decision-making. Additionally, effective communication tools keep participants and staff informed with timely updates. Overall, recreation management software enhances efficiency, improves service delivery, and boosts customer satisfaction.
First Steps with Globus Compute Multi-User EndpointsGlobus
In this presentation we will share our experiences around getting started with the Globus Compute multi-user endpoint. Working with the Pharmacology group at the University of Auckland, we have previously written an application using Globus Compute that can offload computationally expensive steps in the researcher's workflows, which they wish to manage from their familiar Windows environments, onto the NeSI (New Zealand eScience Infrastructure) cluster. Some of the challenges we have encountered were that each researcher had to set up and manage their own single-user globus compute endpoint and that the workloads had varying resource requirements (CPUs, memory and wall time) between different runs. We hope that the multi-user endpoint will help to address these challenges and share an update on our progress here.
SOCRadar Research Team: Latest Activities of IntelBrokerSOCRadar
The European Union Agency for Law Enforcement Cooperation (Europol) has suffered an alleged data breach after a notorious threat actor claimed to have exfiltrated data from its systems. Infamous data leaker IntelBroker posted on the even more infamous BreachForums hacking forum, saying that Europol suffered a data breach this month.
The alleged breach affected Europol agencies CCSE, EC3, Europol Platform for Experts, Law Enforcement Forum, and SIRIUS. Infiltration of these entities can disrupt ongoing investigations and compromise sensitive intelligence shared among international law enforcement agencies.
However, this is neither the first nor the last activity of IntekBroker. We have compiled for you what happened in the last few days. To track such hacker activities on dark web sources like hacker forums, private Telegram channels, and other hidden platforms where cyber threats often originate, you can check SOCRadar’s Dark Web News.
Stay Informed on Threat Actors’ Activity on the Dark Web with SOCRadar!
Check out the webinar slides to learn more about how XfilesPro transforms Salesforce document management by leveraging its world-class applications. For more details, please connect with sales@xfilespro.com
If you want to watch the on-demand webinar, please click here: https://www.xfilespro.com/webinars/salesforce-document-management-2-0-smarter-faster-better/
Cyaniclab : Software Development Agency Portfolio.pdfCyanic lab
CyanicLab, an offshore custom software development company based in Sweden,India, Finland, is your go-to partner for startup development and innovative web design solutions. Our expert team specializes in crafting cutting-edge software tailored to meet the unique needs of startups and established enterprises alike. From conceptualization to execution, we offer comprehensive services including web and mobile app development, UI/UX design, and ongoing software maintenance. Ready to elevate your business? Contact CyanicLab today and let us propel your vision to success with our top-notch IT solutions.
How to Position Your Globus Data Portal for Success Ten Good PracticesGlobus
Science gateways allow science and engineering communities to access shared data, software, computing services, and instruments. Science gateways have gained a lot of traction in the last twenty years, as evidenced by projects such as the Science Gateways Community Institute (SGCI) and the Center of Excellence on Science Gateways (SGX3) in the US, The Australian Research Data Commons (ARDC) and its platforms in Australia, and the projects around Virtual Research Environments in Europe. A few mature frameworks have evolved with their different strengths and foci and have been taken up by a larger community such as the Globus Data Portal, Hubzero, Tapis, and Galaxy. However, even when gateways are built on successful frameworks, they continue to face the challenges of ongoing maintenance costs and how to meet the ever-expanding needs of the community they serve with enhanced features. It is not uncommon that gateways with compelling use cases are nonetheless unable to get past the prototype phase and become a full production service, or if they do, they don't survive more than a couple of years. While there is no guaranteed pathway to success, it seems likely that for any gateway there is a need for a strong community and/or solid funding streams to create and sustain its success. With over twenty years of examples to draw from, this presentation goes into detail for ten factors common to successful and enduring gateways that effectively serve as best practices for any new or developing gateway.
Globus Compute wth IRI Workflows - GlobusWorld 2024Globus
As part of the DOE Integrated Research Infrastructure (IRI) program, NERSC at Lawrence Berkeley National Lab and ALCF at Argonne National Lab are working closely with General Atomics on accelerating the computing requirements of the DIII-D experiment. As part of the work the team is investigating ways to speedup the time to solution for many different parts of the DIII-D workflow including how they run jobs on HPC systems. One of these routes is looking at Globus Compute as a way to replace the current method for managing tasks and we describe a brief proof of concept showing how Globus Compute could help to schedule jobs and be a tool to connect compute at different facilities.
Experience our free, in-depth three-part Tendenci Platform Corporate Membership Management workshop series! In Session 1 on May 14th, 2024, we began with an Introduction and Setup, mastering the configuration of your Corporate Membership Module settings to establish membership types, applications, and more. Then, on May 16th, 2024, in Session 2, we focused on binding individual members to a Corporate Membership and Corporate Reps, teaching you how to add individual members and assign Corporate Representatives to manage dues, renewals, and associated members. Finally, on May 28th, 2024, in Session 3, we covered questions and concerns, addressing any queries or issues you may have.
