Server virtualization has forever changed the way we think about compute resources. Traditional storage architecture is a mismatch for today's virtualized environments. Gridstore's unique and patented architecture solves this problem and increases performance while decreasing costs. Learn how.
The benefits of employing virtualization in the corporate data center are compelling – lower operating
costs, better resource utilization, increased availability of critical infrastructure to name just a few. It is an
apparent “no brainer” which explains why so many organizations are jumping on the bandwagon. Industry
analysts estimate that between 60 and 80 percent of IT departments are actively working on server
consolidation projects using virtualization. But what are the challenges for operations and security staff
when it comes to management and ensuring the security of the new virtual enterprise? With new
technology, complexity and invariably new management challenges generally follow.
Over the last 18 months, Prism Microsystems, a leading security information and event management
(SIEM) vendor, working closely with a set of early adopter customers and prospects, has been working on
extending the capability of EventTracker to provide deep support for virtualization, enabling our customers
to get the same level of security for the virtualized enterprise as they have for their non-virtualized
enterprise. This White Paper examines the technology and management challenges that result from
virtualization, and how EventTracker addresses them.
Virtualization refers to the creation of a virtual resource such as a server, desktop, operating system, file, storage or network.
The main goal of virtualization is to manage workloads by radically transforming traditional computing to make it more scalable.
The server administrator uses a software application to divide one physical server into multiple isolated virtual environments.
The benefits of employing virtualization in the corporate data center are compelling – lower operating
costs, better resource utilization, increased availability of critical infrastructure to name just a few. It is an
apparent “no brainer” which explains why so many organizations are jumping on the bandwagon. Industry
analysts estimate that between 60 and 80 percent of IT departments are actively working on server
consolidation projects using virtualization. But what are the challenges for operations and security staff
when it comes to management and ensuring the security of the new virtual enterprise? With new
technology, complexity and invariably new management challenges generally follow.
Over the last 18 months, Prism Microsystems, a leading security information and event management
(SIEM) vendor, working closely with a set of early adopter customers and prospects, has been working on
extending the capability of EventTracker to provide deep support for virtualization, enabling our customers
to get the same level of security for the virtualized enterprise as they have for their non-virtualized
enterprise. This White Paper examines the technology and management challenges that result from
virtualization, and how EventTracker addresses them.
Virtualization refers to the creation of a virtual resource such as a server, desktop, operating system, file, storage or network.
The main goal of virtualization is to manage workloads by radically transforming traditional computing to make it more scalable.
The server administrator uses a software application to divide one physical server into multiple isolated virtual environments.
Hyperconvergence is the biggest IT shift since the rise of server virtualization. With any budding space, there tends to be some confusion around the technology. The FAQs in this paper were compiled to help clear up some of the confusion and highlight key customer benefits for using hyperconvergence.
There has been a lot of interest and buzz recently around hyperconvergence. It's the biggest IT shift since the rise of server virtualization. As with any budding space there is some confusion. This paper looks at the top 10 benefits of hyperconvergence and and also answers some frequently asked questions.
Virtualization, A Concept Implementation of CloudNishant Munjal
This presentation will guide through deploying virtualization in linux environment and get its access to another machine followed by virtualization concept.
In a globally dispersed enterprise with private cloud environment, where unstructured data is exponentially growing, there is a need to provide 24x7 accesses to business-critical data and be able to restore in case of loss of data. IBM Scale Out Network Attached Storage (IBM SONAS) with its integrated IBM Tivoli Storage Manager client enables enterprises to back up and restore data seamlessly and the IBM Active Cloud Engine offers the capability to replicate data to remote sites.
This presentation offers an introductory explanation of data center virtualization for audiences who are just beginning to learn how it works and why it might make sense for their organization.
Updated lifecycle management, improved analytics and support, and the option of Kubernetes — VMware vSphere® 7 is the biggest re-platform of vSphere in years. Learn more about the most significant vSphere evolution in a decade.
Learn more: http://ms.spr.ly/6005TmX9B
Conozca el texto del acuerdo de Paz que se enviará al Legislativo acompañado de Ley Estatutaria 1806, por medio de la cual se regula el plebiscito para la refrendación del acuerdo final, que fija fecha para 2 de octubre de 2016.
Hyperconvergence is the biggest IT shift since the rise of server virtualization. With any budding space, there tends to be some confusion around the technology. The FAQs in this paper were compiled to help clear up some of the confusion and highlight key customer benefits for using hyperconvergence.
There has been a lot of interest and buzz recently around hyperconvergence. It's the biggest IT shift since the rise of server virtualization. As with any budding space there is some confusion. This paper looks at the top 10 benefits of hyperconvergence and and also answers some frequently asked questions.
Virtualization, A Concept Implementation of CloudNishant Munjal
This presentation will guide through deploying virtualization in linux environment and get its access to another machine followed by virtualization concept.
