Architecting and Tuning IIB/eXtreme Scale for Maximum Performance and Reliabi...Prolifics
Abstract: Recent projects have stressed the "need for speed" while handling large amounts of data, with near zero downtime. An analysis of multiple environments has identified optimizations and architectures that improve both performance and reliability. The session covers data gathering and analysis, discussing everything from the network (multiple NICs, nearby catalogs, high speed Ethernet), to the latest features of extreme scale. Performance analysis helps pinpoint where time is spent (bottlenecks) and we discuss optimization techniques (MQ tuning, IIB performance best practices) as well as helpful IBM support pacs. Log Analysis pinpoints system stress points (e.g. CPU starvation) and steps on the path to near zero downtime.
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- Why performance matters for digital businesses?
- Use Cases for performance / load testing
- Load Test Design Considerations
- Tools and Technologies
- Methodology and Approach
- Activities and Deliverables
- Load Testing Success Stories
How to boost performance of your rails app using dynamo db and memcachedAndolasoft Inc
DynamoDB and Memcached is a powerful combination for your Rails app. If you're looking to improve the performance of your Rails application, this may be the solution for you.
Architecting and Tuning IIB/eXtreme Scale for Maximum Performance and Reliabi...Prolifics
Abstract: Recent projects have stressed the "need for speed" while handling large amounts of data, with near zero downtime. An analysis of multiple environments has identified optimizations and architectures that improve both performance and reliability. The session covers data gathering and analysis, discussing everything from the network (multiple NICs, nearby catalogs, high speed Ethernet), to the latest features of extreme scale. Performance analysis helps pinpoint where time is spent (bottlenecks) and we discuss optimization techniques (MQ tuning, IIB performance best practices) as well as helpful IBM support pacs. Log Analysis pinpoints system stress points (e.g. CPU starvation) and steps on the path to near zero downtime.
This presentation includes:
- Why performance matters for digital businesses?
- Use Cases for performance / load testing
- Load Test Design Considerations
- Tools and Technologies
- Methodology and Approach
- Activities and Deliverables
- Load Testing Success Stories
How to boost performance of your rails app using dynamo db and memcachedAndolasoft Inc
DynamoDB and Memcached is a powerful combination for your Rails app. If you're looking to improve the performance of your Rails application, this may be the solution for you.
AWSQ: an approximated web server queuing algorithm for heterogeneous web serv...IJECEIAES
With the rising popularity of web-based applications, the primary and consistent resource in the infrastructure of World Wide Web are cluster-based web servers. Overtly in dynamic contents and database driven applications, especially at heavy load circumstances, the performance handling of clusters is a solemn task. Without using efficient mechanisms, an overloaded web server cannot provide great performance. In clusters, this overloaded condition can be avoided using load balancing mechanisms by sharing the load among available web servers. The existing load balancing mechanisms which were intended to handle static contents will grieve from substantial performance deprivation under database-driven and dynamic contents. The most serviceable load balancing approaches are Web Server Queuing (WSQ), Server Content based Queue (QSC) and Remaining Capacity (RC) under specific conditions to provide better results. By Considering this, we have proposed an approximated web server Queuing mechanism for web server clusters and also proposed an analytical model for calculating the load of a web server. The requests are classified based on the service time and keep tracking the number of outstanding requests at each webserver to achieve better performance. The approximated load of each web server is used for load balancing. The investigational results illustrate the effectiveness of the proposed mechanism by improving the mean response time, throughput and drop rate of the server cluster.
A Study on Replication and Failover Cluster to Maximize System UptimeYogeshIJTSRD
Different types of clients over the globe uses Cloud services because cloud computing involves various features and advantages such as building cost effectives solutions for business, scale resources up and down according to the current demand and many more. But from the cloud provider point of view, there are many challenges that need to be faced in order to ensure a hassle free service delivery to the clients. One such problem is to maintain high availability of services. This project aims at presenting a high available HA solution for business continuity and disaster recovery through configuration of various other services such as load balancing, elasticity and replication. Miss Pratiksha Bhagawati | Mrs. Priya N "A Study on Replication and Failover Cluster to Maximize System Uptime" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, URL: https://www.ijtsrd.compapers/ijtsrd41249.pdf Paper URL: https://www.ijtsrd.comcomputer-science/other/41249/a-study-on-replication-and-failover-cluster-to-maximize-system-uptime/miss-pratiksha-bhagawati
Tech Talk: Leverage the combined power of CA Unified Infrastructure Managemen...CA Technologies
Take the guesswork out of your infrastructure environment by combining CA Unified Infrastructure Management, CA Network Flow Analysis and CA Application Delivery Analysis. Learn how to optimize your infrastructure by combining IT monitoring, network traffic monitoring and application response time monitoring solutions to give you enhanced end-to-end visibility into your infrastructure. This sessions will review the power of the three solutions and explain how you can easily combine them to give you the information you need.
