This document discusses high availability and database replication techniques. It describes a non-stop service system that aims to minimize downtime through planned and unplanned maintenance. High availability ensures near 100% uptime through techniques implemented at the software and hardware levels. Database replication synchronizes databases across nodes to enable failover. There are two main architectures: shared nothing uses replication over a network while shared disk shares storage. Key considerations in choosing an approach include performance, costs, distance between nodes, and data consistency. The document then outlines the features and benefits of database replication, including its use for high availability, load balancing, and disaster recovery.
Base paper ppt-. A load balancing model based on cloud partitioning for the ...Lavanya Vigrahala
A load balancing model based on cloud partitioning for the public cloud. -Load balancing in the cloud computing environment has an important impact on the performance. Good load balancing makes cloud computing more efficient and improves user satisfaction. This article introduces a better load balance model for the public cloud based on the cloud partitioning concept with a switch mechanism to choose different strategies for different situations. The algorithm applies the game theory to the load balancing strategy to improve the efficiency in the public cloud environment.
Load balancing In cloud - In a semi distributed systemAchal Gupta
Load Balancing in Cloud
What is load balancing in Cloud in semi distributed system and why it is better than a centralized system and distributed system
slides are about load balancing as a concept and implementation of load balancing on computer technical level
slides show the server load balancing
different architectures , algorithms and examples
In the FACTS-based transmission line, if the fault does not include FACTS device, then the impedance calculation is like an ordinary transmission line, and when the fault includes FACTS, then the impedance calculation accounts for the impedances introduced by FACTS device.
Base paper ppt-. A load balancing model based on cloud partitioning for the ...Lavanya Vigrahala
A load balancing model based on cloud partitioning for the public cloud. -Load balancing in the cloud computing environment has an important impact on the performance. Good load balancing makes cloud computing more efficient and improves user satisfaction. This article introduces a better load balance model for the public cloud based on the cloud partitioning concept with a switch mechanism to choose different strategies for different situations. The algorithm applies the game theory to the load balancing strategy to improve the efficiency in the public cloud environment.
Load balancing In cloud - In a semi distributed systemAchal Gupta
Load Balancing in Cloud
What is load balancing in Cloud in semi distributed system and why it is better than a centralized system and distributed system
slides are about load balancing as a concept and implementation of load balancing on computer technical level
slides show the server load balancing
different architectures , algorithms and examples
In the FACTS-based transmission line, if the fault does not include FACTS device, then the impedance calculation is like an ordinary transmission line, and when the fault includes FACTS, then the impedance calculation accounts for the impedances introduced by FACTS device.
PROPOSED LOAD BALANCING ALGORITHM TO REDUCE RESPONSE TIME AND PROCESSING TIME...IJCNCJournal
Cloud computing is a new technology that brings new challenges to all organizations around the world.
Improving response time for user requests on cloud computing is a critical issue to combat bottlenecks. As
for cloud computing, bandwidth to from cloud service providers is a bottleneck. With the rapid development
of the scale and number of applications, this access is often threatened by overload. Therefore, this paper
our proposed Throttled Modified Algorithm(TMA) for improving the response time of VMs on cloud
computing to improve performance for end-user. We have simulated the proposed algorithm with the
CloudAnalyts simulation tool and this algorithm has improved response times and processing time of the
cloud data center.
ieee standard base paper.-Load balancing in the cloud computing environment has an important impact on the performance. Good load balancing makes cloud computing more efficient and improves user satisfaction. This article introduces a better load balance model for the public cloud based on the cloud partitioning concept with a switch mechanism to choose different strategies for different situations. The algorithm applies the game theory to the load balancing strategy to improve the efficiency in the public cloud environment.
A load balancing model based on cloud partitioning for the public cloud. ppt Lavanya Vigrahala
Load balancing in the cloud computing environment has an important impact on the performance. Good load balancing makes cloud computing more efficient and improves user satisfaction. This article introduces a better load balance model for the public cloud based on the cloud partitioning concept with a switch mechanism to choose different strategies for different situations. The algorithm applies the game theory to the load balancing strategy to improve the efficiency in the public cloud environment.