In a globally dispersed enterprise with private cloud environment, where unstructured data is exponentially growing, there is a need to provide 24x7 accesses to business-critical data and be able to restore in case of loss of data. IBM Scale Out Network Attached Storage (IBM SONAS) with its integrated IBM Tivoli Storage Manager client enables enterprises to back up and restore data seamlessly and the IBM Active Cloud Engine offers the capability to replicate data to remote sites.
This presentation offers an introductory explanation of data center virtualization for audiences who are just beginning to learn how it works and why it might make sense for their organization.
Updated lifecycle management, improved analytics and support, and the option of Kubernetes — VMware vSphere® 7 is the biggest re-platform of vSphere in years. Learn more about the most significant vSphere evolution in a decade.
Learn more: http://ms.spr.ly/6005TmX9B
Conozca el texto del acuerdo de Paz que se enviará al Legislativo acompañado de Ley Estatutaria 1806, por medio de la cual se regula el plebiscito para la refrendación del acuerdo final, que fija fecha para 2 de octubre de 2016.
Mora en Aportes Patronales, Mora Pago LicenciaCendap Ltda
La mora en que se puede incurrir en el pago aportes patronales a seguridad social en el sector público genera la consecuente exoneración de la EPS de asumir una licencia o incapacidad dependerá del plazo de los 10 días. (Minsalud, Concepto 201611200447311, 03/17/2016 )
Precisan cuándo hay mora en el giro de aportes patronales a seguridad social en el sector público (1:49 p.m.)
(Minsalud, Concepto 201611200447311, 03/17/2016 )
Con la expedición de la Ley 715 del 2001 y, en especial, del Decreto 1636 del 2006, para el caso de aportes patronales, se modificó el plazo máximo que se tiene para girar los aportes a la seguridad social que regulaba el Decreto 1406 de 1999, modificado por el Decreto 1670 del 2007, por lo que el pago que se realice dentro de los 10 primeros días del mes siguiente al que corresponde la transferencia a que hace alusión el artículo 53 de la ley en mención no constituye mora y, por ende, no genera interés moratorio. Así las cosas, las reglas para el reconocimiento de licencias e incapacidades previstas en el Decreto 2353 del 2015 son aplicables en iguales circunstancias en el sector público y privado, salvo en el caso de giro de aportes patronales en el sector público, caso en el cual la mora en que se puede incurrir en el pago de los mismos y la consecuente exoneración de la EPS de asumir una licencia o incapacidad dependerá del plazo de los 10 días, que de excederse implicaría mora y posiblemente la suspensión de la afiliación, evento en el cual será el empleador quien debe asumir el costo de los servicios de salud que demande el trabajador y su núcleo familiar. Habiéndose producido la suspensión de la afiliación, no habrá lugar al reconocimiento de las prestaciones económicas, salvo que haya mediado un acuerdo de pago o la EPS se hubiese allanado a la mora.
Basics of Cloud Computing and tools required to get into the cloud world. Simply put, cloud computing is the delivery of computing services—including servers, storage, databases, networking, software, analytics, and intelligence—over the Internet (“the cloud”) to offer faster innovation, flexible resources, and economies of scale.
A Survey of Performance Comparison between Virtual Machines and Containersprashant desai
Since the onset of Cloud computing and its inroads into infrastructure as a service, Virtualization has become peak
of importance in the field of abstraction and resource management. However, these additional layers of abstraction provided by virtualization come at a trade-off between performance and cost in a cloud environment where everything is on a pay-per-use basis. Containers which are perceived to be the future of virtualization are developed to address these issues. This study paper scrutinizes the performance of a conventional virtual machine and contrasts them with the containers. We cover the critical
assessment of each parameter and its behavior when its subjected to various stress tests. We discuss the implementations and their performance metrics to help us draw conclusions on which one is ideal to use for desired needs. After assessment of the result and discussion of the limitations, we conclude with prospects for future research
Need for Virtualization – Pros and cons of Virtualization – Types of Virtualization –System VM, Process VM, Virtual Machine monitor – Virtual machine properties - Interpretation and binary translation, HLL VM - supervisors – Xen, KVM, VMware, Virtual Box, Hyper-V.
Virtual versions of servers, applications, networks and storage can be created through virtualization. Its main types include operating system virtualization (VMs), hardware virtualization, application-server virtualization, storage virtualization, network virtualization, administrative virtualization and application virtualization.
In recent years, we have seen an overwhelming number of TV commercials that promise that the Cloud can help with many problems, including some family issues. What stands behind the terms “Cloud” and “Cloud Computing,” and what we can actually expect from this phenomenon? A group of students of the Computer Systems Technology department and Dr. T. Malyuta, whom has been working with the Cloud technologies since its early days, will provide an overview of the business and technological aspects of the Cloud.
Benchmarking a Scalable and Highly Available Architecture for Virtual DesktopsDataCore Software
This paper reports on a configuration for Virtual Desktops (VDs) which reduces the total hardware cost to approximately $32.41 per desktop, including the storage infrastructure. This number is achieved using a configuration with dual node, cross-mirrored, High Availability storage. In comparison to previously published reports, which tout the storage infrastructure costs alone of VDI at from fifty to several hundred dollars per virtual machine, the significance of the data becomes self evident. In this report, storage hardware costs become inconsequential.