For more Tendenci AMS events, check out www.tendenci.com/events
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I ...Juraj Vysvader
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I didn't get rich from it but it did have 63K downloads (powered possible tens of thousands of websites).
Field Employee Tracking System| MiTrack App| Best Employee Tracking Solution|...informapgpstrackings
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May Marketo Masterclass, London MUG May 22 2024.pdfAdele Miller
Can't make Adobe Summit in Vegas? No sweat because the EMEA Marketo Engage Champions are coming to London to share their Summit sessions, insights and more!
This is a MUG with a twist you don't want to miss.
Paketo Buildpacks : la meilleure façon de construire des images OCI? DevopsDa...Anthony Dahanne
Les Buildpacks existent depuis plus de 10 ans ! D’abord, ils étaient utilisés pour détecter et construire une application avant de la déployer sur certains PaaS. Ensuite, nous avons pu créer des images Docker (OCI) avec leur dernière génération, les Cloud Native Buildpacks (CNCF en incubation). Sont-ils une bonne alternative au Dockerfile ? Que sont les buildpacks Paketo ? Quelles communautés les soutiennent et comment ?
Venez le découvrir lors de cette session ignite
Climate Science Flows: Enabling Petabyte-Scale Climate Analysis with the Eart...Globus
The Earth System Grid Federation (ESGF) is a global network of data servers that archives and distributes the planet’s largest collection of Earth system model output for thousands of climate and environmental scientists worldwide. Many of these petabyte-scale data archives are located in proximity to large high-performance computing (HPC) or cloud computing resources, but the primary workflow for data users consists of transferring data, and applying computations on a different system. As a part of the ESGF 2.0 US project (funded by the United States Department of Energy Office of Science), we developed pre-defined data workflows, which can be run on-demand, capable of applying many data reduction and data analysis to the large ESGF data archives, transferring only the resultant analysis (ex. visualizations, smaller data files). In this talk, we will showcase a few of these workflows, highlighting how Globus Flows can be used for petabyte-scale climate analysis.
Into the Box Keynote Day 2: Unveiling amazing updates and announcements for modern CFML developers! Get ready for exciting releases and updates on Ortus tools and products. Stay tuned for cutting-edge innovations designed to boost your productivity.
AI Pilot Review: The World’s First Virtual Assistant Marketing SuiteGoogle
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Unleash Unlimited Potential with One-Time Purchase
BoxLang is more than just a language; it's a community. By choosing a Visionary License, you're not just investing in your success, you're actively contributing to the ongoing development and support of BoxLang.
Code reviews are vital for ensuring good code quality. They serve as one of our last lines of defense against bugs and subpar code reaching production.
Yet, they often turn into annoying tasks riddled with frustration, hostility, unclear feedback and lack of standards. How can we improve this crucial process?
In this session we will cover:
- The Art of Effective Code Reviews
- Streamlining the Review Process
- Elevating Reviews with Automated Tools
By the end of this presentation, you'll have the knowledge on how to organize and improve your code review proces
Custom Healthcare Software for Managing Chronic Conditions and Remote Patient...Mind IT Systems
Healthcare providers often struggle with the complexities of chronic conditions and remote patient monitoring, as each patient requires personalized care and ongoing monitoring. Off-the-shelf solutions may not meet these diverse needs, leading to inefficiencies and gaps in care. It’s here, custom healthcare software offers a tailored solution, ensuring improved care and effectiveness.
Innovating Inference - Remote Triggering of Large Language Models on HPC Clus...Globus
Large Language Models (LLMs) are currently the center of attention in the tech world, particularly for their potential to advance research. In this presentation, we'll explore a straightforward and effective method for quickly initiating inference runs on supercomputers using the vLLM tool with Globus Compute, specifically on the Polaris system at ALCF. We'll begin by briefly discussing the popularity and applications of LLMs in various fields. Following this, we will introduce the vLLM tool, and explain how it integrates with Globus Compute to efficiently manage LLM operations on Polaris. Attendees will learn the practical aspects of setting up and remotely triggering LLMs from local machines, focusing on ease of use and efficiency. This talk is ideal for researchers and practitioners looking to leverage the power of LLMs in their work, offering a clear guide to harnessing supercomputing resources for quick and effective LLM inference.