Web-Server Load Balancing, a process that distributes the load of various incoming requests to several servers (e.g. using a gateway that functions as a dispatcher), in an effort to balance the load among these servers in an optimal way. This thesis inspects the various methods and strategies of server load balancing, clearly identifying the advantages and disadvantages of each strategy. We present a working, high performance implementation of the content-aware traffic redirection strategy, using the most well known scheduling algorithms. We also present the results of testing the effectiveness of the implementation and the scheduling algorithms in several scenarios. Finally, based on our work, we concluded that what seem to be the best scheduling algorithms in the case of identical requests are the least CPU usage and the weighted random scheduling algorithms which have the best response time and the best throughput. While in the case of non-identical requests the weighted round robin and the least CPU usage have the least response time and the greatest throughput.
By: Abdul-Lateef Haji-Ali, Yael Jari,
Bashar Shehadeh, Mhd. Mamdouh Tarabishi
Wael Tayara
Supervised by: Dr. Ghassan Saba
Performance Comparision of Dynamic Load Balancing Algorithm in Cloud ComputingEswar Publications
Cloud computing as a distributed paradigm, it has the latent to make over a large part of the Cooperative industry. In cloud computing it’s automatically describe more technologies like distributed computing, virtualization, software, web services and networking. We review the new cloud computing technologies, and indicate the main challenges for their development in future, among which load balancing problem stands out and attracts our attention Concept of load balancing in networking and in cloud environment both are widely different. Load balancing in networking its complete concern to avoid the problem of overloading and under loading in any sever networking cloud computing its complete different its involves different elements metrics such as security, reliability, throughput, tolerance, on demand services, cost etc. Through these elements we avoiding various node problem of distributing system where many services waiting for request and others are heavily loaded and through these its increase response time and degraded performance optimization. In this paper first we classify algorithms in static and dynamic. Then we analyzed the dynamic algorithms applied in dynamics environments in cloud. Through this paper we have been show compression of various dynamics algorithm in which we include honey bee algorithm, throttled algorithm, Biased random algorithm with different elements and describe how and which is best in cloud environment with different metrics mainly used elements are performance, resource utilization and minimum cost. Our main focus of paper is in the analyze various load
balancing algorithms and their applicability in cloud environment.
This is the Complete Information about Data Replication you need, i am focused on these topics:
What is replication?
Who use it?
Types ?
Implementation Methods?
Scheduling in distributed systems - Andrii VozniukAndrii Vozniuk
My EPFL candidacy exam presentation: http://wiki.epfl.ch/edicpublic/documents/Candidacy%20exam/vozniuk_andrii_candidacy_writeup.pdf
Here I present how schedulers work in three distributed data processing systems and their possible optimizations. I consider Gamma - a parallel database, MapReduce - a data-intensive system and Condor - a compute-intensive system.
This talk is based on the following papers:
1) Batch Scheduling in Parallel Database Systems by Manish Mehta, Valery Soloviev and David J. DeWitt
2) Improving MapReduce performance in heterogeneous environments by Matei Zaharia, Andy Konwinski, Anthony D. Joseph, Randy Katz and Ion Stoica
3) Batch Scheduling in Parallel Database Systems by Manish Mehta, Valery Soloviev and David J. DeWitt
Load Balancing In Distributed ComputingRicha Singh
Load Balancing In Distributed Computing
The goal of the load balancing algorithms is to maintain the load to each processing element such that all the processing elements become neither overloaded nor idle that means each processing element ideally has equal load at any moment of time during execution to obtain the maximum performance (minimum execution time) of the system
Webinar Slides: Real-Time Replication vs. ETL - How Analytics Requires New Te...Continuent
There are many ways of moving data from source databases into your target system. Historically, the Extract, Transform, and Load (ETL) has been the method for moving data effectively between databases and analytics platforms. But ETL is no longer necessarily the right solution for the modern data-movement needs. Back in the early days of data movement, extraction on a monthly, weekly, even daily, basis could be enough. Today, analytics often needs to be executed the same day, sometimes even within seconds of the original data being generated. Replication, where information is moved in near real-time, provides a more efficient, and quicker, data movement solution.
