Search Results

Search found 13151 results on 527 pages for 'performance counters'.

Page 202/527 | < Previous Page | 198 199 200 201 202 203 204 205 206 207 208 209  | Next Page >

• IPgallery banks on Solaris SPARC

  - by Frederic Pariente

  IPgallery is a global supplier of converged legacy and Next Generation Networks (NGN) products and solutions, including: core network components and cloud-based Value Added Services (VAS) for voice, video and data sessions. IPgallery enables network operators and service providers to offer advanced converged voice, chat, video/content services and rich unified social communications in a combined legacy (fixed/mobile), Over-the-Top (OTT) and Social Community (SC) environments for home and business customers. Technically speaking, this offer is a scalable and robust telco solution enabling operators to offer new services while controlling operating expenses (OPEX). In its solutions, IPgallery leverages the following Oracle components: Oracle Solaris, Netra T4 and SPARC T4 in order to provide a competitive and scalable solution without the price tag often associated with high-end systems. Oracle Solaris Binary Application Guarantee A unique feature of Oracle Solaris is the guaranteed binary compatibility between releases of the Solaris OS. That means, if a binary application runs on Solaris 2.6 or later, it will run on the latest release of Oracle Solaris.  IPgallery developed their application on Solaris 9 and Solaris 10 then runs it on Solaris 11, without any code modification or rebuild. The Solaris Binary Application Guarantee helps IPgallery protect their long-term investment in the development, training and maintenance of their applications. Oracle Solaris Image Packaging System (IPS) IPS is a new repository-based package management system that comes with Oracle Solaris 11. It provides a framework for complete software life-cycle management such as installation, upgrade and removal of software packages. IPgallery leverages this new packaging system in order to speed up and simplify software installation for the R&D and production environments. Notably, they use IPS to deliver Solaris Studio 12.3 packages as part of the rapid installation process of R&D environments, and during the production software deployment phase, they ensure software package integrity using the built-in verification feature. Solaris IPS thus improves IPgallery's time-to-market with a faster, more reliable software installation and deployment in production environments. Extreme Network Performance IPgallery saw a huge improvement in application performance both in CPU and I/O, when running on SPARC T4 architecture in compared to UltraSPARC T2 servers.  The same application (with the same activation environment) running on T2 consumes 40%-50% CPU, while it consumes only 10% of the CPU on T4. The testing environment comprised of: Softswitch (Call management), TappS (Telecom Application Server) and Billing Server running on same machine and initiating various services in capacity of 1000 CAPS (Call Attempts Per Second). In addition, tests showed a huge improvement in the performance of the TCP/IP stack, which reduces network layer processing and in the end Call Attempts latency. Finally, there is a huge improvement within the file system and disk I/O operations; they ran all tests with maximum logging capability and it didn't influence any benchmark values. "Due to the huge improvements in performance and capacity using the T4-1 architecture, IPgallery has engineered the solution with less hardware.  This means instead of deploying the solution on six T2-based machines, we will deploy on 2 redundant machines while utilizing Oracle Solaris Zones and Oracle VM for higher availability and virtualization" Shimon Lichter, VP R&D, IPgallery In conclusion, using the unique combination of Oracle Solaris and SPARC technologies, IPgallery is able to offer solutions with much lower TCO, while providing a higher level of service capacity, scalability and resiliency. This low-OPEX solution enables the operator, the end-customer, to deliver a high quality service while maintaining high profitability.

  Read the article

• SQL SERVER – Select the Most Optimal Backup Methods for Server

  - by pinaldave

  Backup and Restore are very interesting concepts and one should be very much with the concept if you are dealing with production database. One never knows when a natural disaster or user error will surface and the first thing everybody wants is to get back on point in time when things were all fine. Well, in this article I have attempted to answer a few of the common questions related to Backup methodology. How to Select a SQL Server Backup Type In order to select a proper SQL Server backup type, a SQL Server administrator needs to understand the difference between the major backup types clearly. Since a picture is worth a thousand words, let me offer it to you below. Select a Recovery Model First The very first question that you should ask yourself is: Can I afford to lose at least a little (15 min, 1 hour, 1 day) worth of data? Resist the temptation to save it all as it comes with the overhead – majority of businesses outside finances can actually afford to lose a bit of data. If your answer is YES, I can afford to lose some data – select a SIMPLE (default) recovery model in the properties of your database, otherwise you need to select a FULL recovery model. The additional advantage of the Full recovery model is that it allows you to restore the data to a specific point in time vs to only last backup time in the Simple recovery model, but it exceeds the scope of this article Backups in SIMPLE Recovery Model In SIMPLE recovery model you can select to do just Full backups or Full + Differential. Full Backup This is the simplest type of backup that contains all information needed to restore the database and should be your first choice. It is often sufficient for small databases, but note that it makes a big impact on the performance of your database Full + Differential Backup After Full, Differential backup picks up all of the changes since the last Full backup. This means if you made Full, Diff, Diff backup – the last Diff backup contains all of the changes and you don’t need the previous Differential backup. Differential backup is obviously smaller and carries less performance overhead Backups in FULL Recovery Model In FULL recovery model you can select Full + Transaction Log or Full + Differential + Transaction Log backup. You have to create Transaction Log backup, because at that time the log is being truncated. Otherwise your Transaction Log will grow uncontrollably. Full + Transaction Log Backup You would always need to perform a Full backup first. Then a series of Transaction log backup. Note that (in contrast to Differential) you need ALL transactions to log since the last Full of Diff backup to properly restore. Transaction log backups have the smallest performance overhead and can be performed often. Full + Differential + Transaction Log Backup If you want to ease the performance overhead on your server, you can replace some of the Full backup in the previous scenario with Differential. You restore scenario would start from Full, then the Last Differential, then all of the remaining transactions log backups Typical backup Scenarios You may say “Well, it is all nice – give me the examples now”. As you may already know, my favorite SQL backup software is SQLBackupAndFTP. If you go to Advanced Backup Schedule form in this program and click “Load a typical backup plan…” link, it will give you these scenarios that I think are quite common – see the image below. The Simplest Way to Schedule SQL Backups I hate to repeat myself, but backup scheduling in SQL agent leaves a lot to be desired. I do not know the simple way to schedule your SQL server backups than in SQLBackupAndFTP – see the image below. The whole backup scheduling with compression, encryption and upload to a Network Folder / HDD / NAS Drive / FTP / Dropbox / Google Drive / Amazon S3 takes just a few minutes – see my previous post for the review. Final Words This post offered an explanation for major backup types only. For more complicated scenarios or to research other options as usually go to MSDN. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Backup and Restore, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

  Read the article

• Tuning Red Gate: #1 of Many

  - by Grant Fritchey

  Everyone runs into performance issues at some point. Same thing goes for Red Gate software. Some of our internal systems were running into some serious bottlenecks. It just so happens that we have this nice little SQL Server monitoring tool. What if I were to, oh, I don't know, use the monitoring tool to identify the bottlenecks, figure out the causes and then apply a fix (where possible) and then start the whole thing all over again? Just a crazy thought. OK, I was asked to. This is my first time looking through these servers, so here's how I'd go about using SQL Monitor to get a quick health check, sort of like checking the vitals on a patient. First time opening up our internal SQL Monitor instance and I was greeted with this: Oh my. Maybe I need to get our internal guys to read my blog. Anyway, I know that there are two servers where most of the load is. I'll drill down on the first. I'm selecting the server, not the instance, by clicking on the server name. That opens up the Global Overview page for the server. The information here much more applicable to the "oh my gosh, I have a problem now" type of monitoring. But, looking at this, I am seeing something immediately. There are four(4) drives on the system. The C:\ has an average read time of 16.9ms, more than double the others. Is that a problem? Not sure, but it's something I'll look at. It's write time is higher too. I'll keep drilling down, first, to the unclosed alerts on the server. Now things get interesting. SQL Monitor has a number of different types of alerts, some related to error states, others to service status, and then some related to performance. Guess what I'm seeing a bunch of right here: Long running queries and long job durations. If you check the dates, they're all recent, within the last 24 hours. If they had just been old, uncleared alerts, I wouldn't be that concerned. But with all these, all performance related, and all in the last 24 hours, yeah, I'm concerned. At this point, I could just start responding to the Alerts. If I click on one of the the Long-running query alerts, I'll get all kinds of cool data that can help me determine why the query ran long. But, I'm not in a reactive mode here yet. I'm still gathering data, trying to understand how the server works. I have the information that we're generating a lot of performance alerts, let's sock that away for the moment. Instead, I'm going to back up and look at the Global Overview for the SQL Instance. It shows all the databases on the server and their status. Then it shows a number of basic metrics about the SQL Server instance, again for that "what's happening now" view or things. Then, down at the bottom, there is the Top 10 expensive queries list: This is great stuff. And no, not because I can see the top queries for the last 5 minutes, but because I can adjust that out 3 days. Now I can see where some serious pain is occurring over the last few days. Databases have been blocked out to protect the guilty. That's it for the moment. I have enough knowledge of what's going on in the system that I can start to try to figure out why the system is running slowly. But, I want to look a little more at some historical data, to understand better how this server is behaving. More next time.