For more information, please visit http://cainc.to/Nv2VOe
Automatic scaling of web applications for cloud computing serviceseSAT Journals
Abstract Now days there are many web applications can get benefit from automatic scaling property of cloud where the no of resources usage can be scale up and down automatically by cloud service provider. So here present system that provides automatic scaling for web application in cloud environment. So every application instance encapsulated inside virtual machine and model it as the Class Constraint Bin Packing (CCBP) problem. Where each class represents an application and each server is a bin and uses virtualization technology for fault isolation. Now many business customers need good satisfy response services from cloud. So design and develop semi online color set algorithm that achieve good demand satisfaction ratio and as well as when load becomes low it reducing number of server and save energy. Experiment results compare open source implementation of Amazon EC2 demonstrates that system can improve the throughput by 180% over. And system can restore the normal quality of service five times as fast when huge crowd happens. Take supports of green computing to adjusting the placement of application instance adaptively and putting ideal machine into the standby mode. Key Words: auto scaling, cloud computing, CCBP, green computing, virtualization etc…
load speed problems of web resources on the client side classification and ...INFOGAIN PUBLICATION
This article is concerned about client side issues of web resources load process related to user agents (browsers) behavior. a lot of modern problems such as improving global availability and reducing bandwidth, the main problem they address is latency: the amount of time it takes for the host server to receive, process, and deliver on a request for a page resource (images, css files, etc.). latency depends largely on how far away the user is from the server, and it’s compounded by the number of resources a web page contains; current load algorithms are investigated and all known solutions with their area or efficiency are explained. We have described four main optimization methods.
This paper describes the importance of a performant presentation tier. It presents the easiest way of optimizing the client-side code, providing source code examples for good practices. It then shows the correct approach to using CSS and HTML and the impact it has on the website response time. The Ajax technology is briefly described, emphasizing the role of JavaScript and presenting methods for improving its performance. In the end, some popular tools for monitoring and testing web applications are introduced.
Node Summit 2016: Web App ArchitecturesChris Bailey
While Node.js is becoming the platform of choice for web-scale applications, enterprises are resistant to change and have legacy applications based on other technologies, typically Java. Emerging web application architectures bring together the web-scale and integrated browser characteristics of Node.js with the transactional nature of Java to deliver high-performance, engaging web applications. Learn how the complimentary characteristics of Node.js and Java are being used to build the next generation of web applications.
VMworld 2013: How to Replace Websphere Application Server (WAS) with TCserver VMworld
VMworld 2013
Kaushik Bhattacharya, Pivotal
Michel Bond, VMware
Learn more about VMworld and register at http://www.vmworld.com/index.jspa?src=socmed-vmworld-slideshare
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
IEEE 2014 DOTNET CLOUD COMPUTING PROJECTS Automatic scaling of internet appli...IEEEMEMTECHSTUDENTPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
Using Grid Technologies in the Cloud for High Scalabilitymabuhr
An unstated assumption is that clouds are scalable. But are they? Stick thousands upon thousands of machines together and there are a lot of potential bottlenecks just waiting to choke off your scalability supply. And if the cloud is scalable what are the chances that your application is really linearly scalable? At 10 machines all may be well. Even at 50 machines the seas look calm. But at 100, 200, or 500 machines all hell might break loose. How do you know?
You know through real life testing. These kinds of tests are brutally hard and complicated. who wants to do all the incredibly precise and difficult work of producing cloud scalability tests? GridDynamics has stepped up to the challenge and has just released their Cloud Performance Reports.
Global Situational Awareness of A.I. and where its headedvikram sood
You can see the future first in San Francisco.