AGENDA
- How ETL operates
- How Change Data Capture (CDC) operates
- Replication operation
- Comparing data movement cadence
- The data impedance mismatch
Super, Mainframe computers are not cost effective
Cluster technology have been developed that allow multiple low cost computers to work in coordinated fashion to process applications.
PROPOSED LOAD BALANCING ALGORITHM TO REDUCE RESPONSE TIME AND PROCESSING TIME...IJCNCJournal
Cloud computing is a new technology that brings new challenges to all organizations around the world.
Improving response time for user requests on cloud computing is a critical issue to combat bottlenecks. As
for cloud computing, bandwidth to from cloud service providers is a bottleneck. With the rapid development
of the scale and number of applications, this access is often threatened by overload. Therefore, this paper
our proposed Throttled Modified Algorithm(TMA) for improving the response time of VMs on cloud
computing to improve performance for end-user. We have simulated the proposed algorithm with the
CloudAnalyts simulation tool and this algorithm has improved response times and processing time of the
cloud data center.
ieee standard base paper.-Load balancing in the cloud computing environment has an important impact on the performance. Good load balancing makes cloud computing more efficient and improves user satisfaction. This article introduces a better load balance model for the public cloud based on the cloud partitioning concept with a switch mechanism to choose different strategies for different situations. The algorithm applies the game theory to the load balancing strategy to improve the efficiency in the public cloud environment.
A load balancing model based on cloud partitioning for the public cloud. ppt Lavanya Vigrahala
Load balancing in the cloud computing environment has an important impact on the performance. Good load balancing makes cloud computing more efficient and improves user satisfaction. This article introduces a better load balance model for the public cloud based on the cloud partitioning concept with a switch mechanism to choose different strategies for different situations. The algorithm applies the game theory to the load balancing strategy to improve the efficiency in the public cloud environment.
Web-Server Load Balancing, a process that distributes the load of various incoming requests to several servers (e.g. using a gateway that functions as a dispatcher), in an effort to balance the load among these servers in an optimal way. This thesis inspects the various methods and strategies of server load balancing, clearly identifying the advantages and disadvantages of each strategy. We present a working, high performance implementation of the content-aware traffic redirection strategy, using the most well known scheduling algorithms. We also present the results of testing the effectiveness of the implementation and the scheduling algorithms in several scenarios. Finally, based on our work, we concluded that what seem to be the best scheduling algorithms in the case of identical requests are the least CPU usage and the weighted random scheduling algorithms which have the best response time and the best throughput. While in the case of non-identical requests the weighted round robin and the least CPU usage have the least response time and the greatest throughput.
By: Abdul-Lateef Haji-Ali, Yael Jari,
Bashar Shehadeh, Mhd. Mamdouh Tarabishi
Wael Tayara
Supervised by: Dr. Ghassan Saba
Performance Comparision of Dynamic Load Balancing Algorithm in Cloud ComputingEswar Publications
Cloud computing as a distributed paradigm, it has the latent to make over a large part of the Cooperative industry. In cloud computing it’s automatically describe more technologies like distributed computing, virtualization, software, web services and networking. We review the new cloud computing technologies, and indicate the main challenges for their development in future, among which load balancing problem stands out and attracts our attention Concept of load balancing in networking and in cloud environment both are widely different. Load balancing in networking its complete concern to avoid the problem of overloading and under loading in any sever networking cloud computing its complete different its involves different elements metrics such as security, reliability, throughput, tolerance, on demand services, cost etc. Through these elements we avoiding various node problem of distributing system where many services waiting for request and others are heavily loaded and through these its increase response time and degraded performance optimization. In this paper first we classify algorithms in static and dynamic. Then we analyzed the dynamic algorithms applied in dynamics environments in cloud. Through this paper we have been show compression of various dynamics algorithm in which we include honey bee algorithm, throttled algorithm, Biased random algorithm with different elements and describe how and which is best in cloud environment with different metrics mainly used elements are performance, resource utilization and minimum cost. Our main focus of paper is in the analyze various load
balancing algorithms and their applicability in cloud environment.