  Read the article

• Expanding the Partner Ecosystem with Third-Party Plug-ins

  - by Joe Diemer

  Oracle Enterprise Manager’s extensibility capabilities are designed to allow customers and partners to adapt Enterprise Manager for management of heterogeneous environments with Plug-ins and Connectors.  Third-party developers continue to take advantage of Oracle Enterprise Manager’s Extensibility Development Kit (EDK) to build plug-ins to Enterprise Manager 12c, such as F5’s BIG IP Plug-in and Entuity’s Eye of the Storm Network Management Plug-In.  Partners can also validate their plug-ins through the Oracle Validated Integration (OVI) program, which assures customers that the plug-in has been tested and is functionally and technically sound, is designed in a reliable and standardized manner, and operates and performs as documented.   Two very recent examples of partners which have beta versions of their plug-ins are Blue Medora's VMware vSphere plug-in and the NetApp Storage plug-in.  VMware vSphere Plug-in by Blue Medora Blue Medora, an Oracle Partner Network (OPN) “Gold” member, which just announced that it is now signing up customers to try a beta version of their new VMware vSphere plug-in for Enterprise Manager 12c.  According to Blue Medora, the vSphere plug-in monitors critical VMware metrics (CPU, Memory, Disk, Network, etc) at the Host, VM, Cluster and Resource Pool levels.  It has minimal performance impact via an “agentless” approach that requires no installation directly on VMware servers.  It has discovery capabilities for VMware Datacenters, ESX Hosts, Clusters, Virtual Machines, and Datastores.  It offers integration of native VMware Events into Enterprise Manager, and it provides over 300 VMware-related health, availability, performance, and configuration metrics.  It comes with more than 30 out-of-the-box pre-defined thresholds and can manage VMware via a series of jobs split between cluster, host and VM target types.The company reports that the Enterprise Manager 12c plug-in supports vSphere versions 4.0, 4.5 and 5.0.  Platforms supported include Linux 64-bit, Windows, AIX and Solaris SPARC and x86.  Information about the plug-in, including how to sign up for the beta, is available at their web site at http://bluemedora.com after selecting the "Products" tab. NetApp Storage Plug-in NetApp believes the combination of storage system monitoring with comprehensive management of Oracle systems with Enterprise Manager will help customers reduce the cost and complexity of managing applications that rely on NetApp storage and Oracle technologies.  So, NetApp built a plug-in and reports that it has comprehensive availability and performance information for NetApp storage systems.  Using the plug-in, Oracle Enterprise Manager customers with NetApp storage solutions can track the association between databases and storage components and thereby respond to faults and IO performance bottlenecks quickly. With the latest configuration management capabilities, one can also perform drift analysis to make sure all storage systems are configured as per established gold standards. The company is also now signing up beta customers, which can be done at the NetApp Communities site at https://communities.netapp.com/groups/netapp-storage-system-plug-in-for-oem12c-beta. Learn More about Enterprise Manager Extensibility More plug-ins from other partners are soon to come, which I'll be reporting on them here.  To learn more about Enterprise Manager and how customers and partners can build plug-ins using the EDK to manage a multi-vendor data center, go to http://oracle.com/enterprisemanager in the Heterogeneous Management solution area.  The site also lists the plug-ins available with information on how to obtain them.  More info about the Oracle Validated Integration program can be found at the OPN Enterprise Manager Knowledge Zone in the "Develop" tab.

  Read the article

• Exalytics and Oracle Business Intelligence Enterprise Edition (OBIEE) Partner Workshop

  - by mseika

  Workshop Description Oracle Fusion Middleware 11g is the #1 application infrastructure foundation. It enables enterprises to create and run agile and intelligent business applications and maximize IT efficiency by exploiting modern hardware and software architectures. Oracle Exalytics Business Intelligence Machine is the world’s first engineered system specifically designed to deliver high performance analysis, modeling and planning. Built using industry-standard hardware, market-leading business intelligence software and in-memory database technology, Oracle Exalytics is an optimized system that delivers unmatched speed, visualizations and scalability for Business Intelligence and Enterprise Performance Management applications. This FREE hands-on, partner workshop highlights both the hardware and software components that are engineered to work together to deliver Oracle Exalytics - an optimized version of the industry-leading Oracle TimesTen In-Memory Database with analytic extensions, a highly scalable Oracle server designed specifically for in-memory business intelligence, and Oracle’s proven Business Intelligence Foundation with enhanced visualization capabilities and performance optimizations. This workshop will provide hands-on experience with Oracle's latest engineered system. Topics covered will include TimesTen In-Memory Database and the new Summary Advisor for Exalytics, the technical details (including mobile features) of the latest release of visualization enhancements for OBI-EE, and technical updates on Essbase. After taking this course, you will be well prepared to architect, build, demo, and implement an end-to-end Exalytics solution. You will also be able to extend your current analytical and enterprise performance management application implementations with numerous Oracle technologies specifically enhanced to take advantage of the compute capacity and in-memory capabilities of Oracle Exalytics.If you are a BI or Data Warehouse Architect, developer or consultant, you don’t want to miss this 3-day workshop. Register Now! Presentations Exalytics Architectural Overview Upgrade and Lifecycle Management Times Ten for Exalytics Summary Advisor Utility Essbase and EPM System on Exalytics Dashboard and Analysis Interactions OBIEE 11.1.1.6 Features and Advanced Topics Lab OutlineThe labs showcase Oracle Exalytics core components and functionality and provide expertise of Oracle Business Intelligence 11.1.1.6 new features and updates from prior releases. The hands-on activities are based on an Oracle VirtualBox image with software and training samples pre-installed. Lab Environment Setup Creating and Working with Oracle TimesTen In-Memory Database Running Summary Advisor Utility Working with Exalytics Visualization Features – Dashboard and Analysis Interactions Audience Oracle Partners BI and EPM Application Developers and Implementers System Integrators and Solution Consultants Data Warehouse Developers Enterprise Architects Prerequisites Experience and understanding of OBIEE 11g is required Previous attendance of Oracle Business Intelligence Foundation Suite Workshop or BIEE 11gIntroduction Workshop is highly recommended Good understanding of data warehousing and data modeling for reporting and analysis purpose Strong experience with database technologies preferred Equipment RequirementsThis workshop requires attendees to provide their own laptops for this class.Attendee laptops must meet the following minimum hardware/software requirements: Hardware Minimum 8GB RAM 60 GB free space (includes staging) USB 2.0 port (at least one available) It is strongly recommended that you bring a mouse. You will be working in a development environment and using the mouse heavily. Software One of the following operating systems: 64-bit Windows host/laptop OS 64-bit host/laptop OS with a Windows VM (XP, Server, or Win 7, BIC2g, etc.) Internet Explorer 7.x/8.x or Firefox 3.5.x WINRAR or 7ziputility to unzip workshop files: Download-able from http://www.win-rar.com/download.html Download-able from http://www.7zip.com/ Oracle VirtualBox 4.0.2 or higher Downloadable from http://www.virtualbox.org/wiki/Downloads CPU virtualization mode needs to be enabled. We will provide guidance on the day of the workshop. Attendees will be given a VirtualBox image containing a pre-installed Oracle Exalytics environment. Schedule This workshop is 3 days. - Times vary by country!9:00am: Sign-in and technical setup 9:30am: Workshop starts 5:00pm: Workshop ends Oracle Exalytics and Business Intelligence (OBIEE) Workshop December 11-13, 2012: Oracle BVP, Birmingham, UK Register Here. Questions? Send email to: [email protected] Oracle Platform Technologies Enablement Services