Strange but true: most infrastructure architectures are deliberately designed from the outset to need little or no change over their lifetimes. There are two main reasons for this:
1. Change often means outages and customer impact and must be avoided
2. Budgets are set at the beginning of a project and getting more cash later is tough
Typically, then, applications are configured with all of the storage capacity they need to support the wildest dreams of their business sponsors (and then some extra is added for contingency by IT). Equally, storage is always configured with the performance level (storage tier) set to cope with the wildest transactional dreams of the business sponsor (and guess what? IT generally adds a bit more for good measure.).
No wonder storage is now one of the largest cost components involved in delivering and running a business application.
This is a paper was written by David Reine, an IT analyst for The Clipper Group, and highlights IBM’s SAN Volume Controller new features, capabilities and benefits. These new capabilities were announced on October 20, 2009Virtualization is at the center of all 21st Century IT systems, yet many CIOs fail to fully understand all of the benefits it can deliver to the data center operation. When we think of virtualization, we think compute, network, and storage—and we mostly think about driving up utilization on each. Storage controllers have always offered the ability to carve out pieces of real storage from a large pool and deliver them efficiently to a number of hosts, but it is storage virtualization itself that offers improvements that drive operational efficiency. IBM has been quietly addressing storage virtualization with SAN Volume Controller (SVC) for the last six years, building up a significant technical lead in this space.
Short Economic EssayPlease answer MINIMUM 400 word I need this.docxbudabrooks46239
Short Economic Essay
Please answer MINIMUM 400 word
I need this maximum in 2,5 hour because now I’m doing the online final exam and the clock is ticking.
Question:
What is the purpose of the term sheet and why is it important? Be sure to write a detailed long essay to this question. Think about who the term sheet is written for, why it is written, and what does it need to convey.
Cloud Computing: Virtualization and Resiliency for
Data Center Computing
Valentina Salapura
IBM T. J. Watson Research Center
Yorktown Heights, NY, USA
[email protected]
Index Terms — Cloud computing, data center management,
data center optimization, virtualization, Infrastructure as a
service (IaaS), Platform as a service (PaaS), Software as a service
(SaaS), high availability, disaster recovery, virtual appliance.
INTRODUCTION
Cloud computing is being rapidly adopted across the IT
industry, driven by the need to reduce the total cost of
ownership of increasingly more demanding workloads. Within
companies, private clouds are offering a more efficient way to
manage and use private data centers. In the broader
marketplace, public clouds offer the promise of buying
computing capabilities based on a utility model. This utility
model enables IT consumers to purchase compute resources on
demand to fit current business needs and scale expenses
associated with computing resources. Thus, cloud computing
offers IT to be treated as an ongoing variable operating expense
billed by usage rather than requiring capital expenditures that
must be planned years in advance. Advantageously, operating
expenses can be charged against the revenue generated by these
expenses directly. In contrast, capital expenses incurred by the
purchase of a system need to be paid at the time of purchase,
but can only be depreciated to reduce the taxable income over
the lifetime of the system.
THE MAIN ATTRIBUTES OF CLOUD COMPUTING
The main attributes of cloud computing are scalable,
shared, on-demand computing resources delivered over the
network, and pay-per-use pricing. This offers flexibility in
using as few or as many IT resources as needed at any point in
time. Thus, users do not need to predict future resources they
might need, and to commit to capital investment in hardware.
This is especially advantageous for start-ups, and small and
medium businesses which might otherwise not be able to afford
the IT infrastructure they need to support their growing
business. At the same time, redirecting capital investment from
IT infrastructure to the core business is attractive even for large
and financially strong businesses.
From a technical perspective, cloud computing brings the
benefits of virtualization and multi-tenancy to scale-out
systems. Virtualization techniques allow multiple system
images to share the same hardware resources: CPU
virtualization techniques create multiple virtual hardware
systems, while network virtualization .
The Future of Computing: Exploring the Potential of Virtualization ServerFredReynolds2
Virtualization Server may be a viable option if you want to reduce IT expenditures while maximizing your current IT infrastructure’s resources. This method of deploying multiple server applications on a single physical system has gained widespread market acceptance and is proving quite advantageous for small and large businesses.
Enterprise data-centers are straining to keep pace with dynamic business demands, as well as to incorporate advanced technologies and architectures that aim to improve infrastructure performance
Understanding Globus Data Transfers with NetSageGlobus
NetSage is an open privacy-aware network measurement, analysis, and visualization service designed to help end-users visualize and reason about large data transfers. NetSage traditionally has used a combination of passive measurements, including SNMP and flow data, as well as active measurements, mainly perfSONAR, to provide longitudinal network performance data visualization. It has been deployed by dozens of networks world wide, and is supported domestically by the Engagement and Performance Operations Center (EPOC), NSF #2328479. We have recently expanded the NetSage data sources to include logs for Globus data transfers, following the same privacy-preserving approach as for Flow data. Using the logs for the Texas Advanced Computing Center (TACC) as an example, this talk will walk through several different example use cases that NetSage can answer, including: Who is using Globus to share data with my institution, and what kind of performance are they able to achieve? How many transfers has Globus supported for us? Which sites are we sharing the most data with, and how is that changing over time? How is my site using Globus to move data internally, and what kind of performance do we see for those transfers? What percentage of data transfers at my institution used Globus, and how did the overall data transfer performance compare to the Globus users?