4. • System architecture setup
• Hardware/processor/memory
• Operating System performance
• Application server configuration
• Scheduled tasks (cron tasks)
• Reporting
• Integration with other systems using the Integration framework
• Network
Factors in System Performance
FMMUG18 :: Seattle 4
9. • Using the minimum hardware requirements may produce the
minimum acceptable application performance
• Using virtual technology to maximize hardware availability can
reduce overall performance (VM overhead, shared resources)
• Use physical memory. Sharing memory and swapping to disk has a
performance impact
• Use Operating System tuning to maximize throughput (temp/swap
space, background processing, disk/storage tuning)
Hardware/Operating System
FMMUG18 :: Seattle 9
10. • Each application server vendor will have their own requirements and
recommendations related to supporting infrastructure and settings.
There is no “one size fits all”
• IBM WebSphere
• Generic JVM argument: -Dsun.rmi.dgc.ackTimeout=10000
• Oracle WebLogic
Application Server
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11. • For both platforms – Memory settings: Initial: 4096m / Maximum:
4096m
• Minimum settings
• Recommended settings: Initial 6144m / Maximum: 6144m
• More memory is not always a good answer: Too much memory can
slow GC (garbage collection)
Application Server
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12. • Application Servers should always be setup in a cluster
• JVMs per cluster based on load
• UI cluster – End user logins
• 1 CPU per JVM / 4-6GB heap / 50-75 users per JVM
• Cron task cluster – Background tasks
• 1 CPU per JVM / 4-6 GB heap / At least 2 JVMs
• Integration cluster – Integration transactions
• 1 CPU per JVM / 4-6 GB heap / At least 2 JVMs
• Report cluster – Report execution
• 1 CPU per JVM / 4-6 GB heap / At least 2 JVMs
Application Server
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13. • Use replication to populate and synchronize a reporting database
• JVM tuning
• Heap
• Garbage collection
• Load balancing
Application Server
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14. • Per JVM – allocate and additional 1GB of memory for internal usage
• 4GB JVM needs 5GB total memory
• Allocate 25% additional memory for the Operating System
• Take into account all processes that might be started on the
physical/virtual server
• Eg. JVM, node manager, deployment manager, web server, anti-virus, etc.
Application Server
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15. • JVM arguments
• -Dsun.rmi.dgc.ackTimeout
• This represents how often the server checks for objects that can be garbage collected.
The time value is in milliseconds
• The best practice for this is 10000 (10 seconds). The default value is 5 minutes – this can
cause out of memory
• Setting this value too low can increase CPU usage
Application Server
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16. • JVM arguments
• -Xdisableexplicitgc
• This property should be set to disable explicit garbage collection, this disables all
System.gc() calls from initiating garbage collection
• -Xmn
• The nursery size should be set to 25% of the maximum heap. This property should be
used along side the –Xgcpolicy:gencon in which garbage collection policy places objects in
separate areas of the heap based on lifetime
Application Server
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17. • JVM arguments
• -Xgcpolicy:gencon
• The gencon policy is now the default policy in WebSphere 8.5.5 and is set out of the box
when doing Maximo install. This is the recommended policy. The gencon policy places
objects into the heap in separate areas based on how long they have been active. The
heap is split into a nursery based on the –Xmn setting. The nursery can be garbage
collected without the overhead of cleaning up the entire heap at the same time
Application Server
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18. • JVM arguments
• -Xgcpolicy:optthruput
• This used to be the default policy for WebSphere, in version 8 and forward the default
policy has been changed to gencon. Optthruput works based on multiple passes. First it
goes through all reachable objects and marks it as active data, it then passes through a
second time to clean up any non marked objects, freeing up memory
• This can not be used along with –Xmn (nursery) parameter
Application Server
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19. • Thread pool
• Thread pools are a collection of threads on a server that can be reused when
the JVM creates a request rather then create a new thread with each new
request
• Best practices
• Minimum number of threads in the pool should be set to 20 for the default
thread pool and 120 for the WebContainer thread pool
• The thread inactivity timeout defines how long a thread can be inactive before
the thread is returned to the pool. The default thread pool should be set to
30000 and WebContainer thread pool to 60000
Application Server
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20. • Best practices
• Enable Allow thread allocation beyond the maximum size. This defines if a
thread can be created past the maximum thread pool value
• Thread pool settings are defined for each individual server
Application Server
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21. • Each database vendor will have their own requirements and
recommendations related to supporting infrastructure and settings.