  Read the article

• SQL Constraints &ndash; CHECK and NOCHECK

  - by David Turner

  One performance issue i faced at a recent project was with the way that our constraints were being managed, we were using Subsonic as our ORM, and it has a useful tool for generating your ORM code called SubStage – once configured, you can regenerate your DAL code easily based on your database schema, and it can even be integrated into your build as a pre-build event if you want to do this.  SubStage also offers the useful feature of being able to generate DDL scripts for your entire database, and can script your data for you too. The problem came when we decided to use the generate scripts feature to migrate the database onto a test database instance – it turns out that the DDL scripts that it generates include the WITH NOCHECK option, so when we executed them on the test instance, and performed some testing, we found that performance wasn’t as expected. A constraint can be disabled, enabled but not trusted, or enabled and trusted.  When it is disabled, data can be inserted that violates the constraint because it is not being enforced, this is useful for bulk load scenarios where performance is important.  So what does it mean to say that a constraint is trusted or not trusted?  Well this refers to the SQL Server Query Optimizer, and whether it trusts that the constraint is valid.  If it trusts the constraint then it doesn’t check it is valid when executing a query, so the query can be executed much faster. Here is an example base in this article on TechNet, here we create two tables with a Foreign Key constraint between them, and add a single row to each.  We then query the tables: 1 DROP TABLE t2 2 DROP TABLE t1 3 GO 4 5 CREATE TABLE t1(col1 int NOT NULL PRIMARY KEY) 6 CREATE TABLE t2(col1 int NOT NULL) 7 8 ALTER TABLE t2 WITH CHECK ADD CONSTRAINT fk_t2_t1 FOREIGN KEY(col1) 9 REFERENCES t1(col1) 10 11 INSERT INTO t1 VALUES(1) 12 INSERT INTO t2 VALUES(1) 13 GO14 15 SELECT COUNT(*) FROM t2 16 WHERE EXISTS17 (SELECT *18 FROM t1 19 WHERE t1.col1 = t2.col1) This all works fine, and in this scenario the constraint is enabled and trusted.  We can verify this by executing the following SQL to query the ‘is_disabled’ and ‘is_not_trusted’ properties: 1 select name, is_disabled, is_not_trusted from sys.foreign_keys This gives the following result: We can disable the constraint using this SQL: 1 alter table t2 NOCHECK CONSTRAINT fk_t2_t1 And when we query the constraints again, we see that the constraint is disabled and not trusted: So the constraint won’t be enforced and we can insert data into the table t2 that doesn’t match the data in t1, but we don’t want to do this, so we can enable the constraint again using this SQL: 1 alter table t2 CHECK CONSTRAINT fk_t2_t1 But when we query the constraints again, we see that the constraint is enabled, but it is still not trusted: This means that the optimizer will check the constraint each time a query is executed over it, which will impact the performance of the query, and this is definitely not what we want, so we need to make the constraint trusted by the optimizer again.  First we should check that our constraints haven’t been violated, which we can do by running DBCC: 1 DBCC CHECKCONSTRAINTS (t2) Hopefully you see the following message indicating that DBCC completed without finding any violations of your constraint: Having verified that the constraint was not violated while it was disabled, we can simply execute the following SQL:   1 alter table t2 WITH CHECK CHECK CONSTRAINT fk_t2_t1 At first glance this looks like it must be a typo to have the keyword CHECK repeated twice in succession, but it is the correct syntax and when we query the constraints properties, we find that it is now trusted again: To fix our specific problem, we created a script that checked all constraints on our tables, using the following syntax: 1 ALTER TABLE t2 WITH CHECK CHECK CONSTRAINT ALL

  Read the article

• VirtualBox 3.2 is released! A Red Letter Day?

  - by Fat Bloke

  Big news today! A new release of VirtualBox packed full of innovation and improvements. Over the next few weeks we'll take a closer look at some of these new features in a lot more depth, but today we'll whet your appetite with the headline descriptions. To start with, we should point out that this is the first Oracle-branded version which makes today a real Red-letter day ;-)  Oracle VM VirtualBox 3.2 Version 3.2 moves VirtualBox forward in 3 main areas ( handily, all beginning with "P" ) : performance, power and supported guest operating system platforms.  Let's take a look: Performance New Latest Intel hardware support - Harnessing the latest in chip-level support for virtualization, VirtualBox 3.2 supports new Intel Core i5 and i7 processor and Intel Xeon processor 5600 Series support for Unrestricted Guest Execution bringing faster boot times for everything from Windows to Solaris guests; New Large Page support - Reducing the size and overhead of key system resources, Large Page support delivers increased performance by enabling faster lookups and shorter table creation times. New In-hypervisor Networking - Significant optimization of the networking subsystem has reduced context switching between guests and host, increasing network throughput by up to 25%. New New Storage I/O subsystem - VirtualBox 3.2 offers a completely re-worked virtual disk subsystem which utilizes asynchronous I/O to achieve high-performance whilst maintaining high data integrity; New Remote Video Acceleration - The unique built-in VirtualBox Remote Display Protocol (VRDP), which is primarily used in virtual desktop infrastructure deployments, has been enhanced to deliver video acceleration. This delivers a rich user experience coupled with reduced computational expense, which is vital when servers are running hundreds of virtual machines; Power New Page Fusion - Traditional Page Sharing techniques have suffered from long and expensive cache construction as pages are scrutinized as candidates for de-duplication. Taking a smarter approach, VirtualBox Page Fusion uses intelligence in the guest virtual machine to determine much more rapidly and accurately those pages which can be eliminated thereby increasing the capacity or vm density of the system; New Memory Ballooning- Ballooning provides another method to increase vm density by allowing the memory of one guest to be recouped and made available to others; New Multiple Virtual Monitors - VirtualBox 3.2 now supports multi-headed virtual machines with up to 8 virtual monitors attached to a guest. Each virtual monitor can be a host window, or be mapped to the hosts physical monitors; New Hot-plug CPU's - Modern operating systems such Windows Server 2008 x64 Data Center Edition or the latest Linux server platforms allow CPUs to be dynamically inserted into a system to provide incremental computing power while the system is running. Version 3.2 introduces support for Hot-plug vCPUs, allowing VirtualBox virtual machines to be given more power, with zero-downtime of the guest; New Virtual SAS Controller - VirtualBox 3.2 now offers a virtual SAS controller, enabling it to run the most demanding of high-end guests; New Online Snapshot Merging - Snapshots are powerful but can eat up disk space and need to be pruned from time to time. Historically, machines have needed to be turned off to delete or merge snapshots but with VirtualBox 3.2 this operation can be done whilst the machines are running. This allows sophisticated system management with minimal interruption of operations; New OVF Enhancements - VirtualBox has supported the OVF standard for virtual machine portability for some time. Now with 3.2, VirtualBox specific configuration data is also stored in the standard allowing richer virtual machine definitions without compromising portability; New Guest Automation - The Guest Automation APIs allow host-based logic to drive operations in the guest; Platforms New USB Keyboard and Mouse - Support more guests that require USB input devices; New Oracle Enterprise Linux 5.5 - Support for the latest version of Oracle's flagship Linux platform; New Ubuntu 10.04 ("Lucid Lynx") - Support for both the desktop and server version of the popular Ubuntu Linux distribution; And as a man once said, "just one more thing" ... New Mac OS X (experimental) - On Apple hardware only, support for creating virtual machines run Mac OS X. All in all this is a pretty powerful release packed full of innovation and speedups. So what are you waiting for?  -FB 

  Read the article

• How Do You Actually Model Data?