Gamify Your Mind; The Secret Sauce to Delivering Success, Continuously Improv...Shahin Sheidaei
Games are powerful teaching tools, fostering hands-on engagement and fun. But they require careful consideration to succeed. Join me to explore factors in running and selecting games, ensuring they serve as effective teaching tools. Learn to maintain focus on learning objectives while playing, and how to measure the ROI of gaming in education. Discover strategies for pitching gaming to leadership. This session offers insights, tips, and examples for coaches, team leads, and enterprise leaders seeking to teach from simple to complex concepts.
Large Language Models and the End of ProgrammingMatt Welsh
Talk by Matt Welsh at Craft Conference 2024 on the impact that Large Language Models will have on the future of software development. In this talk, I discuss the ways in which LLMs will impact the software industry, from replacing human software developers with AI, to replacing conventional software with models that perform reasoning, computation, and problem-solving.
AI Pilot Review: The World’s First Virtual Assistant Marketing SuiteGoogle
AI Pilot Review: The World’s First Virtual Assistant Marketing Suite
👉👉 Click Here To Get More Info 👇👇
https://sumonreview.com/ai-pilot-review/
AI Pilot Review: Key Features
✅Deploy AI expert bots in Any Niche With Just A Click
✅With one keyword, generate complete funnels, websites, landing pages, and more.
✅More than 85 AI features are included in the AI pilot.
✅No setup or configuration; use your voice (like Siri) to do whatever you want.
✅You Can Use AI Pilot To Create your version of AI Pilot And Charge People For It…
✅ZERO Manual Work With AI Pilot. Never write, Design, Or Code Again.
✅ZERO Limits On Features Or Usages
✅Use Our AI-powered Traffic To Get Hundreds Of Customers
✅No Complicated Setup: Get Up And Running In 2 Minutes
✅99.99% Up-Time Guaranteed
✅30 Days Money-Back Guarantee
✅ZERO Upfront Cost
See My Other Reviews Article:
(1) TubeTrivia AI Review: https://sumonreview.com/tubetrivia-ai-review
(2) SocioWave Review: https://sumonreview.com/sociowave-review
(3) AI Partner & Profit Review: https://sumonreview.com/ai-partner-profit-review
(4) AI Ebook Suite Review: https://sumonreview.com/ai-ebook-suite-review
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.
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.
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.
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.
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.
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.
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
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
Developing Distributed High-performance Computing Capabilities of an Open Sci...Globus
COVID-19 had an unprecedented impact on scientific collaboration. The pandemic and its broad response from the scientific community has forged new relationships among public health practitioners, mathematical modelers, and scientific computing specialists, while revealing critical gaps in exploiting advanced computing systems to support urgent decision making. Informed by our team’s work in applying high-performance computing in support of public health decision makers during the COVID-19 pandemic, we present how Globus technologies are enabling the development of an open science platform for robust epidemic analysis, with the goal of collaborative, secure, distributed, on-demand, and fast time-to-solution analyses to support public health.
top nidhi software solution freedownloadvrstrong314
This presentation emphasizes the importance of data security and legal compliance for Nidhi companies in India. It highlights how online Nidhi software solutions, like Vector Nidhi Software, offer advanced features tailored to these needs. Key aspects include encryption, access controls, and audit trails to ensure data security. The software complies with regulatory guidelines from the MCA and RBI and adheres to Nidhi Rules, 2014. With customizable, user-friendly interfaces and real-time features, these Nidhi software solutions enhance efficiency, support growth, and provide exceptional member services. The presentation concludes with contact information for further inquiries.
Enhancing Project Management Efficiency_ Leveraging AI Tools like ChatGPT.pdfJay Das
With the advent of artificial intelligence or AI tools, project management processes are undergoing a transformative shift. By using tools like ChatGPT, and Bard organizations can empower their leaders and managers to plan, execute, and monitor projects more effectively.
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.
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.
1. WHITE PAPER
The End of Big Storage
The explosion of virtualization gives rise to a new
software-defined storage architecture
INTRODUCTION Server virtualization has forever changed the way we think about compute resources. The drawback
though, is that it breaks the traditional storage architecture, which was designed almost two decades before server
virtualization changed the infrastructure architecture. The architectural mismatch between the old and the new leads
to poorly performing storage, high storage costs and complex storage management. Enter Software-Defined Storage
(SDS). SDS realigns storage with virtualization, offering high-performance storage, simple management and lower costs.