Over the past year, the talk of the town has shifted from $10 billion compute clusters to $100 billion clusters to trillion-dollar clusters. Every six months another zero is added to the boardroom plans. Behind the scenes, there’s a fierce scramble to secure every power contract still available for the rest of the decade, every voltage transformer that can possibly be procured. American big business is gearing up to pour trillions of dollars into a long-unseen mobilization of American industrial might. By the end of the decade, American electricity production will have grown tens of percent; from the shale fields of Pennsylvania to the solar farms of Nevada, hundreds of millions of GPUs will hum.
The AGI race has begun. We are building machines that can think and reason. By 2025/26, these machines will outpace college graduates. By the end of the decade, they will be smarter than you or I; we will have superintelligence, in the true sense of the word. Along the way, national security forces not seen in half a century will be un-leashed, and before long, The Project will be on. If we’re lucky, we’ll be in an all-out race with the CCP; if we’re unlucky, an all-out war.
Everyone is now talking about AI, but few have the faintest glimmer of what is about to hit them. Nvidia analysts still think 2024 might be close to the peak. Mainstream pundits are stuck on the wilful blindness of “it’s just predicting the next word”. They see only hype and business-as-usual; at most they entertain another internet-scale technological change.
Before long, the world will wake up. But right now, there are perhaps a few hundred people, most of them in San Francisco and the AI labs, that have situational awareness. Through whatever peculiar forces of fate, I have found myself amongst them. A few years ago, these people were derided as crazy—but they trusted the trendlines, which allowed them to correctly predict the AI advances of the past few years. Whether these people are also right about the next few years remains to be seen. But these are very smart people—the smartest people I have ever met—and they are the ones building this technology. Perhaps they will be an odd footnote in history, or perhaps they will go down in history like Szilard and Oppenheimer and Teller. If they are seeing the future even close to correctly, we are in for a wild ride.
Let me tell you what we see.
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Discussion on Vector Databases, Unstructured Data and AI
https://www.meetup.com/unstructured-data-meetup-new-york/
This meetup is for people working in unstructured data. Speakers will come present about related topics such as vector databases, LLMs, and managing data at scale. The intended audience of this group includes roles like machine learning engineers, data scientists, data engineers, software engineers, and PMs.This meetup was formerly Milvus Meetup, and is sponsored by Zilliz maintainers of Milvus.
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AWSQ: an approximated web server queuing algorithm for heterogeneous web serv...IJECEIAES
With the rising popularity of web-based applications, the primary and consistent resource in the infrastructure of World Wide Web are cluster-based web servers. Overtly in dynamic contents and database driven applications, especially at heavy load circumstances, the performance handling of clusters is a solemn task. Without using efficient mechanisms, an overloaded web server cannot provide great performance. In clusters, this overloaded condition can be avoided using load balancing mechanisms by sharing the load among available web servers. The existing load balancing mechanisms which were intended to handle static contents will grieve from substantial performance deprivation under database-driven and dynamic contents. The most serviceable load balancing approaches are Web Server Queuing (WSQ), Server Content based Queue (QSC) and Remaining Capacity (RC) under specific conditions to provide better results. By Considering this, we have proposed an approximated web server Queuing mechanism for web server clusters and also proposed an analytical model for calculating the load of a web server. The requests are classified based on the service time and keep tracking the number of outstanding requests at each webserver to achieve better performance. The approximated load of each web server is used for load balancing. The investigational results illustrate the effectiveness of the proposed mechanism by improving the mean response time, throughput and drop rate of the server cluster.
A Study on Replication and Failover Cluster to Maximize System UptimeYogeshIJTSRD
Different types of clients over the globe uses Cloud services because cloud computing involves various features and advantages such as building cost effectives solutions for business, scale resources up and down according to the current demand and many more. But from the cloud provider point of view, there are many challenges that need to be faced in order to ensure a hassle free service delivery to the clients. One such problem is to maintain high availability of services. This project aims at presenting a high available HA solution for business continuity and disaster recovery through configuration of various other services such as load balancing, elasticity and replication. Miss Pratiksha Bhagawati | Mrs. Priya N "A Study on Replication and Failover Cluster to Maximize System Uptime" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, URL: https://www.ijtsrd.compapers/ijtsrd41249.pdf Paper URL: https://www.ijtsrd.comcomputer-science/other/41249/a-study-on-replication-and-failover-cluster-to-maximize-system-uptime/miss-pratiksha-bhagawati
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Take the guesswork out of your infrastructure environment by combining CA Unified Infrastructure Management, CA Network Flow Analysis and CA Application Delivery Analysis. Learn how to optimize your infrastructure by combining IT monitoring, network traffic monitoring and application response time monitoring solutions to give you enhanced end-to-end visibility into your infrastructure. This sessions will review the power of the three solutions and explain how you can easily combine them to give you the information you need.