  Since the 1970’s Developers, Analysts and DBAs have been able to represent concepts and relations in the form of data through the use of generic symbols.  But what is data modeling?  The first time I actually heard this term I could not understand why anyone would want to display a computer on a fashion show runway. Hey, what do you expect? At that time I was a freshman in community college, and obviously this was a long time ago.  I have since had the chance to learn what data modeling truly is through using it. Data modeling is a process of breaking down information and/or requirements in to common categories called objects. Once objects start being defined then relationships start to form based on dependencies found amongst other existing objects.  Currently, there are several tools on the market that help data designer actually map out objects and their relationships through the use of symbols and lines.  These diagrams allow for designs to be review from several perspectives so that designers can ensure that they have the optimal data design for their project and that the design is flexible enough to allow for potential changes and/or extension in the future. Additionally these basic models can always be further refined to show different levels of details depending on the target audience through the use of three different types of models. Conceptual Data Model(CDM)Conceptual Data Models include all key entities and relationships giving a viewer a high level understanding of attributes. Conceptual data model are created by gathering and analyzing information from various sources pertaining to a project during the typical planning phase of a project. Logical Data Model (LDM)Logical Data Models are conceptual data models that have been expanded to include implementation details pertaining to the data that it will store. Additionally, this model typically represents an origination’s business requirements and business rules by defining various attribute data types and relationships regarding each entity. This additional information can be directly translated to the Physical Data Model which reduces the actual time need to implement it. Physical Data Model(PDMs)Physical Data Model are transformed Logical Data Models that include the necessary tables, columns, relationships, database properties for the creation of a database. This model also allows for considerations regarding performance, indexing and denormalization that are applied through database rules, data integrity. Further expanding on why we actually use models in modern application/database development can be seen in the benefits that data modeling provides for data modelers and projects themselves, Benefits of Data Modeling according to Applied Information Science Abstraction that allows data designers remove concepts and ideas form hard facts in the form of data. This gives the data designers the ability to express general concepts and/or ideas in a generic form through the use of symbols to represent data items and the relationships between the items. Transparency through the use of data models allows complex ideas to be translated in to simple symbols so that the concept can be understood by all viewpoints and limits the amount of confusion and misunderstanding. Effectiveness in regards to tuning a model for acceptable performance while maintaining affordable operational costs. In addition it allows systems to be built on a solid foundation in terms of data. I shudder at the thought of a world without data modeling, think about it? Data is everywhere in our lives. Data modeling allows for optimizing a design for performance and the reduction of duplication. If one was to design a database without data modeling then I would think that the first things to get impacted would be database performance due to poorly designed database and there would be greater chances of unnecessary data duplication that would also play in to the excessive query times because unneeded records would need to be processed. You could say that a data designer designing a database is like a box of chocolates. You will never know what kind of database you will get until after it is built.

  Read the article

• Best Practices - Core allocation

  - by jsavit

  This post is one of a series of "best practices" notes for Oracle VM Server for SPARC (also called Logical Domains) Introduction SPARC T-series servers currently have up to 4 CPU sockets, each of which has up to 8 or (on SPARC T3) 16 CPU cores, while each CPU core has 8 threads, for a maximum of 512 dispatchable CPUs. The defining feature of Oracle VM Server for SPARC is that each domain is assigned CPU threads or cores for its exclusive use. This avoids the overhead of software-based time-slicing and emulation (or binary rewriting) of system state-changing privileged instructions used in traditional hypervisors. To create a domain, administrators specify either the number of CPU threads or cores that the domain will own, as well as its memory and I/O resources. When CPU resources are assigned at the individual thread level, the logical domains constraint manager attempts to assign threads from the same cores to a domain, and avoid "split core" situations where the same CPU core is used by multiple domains. Sometimes this is unavoidable, especially when domains are allocated and deallocated CPUs in small increments. Why split cores can matter Split core allocations can silenty reduce performance because multiple domains with different address spaces and memory contents are sharing the core's Level 1 cache (L1$). This is called false cache sharing since even identical memory addresses from different domains must point to different locations in RAM. The effect of this is increased contention for the cache, and higher memory latency for each domain using that core. The degree of performance impact can be widely variable. For applications with very small memory working sets, and with I/O bound or low-CPU utilization workloads, it may not matter at all: all machines wait for work at the same speed. If the domains have substantial workloads, or are critical to performance then this can have an important impact: This blog entry was inspired by a customer issue in which one CPU core was split among 3 domains, one of which was the control and service domain. The reported problem was increased I/O latency in guest domains, but the root cause might be higher latency servicing the I/O requests due to the control domain being slowed down. What to do about it Split core situations are easily avoided. In most cases the logical domain constraint manager will avoid it without any administrative action, but it can be entirely prevented by doing one of the several actions: Assign virtual CPUs in multiples of 8 - the number of threads per core. For example: ldm set-vcpu 8 mydomain or ldm add-vcpu 24 mydomain. Each domain will then be allocated on a core boundary. Use the whole core constraint when assigning CPU resources. This allocates CPUs in increments of entire cores instead of virtual CPU threads. The equivalent of the above commands would be ldm set-core 1 mydomain or ldm add-core 3 mydomain. Older syntax does the same thing by adding the -c flag to the add-vcpu, rm-vcpu and set-vcpu commands, but the new syntax is recommended. When whole core allocation is used an attempt to add cores to a domain fails if there aren't enough completely empty cores to satisfy the request. See https://blogs.oracle.com/sharakan/entry/oracle_vm_server_for_sparc4 for an excellent article on this topic by Eric Sharakan. Don't obsess: - if the workloads have minimal CPU requirements and don't need anywhere near a full CPU core, then don't worry about it. If you have low utilization workloads being consolidated from older machines onto a current T-series, then there's no need to worry about this or to assign an entire core to domains that will never use that much capacity. In any case, make sure the most important domains have their own CPU cores, in particular the control domain and any I/O or service domain, and of course any important guests. Summary Split core CPU allocation to domains can potentially have an impact on performance, but the logical domains manager tends to prevent this situation, and it can be completely and simply avoided by allocating virtual CPUs on core boundaries.

  Read the article

• Organization &amp; Architecture UNISA Studies &ndash; Chap 6

  - by MarkPearl

  Learning Outcomes Discuss the physical characteristics of magnetic disks Describe how data is organized and accessed on a magnetic disk Discuss the parameters that play a role in the performance of magnetic disks Describe different optical memory devices Magnetic Disk The way data is stored on and retried from magnetic disks Data is recorded on and later retrieved form the disk via a conducting coil named the head (in many systems there are two heads) The writ mechanism exploits the fact that electricity flowing through a coil produces a magnetic field. Electric pulses are sent to the write head, and the resulting magnetic patterns are recorded on the surface below with different patterns for positive and negative currents The physical characteristics of a magnetic disk   Summarize from book   The factors that play a role in the performance of a disk Seek time – the time it takes to position the head at the track Rotational delay / latency – the time it takes for the beginning of the sector to reach the head Access time – the sum of the seek time and rotational delay Transfer time – the time it takes to transfer data RAID The rate of improvement in secondary storage performance has been considerably less than the rate for processors and main memory. Thus secondary storage has become a bit of a bottleneck. RAID works on the concept that if one disk can be pushed so far, additional gains in performance are to be had by using multiple parallel components. Points to note about RAID… RAID is a set of physical disk drives viewed by the operating system as a single logical drive Data is distributed across the physical drives of an array in a scheme known as striping Redundant disk capacity is used to store parity information, which guarantees data recoverability in case of a disk failure (not supported by RAID 0 or RAID 1) Interesting to note that the increase in the number of drives, increases the probability of failure. To compensate for this decreased reliability RAID makes use of stored parity information that enables the recovery of data lost due to a disk failure.   The RAID scheme consists of 7 levels…   Category Level Description Disks Required Data Availability Large I/O Data Transfer Capacity Small I/O Request Rate Striping 0 Non Redundant N Lower than single disk Very high Very high for both read and write Mirroring 1 Mirrored 2N Higher than RAID 2 – 5 but lower than RAID 6 Higher than single disk Up to twice that of a signle disk for read Parallel Access 2 Redundant via Hamming Code N + m Much higher than single disk Highest of all listed alternatives Approximately twice that of a single disk Parallel Access 3 Bit interleaved parity N + 1 Much higher than single disk Highest of all listed alternatives Approximately twice that of a single disk Independent Access 4 Block interleaved parity N + 1 Much higher than single disk Similar to RAID 0 for read, significantly lower than single disk for write Similar to RAID 0 for read, significantly lower than single disk for write Independent Access 5 Block interleaved parity N + 1 Much higher than single disk Similar to RAID 0 for read, lower than single disk for write Similar to RAID 0 for read, generally  lower than single disk for write Independent Access 6 Block interleaved parity N + 2 Highest of all listed alternatives Similar to RAID 0 for read; lower than RAID 5 for write Similar to RAID 0 for read, significantly lower than RAID 5  for write   Read page 215 – 221 for detailed explanation on RAID levels Optical Memory There are a variety of optical-disk systems available. Read through the table on page 222 – 223 Some of the devices include… CD CD-ROM CD-R CD-RW DVD DVD-R DVD-RW Blue-Ray DVD Magnetic Tape Most modern systems use serial recording – data is lade out as a sequence of bits along each track. The typical recording used in serial is referred to as serpentine recording. In this technique when data is being recorded, the first set of bits is recorded along the whole length of the tape. When the end of the tape is reached the heads are repostioned to record a new track, and the tape is again recorded on its whole length, this time in the opposite direction. That process continued back and forth until the tape is full. To increase speed, the read-write head is capable of reading and writing a number of adjacent tracks simultaneously. Data is still recorded serially along individual tracks, but blocks in sequence are stored on adjacent tracks as suggested. A tape drive is a sequential access device. Magnetic tape was the first kind of secondary memory. It is still widely used as the lowest-cost, slowest speed member of the memory hierarchy.