The success of server virtualization lies in the fact that nothing in the infrastructure knows
that anything has changed to applications, OSs, servers, networks or storage. By inserting
the hypervisor into the infrastructure stack, the relationship between virtual machines and
the underlying storage radically changes. Traditional storage was never designed for the
new architecture of virtualization. Rather than being limited by physical constraints, CPU
and memory can now be flexibly allocated to virtual machines (VMs) in the exact increments
required. Resource allocations can also be very easily changed to accommodate workload
evolution selecting or returning resources from/to a resource pool shared across all VMs
on a given host. This enables significantly more efficient use of existing compute resources,
providing not only much greater operational flexibility but also driving cost savings and the
ease of use of centralized management.
Over half of existing x86 workloads have been virtualized, and most new applications coming
online today run on virtual infrastructures. What makes server virtualization so successful
is its transparent insertion into the infrastructure stack. Resources are virtualized in a way
that does not require any changes in operating systems, applications or physical hardware.
It effectively creates a software container — called a virtual machine (VM)—that enables
complete freedom of movement for resources in that container, from one physical host to
another as an atomic entity.
VMs are basically a collection of compute, storage and network resources. Server virtualiza-
tion introduces a new, many-to-one architecture that governs how compute resources are
allocated. It does nothing, however, to change how physical storage resources are allocated.
Unfortunately, storage resources continue to use a traditional one-to-one architectural
design that results in significant inefficiencies and challenges in virtual computing environ-
ments. To achieve the true promise of the software-defined data center, storage resources
need to undergo the same architectural transformation that compute resources have done
with server virtualization. This white paper will discuss the why and how of the architectural
transformation storage must undergo in the context of the software-defined data center.
2. PAGE 2White Paper | The End of Big Storage
Virtualization Breaks Traditional Storage
The 1980s heralded the rise of a new client/server computing architecture, which was
significantly different from the legacy mainframe architectures that dominated the 1960s
and 1970s. Taking advantage of advances in processor and memory technology, client/server
computing architectures cost-effectively paired single applications with individual servers. The
pairing was done completely with their own dedicated CPU, memory, storage and network
resources. Storage architectures for these environments used a one-to-one architecture
design that assumed storage would be owned and used only by a single server. This was
called direct attached storage. Storage objects, known as logical unit numbers (LUNs)1, were
presented to that single server. Storage management operations—like snapshots, cloning
and replication, also known as “data services”— all operated at the LUN level. Generally,
storage controllers internal to the servers dealt with only a single application, and could be
tuned to perform optimally for that workload. Data-services policies could also be tailored for
the requirements of that single workload. As data growth rates began to increase, external
storage was introduced as a way to provide the flexibility necessary to grow storage capacity
at rates different than compute resources. External storage was packaged as a separate stor-
age array, complete with its own controllers and data services. These arrays were connected
to the server over a storage network usually Fibre Channel in this time frame. Storage LUNs
in these arrays appeared to the server as local disk, and an array’s controllers could still be
tuned for the application of a single server.
Virtualization Changed Nothing (But Changed Everything)
The success of server virtualization lies with the fact that nothing else in the infrastructure
knows that anything has changed. At a bare minimum, infrastructure is hard to change and is
disruptive, because of:
■■ Defined protocols on how layers of the infrastructure stack interact with layers above
and below
■■ Well-established business ecosystems throughout the infrastructure industry, hundreds
of thousands of applications run perfectly fine in data centers
The brilliance of server virtualization was its transparent insertion into the infrastructure
stack. No changes to applications, OSs, servers, networks or storage are required. If any of
these elements had to change, server virtualization would not have been the success it is
today. Even with this transparent insertion, it has taken virtualization a decade to get to where
it is today. While the hypervisor did not force any changes—particularly to the application/
server workload operating in a VM — the relationship between the infrastructure compo-
nents has been changed. While the virtual machine perceives no change, the reality is that
everything around it has changed.
1 A LUN is a logical device addressed by the SCSI protocol. LUNs are logical storage objects that are “carved” (created)
from the actual physical storage, and are what is actually presented as storage to the server.
The success of server
virtualization lies with the
fact that nothing else in the
infrastructure knows that
anything has changed.
3. PAGE 3White Paper | The End of Big Storage
A New Container—The Virtual Machine
Virtualization does two specific things. First, it virtualizes or abstracts the hardware resources
through the hypervisor. Second, it creates a new software-defined container, a VM, which
allocates and isolates resources to this container. Virtualization effectively places all physical
resources on a hardware platform into a pool. This enables them to be easily selected
and allocated to one or more VMs. Tens or hundreds of VMs can potentially be created
from a single physical hardware platform, each of which can be running its own individual
application. This transforms the one-to-one architecture from the client/server era to a new
many-to-one architecture, making it very easy to create, move and delete VMs.
Combined with external storage that is shared across two or more physical hardware
platforms (hosts), virtualization also enables administrators to quickly and easily move VMs
across physical boundaries from one host to another. Each container representing a VM is
just a file that resides on the external storage. The host on which it is running accesses the
file and executes the compute for it. To move the VM to another host, simply shut it down on
one host, access the file from another host and execute its compute there.