There is no “one size fits all”
• Tune database as per install and best practices documents
• Specific settings are documented
• Oracle
• Use cursor_sharing=force
• The more memory the better
Database
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22. • Tune database as per install and best practices documents
• DB2
• Lock timeout
• Memory settings
• Schedule regular maintenance for reorganization and runstats
• For DB2 9.5 and later, set DB2_WORKLOAD=MAXIMO
• SQL Server
• Turn off page level locking
• Use Maximo properties for SQL Server
• Do not try to use with more than 250 concurrent users
Database
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23. • Database tuning is the most important performance improvement task
• Maximo is extremely database centric
• Use database tools to find long running queries and recommended indexes
• Analyze database memory and user I/O
• Maximo fetches a lot of data into application server
• Increase system memory, helps reduce user I/O
• Separate tablespace and mount points to optimize I/O
• Dedicated hardware for optimal performance
• Performance impact in virtualized environment
Database
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24. • Setup an index statistics update schedule
• Weekly update helps in better performance
• Purge/Archive data
• Transactional data needs archiving plus purging
• Purge on a regular basis
• Eg. Workflow transaction data, login tacking, start center
• Add indexes as they are needed
• Do not be scared to add indexes
• In Maximo, 80% is data fetch, 20% is data insert/update
• Lack of right indexes causes more performance problem than slowing down on
insert/update
Database
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25. • Sequences (Oracle & DB2)
• Enable sequence caching
• Increase cache size for sequences to 50 (except maxseq)
• Increase cache size for maxseq sequence to 500
Database
FMMUG18 :: Seattle 25
26. • High availability database setup
• DB2 provides HACMP and HADR
• Oracle has RAC
• SQL Server High Availability
• High availability helps in failover
• Separate reporting database helps reduce load on the primary
database
• Multi-site setup – use the property to improve SQL timing
• mxe.db.useSiteInListQuery=1
• This includes the list of sites the user has access in the SQL statement
instead of figuring out through complex SQL against multiple tables
Database
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27. • 1 CPU for every 100 database connections
• Environment of 400 concurrent users, total database connections
may be double
• 400 concurrent users requires at least 8 CPUs
• Consider peak load
• Heavy reporting usage will increase database load and requires more
database CPU
• 2GB SGA memory for every 100 database connections
• 400 concurrent users = 8GB of SGA
Database
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28. • Tuning the application is sometimes a cross between application
and middleware settings. This occurs with both database server
and application server
• Tuning the database server and then sending it bad queries will still
result in poor performance
• Make sure any application properties for connecting to the database are set
• Use the approved versions of JDBC drives
• Use logging best practices – too much SQL logging impacts results
The Gray Area
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29. • Tuning the application server and then putting too much load on it
will still result in poor performance
• Separate functionality into dedicated JVMs (UI, Cron, Report, Integration)
• Limit concurrent users to 75 per dedicated UI JVM
The Gray Area
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30. • Search Methodologies – Default to “EXACT”
• If possible, change WILD card searches to EXACT
• Educate users to use % wild card option in search fields
• Reduces ‘like’ searches and greatly improves database query times
• Do not use leading % wild card character
• Set most ALN fields to UPPER
• Do not use ‘not in’ or ‘!=‘ (this does a full table scan)
• Use ‘in’ or ‘not exist’
Querying/SQL
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31. • Educate users on ad-hoc queries
• Check for newly created user queries and optimize
• Identify long running reports
• Review SQL in reports
• Escalations, Conditions
• Start Center result sets, KPIs, Doclinks query
• List panel ‘order by’ queries
• Can remove ‘order by’ in presentation XMLs
Querying/SQL
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33. • Reporting cluster (BROS)
• Reporting database
• Identify log running reports from report usage and tune them
• Identify poor performing ad hoc reports
• Scheduled report cron tasks
• Execute in cron cluster
• Separate these out of UI servers
• Ensure long running scheduled reports are not submitted at the same time
Reporting
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34. • Property mxe.report.birt/maxconcurrentrun defines how many
concurrent reports can run on a given Maximo JVM
• Default value is 5 – good starting point
• Recommendations
• 2* num of CPU
• Depends on the complexity of the reports
Reporting
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35. • Separate sequential inbound and sequential outbound queues for
integrated system
• Limit the number of message driven beans (MDBs) on the
continuous queue
• Exception handling queues
• ‘bad’ data redirect out of continuous queue
• XML/HTTP instead of Simple Object Access Protocol (SOAP) web
services
• Less overhead and better performer under load
• File import for XML documents containing multiple records
Integration Framework
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36. • 50ms or faster round-trip packet response between client and application
server
• Low bandwidth or high latency network
• Citrix or Terminal Server
• Compression techniques
• HTTP compression
• Web server
• Hardware compression
• Network appliances – Juniper and Riverbed
• Provide compression and caching
• Gzip compression
• Maximo configuration
Network
FMMUG18 :: Seattle 36
37. • Acceleration
• Caching
• MaxAge – enabled by default on the application server
• Configuring asynchronous and client side validation can improve the
users experience
• Good screen design can reduce traffic
Network
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38. • Best performance is achieved by using the newest supported
Operating Systems and the latest hardware
• Robust workstations provide better performance
• Limit or prevent some workstation activities and processes
• Monitor the network for streaming audio and video
• Have only one network link active
• Monitor for hung processes and applications
Client Workstation
FMMUG18 :: Seattle 38
39. • Task focused screen design – create small screens
• Off hours WO generation, Reorder, crons, and reporting
• Reduce start center data retrieval
• Keep the default start center simple to no data fetch portlets
• There can be multiple start centers – the first one displayed should be simple
to avoid excessive data fetch
• Be sure that queries used on the start centers return small numbers of rows
and are well tuned
Miscellaneous
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40. • Database connection pooling
• Lower properties values
• Limit query times
• System properties
• Limit number of fields on a single screen / develop silo (business
unit) based screens with only the fields required for that silo
• Configure client side and asynchronous validation to limit real time
interaction with the database server
Miscellaneous
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41. • Tune DOCLINKS relationships or disable DOCLINKS
• Limit the number of objects that can be fetched from the database in
a single result set (system properties)
• Fetch stop limits
• Carefully consider business requirements for frequency of cron
tasks and escalations
Miscellaneous
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42. • Tune cron tasks and escalations
• Adjust start timings to spread the load
• Load balance across multiple JVMs
• New in Maximo 7.6 – cron task load balancing
• Control queries in left hand navigation
• Limit the number of queries that display for an application in the side
navigation bar under ‘Available Queries’ (system properties)
Miscellaneous
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43. • Analyze and clearly define reported problem
• Understand what is being reported. “Application is slow” is not a definition.