  Read the article

• Efficiently separating Read/Compute/Write steps for concurrent processing of entities in Entity/Component systems

  - by TravisG

  Setup I have an entity-component architecture where Entities can have a set of attributes (which are pure data with no behavior) and there exist systems that run the entity logic which act on that data. Essentially, in somewhat pseudo-code: Entity { id; map<id_type, Attribute> attributes; } System { update(); vector<Entity> entities; } A system that just moves along all entities at a constant rate might be MovementSystem extends System { update() { for each entity in entities position = entity.attributes["position"]; position += vec3(1,1,1); } } Essentially, I'm trying to parallelise update() as efficiently as possible. This can be done by running entire systems in parallel, or by giving each update() of one system a couple of components so different threads can execute the update of the same system, but for a different subset of entities registered with that system. Problem In reality, these systems sometimes require that entities interact(/read/write data from/to) each other, sometimes within the same system (e.g. an AI system that reads state from other entities surrounding the current processed entity), but sometimes between different systems that depend on each other (i.e. a movement system that requires data from a system that processes user input). Now, when trying to parallelize the update phases of entity/component systems, the phases in which data (components/attributes) from Entities are read and used to compute something, and the phase where the modified data is written back to entities need to be separated in order to avoid data races. Otherwise the only way (not taking into account just "critical section"ing everything) to avoid them is to serialize parts of the update process that depend on other parts. This seems ugly. To me it would seem more elegant to be able to (ideally) have all processing running in parallel, where a system may read data from all entities as it wishes, but doesn't write modifications to that data back until some later point. The fact that this is even possible is based on the assumption that modification write-backs are usually very small in complexity, and don't require much performance, whereas computations are very expensive (relatively). So the overhead added by a delayed-write phase might be evened out by more efficient updating of entities (by having threads work more % of the time instead of waiting). A concrete example of this might be a system that updates physics. The system needs to both read and write a lot of data to and from entities. Optimally, there would be a system in place where all available threads update a subset of all entities registered with the physics system. In the case of the physics system this isn't trivially possible because of race conditions. So without a workaround, we would have to find other systems to run in parallel (which don't modify the same data as the physics system), other wise the remaining threads are waiting and wasting time. However, that has disadvantages Practically, the L3 cache is pretty much always better utilized when updating a large system with multiple threads, as opposed to multiple systems at once, which all act on different sets of data. Finding and assembling other systems to run in parallel can be extremely time consuming to design well enough to optimize performance. Sometimes, it might even not be possible at all because a system just depends on data that is touched by all other systems. Solution? In my thinking, a possible solution would be a system where reading/updating and writing of data is separated, so that in one expensive phase, systems only read data and compute what they need to compute, and then in a separate, performance-wise cheap, write phase, attributes of entities that needed to be modified are finally written back to the entities. The Question How might such a system be implemented to achieve optimal performance, as well as making programmer life easier? What are the implementation details of such a system and what might have to be changed in the existing EC-architecture to accommodate this solution?

  Read the article

• Blink-Data vs Instinct?

  - by Samantha.Y. Ma

  In his landmark bestseller Blink, well-known author and journalist Malcolm Gladwell explores how human beings everyday make seemingly instantaneous choices --in the blink of an eye--and how we “think without thinking.”  These situations actually aren’t as simple as they seem, he postulates; and throughout the book, Gladwell seeks answers to questions such as: 1.    What makes some people good at thinking on their feet and making quick spontaneous decisions?2.    Why do some people follow their instincts and win, while others consistently seem to stumble into error?3.    Why are some of the best decisions often those that are difficult to explain to others?In Blink, Gladwell introduces us to the psychologist who has learned to predict whether a marriage will last, based on a few minutes of observing a couple; the tennis coach who knows when a player will double-fault before the racket even makes contact with the ball; the antiquities experts who recognize a fake at a glance. Ultimately, Blink reveals that great decision makers aren't those who spend the most time deliberating or analyzing information, but those who focus on key factors among an overwhelming number of variables-- i.e., those who have perfected the art of "thin-slicing.” In Data vs. Instinct: Perfecting Global Sales Performance, a new report sponsored by Oracle, the Economist Intelligence Unit (EIU) explores the roles data and instinct play in decision-making by sales managers and discusses how sales executives can increase sales performance through more effective  territory planning and incentive/compensation strategies.If you are a sales executive, ask yourself this:  “Do you rely on knowledge (data) when you plan out your sales strategy?  If you rely on data, how do you ensure that your data sources are reliable, up-to-date, and complete?  With the emergence of social media and the proliferation of both structured and unstructured data, how do you know that you are applying your information/data correctly and in-context?  Three key findings in the report are:•    Six out of ten executives say they rely more on data than instinct to drive decisions. •    Nearly one half (48 percent) of incentive compensation plans do not achieve the desired results. •    Senior sales executives rely more on current and historical data than on forecast data. Strikingly similar to what Gladwell concludes in Blink, the report’s authors succinctly sum up their findings: "The best outcome is a combination of timely information, insightful predictions, and support data."Applying this insight is crucial to creating a sound sales plan that drives alignment and results.  In the area of sales performance management, “territory programs and incentive compensation continue to present particularly complex challenges in an increasingly globalized market," say the report’s authors. "It behooves companies to get a better handle on translating that data into actionable and effective plans." To help solve this challenge, CRM Oracle Fusion integrates forecasting, quotas, compensation, and territories into a single system.   For example, Oracle Fusion CRM provides a natural integration between territories, which define the sales targets (e.g., collection of accounts) for the sales force, and quotas, which quantify the sales targets. In fact, territory hierarchy is a core analytic dimension to slice and dice sales results, using sales analytics and alerts to help you identify where problems are occurring. This makes territoriesStart tapping into both data and instinct effectively today with Oracle Fusion CRM.   Here is a short video to provide you with a snapshot of how it can help you optimize your sales performance.  