This is the Complete Information about Data Replication you need, i am focused on these topics:
What is replication?
Who use it?
Types ?
Implementation Methods?
Scheduling in distributed systems - Andrii VozniukAndrii Vozniuk
My EPFL candidacy exam presentation: http://wiki.epfl.ch/edicpublic/documents/Candidacy%20exam/vozniuk_andrii_candidacy_writeup.pdf
Here I present how schedulers work in three distributed data processing systems and their possible optimizations. I consider Gamma - a parallel database, MapReduce - a data-intensive system and Condor - a compute-intensive system.
This talk is based on the following papers:
1) Batch Scheduling in Parallel Database Systems by Manish Mehta, Valery Soloviev and David J. DeWitt
2) Improving MapReduce performance in heterogeneous environments by Matei Zaharia, Andy Konwinski, Anthony D. Joseph, Randy Katz and Ion Stoica
3) Batch Scheduling in Parallel Database Systems by Manish Mehta, Valery Soloviev and David J. DeWitt
Load Balancing In Distributed ComputingRicha Singh
Load Balancing In Distributed Computing
The goal of the load balancing algorithms is to maintain the load to each processing element such that all the processing elements become neither overloaded nor idle that means each processing element ideally has equal load at any moment of time during execution to obtain the maximum performance (minimum execution time) of the system
Webinar Slides: Real-Time Replication vs. ETL - How Analytics Requires New Te...Continuent
There are many ways of moving data from source databases into your target system. Historically, the Extract, Transform, and Load (ETL) has been the method for moving data effectively between databases and analytics platforms. But ETL is no longer necessarily the right solution for the modern data-movement needs. Back in the early days of data movement, extraction on a monthly, weekly, even daily, basis could be enough. Today, analytics often needs to be executed the same day, sometimes even within seconds of the original data being generated. Replication, where information is moved in near real-time, provides a more efficient, and quicker, data movement solution.
AGENDA
- How ETL operates
- How Change Data Capture (CDC) operates
- Replication operation
- Comparing data movement cadence
- The data impedance mismatch
Super, Mainframe computers are not cost effective
Cluster technology have been developed that allow multiple low cost computers to work in coordinated fashion to process applications.
Advanced Health Support Supplement for Men. EASIER AND FASTER than taking hard to swallow pills, capsules or tablets. Large 2 oz bottle allows you to get more bang for your buck.
These slides cover a topic on X.25, Frame relay and ATM in Data Communication. All the slides are explained in a very simple manner. It is useful for engineering students & also for the candidates who want to master data communication & computer networking.
Network-aware Data Management for Large Scale Distributed Applications, IBM R...balmanme
IBM Research – Talk – June 24, 2015
Title:
Network-aware Data Management for Large Scale Distributed Applications
Abstract:
As current technology enables faster storage devices and larger interconnect bandwidth, there is a substantial need for novel system design and middleware architecture to address increasing latency, scalability, and throughput requirements. In this talk, I will outline network-aware data management and present solutions based on my past experience in large-scale data migration between remote repositories.
I will first describe my experience in the initial evaluation of 100Gbps network as a part of the Advance Network Initiative project. We needed intense fine-tuning in network, storage, and application layers, to take advantage of the higher network capacity. End-system bottlenecks and system performance play an important role especially in many-core platforms. I will introduce a special data movement prototype, successfully tested in one of the first 100Gbps demonstrations, in which applications map memory blocks for remote data, in contrast to the send/receive semantics. This prototype was used to stream climate data over wide-area for in-memory application processing and visualization.