Find out what is slow. See it for yourself if possible
• Determine/define what is successful resolution
• Do not allow user perception to interfere with a solution. Get a clear definition
of what is acceptable so you have a measure of success
• Focus on technologies that might impact issue
• If users at one plant are affected but users at another plant are not affected, it
is likely not a server problem. Focus on items that can impact the affected
area
Troubleshooting
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44. • Debug in development or test environment if problem is reproducible
there
• Setup a stand alone application server for debugging
Troubleshooting
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45. • Keep Maximo as well as application server logging to minimal level
unless investigating a problem
• Set everything except Maximo root logger to ERROR
• Maximo logging adds 5%+ overhead
• WebSphere logs for errors and messages
• Clean up log folders from filling up
• Watch out for heap dumps as these files are very large
• Since logging changes can be applied dynamically, turn logging on
when needed and turn it off when done – Logging application
Troubleshooting - Logging
FMMUG18 :: Seattle 45
46. • SQL logging to collect all SQL statements
• New in Maximo 7.6 – logging marker
• If analyzing memory usage
• Use verbose GC logging
• Web server logs
• Database traces and snapshots. Specific database ‘logging’ tools
• Network traces/logging
Troubleshooting - Logging
FMMUG18 :: Seattle 46
47. • System Properties used as part of logging
• Enabled through System Properties application. Dynamic, can be enabled
without re-building Maximo EAR file
• Performance properties
• mxe.mbocount
• Capture snapshot intervals of memory usage
• Total memory allocated and memory available
• Maximo Business Objects (MBOs) loaded
• Total concurrent users
• Users connected to each JVM in the system
• Cron tasks running on JVMs
Troubleshooting -
Properties
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48. mxe.mbcount
[INFO] [MAXIMO] [] WOSERVICEADDRESS: mbosets (6), mbos (10)
[INFO] [MAXIMO] [] WOTAGLOCK: mbosets (2), mbos (1)
[INFO] [MAXIMO] [] WOTASKRELATION: mbosets (4), mbos (4)
[INFO] [MAXIMO] [] WPITEM: mbosets (3), mbos (3)
[INFO] [MAXIMO] [] WPLABOR: mbosets (4), mbos (4)
[INFO] [MAXIMO] [] WPMATERIAL: mbosets (4), mbos (4)
[INFO] [MAXIMO] [] WPSERVICE: mbosets (3), mbos (3)
[INFO] [MAXIMO] [] WPTOOL: mbosets (3), mbos (3)
[INFO] [MAXIMO] [] BMXAA6372I - Host name: xxx.xxx.xxx.xxx. Server name: MAXIMO. Cron task name: AssetTopoCacheCron.AssetTopoCacheCron01. Last run: 2018-02-01 15:03:56.119
[INFO] [MAXIMO] [] BMXAA6372I - Host name: xxx.xxx.xxx.xxx. Server name: MAXIMO. Cron task name: AsyncImmediateJobCron.AsyncImmediate. Last run: 2018-02-01 15:06:53.61
[INFO] [MAXIMO] [] BMXAA6372I - Host name: xxx.xxx.xxx.xxx. Server name: MAXIMO. Cron task name: AsyncJobCleanupCron.AsyncJobCleanup. Last run: 2018-02-01 13:48:55.215
[INFO] [MAXIMO] [] BMXAA6372I - Host name: xxx.xxx.xxx.xxx. Server name: MAXIMO. Cron task name: AsyncScheduledJobCron.AsyncScheduled. Last run: 2018-02-01 15:05:56.618
[INFO] [MAXIMO] [] BMXAA6372I - Host name: xxx.xxx.xxx.xxx. Server name: MAXIMO. Cron task name: BBCron.BBCRON1. Last run: 2018-02-01 13:00:58.184
[INFO] [MAXIMO] [] BMXAA6369I - Server host: xxx.xxx.xxx.xxx. Server name: MAXIMO. Number of users: 7. WebClientSessions: (7)
[INFO] [MAXIMO] [] BMXAA6370I - Total number of users connected to the system: 7
[INFO] [MAXIMO] [] BMXAA7019I - The total memory is 4294967296 and the memory available is 3428580392.