  Read the article

• The Best Data Integration for Exadata Comes from Oracle

  - by maria costanzo

  Oracle Data Integrator and Oracle GoldenGate offer unique and optimized data integration solutions for Oracle Exadata. For example, customers that choose to feed their data warehouse or reporting database with near real-time throughout the day, can do so without decreasing  performance or availability of source and target systems. And if you ask why real-time, the short answer is: in today’s fast-paced, always-on world, business decisions need to use more relevant, timely data to be able to act fast and seize opportunities. A longer response to "why real-time" question can be found in a related blog post. If we look at the solution architecture, as shown on the diagram below,  Oracle Data Integrator and Oracle GoldenGate are both uniquely designed to take full advantage of the power of the database and to eliminate unnecessary middle-tier components. Oracle Data Integrator (ODI) is the best bulk data loading solution for Exadata. ODI is the only ETL platform that can leverage the full power of Exadata, integrate directly on the Exadata machine without any additional hardware, and by far provides the simplest setup and fastest overall performance on an Exadata system. We regularly see customers achieving a 5-10 times boost when they move their ETL to ODI on Exadata. For  some companies the performance gain is even much higher. For example a large insurance company did a proof of concept comparing ODI vs a traditional ETL tool (one of the market leaders) on Exadata. The same process that was taking 5hrs and 11 minutes to complete using the competing ETL product took 7 minutes and 20 seconds with ODI. Oracle Data Integrator was 42 times faster than the conventional ETL when running on Exadata.This shows that Oracle's own data integration offering helps you to gain the most out of your Exadata investment with a truly optimized solution. GoldenGate is the best solution for streaming data from heterogeneous sources into Exadata in real time. Oracle GoldenGate can also be used together with Data Integrator for hybrid use cases that also demand non-invasive capture, high-speed real time replication. Oracle GoldenGate enables real-time data feeds from heterogeneous sources non-invasively, and delivers to the staging area on the target Exadata system. ODI runs directly on Exadata to use the database engine power to perform in-database transformations. Enterprise Data Quality is integrated with Oracle Data integrator and enables ODI to load trusted data into the data warehouse tables. Only Oracle can offer all these technical benefits wrapped into a single intelligence data warehouse solution that runs on Exadata. Compared to traditional ETL with add-on CDC this solution offers: §  Non-invasive data capture from heterogeneous sources and avoids any performance impact on source §  No mid-tier; set based transformations use database power §  Mini-batches throughout the day –or- bulk processing nightly which means maximum availability for the DW §  Integrated solution with Enterprise Data Quality enables leveraging trusted data in the data warehouse In addition to Starwood Hotels and Resorts, Morrison Supermarkets, United Kingdom’s fourth-largest food retailer, has seen the power of this solution for their new BI platform and shared their story with us. Morrisons needed to analyze data across a large number of manufacturing, warehousing, retail, and financial applications with the goal to achieve single view into operations for improved customer service. The retailer deployed Oracle GoldenGate and Oracle Data Integrator to bring new data into Oracle Exadata in near real-time and replicate the data into reporting structures within the data warehouse—extending visibility into operations. Using Oracle's data integration offering for Exadata, Morrisons produced financial reports in seconds, rather than minutes, and improved staff productivity and agility. You can read more about Morrison’s success story here and hear from Starwood here. From an Irem Radzik article.

  Read the article

• JavaOne 2012: Nashorn Edition

  - by $utils.escapeXML($entry.author)

  As with my JavaOne 2012: OpenJDK Edition post a while back (now updated to reflect the schedule of the talks), I find it convenient to have my JavaOne schedule ordered by subjects of interest. Beside OpenJDK in all its flavors, another subject I find very exciting is Nashorn. I blogged about the various material on Nashorn in the past, and we interviewed Jim Laskey, the Project Lead on Project Nashorn in the Java Spotlight podcast. So without further ado, here are the JavaOne 2012 talks and BOFs with Nashorn in their title, or abstract:CON5390 - Nashorn: Optimizing JavaScript and Dynamic Language Execution on the JVM - Monday, Oct 1, 8:30 AM - 9:30 AMThere are many implementations of JavaScript, meant to run either on the JVM or standalone as native code. Both approaches have their respective pros and cons. The Oracle Nashorn JavaScript project is based on the former approach. This presentation goes through the performance work that has gone on in Oracle’s Nashorn JavaScript project to date in order to make JavaScript-to-bytecode generation for execution on the JVM feasible. It shows that the new invoke dynamic bytecode gets us part of the way there but may not quite be enough. What other tricks did the Nashorn project use? The presentation also discusses future directions for increased performance for dynamic languages on the JVM, covering proposed enhancements to both the JVM itself and to the bytecode compiler.CON4082 - Nashorn: JavaScript on the JVM - Monday, Oct 1, 3:00 PM - 4:00 PMThe JavaScript programming language has been experiencing a renaissance of late, driven by the interest in HTML5. Nashorn is a JavaScript engine implemented fully in Java on the JVM. It is based on the Da Vinci Machine (JSR 292) and will be available with JDK 8. This session describes the goals of Project Nashorn, gives a top-level view of how it all works, provides the current status, and demonstrates examples of JavaScript and Java working together.BOF4763 - Meet the Nashorn JavaScript Team - Tuesday, Oct 2, 4:30 PM - 5:15 PMCome to this session to meet the Oracle JavaScript (Project Nashorn) language teamBOF6661 - Nashorn, Node, and Java Persistence - Tuesday, Oct 2, 5:30 PM - 6:15 PMWith Project Nashorn, developers will have a full and modern JavaScript engine available on the JVM. In addition, they will have support for running Node applications with Node.jar. This unique combination of capabilities opens the door for best-of-breed applications combining Node with Java SE and Java EE. In this session, you’ll learn about Node.jar and how it can be combined with Java EE components such as EclipseLink JPA for rich Java persistence. You’ll also hear about all of Node.jar’s mapping, caching, querying, performance, and scaling features.CON10657 - The Polyglot Java VM and Java Middleware - Thursday, Oct 4, 12:30 PM - 1:30 PMIn this session, Red Hat and Oracle discuss the impact of polyglot programming from their own unique perspectives, examining non-Java languages that utilize Oracle’s Java HotSpot VM. You’ll hear a discussion of topics relating to Ruby, Lisp, and Clojure and the intersection of other languages where they may touch upon individual frameworks and projects, and you’ll get perspectives on JavaScript via the Nashorn Project, an upcoming JavaScript engine, developed fully in Java.CON5251 - Putting the Metaobject Protocol to Work: Nashorn’s Java Bindings - Thursday, Oct 4, 2:00 PM - 3:00 PMProject Nashorn is Oracle’s new JavaScript runtime in Java 8. Being a JavaScript runtime running on the JVM, it provides integration with the underlying runtime by enabling JavaScript objects to manipulate Java objects, implement Java interfaces, and extend Java classes. Nashorn is invokedynamic-based, and for its Java integration, it does away with the concept of wrapper objects in favor of direct virtual machine linking to Java objects’ methods provided by a metaobject protocol, providing much higher performance than what could be expected from a scripting runtime. This session looks at the details of the integration, a topic of interest to other language implementers on the JVM and a wider audience of developers who want to understand how Nashorn works.That's 6 sessions tooting the Nashorn this year at JavaOne, up from 2 last year.

  Read the article

• Drive

  - by erikanollwebb

  Picking up where we left off, let's summarize.  People have both intrinsic motivation and extrinsic motivation, and whether reward works depends a bit on what you are rewarding.  Rewards don't decreased intrinsic motivation provided you know what you are getting and why, and when you reward high performance.  But as anyone who has watched the great animation of Dan Pink's TED talk knows, even that doesn't tell the whole story.  Although people may not be less intrinsically motivated by rewards, the impact of rewards on actual performance is a really odd questions.  Larger rewards don't necessarily lead to better performance and in fact, some times lead to worse performance.  Pink argues that people are driven and engaged when they have autonomy, mastery and purpose.  If they can self-direct and can be good at what they do and have a sense of purpose for what they are doing, they show the highest engagement.   (Personally, I would add progress to the list.  My experience is that if you have autonomy, mastery and a sense of purpose but don't get a feeling that you are making any progress day to day, your level of engagement will drop rapidly.) So Pink is arguing if we could set up work so that people have a sense of purpose in what they do, have some autonomy and the ability to build mastery, you'll have better companies.  And that's probably true in a lot of ways, but there's a problem.  Sometimes, you have things you need to do but maybe you don't really want to do.  Or that you don't really see the point of.  Or that doesn't have a lot of value to you at the end of the day.  Then what does a company do?  Let me give you an example.  I've worked on some customer relationship management (CRM) tools over the years and done user research with sales people to try and understand their world.  And there's a funny thing about sales tools in CRM.  Sometimes what the company wants a sales person to do is at odds with what a sales person thinks is useful to them.  For example, companies would like to know who a sales person talked to at the company and the person level.  They'd like to know what they talked about, when, and whether the deals closed.  Those metrics would help you build a better sales force and understand what works and what does not.  But sales people see that as busy work that doesn't add any value to their ability to sell.  So you have a sales person who has a lot of autonomy, they like to do things that improve their ability to sell and they usually feel a sense of purpose--the group is trying to make a quota!  That quota will help the company succeed!  But then you have tasks that they don't think fit into that equation.  The company would like to know more about what makes them successful and get metrics on what they do and frankly, have a record of what they do in case they leave, but the sales person thinks it's a waste of time to put all that information into a sales application. They have drive, just not for all the things the company would like.   You could punish them for not entering the information, or you could try to reward them for doing it, but you still have an imperfect model of engagement.  Ideally, you'd like them to want to do it.  If they want to do it, if they are motivated to do it, then the company wins.  If *something* about it is rewarding to them, then they are more engaged and more likely to do it.  So the question becomes, how do you create that interest to do something?