Within this scope, I will introduce a flexible network reservation algorithm for on-demand bandwidth guaranteed virtual circuit services. Flexible reservations find best path in a time-dependent dynamic network topology to support predictable application performance. I will then present a data-scheduling model with advance provisioning, in which data movement operations are defined with earliest start and latest completion times.
I will conclude my talk with a very brief overview of my other related projects on performance engineering, hyper-converged virtual storage, and optimization in control and data path for virtualized environments.
Network-aware Data Management for High Throughput Flows Akamai, Cambridge, ...balmanme
As current technology enables faster storage devices and larger interconnect bandwidth, there is a substantial need for novel system design and middleware architecture to address increasing latency, scalability, and throughput requirements. In this talk, I will outline network-aware data management and present solutions based on my past experience in large-scale data migration between remote repositories.
I will first describe my experience in the initial evaluation of 100Gbps network as a part of the Advance Network Initiative project. We needed intense fine-tuning in network, storage, and application layers, to take advantage of the higher network capacity. I will introduce a special data movement prototype, successfully tested in one of the first 100Gbps demonstrations, in which applications map memory blocks for remote data, in contrast to the send/receive semantics.
Within this scope, I will introduce a flexible network reservation algorithm for on-demand bandwidth guaranteed virtual circuit services. Flexible reservations find best path in a time-dependent dynamic network topology to support predictable application performance. I will then present a data-scheduling model with advance provisioning, in which data movement operations are defined with earliest start and latest completion times.
I will conclude my talk with a very brief overview of my other related projects on performance engineering, hyper-converged virtual storage, and optimization in control and data path for virtualized environments.
Sept 28, 2015
Akamai, Cambridge, MA
Cloud computing system models for distributed and cloud computinghrmalik20
System Models for Distributed and Cloud
Computing,Peer-to-peer (P2P) Networks,Computational and Data Grids,Clouds,Advantage of Clouds over Traditional
Distributed Systems,Performance Metrics and Scalability Analysis,System Efficiency,Performance Challenges in Cloud Computing,WHY CLOUD COMPUTING,What is cloud computing and why is it distinctive,CLOUD SERVICE DELIVERY MODELS AND THEIR
PERFORMANCE CHALLENGES,Cloud computing security,What does Cloud Computing Security mean,Cloud Security Landscape,Energy Efficiency of Cloud Computing,How energy-efficient is cloud computing?
Cloud Computing System models for Distributed and cloud computing & Performan...hrmalik20
Advantage of Clouds over Traditional
Distributed Systems,Clouds,Service-Oriented Architecture (SOA) Layered Architecture,Performance Metrics and Scalability Analysis,System Efficiency,Performance Challenges in Cloud Computing,What is cloud computing and why is it distinctive?,CLOUD SERVICE DELIVERY MODELS AND THEIR
PERFORMANCE CHALLENGES,Cloud computing security,What does Cloud Computing Security mean,Cloud Security Landscape,Distinctions between Security and Privacy,Energy Efficiency of Cloud Computing,How energy-efficient is cloud computing?
Tales From The Front: An Architecture For Multi-Data Center Scalable Applicat...DataStax Academy
- Quick review of Cassandra functionality that applies to this use case
- Common Data Center and application architectures for highly available inventory applications, and why the were designed that way
- Cassandra implementations vis-a-vis infrastructure capabilities
The impedance mismatch: compromises made to fit into IT infrastructures designed and implemented with an old mindset
A Parallel Sysplex is a cluster of IBM mainframes acting together as a single system image with z/OS that cooperate, using certain hardware and software products, to process work. Used for disaster recovery, Parallel Sysplex combines data sharing and parallel computing to allow a cluster of up to 32 mainframes to share a workload for high performance and high availability.Parallel Sysplex is analogous in concept to a UNIX cluster – allow the customer to operate multiple copies of the operating system as a single system. This allows systems to be added or removed as needed, while applications continue to run.