Troubleshooting - Properties
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49. • Performance properties
• mxe.db.logSQLTimeLimit
• Captures SQL statements that take longer than the specified amount of time to return
• mxe.db.fetchResultLogLimit
• Captures the number of objects an MBO loads while it is processing
• Helps in identifying excessive data fetch
• mxe.db.logSQLPlan (Oracle only)
• mxe.db.sqlTableScanExclude (Oracle only)
Troubleshooting -
Properties
FMMUG18 :: Seattle 49
50. mxe.db.logSQLTimeLimit
[INFO] app (null) object (INVOICELINE) :select * from invoiceline where (cstm_invsuspcode='QTY'
and invoicenum in (select invoicenum from maximo.invoice where exists (select * from
maximo.wfassignment where processname='INVQTYDISC' and ownerid=invoiceid)) and(select
sum(invoiceqty*conversion) from maximo.invoiceline i1, maximo.invoice i2 where
invoiceline.ponum=i1.ponum and invoiceline.polinenum=i1.polinenum and invoiceline.orgid=i1.orgid
and invoiceline.siteid=i1.siteid and i1.invoicenum = i2.invoicenum and i1.orgid = i2.orgid and
i1.siteid = i2.siteid and i2.documenttype not in ('CREDIT') and i2.status not in (select value from
maximo.synonymdomain where maxvalue='CANCEL' and domainid = 'IVSTATUS')) <= (select
1.05*nvl(sum(quantity),0) from maximo.matrectrans, maximo.poline where
matrectrans.ponum=poline.ponum and matrectrans.polinenum=poline.polinenum and
matrectrans.orgid = poline.orgid and matrectrans.siteid = poline.siteid and
matrectrans.polinenum=invoiceline.polinenum and matrectrans.ponum=invoiceline.ponum and
matrectrans.orgid = invoiceline.orgid and matrectrans.siteid = invoiceline.siteid and
((matrectrans.issuetype in ('RECEIPT', 'RETURN') and poline.inspectionrequired=0) or
(matrectrans.issuetype in ('TRANSFER', 'RETURN') and poline.inspectionrequired=1)) )) (execution
took 336836 milliseconds)
Troubleshooting - Properties
FMMUG18 :: Seattle 50
51. Troubleshooting - Properties
FMMUG18 :: Seattle 51
mxe.db.fetchResultLogLimit
-------FetchResultLogLimit logging starts------
[INFO] [MXServer] [] BMXAA6703I - User Name : MAXUSER
[INFO] [MXServer] [] BMXAA6705I - Query : select * from wfassignment where assigncode = 'MAXUSER' and assignstatus in ( 'ACTIVE' )
[INFO] [MXServer] [] BMXAA6706I - MboSet Name : WFASSIGNMENT Reference = psdi.workflow.WFAssignmentSet@e98ec5e9
[INFO] [MXServer] [] BMXAA6707I - MboSet Size : 400
[INFO] [MXServer] [] BMXAA6708I - Fetch count so far : 400
[INFO] [MXServer] [] psdi.util.MXSystemException: BMXAA6709I - Printing StackTrace: java.lang.Exception
java.lang.Exception
at psdi.mbo.MboSet.fetchMbosActual(MboSet.java:2970)
at psdi.mbo.MboSet.fetchMbos(MboSet.java:2806)
at psdi.mbo.MboSet.getMbo(MboSet.java:2053)
at psdi.mbo.MboSetEnumeration.nextMbo(MboSetEnumeration.java:64)
at psdi.workflow.WFAssignmentSet.setOwnerRecordLock(WFAssignmentSet.java:101)
at psdi.workflow.WFAssignmentSet.getInboxAssignments(WFAssignmentSet.java:69)
at psdi.app.inbxconfig.InbxConfigSet.getAssignments(InbxConfigSet.java:236)
at psdi.webclient.controls.InboxPortlet.getAssignments(InboxPortlet.java:81)
…
[INFO] [mxui103] [] BMXAA6710I - -------FetchResultLogLimit logging ends------
52. • Fetch stop limit
• Enable and use until you reach a stable state. Returns an error to the end
user
• mxe.db.fetchStopLimitEnabled
• mxe.db.fetchResultStopLimit
• mxe.db.fetchResultStopLimit.OBJECTNAME
• mxe.db.fetchStopExclusion
Troubleshooting -
Properties
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53. • Enable Connection Pool Watchdog to monitor database connection
pool
• Enabled in the Logging application
• Close long running database connections
• Maximo 7.5.0.3 properties introduced
• Use database tools to find long running queries and recommended
indexes
• Test queries through SQL development tools and add required
indexes
• Always make sure the indexes are added through Maximo Database
Configuration to retain during fix pack installation and upgrades
Troubleshooting
FMMUG18 :: Seattle 53
54. Dbconnection watchdog
logger
[INFO] BMXAA7084I - The
DbConnectionWatchDog class has