For more information, please visit http://cainc.to/Nv2VOe
Automatic scaling of web applications for cloud computing serviceseSAT Journals
Abstract Now days there are many web applications can get benefit from automatic scaling property of cloud where the no of resources usage can be scale up and down automatically by cloud service provider. So here present system that provides automatic scaling for web application in cloud environment. So every application instance encapsulated inside virtual machine and model it as the Class Constraint Bin Packing (CCBP) problem. Where each class represents an application and each server is a bin and uses virtualization technology for fault isolation. Now many business customers need good satisfy response services from cloud. So design and develop semi online color set algorithm that achieve good demand satisfaction ratio and as well as when load becomes low it reducing number of server and save energy. Experiment results compare open source implementation of Amazon EC2 demonstrates that system can improve the throughput by 180% over. And system can restore the normal quality of service five times as fast when huge crowd happens. Take supports of green computing to adjusting the placement of application instance adaptively and putting ideal machine into the standby mode. Key Words: auto scaling, cloud computing, CCBP, green computing, virtualization etc…
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This paper describes the importance of a performant presentation tier. It presents the easiest way of optimizing the client-side code, providing source code examples for good practices. It then shows the correct approach to using CSS and HTML and the impact it has on the website response time. The Ajax technology is briefly described, emphasizing the role of JavaScript and presenting methods for improving its performance. In the end, some popular tools for monitoring and testing web applications are introduced.
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IEEE 2014 DOTNET CLOUD COMPUTING PROJECTS Automatic scaling of internet appli...IEEEMEMTECHSTUDENTPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
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An unstated assumption is that clouds are scalable. But are they? Stick thousands upon thousands of machines together and there are a lot of potential bottlenecks just waiting to choke off your scalability supply. And if the cloud is scalable what are the chances that your application is really linearly scalable? At 10 machines all may be well. Even at 50 machines the seas look calm. But at 100, 200, or 500 machines all hell might break loose. How do you know?
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You can see the future first in San Francisco.
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The AGI race has begun. We are building machines that can think and reason. By 2025/26, these machines will outpace college graduates. By the end of the decade, they will be smarter than you or I; we will have superintelligence, in the true sense of the word. Along the way, national security forces not seen in half a century will be un-leashed, and before long, The Project will be on. If we’re lucky, we’ll be in an all-out race with the CCP; if we’re unlucky, an all-out war.
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Let me tell you what we see.
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short presentation on caching Caching.ppt
1. 1
Analysis of Caching and
Replication Strategies for Web
Applications
Presented By
Sudarsan Maddi
Graduate Student
Authors:
Swaminathan Sivasubramaniam,
Guillaume Pierre,
Maarten van Steen.
2. Analysis of Caching and Replication
Strategies for Web Applications 2
Topics That We Will be Seeing…
Introduction
Techniques to scale Web applications
Performance Analysis
Choosing the Right Strategy
3. Analysis of Caching and Replication
Strategies for Web Applications 3
Introduction
In this paper the authors present qualitative
and quantitative analysis of replication and
caching techniques to host Web applications.
Their analysis shows that selecting the best
mechanism depends heavily on data
workload and application characteristics.
4. Analysis of Caching and Replication
Strategies for Web Applications 4
Introduction
Web sites are slow dew to many reasons,
one of the main reason is dynamic generation
of web documents.
Web page caching: Fragments of HTML
pages the application generates are cached
to serve future requests.
Content-delivery networks such as Akamai do
this by deploying edge servers around the
Internet thus reducing request’s network
latency.
5. Analysis of Caching and Replication
Strategies for Web Applications 5
Introduction
Limitations of page caching have given raise
to different approaches for scalable Web
applications, classified broadly into:
Application code replication
Cache database records
Cache query results
Entire Database replication
In this article they have given overview of
various scalable techniques compared and
analyzed their features and performance.