Geographically Dispersed Parallel Sysplex (GDPS) is an end to end application availability solution. It is the ultimate disaster recovery and continuous availability solution for a multi-site enterprise. GDPS disk replication technology enhances the resiliency and provides continues availability of data by masking disk outages.
Similar to [Altibase] 8 replication part1 (overview) (20)
Providing Globus Services to Users of JASMIN for Environmental Data AnalysisGlobus
JASMIN is the UK’s high-performance data analysis platform for environmental science, operated by STFC on behalf of the UK Natural Environment Research Council (NERC). In addition to its role in hosting the CEDA Archive (NERC’s long-term repository for climate, atmospheric science & Earth observation data in the UK), JASMIN provides a collaborative platform to a community of around 2,000 scientists in the UK and beyond, providing nearly 400 environmental science projects with working space, compute resources and tools to facilitate their work. High-performance data transfer into and out of JASMIN has always been a key feature, with many scientists bringing model outputs from supercomputers elsewhere in the UK, to analyse against observational or other model data in the CEDA Archive. A growing number of JASMIN users are now realising the benefits of using the Globus service to provide reliable and efficient data movement and other tasks in this and other contexts. Further use cases involve long-distance (intercontinental) transfers to and from JASMIN, and collecting results from a mobile atmospheric radar system, pushing data to JASMIN via a lightweight Globus deployment. We provide details of how Globus fits into our current infrastructure, our experience of the recent migration to GCSv5.4, and of our interest in developing use of the wider ecosystem of Globus services for the benefit of our user community.
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.
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
Top Features to Include in Your Winzo Clone App for Business Growth (4).pptxrickgrimesss22
Discover the essential features to incorporate in your Winzo clone app to boost business growth, enhance user engagement, and drive revenue. Learn how to create a compelling gaming experience that stands out in the competitive market.
A Comprehensive Look at Generative AI in Retail App Testing.pdfkalichargn70th171
Traditional software testing methods are being challenged in retail, where customer expectations and technological advancements continually shape the landscape. Enter generative AI—a transformative subset of artificial intelligence technologies poised to revolutionize software testing.
Accelerate Enterprise Software Engineering with PlatformlessWSO2
Key takeaways:
Challenges of building platforms and the benefits of platformless.
Key principles of platformless, including API-first, cloud-native middleware, platform engineering, and developer experience.
How Choreo enables the platformless experience.
How key concepts like application architecture, domain-driven design, zero trust, and cell-based architecture are inherently a part of Choreo.
Demo of an end-to-end app built and deployed on Choreo.
TROUBLESHOOTING 9 TYPES OF OUTOFMEMORYERRORTier1 app
Even though at surface level ‘java.lang.OutOfMemoryError’ appears as one single error; underlyingly there are 9 types of OutOfMemoryError. Each type of OutOfMemoryError has different causes, diagnosis approaches and solutions. This session equips you with the knowledge, tools, and techniques needed to troubleshoot and conquer OutOfMemoryError in all its forms, ensuring smoother, more efficient Java applications.
Prosigns: Transforming Business with Tailored Technology SolutionsProsigns
Unlocking Business Potential: Tailored Technology Solutions by Prosigns
Discover how Prosigns, a leading technology solutions provider, partners with businesses to drive innovation and success. Our presentation showcases our comprehensive range of services, including custom software development, web and mobile app development, AI & ML solutions, blockchain integration, DevOps services, and Microsoft Dynamics 365 support.
Custom Software Development: Prosigns specializes in creating bespoke software solutions that cater to your unique business needs. Our team of experts works closely with you to understand your requirements and deliver tailor-made software that enhances efficiency and drives growth.
Web and Mobile App Development: From responsive websites to intuitive mobile applications, Prosigns develops cutting-edge solutions that engage users and deliver seamless experiences across devices.
AI & ML Solutions: Harnessing the power of Artificial Intelligence and Machine Learning, Prosigns provides smart solutions that automate processes, provide valuable insights, and drive informed decision-making.