Storage arrays typically support a limited number of LUNs. Because of this,
it is inevitable that more than one VM will reside on any given LUN. In fact,
virtualization moves administrators from an environment in which a single
server owns one or more LUNs to an environment where tens or hundreds
of VMs may reside on a single LUN. This creates an architectural mismatch
between the many-to-one architecture that virtualization offers for compute
resources and the one-to-one architecture that traditional storage based on
LUN management offers. This architectural mismatch has significant negative
implications, all of which result in higher costs to make virtualization work
effectively.
IMPLICATION 1: POOR PERFORMANCE—THE I/O BLENDER EFFECT
Most server operating systems were written with the assumption that they
would have direct access to dedicated storage devices. Operating systems
have evolved over the past 20 years to optimize the I/O before writing it to
storage, in order to increase performance. This is a valid assumption with the traditional one-
to-one server-to-storage architecture, and a server’s dedicated storage controllers could be
tuned to optimize performance for the specific I/O pattern that application was generating.
In general, this meant re-ordering the I/O from an individual application to enable it to be
written sequentially to spinning disk as much as possible, providing a RAID configuration that
delivered the desired reliability at minimum cost.
The many-to-one orientation of virtual computing throws a huge wrench into this approach.
The operating systems on each of the VMs no longer interact directly with the storage.
Instead, they interact with the hypervisor, which, in turn, interacts with the storage. As the
largely sequential I/O streams from each VM flow through it, the hypervisor multiplexes them,
producing an extremely random I/O pattern, which it then writes to disk. Spinning disks
handle random I/O up to 10 times slower than sequential I/O.
Optimized
I/O
Traditional Storage
Optimized 1:1
OS
APP
Capacity
Controller
Hypervisor
VM VM VM VM
I/O
Blender
Optimized
I/O
Random I/O
Traditional Storage
Many to One
Capacity
Controller
Figure 1. In virtual environments, administrators
inevitably end up with tens or hundreds of VMs per LUN
4. PAGE 4White Paper | The End of Big Storage
On top of that, I/O patterns in virtual computing environments tend to be much more write-in-
tensive. With the traditional client/server model, an application workload that required 20%
writes (and 80% reads) was considered “write-in-
tensive.” In virtual environments, most virtual
server workloads generate at least 40% to 50%
writes, and virtual-desktop environments, on the
other hand, can generate as much as 90% writes.
Enterprise-class spinning disks handle writes that
are roughly 35%-50% slower than reads.
This extremely random, extremely write-intensive
I/O pattern is referred to as the “I/O blender
effect.” It causes traditional storage architectures
built around the one-to-one orientation to
perform between 40% and 60% slower than
that same storage performed in client/server
environments. As administrators seek to build
storage configurations back up to meet perfor-
mance requirements, storage costs increase
and, in turn, drive up the cost per VM. The result
is unexpectedly high storage costs with storage
configurations that are significantly over-provi-
sioned in terms of capacity.
IMPLICATION 2: MANAGEMENT COMPLEXITY
As mentioned earlier, traditional storage architectures manage all storage operations
at the LUN level. When migrating a virtual server (i.e. VM) from one host to another,
exclusive ownership of the LUN on which it resides is transferred from the “source”
host to the “target” host. The same is true with data services like snapshots, clones and
replication managed at the array level. They can be performed on LUNs but not on
individual VMs.
This works fine when there is only one server per LUN. However, we know that with
virtual computing, it is rare to have just a single VM per LUN. For any storage operation
an administrator wants to perform on a single VM, the same must be performed on
other VMs residing on the same LUN as the target VM. Administrators do not have
the management granularity to perform storage operations on individual VMs the way
they did for individual servers in the traditional client/server model.
This leads to potentially significant management inefficiencies. For example, to snap-
shot VM1 on LUN1, all other VMs on LUN1 will also be snapshot. Snapshots take up
storage capacity, and larger snapshots take up more storage capacity. Administrators
will be storing snapshots of VMs they don’t care about, just to get a snapshot of the
one they do care about. If administrators want to replicate that snapshot to a remote
location for disaster-recovery purposes, then they must replicate all the VMs on the
LUN, taking up not only additional storage capacity at the remote location, but also
consuming additional bandwidth to replicate VMs they don’t even care about. Clearly,
this wastes precious resources.
VM.1 VM.2 VM.3 VM.n
Hypervisor
I/O Blender
Server
Storage Array
VM.1 VM.2 VM.3
LUN
Traditional Storage Architecture
Control Plane
Data Services
Data Plane (I/O)
Capacity
StorageControlPerLUN
Figure 2. Even within a single host, an
extremely random I/O pattern predominates,
and gets much worse as more hosts share
a storage array
VM.1 VM.2 VM.3 VM.n
Server
Hypervisor
VM-Centric View: Manage snapshots,
replication per VM
LUN-Centric View: Manage snapshots,
replication per LUN (all VMs)
One-to-many data services
Clustered file system
Storage Array
VM.1 VM.2 VM.3
VM.1 VM.2 VM.3 VM.nVM.1 VM.2 VM.3
Traditional Storage Architecture
Control Plane
Data Services (Snapshot, Replicate...)