6. Analysis of Caching and Replication
Strategies for Web Applications 6
Techniques to scale Web Applications
The techniques we are going to see are
Edge Computing
Data Replication
Content-Aware data Caching (CAC)
Content-Blind data Caching (CBC)
7. Techniques to Scale Web Applications 7
Edge Computing
In this the application code is replicated at
multiple edge servers and data is centralized.
Akamai and ACDN use this technique.
The data centralization create problems,
If the edge servers are located worldwide, each data
access incurs WAN latency.
The central database becomes a performance
bottleneck if the load increases.
8. Techniques to Scale Web Applications 8
Data Replication
Solution for Edge computing is to place the
data at each edge server.
Database replication (REPL) techniques can
help maintaining identical copies at multiple
locations.
Continued…
9. Techniques to Scale Web Applications 9
Data Replication
The problem with this is when there is a
database update.
This creates huge network traffic and
performance overhead.
10. Techniques to Scale Web Applications 10
Content-Aware data Caching (CAC)
Instead of maintaining full copies of database CAC
systems cache database query results as the
application code issues them.
Query Containment Check: The application running
at the edge-server issues a query, the local
database checks if it has enough data to answer the
query locally.
Containment check results positive query is present
locally, else its sent to central database and inserts
the result in its local database.
Continued…
11. Analysis of Caching and Replication
Strategies for Web Applications 11
An Example of CAC
CAC store query results efficiently
For example:
Query Q1: Select* from items where price<50
Query Q2: Select* from items where price<20
Query template QT1:
“Select* from items where price<”
12. Techniques to Scale Web Applications 12
Content-Aware data Caching (CAC)
This query containment check is highly
computationally expensive because it must
check the new query with all previously
cached queries.
In order to reduce this cost CAC makes use
of query template, which is a parameterized
SQL query whose parameter values are
parse at runtime
In, CAC systems update queries is always
executed at the central database.
13. Techniques to Scale Web Applications 13
Content-Blind data Caching (CBC)
Here, edge servers don’t need to run a
database at all.
Instead they store the results of remote
database queries independently.
The query results aren't merged here storing
redundant information, and will have a hit
only if application issues exact query, so hit
rates are low
Continued….
14. Techniques to Scale Web Applications 14
Content-Blind data Caching (CBC)
This have some advantages over CAC as,
Incurs very little computational load.
Caching query results as result sets instead of database
records, so can return results immediately.
Finally, inserting a new element into the cache doesn't
require a query rewrite.
15. 15
Scalable Web hosting.
(a) edge computing, (b) content-aware caching,
(c) content-blind caching, and (d) data replication.
16. Analysis of Caching and Replication
Strategies for Web Applications 16
Performance Analysis
To compare the four techniques, they have
made use of two different applications,
RUBBoS, a bulletin-board benchmark application that
models Slashdot.org,
http://jmob.objectweb.org/rubbos.html
TPC-W, an industry-standard e-commerce benchmark
that models an online book store such as Amazon.com,
http://pgfoundry.org/projects/tpc-w-php/
17. Analysis of Caching and Replication
Strategies for Web Applications 17
Performance Analysis
They have measured the end-to-end client
latency, which is the sum of network latency
and internal latency.
The results shows that CBC performed best
in terms of client latency whereas EC
performed the worst for RUBBoS.
Were as for TPC-W REPL performed the best
and EC worst again.
18. Analysis of Caching and Replication
Strategies for Web Applications 18
Performance Results
(a) RUBBoS benchmark
(b) TPC-W Browsing
(c) TPC-W Ordering
19. Analysis of Caching and Raeplication
Strategies for Web Applications 19
Choosing the Right Strategy
According to the author the Web designers should
choose the scalable technique by carefully
analyzing their Web application characteristics.
They have suggested the best strategy is the one
that minimizes the applications end-to-end client
latency.
This latency is affected by many parameters as hit
ratio, database query execution time, application
server execution time.
To do this they have proposed a concept called
virtual caches (VC).
Continued…
20. Analysis of Caching and Raeplication
Strategies for Web Applications 20
Choosing the Right Strategy
VC behaves just like a real cache but it stores
only meta data, such as the list of objects in
the cache, sizes. So this requires less
memory compared to real caches.
So with the help of these VC we can get the
hit ratios and execution times for servers and
can estimate end-to-end latency.
21. Analysis of Caching and Replication
Strategies for Web Applications 21
Thank You.