Blockchain Integration: Prosigns offers comprehensive blockchain solutions, including development, integration, and consulting services, enabling businesses to leverage blockchain technology for enhanced security, transparency, and efficiency.
DevOps Services: Prosigns' DevOps services streamline development and operations processes, ensuring faster and more reliable software delivery through automation and continuous integration.
Microsoft Dynamics 365 Support: Prosigns provides comprehensive support and maintenance services for Microsoft Dynamics 365, ensuring your system is always up-to-date, secure, and running smoothly.
Learn how our collaborative approach and dedication to excellence help businesses achieve their goals and stay ahead in today's digital landscape. From concept to deployment, Prosigns is your trusted partner for transforming ideas into reality and unlocking the full potential of your business.
Join us on a journey of innovation and growth. Let's partner for success with Prosigns.
Software Engineering, Software Consulting, Tech Lead.
Spring Boot, Spring Cloud, Spring Core, Spring JDBC, Spring Security,
Spring Transaction, Spring MVC,
Log4j, REST/SOAP WEB-SERVICES.
Exploring Innovations in Data Repository Solutions - Insights from the U.S. G...Globus
The U.S. Geological Survey (USGS) has made substantial investments in meeting evolving scientific, technical, and policy driven demands on storing, managing, and delivering data. As these demands continue to grow in complexity and scale, the USGS must continue to explore innovative solutions to improve its management, curation, sharing, delivering, and preservation approaches for large-scale research data. Supporting these needs, the USGS has partnered with the University of Chicago-Globus to research and develop advanced repository components and workflows leveraging its current investment in Globus. The primary outcome of this partnership includes the development of a prototype enterprise repository, driven by USGS Data Release requirements, through exploration and implementation of the entire suite of the Globus platform offerings, including Globus Flow, Globus Auth, Globus Transfer, and Globus Search. This presentation will provide insights into this research partnership, introduce the unique requirements and challenges being addressed and provide relevant project progress.
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
In software engineering, the right architecture is essential for robust, scalable platforms. Wix has undergone a pivotal shift from event sourcing to a CRUD-based model for its microservices. This talk will chart the course of this pivotal journey.
Event sourcing, which records state changes as immutable events, provided robust auditing and "time travel" debugging for Wix Stores' microservices. Despite its benefits, the complexity it introduced in state management slowed development. Wix responded by adopting a simpler, unified CRUD model. This talk will explore the challenges of event sourcing and the advantages of Wix's new "CRUD on steroids" approach, which streamlines API integration and domain event management while preserving data integrity and system resilience.
Participants will gain valuable insights into Wix's strategies for ensuring atomicity in database updates and event production, as well as caching, materialization, and performance optimization techniques within a distributed system.
Join us to discover how Wix has mastered the art of balancing simplicity and extensibility, and learn how the re-adoption of the modest CRUD has turbocharged their development velocity, resilience, and scalability in a high-growth environment.
OpenFOAM solver for Helmholtz equation, helmholtzFoam / helmholtzBubbleFoamtakuyayamamoto1800
In this slide, we show the simulation example and the way to compile this solver.
In this solver, the Helmholtz equation can be solved by helmholtzFoam. Also, the Helmholtz equation with uniformly dispersed bubbles can be simulated by helmholtzBubbleFoam.
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/
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.
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.
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 Connect Server Deep Dive - GlobusWorld 2024Globus
We explore the Globus Connect Server (GCS) architecture and experiment with advanced configuration options and use cases. This content is targeted at system administrators who are familiar with GCS and currently operate—or are planning to operate—broader deployments at their institution.