Data Plane (I/O)
LUN-1
LUN
StorageControlPerLUN
Figure 3. With multiple VMs per LUN,
LUN-level management does not provide
the desired management granularity
VM.1 VM.2 VM.3 VM.nVM.1 VM.2 VM.3
5. PAGE 5White Paper | The End of Big Storage
It also forces administrators to adopt a fragmented management model that is harder and
more costly to administer. VMs are managed from a centralized management platform, like
Microsoft System Center, that allows management operations to be performed on individually
selected VMs. But the storage for these VMs is managed from the management GUI associated
with the storage array, which imposes a LUN-level management paradigm. What virtual
administrators want is the same ability to manage all resources associated with individual
servers, including storage that they had with the traditional client/server model. The difference
is that they want it applied to virtual infrastructure. Traditional one-to-one storage architectures
just can’t provide this.
IMPLICATION 3: UNPREDICTABLE SCALABILITY
In the last decade, data growth rates have skyrocketed for most commercial enterprises.
More and more data is being generated and retained by enterprises for longer periods to
meet compliance requirements. On top of that, social media is generating huge amounts of
data. Enterprises plan to add an average of 43TB of physical storage capacity this year.2 The
increasing importance of virtualization has also contributed to this growth in storage capacity
requirements. This is attributed to the I/O blender effect, as well as the ease of creating new
servers in the virtual world. As a result of this data growth, storage platforms targeted for use
in virtual environments have higher scalability standards to meet. Traditional storage archi-
tectures have had difficulty meeting these scalability requirements in a cost-effective manner.
In general, storage-processing power is not increased as capacity as added to traditional
storage—resulting in diminishing performance as capacity is scaled. To add processing
power, you are forced into disruptive and expensive forklift upgrades. As more and more
VMs use the shared storage capacity in these environments, performance can become
unpredictable as the array struggles to handle a high number of disparate workloads across
multiple hosts. Because of the inefficiency with which traditional storage architectures handle
the I/O blender effect, storage requirements increase faster in virtual environments, making
scalability an even greater concern.
IMPLICATION 4:
INCREASED STORAGE COSTS THAT REDUCE SAVINGS FROM VIRTUALIZATION
The I/O blender effect, bloated data services and unpredictable scalability all drive the need
for significantly more storage. The added storage costs often consume more than the cost
savings driven by server consolidation, making virtual computing much less economically
compelling than it first appeared to be. The reasons behind this may not be clear to the
casual observer. The net result of the I/O blender effect is that traditional storage used in
virtual infrastructures produce 40% - 60% fewer IOPS than they do in physical infrastructures.
This poor performance can drive higher costs in several ways. If not addressed from the
storage side, then each host can effectively support far fewer VMs, increasing the cost per
server and reducing the server-consolidation savings. If additional spinning disks are added
to increase the IOPS the storage can handle, then costs increase accordingly. If SSD arrays
are used, costs also increase, due to the expense of the solid-state storage. This high cost
storage is applied to all workloads, many of which may not be able to justify the expense. The
LUN-based management imposed by traditional storage results in “bloated” data services.
These services unnecessarily consume storage resources through an inability to operate
at the desired level of granularity—the individual VM. In addition, the resulting fragmented
2 Storage Magazine, May 2013 Reader Survey, p. 25.
6. PAGE 6White Paper | The End of Big Storage
management model drives additional training requirements and is harder to administer. Both
issues drive up cost. Virtual computing requires much more rapid storage expansion than
physical computing. Both the I/O blender effect and LUN-based management drive relatively
higher storage growth rates. The relative ease of creating new servers, each of which
requires its own storage, also adds to this burden. Traditional storage architectures don’t
support incremental, linear scalability. Instead, they require storage to be purchased in larger
“chunks,” resulting in higher up-front costs and over-buying. Scalability limits drive the need
for forklift upgrades, which add not only additional expense, but which are also disruptive.
Clustered storage designs can address the scalability problem, but are generally designed for
traditional file serving workloads—not the type of low-latency, high IOPS workloads demand-
ed by virtualization.
Software-Defined Storage Provides the Needed
Architectural Transformation
Software-defined storage (SDS) aligns the storage architecture and its management
model to match the architecture and management model of virtualization. The goal of this
alignment is to deliver three key benefits:
1. Higher, more reliable performance for applications running in virtual environments
2. Simplified management of storage, including storage provisioning, data services and scaling
3. Lower overall cost per virtual server driven primarily by storage savings
To achieve this, SDS works on the exact same principles that made server virtualization so
successful:
1. Virtualizing storage resources into a shared resource pool
2. Creating a new container for storage that matches the VM architecture
3. Inserting transparently into the infrastructure stack
SDS Virtualizes Storage Resources into Pools
In the same way that the hypervisor virtualized compute resources, SDS virtualizes storage
resources (capacity, bandwidth, memory, cache, processing) from many physical storage
appliances (storage nodes) into a scalable, fault-tolerant storage pool. By simply adding more
storage nodes into the pool, we eliminate the scaling limitation of traditional storage. Each
node instantly and seamlessly adds capacity, bandwidth and processing to the storage pool,
making these resources easily available to the VMs. Different classes of storage resources
can be added into pools, which can then be presented to VMs as different classes of disk.