  Read the article

• Concurrent Affairs

  - by Tony Davis

  I once wrote an editorial, multi-core mania, on the conundrum of ever-increasing numbers of processor cores, but without the concurrent programming techniques to get anywhere near exploiting their performance potential. I came to the.controversial.conclusion that, while the problem loomed for all procedural languages, it was not a big issue for the vast majority of programmers. Two years later, I still think most programmers don't concern themselves overly with this issue, but I do think that's a bigger problem than I originally implied. Firstly, is the performance boost from writing code that can fully exploit all available cores worth the cost of the additional programming complexity? Right now, with quad-core processors that, at best, can make our programs four times faster, the answer is still no for many applications. But what happens in a few years, as the number of cores grows to 100 or even 1000? At this point, it becomes very hard to ignore the potential gains from exploiting concurrency. Possibly, I was optimistic to assume that, by the time we have 100-core processors, and most applications really needed to exploit them, some technology would be around to allow us to do so with relative ease. The ideal solution would be one that allows programmers to forget about the problem, in much the same way that garbage collection removed the need to worry too much about memory allocation. From all I can find on the topic, though, there is only a remote likelihood that we'll ever have a compiler that takes a program written in a single-threaded style and "auto-magically" converts it into an efficient, correct, multi-threaded program. At the same time, it seems clear that what is currently the most common solution, multi-threaded programming with shared memory, is unsustainable. As soon as a piece of state can be changed by a different thread of execution, the potential number of execution paths through your program grows exponentially with the number of threads. If you have two threads, each executing n instructions, then there are 2^n possible "interleavings" of those instructions. Of course, many of those interleavings will have identical behavior, but several won't. Not only does this make understanding how a program works an order of magnitude harder, but it will also result in irreproducible, non-deterministic, bugs. And of course, the problem will be many times worse when you have a hundred or a thousand threads. So what is the answer? All of the possible alternatives require a change in the way we write programs and, currently, seem to be plagued by performance issues. Software transactional memory (STM) applies the ideas of database transactions, and optimistic concurrency control, to memory. However, working out how to break down your program into sufficiently small transactions, so as to avoid contention issues, isn't easy. Another approach is concurrency with actors, where instead of having threads share memory, each thread runs in complete isolation, and communicates with others by passing messages. It simplifies concurrent programs but still has performance issues, if the threads need to operate on the same large piece of data. There are doubtless other possible solutions that I haven't mentioned, and I would love to know to what extent you, as a developer, are considering the problem of multi-core concurrency, what solution you currently favor, and why. Cheers, Tony.

  Read the article

• Applications on the Web/Cloud the way to go? over Desktop apps?

  - by jiewmeng

  i am currently a mainly web developer, but is quite attracted to the performance and great integration with the OS (eg. Windows 7, Jump Lists, Taskbar Thumbnails, etc) something like WPF/C# can provide to the user, improving workflow and productivity. privacy and performance seems like a major downside of web/cloud apps compared to desktop apps. applications on the cloud/web work on the go, increased popularity of smartphones/netbooks majority of users may not benefit as much from increased performance of desktop apps, eg. internet surfing, word processing, probably benefit more from decreased startup times, lower costs and data on the cloud desktop applications increased performance benefits power users like 3D rendering, HD video/photo editing, gamers (i wonder if such processing maybe offset to cloud processing) integration with OS increases productivity (maybe such features can be adapted to a web version? maybe with a local desktop app to work with Web App API) more control over privacy (maybe fixed by encryption?) local data access (esp. large files) guaranteed and fast (YouTube HD fast enough most of the time) work not affected by intermittent/slow/availability internet connections (i know this is changing tho) what do you think?

  Read the article

• Surprising results with .NET multi-theading algorithm

  - by Myles J

  Hi, I've recently wrote a C# console time tabling algorithm that is based on a combination of a genetic algorithm with a few brute force routines thrown in. The initial results were promising but I figured I could improve the performance by splitting the brute force routines up to run in parallel on multi processor architectures. To do this I used the well documented Producer/Consumer model (as documented in this fantastic article http://www.albahari.com/threading/part2.aspx#_ProducerConsumerQWaitHandle). I changed my code to create one thread per logical processor during the brute force routines. The performance gains on my work station were very pleasing. I am running Windows XP on the following hardware: Intel Core 2 Quad CPU 2.33 GHz 3.49 GB RAM Initial tests indicated average performance gains of approx 40% when using 4 threads. The next step was to deploy the new multi-threading version of the algorithm to our higher spec UAT server. Here is the spec of our UAT server: Windows 2003 Server R2 Enterprise x64 8 cpu (Quad-Core) AMD Opteron 2.70 GHz 255 GB RAM After running the first round of tests we were all extremely surprised to find that the algorithm actually runs slower on the high spec W2003 server than on my local XP work station! In fact the tests seem to indicate that it doesn't matter how many threads are generated (tests were ran with the app spawning between 2 to 32 threads). The algorithm always runs significantly slower on the UAT W2003 server? How could this be? Surely the app should run faster on a 8 cpu (Quad-Core) than my 2 Quad work station? Why are we seeing no performance gains with the multi-threading on the W2003 server whilst the XP workstation tests show gains of up to 40%? Any help or pointers would be appreciated. Regards Myles

  Read the article

• How to simply a foreach iteration using reflection

  - by Priya

  Consider that I have to get the overall performance of X. X has Y elements and Y in turn has Z elements which inturn has some N elements. To get the performance of X I do this: List<double> XQ = new List<double>(); foreach (Elem Y in X.Y){ List<double> YQ = new List<double>(); foreach (Elem Z in Y.Z){ List<double> ZQ = new List<double>(); foreach (Elem N in Z.N){ ZQ.Add(GetPerformance(N)); } YQ.Add(AVG(ZQ)); } XQ.Add(AVG(YQ)); } AVG of XQ list gives the performance of X. The performance can be calculated for either X or Y or for Z. X, Y and Z share the same base class. So depending on the item given the foreach loop has to be executed. Currently I have a switch case to determine each item (X or Y or Z) and the foreach loop is repeated in the code pertaining to the item (eg. If Y foreach starts from Y.Z). Is is possible to convert this whole code generic using reflection instead of having to repeat it in each switch case? Thanks

  Read the article

• Slow Python HTTP server on localhost

  - by Abiel

  I am experiencing some performance problems when creating a very simple Python HTTP server. The key issue is that performance is varying depending on which client I use to access it, where the server and all clients are being run on the local machine. For instance, a GET request issued from a Python script (urllib2.urlopen('http://localhost/').read()) takes just over a second to complete, which seems slow considering that the server is under no load. Running the GET request from Excel using MSXML2.ServerXMLHTTP also feels slow. However, requesting the data Google Chrome or from RCurl, the curl add-in for R, yields an essentially instantaneous response, which is what I would expect. Adding further to my confusion is that I do not experience any performance problems for any client when I am on my computer at work (the performance problems are on my home computer). Both systems run Python 2.6, although the work computer runs Windows XP instead of 7. Below is my very simple server example, which simply returns 'Hello world' for any get request. from BaseHTTPServer import BaseHTTPRequestHandler, HTTPServer class MyHandler(BaseHTTPRequestHandler): def do_GET(self): print("Just received a GET request") self.send_response(200) self.send_header("Content-type", "text/html") self.end_headers() self.wfile.write('Hello world') return def log_request(self, code=None, size=None): print('Request') def log_message(self, format, *args): print('Message') if __name__ == "__main__": try: server = HTTPServer(('localhost', 80), MyHandler) print('Started http server') server.serve_forever() except KeyboardInterrupt: print('^C received, shutting down server') server.socket.close() Note that in MyHandler I override the log_request() and log_message() functions. The reason is that I read that a fully-qualified domain name lookup performed by one of these functions might be a reason for a slow server. Unfortunately setting them to just print a static message did not solve my problem. Also, notice that I have put in a print() statement as the first line of the do_GET() routine in MyHandler. The slowness occurs prior to this message being printed, meaning that none of the stuff that comes after it is causing a delay.