been trying to close the database
connection for: 230233001 ms
DbConnectionWatchDog:Db
Connection reference id=436107
SPID=397
Create time:1302986384636
Life time:230233001 ms
Troubleshooting
FMMUG18 :: Seattle 54
• Back in logs at start of connection will be stack trace
[INFO] BMXAA7084I - The DbConnectionWatchDog class has been trying to close the database
connection for: 73000 ms
DbConnectionWatchDog:Db Connection reference id=436107 SPID=397
Create time:1302986384636
Create stack trace:
psdi.server.DbConnectionWatchDog$ConnectionData.<init>(DbConnectionWatchDog.java:40)
psdi.server.DbConnectionWatchDog.addConnection(DbConnectionWatchDog.java:206)
psdi.server.ConRef.incrementRefCount(ConRef.java:129)
psdi.server.DBManager.getConnectionDetail(DBManager.java:1268)
psdi.server.DBManager.getConnection(DBManager.java:1179)
psdi.server.AppService.getDBConnection(AppService.java:548)
psdi.mbo.MboSet.getNextRecordData(MboSet.java:2794)
psdi.mbo.MboSet.fetchMbosActual(MboSet.java:2528)
psdi.mbo.MboSet.fetchMbos(MboSet.java:2494)
psdi.mbo.MboSet.getMbo(MboSet.java:1821)
psdi.mbo.MboSet.isEmpty(MboSet.java:3777)
psdi.app.asset.Asset.getParentAsset(Asset.java:7148)
psdi.app.asset.Asset.getWarrantyInfo(Asset.java:7082)
psdi.app.asset.Asset.getWarrantyInfo(Asset.java:7067)
psdi.app.workorder.WO.updateWarrantyContracts(WO.java:9777)
psdi.app.workorder.FldWOAssetnum.performWarrantyContractCheck(FldWOAssetnum.java:380)
psdi.app.workorder.FldWOAssetnum.action(FldWOAssetnum.java:201)
psdi.plust.app.workorder.PlusTFldWOAssetnum.action(Unknown Source)
55. • Network pings and trace routes from client to Maximo server
• Monitor CPU and memory usage
• Apply the latest patches
Troubleshooting
FMMUG18 :: Seattle 55
56. • Integrity Checker to find Maximo schema problems that can affect
applications as well as performance
• Integrity Checker can be found in the Maximo tools folder (integrityui)
• Integrity Checker should be done in development phase to production phase
• LA Test Fix tool
• Report of limited availability fixes (one-offs) installed
• LA test fix tool can be found in the Maximo tools folder
(LATestFixReportWriter)
Tools
FMMUG18 :: Seattle 56
57. • IBM Support Assistant (ISA)
• Add-on tools for heap and thread analysis
• Real world load testing
• WebSphere Performance Monitoring Infrastructure (PMI)
• Database Utilities
• AWR/ADDM Reports
• IBM DB2 monitors and snapshots
• IBM Data Studio
• IBM standalone db2advis and execution plans
Tools
FMMUG18 :: Seattle 57
58. • Operating System tools
• PerfMon – gather performance metrics on Windows based systems
• nmon – gather performance statistics on AIX or Linux based systems
• rstatd – gather performance metrics from a UNIX system kernel
• sysstat – package for utilities containing the sar, sadf, iostat, mpstat, and
pidstat commands for AIX and Linux
• vmstat – reports statistics about kernel threads, virtual memory, disks, traps,
and CPU activity on UNIX systems
Tools
FMMUG18 :: Seattle 58
59. • Bandwidth / Throughput monitoring tools
• HTTPWatch – logs and allows inspection of HTTP and HTTPS traffic
• Wireshark – network protocol analyzer that can be used to capture network
traffic for bandwidth analysis
• WinPcap – packet capture and filtering engine used by many network protocol
analyzers, including Wireshark
Tools
FMMUG18 :: Seattle 59
60. • IBM Thread and Monitor Dump Analyzer for Java
• Identification of hangs, deadlocks, resource contention and bottlenecks in
Java threads
• Classpath
• Java and Garbage Collection parameters
Tools
FMMUG18 :: Seattle 60
61. • IBM Thread and Monitor Dump Analyzer for Java
Tools
FMMUG18 :: Seattle 61
62. • Heap Analyzer
• Possible heap leak detection
• A graphical tool for discovering possible Java heap leaks
Tools
FMMUG18 :: Seattle 62
64. • Customization Detection Tools
• Report that lists all the services, objects, and attribute classes that have been
extended
• Displays extensions (class customizations) in a class hierarchy structure
• Shows percentage customized
• Reports on services, objects, and attributes