Globus Connect Server Deep Dive - GlobusWorld 2024
[Altibase] 8 replication part1 (overview)
1. Non-Stop Service System
Minimizing Downtime and Maintaining the system availability up to 100%
Planed Downtime – Regular inspection & System upgrade/patch
Executing Switch-Over : Main modification of normal service
Unplanned Downtime – Failure in some systems
Executing Fail-Over : Main modification of urgent service
High Availability / HA
Non-stop system or the availability of its contents
five 9 (99.999%)
Various techniques exist at the level of S/W and H/W
HA of DBMS
Activates by synchronizing the databases through nodes
Techniques are different depending on the architecture of parallel database
2. Categories Shared Nothing Architecture Shared Disk Architecture
Shared resources There is no shared resources Disk
Data
synchronization
Replication through network Sharing disk
Performance*
Fast performance as there is no shared
resources
Performance reduced by complicated
Processing(2PC/3PC) of shared resources
System costs* Low costs (Local disk & Network) High costs(Shared storage facilities)
Distance*
There are not too much harsh in a long distance
as the general TCP based network is used
There is a restriction of distance as the dedicated
network of high cost for sharing disk is required
Data conformity*
The extra consideration is required to control
the data inconsistency in each node for the
features of network replication
The data conformity is guaranteed in each nodes as
the data is shared
Critical Failures
Unable to synchronize nodes when there is a
network failure
Entire services in system do not work when there is a
disk failure
Appropriate system
Faster performance is more required than
data conformity
Data conformity is more required than
performance
Relevant DBMS
technique
Replication RAC (Real Application Cluster)
Relevant DBMS
ALTIBASE HDB, DB2, MS-SQL, ORACLE,
SYBASE
ORACLE, DB2
▣Trade-off between “performance, system establishment costs, distance” and “ data conformity”
3. DB
SERVER main
DB
SERVER sub
replication
AP 1 AP n
Fail-Over
AP 1 APm+1AP m AP n
DB
SERVER main
DB
SERVER sub
replication
[Figure 1, High Availability secured in a 2-Way Replication System] [Figure 2, Scalability improved in a 2-Way Replication System]
What is Replication?
Replication is a technique for sending information about the changes to the contents of
a single database over a network to one or more other databases.
The Purpose of Replication
♦ Secures High Availability
♦ Improves performance and scalability by Load-balancing
♦ Minimizes Data Loss in the Event of a Physical Outage or Disaster
4. Main Features Description
TCP/IP Network-Based
Because the only facility that is required for replication is a network connection, no
additional expenses are incurred. Replication over long distances is possible, depending on
network performance (a Gigabit LAN is recommended)
Heterogeneous OS Support
Replication is possible between heterogeneous operating systems, and regardless of the
number of OS bits (32 or 64) or CPU endian
Integrated Replication
High Performance as the replication module is completely integrated with DBMS
No additional ALTIBASE HDB packages are required for replication
ALTIBASE HDB can be flexibly used depending on the user’s requirements
Redo Log-based Redo logs are sent in real time by records
Table-Based Management
Replication is managed by table
Table can be added to replication or deleted from replication while database is running
Two Modes: LAZY and EAGER Supports both LAZY(Async) and EAGER(Sync) replication modes
High-Speed Replication
In LAZY mode, the replication is executed with at least 95% of master transactions speed
while not affecting the master transaction
(Measured on a UNIX system in a Gigabit LAN environment)
Up to 32-Way Replication
A single ALTIBASE HDB node can have up to 32 replication objects
Load distribution across heterogeneous systems is supported
5. Main Features Description
Point-To-Point Replication Replicating 1:1 only between nodes that it does not transfer to other nodes
Network Fault Detection ALTIBASE HDB provides dedicated threads to detect physical network faults
Automatic Recovery
The time point at which replication was most recently performed is recorded. In the event
of network failure, replication resumes automatically once the network connection is
restored.
Support for Multiple IPs
If two or more IP addresses are assigned to a single replication, replication can
automatically switch to the other IP address in the event of a network fault, thus increasing
the availability of replication.
Control via SQL Interface
All commands required in order to use and manage replication have an SQL interface thus
it is convenient to use.
Data Conflict Resolution Methods Three (3) schemes and one (1) utility are provided to resolve data conflicts.
Additional Functions
Replication can be used to clone (i.e. copy the entire contents of) tables.
If the active node fails, offline replication can be conducted to access the redo log files on
the node that failed and resume replication on the standby node.