Representative classes might include:
■■ Standard performance - hybrid storage combining flash performance with backing
SATA capacity that is cost effective for general-purpose virtualized workloads
■■ Extreme performance - all-flash storage that consistently delivers the highest perfor-
mance for every I/O for select workloads
■■ Capacity - cost-effective storage for workloads that require large amounts of capacity for
working sets
■■ Archive - low-cost storage for data that must be retained and kept immutable for long
periods
Software-defined storage
aligns the storage
and virtualization
architectures to deliver
on the promise of
virtualization.
7. PAGE 7White Paper | The End of Big Storage
SDS Creates a New Storage
Container Aligned to the VM
Just as server virtualization created a new
container with the VM, allowing for much
more efficient allocation and management
of compute resources, another new
container needs to be defined— one that
resolves the current mismatch between
compute and storage architectures in
virtual environments. This new storage
container is a virtual controller. Software-
defined compute defined the VM, while
software-defined storage will define the
virtual controller. Together, they provide
the one-to-one relationship between
server and storage that virtualization
broke. The virtual controller utilizes the
storage resources from virtualized pools
and presents a subset of these resources
to each VM. The virtual controller also
optimizes how these resources are utilized
and presents a unified management
structure for provisioning and data services
on a per-VM basis.
Isolation, Optimization and Prioritization I/O on A Per-VM Basis
The virtual controller operates at the hypervisor layer, isolating the I/O for each VM to
eliminate the I/O blender effect. This isolation effectively creates the container that connects
the VM with storage. By isolating the I/O from each VM, the virtual controller creates virtual
storage stacks for each VM. Once the isolated I/O is in the stack, it is dynamically optimized
to provide optimal storage performance for the VM’s application workload, regardless of
what other VM workloads are accessing the shared storage resource. Every application has
an optimal I/O pattern and configuration. The dynamic optimization detects this I/O pattern
and then optimizes for it. By creating these virtual storage stacks, the I/O stream from
each individual VM can be optimized as it passes from the hypervisor through the network
and down into the storage pools. Where there is resource contention, all resources within
this virtual storage stack can be dynamically allocated and prioritized by policy. The virtual
controller has intelligence that operates at both ends of the stack to affect the policies for
each VM. This end-to-end architecture eliminates the problems associated with traditional
storage architectures that cannot start optimizing I/O streams until they are inside the
storage array. Attempting to manage quality of service (QoS) this late in the game results in
congestion, along with I/O queuing and blocking. Large writes to the array from a low-priority
workload can completely block latency-sensitive, small-block random I/O from a high-priority
workload. When I/O is isolated and channeled from the VM through the network into the
shared storage, the I/O of each VM operates within a sealed container. As such, other VMs
cannot interfere.
Figure 4. Each VM gets its own virtual
controller,allowing its storage to be optimized
for its particular needs
8. PAGE 8White Paper | The End of Big Storage
Management Data Services on a Per-VM Basis
Software-defined storage and its new container consolidate the management model back
into a single, VM-centric model. This allows storage operations to be performed at the
desired level of granularity from the same management platform used to manage the VMs
themselves. With this centralized model in place, administrators will no longer be forced to
license and pay for storage functionality as part of a hardware purchase. Their storage-man-
agement capabilities will no longer be defined by their storage hardware. The storage
resources required to meet application requirements can now be as easily and flexibly
defined as compute resources in virtualized environments.
This virtual-storage container extends the VM management model into the virtualized
storage pool. It re-institutes the one-to-one relationship between servers and storage in the
new context of virtualized environments. Storage managed by each virtual controller can be
defined to meet certain performance, reliability and functional requirements:
■■ I/O streaming sequenced before it is written to storage in order to remove the inefficien-
cies of the I/O blender effect
■■ Defining RAID levels to meet reliability requirements
■■ Defining data-services policies regarding snapshots, clones, failover, replication and other
functions as needed — all on a VM-by-VM basis
Transparent Deployment
Software-defined compute was transparently inserted into the infrastructure stack without
requiring any changes to operating systems, application software, or underlying hardware.
Software-defined storage must follow a similar path. From each VM’s point of view, the virtual
controller presents to the hypervisor what appears to be a standard SCSI device — a local
disk. The hypervisor can mount it and lay out its clustered file systems across this device with-
out any changes. This new storage stack is usable by the VMs without requiring any changes
to operating systems, application software or the hypervisor. For software-defined storage to
be successful, this transformative change to the storage architecture must be transparent.