Tools
FMMUG18 :: Seattle 64
66. • Performance Analysis Suite
• Help analyze performance problems
• Plugins
• TPAE:Config plugin
• Performance white paper compliance checking
• Dashboard tab shows a high level result of performance compliance checking result
Tools
FMMUG18 :: Seattle 66
68. • Wait tool
• Identifies the bottlenecked resources, and shows the code that drives this
load
• Works in any Java application
• No system of agents
• Output in an HTML report
Tools
FMMUG18 :: Seattle 68
70. • Maximo Management Interface (MMI)
• New in Maximo 7.6 – http://hostname:port/maximo/oslc/members
• Integrated into Maximo framework
• Real time access to the environment
• Extendable
• Provides input to monitoring tools
• Standardized JSON output
• Set of REST APIs that enable HTTP based clients to access information that
is related to the current state of Maximo
Tools
FMMUG18 :: Seattle 70
71. • Maximo Management Interface (MMI)
• The Maximo server processes that are part of the deployment, potentially in a
multi-clustered setup
• Information about resources, such as the JVM, memory, operating system,
application server, JVM threads, database connection pool, class or
classloader, MBO count, event topic tree, JMS queue connectivity, and cache
information
Tools
FMMUG18 :: Seattle 71
73. Application Server
IBM WebSphere Tuning (can cause application to hold objects too long
if not set correctly)
http://www.ibm.com/support/docview.wss?rs=3214&uid=swg21261874
Oracle WebLogic Tuning
http://www.ibm.com/support/docview.wss?rs=3214&uid=swg21261853
Using Multiple JVMs to Support Users and Functionality
http://www-01.ibm.com/support/docview.wss?uid=swg21329219
Resources
FMMUG18 :: Seattle 73
74. Network Performance
Network caching and compression properties
http://www.ibm.com/support/docview.wss?rs=3214&uid=swg21262009
Browser Caching (Helps with Wide Area Network -WAN- performance
and high latency)
http://www.ibm.com/support/docview.wss?rs=3214&uid=swg21292557
Resources
FMMUG18 :: Seattle 74
76. Database Server Performance
SQL Server Index Tuning
http://www.ibm.com/support/docview.wss?rs=3214&uid=swg21261979
SQL Server Row Versioning
http://www.ibm.com/support/docview.wss?rs=3214&uid=swg21440598
Maximo 7.5 on SQL Server Performance
http://www-01.ibm.com/support/docview.wss?uid=swg21592716
SQL Server Turning of Page Locking
http://www-01.ibm.com/support/docview.wss?uid=swg21268567
Resources
FMMUG18 :: Seattle 76
77. Database Server Performance
Oracle Cursor Sharing
http://www.ibm.com/support/docview.wss?rs=3214&uid=swg21262959
DB2 Parameter Tuning
https://www-304.ibm.com/support/docview.wss?uid=swg21451593
Database Connection Leak Resolution
http://www-01.ibm.com/support/docview.wss?uid=swg21622010
How to detect database connection leak
https://www.ibm.com/developerworks/community/blogs/a9ba1efe-b731-4317-9724-
a181d6155e3a/entry/Maximo_How_to_detect_database_connection_leak?lang=en
How to solve database connection leak
https://www.ibm.com/developerworks/community/blogs/a9ba1efe-b731-4317-9724-
a181d6155e3a/entry/Maximo_How_to_solve_database_connection_leak?lang=en
Resources
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78. Application Performance
Understanding Search Methodologies
http://www-01.ibm.com/support/docview.wss?uid=swg21375684
Start Center Performance
http://www-01.ibm.com/support/docview.wss?uid=swg21405898
Improving Performance Using Small User Interface (UI) Screens
http://www-01.ibm.com/support/docview.wss?uid=swg21420509
Disable Data Validation
http://www-01.ibm.com/support/docview.wss?uid=swg21516856
Resources
FMMUG18 :: Seattle 78
84. Tools
IBM Support Assistant
http://www-01.ibm.com/software/support/isa/
IBM Thread and Monitor Dump Analyzer for Java
https://www.ibm.com/developerworks/community/groups/service/html/communit
yview?communityUuid=2245aa39-fa5c-4475-b891-14c205f7333c
Heap Analyzer
https://www.ibm.com/developerworks/community/groups/service/html/communit
yview?communityUuid=4544bafe-c7a2-455f-9d43-eb866ea60091
Resources
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