  Read the article

• duplicate rows in join table with has_many => through and accepts_nested_attributes_for

  - by shalako

  An event has many artists, and an artist has many events. The join of an artist and an event is called a performance. I want to add artists to an event. This works except that I'm getting duplicate entries into my join table when creating a new event. This causes problems elsewhere. event.rb has_many :performances, :dependent => :destroy has_many :artists, :through => :performances accepts_nested_attributes_for :artists, :reject_if => proc {|a| a['name'].blank?} accepts_nested_attributes_for :performances, :reject_if => proc { |a| a['artist_id'].blank? }, :allow_destroy => true artist.rb has_many :performances, :dependent => :destroy has_many :artists, :through => :performances performance.rb belongs_to :artist belongs_to :event events_controller.rb def new @event = Event.new @event.artists.build respond_to do |format| format.html # new.html.erb format.xml { render :xml => @event } end end def create @event = Event.new(params[:event]) respond_to do |format| if @event.save flash[:notice] = 'Event was successfully created.' format.html { redirect_to(admin_events_url) } format.xml { render :xml => @event, :status => :created, :location => @event } else format.html { render :action => "new" } format.xml { render :xml => @event.errors, :status => :unprocessable_entity } end end end output Performance Create (0.2ms) INSERT INTO `performances` (`event_id`, `artist_id`) VALUES(7, 19) Performance Create (0.1ms) INSERT INTO `performances` (`event_id`, `artist_id`) VALUES(7, 19)

  Read the article

• genStrAsCharArray optimisation benefits

  - by Rich

  Hi I am looking into the options available to me for optimising the performance of JBoss 5.1.0. One of the options I am looking at is setting genStrAsCharArray to true in <JBOSS_HOME>/server/<PROFILE>/deployers/jbossweb.deployer/web.xml. This affects the generation of .java code from .JSPs. The comment describes this flag as: Should text strings be generated as char arrays, to improve performance in some cases? I have a few questions about this. Is this the generation of Strings in the dynamic parts of the JSP page (ie each time the page is called) or is it the generation of Strings in the static parts (ie when the .java is built from the JSP)? "in some cases" - which cases are these? What are the situations where the performance is worse? Does this speed up the generation of the .java, the compilation of the .class or the execution of the .class? At a more technical level (and the answer to this will probably depend on the answer to part 1), why can the use of char arrays improve performance? Thanks in advance Rich

  Read the article

• Oracle Enterprise Manager 11g Application Management Suite for Oracle E-Business Suite Now Available

  - by chung.wu

  Oracle Enterprise Manager 11g Application Management Suite for Oracle E-Business Suite is now available. The management suite combines features that were available in the standalone Application Management Pack for Oracle E-Business Suite and Application Change Management Pack for Oracle E-Business Suite with Oracle's market leading real user monitoring and configuration management capabilities to provide the most complete solution for managing E-Business Suite applications. The features that were available in the standalone management packs are now packaged into Oracle E-Business Suite Plug-in 4.0, which is now fully certified with Oracle Enterprise Manager 11g Grid Control. This latest plug-in extends Grid Control with E-Business Suite specific management capabilities and features enhanced change management support. In addition, this latest release of Application Management Suite for Oracle E-Business Suite also includes numerous real user monitoring improvements. General Enhancements This new release of Application Management Suite for Oracle E-Business Suite offers the following key capabilities: Oracle Enterprise Manager 11g Grid Control Support: All components of the management suite are certified with Oracle Enterprise Manager 11g Grid Control. Built-in Diagnostic Ability: This release has numerous major enhancements that provide the necessary intelligence to determine if the product has been installed and configured correctly. There are diagnostics for Discovery, Cloning, and User Monitoring that will validate if the appropriate patches, privileges, setups, and profile options have been configured. This feature improves the setup and configuration time to be up and operational. Lifecycle Automation Enhancements Application Management Suite for Oracle E-Business Suite provides a centralized view to monitor and orchestrate changes (both functional and technical) across multiple Oracle E-Business Suite systems. In this latest release, it provides even more control and flexibility in managing Oracle E-Business Suite changes.Change Management: Built-in Diagnostic Ability: This latest release has numerous major enhancements that provide the necessary intelligence to determine if the product has been installed and configured correctly. There are diagnostics for Customization Manager, Patch Manager, and Setup Manager that will validate if the appropriate patches, privileges, setups, and profile options have been configured. Enhancing the setup time and configuration time to be up and operational. Customization Manager: Multi-Node Custom Application Registration: This feature automates the process of registering and validating custom products/applications on every node in a multi-node EBS system. Public/Private File Source Mappings and E-Business Suite Mappings: File Source Mappings & E-Business Suite Mappings can be created and marked as public or private. Only the creator/owner can define/edit his/her own mappings. Users can use public mappings, but cannot edit or change settings. Test Checkout Command for Versions: This feature allows you to test/verify checkout commands at the version level within the File Source Mapping page. Prerequisite Patch Validation: You can specify prerequisite patches for Customization packages and for Release 12 Oracle E-Business Suite packages. Destination Path Population: You can now automatically populate the Destination Path for common file types during package construction. OAF File Type Support: Ability to package Oracle Application Framework (OAF) customizations and deploy them across multiple Oracle E-Business Suite instances. Extended PLL Support: Ability to distinguish between different types of PLLs (that is, Report and Forms PLL files). Providing better granularity when managing PLL objects. Enhanced Standard Checker: Provides greater and more comprehensive list of coding standards that are verified during the package build process (for example, File Driver exceptions, Java checks, XML checks, SQL checks, etc.) HTML Package Readme: The package Readme is in HTML format and includes the file listing. Advanced Package Search Capabilities: The ability to utilize more criteria within the advanced search package (that is, Public, Last Updated by, Files Source Mapping, and E-Business Suite Mapping). Enhanced Package Build Notifications: More detailed information on the results of a package build process. Better, more detailed troubleshooting guidance in the event of build failures. Patch Manager:Staged Patches: Ability to run Patch Manager with no external internet access. Customer can download Oracle E-Business Suite patches into a shared location for Patch Manager to access and apply. Supports highly secured production environments that prohibit external internet connections. Support for Superseded Patches: Automatic check for superseded patches. Allows users to easily add superseded patches into the Patch Run. More comprehensive and correct Patch Runs. Removes many manual and laborious tasks, frees up Apps DBAs for higher value-added tasks. Automatic Primary Node Identification: Users can now specify which is the "primary node" (that is, which node hosts the Shared APPL_TOP) during the Patch Run interview process, available for Release 12 only. Setup Manager:Preview Extract Results: Ability to execute an extract in "proof mode", and examine the query results, to determine accuracy. Used in conjunction with the "where" clause in Advanced Filtering. This feature can provide better and more accurate fine tuning of extracts. Use Uploaded Extracts in New Projects: Ability to incorporate uploaded extracts in new projects via new LOV fields in package construction. Leverages the Setup Manager repository to access extracts that have been uploaded. Allows customer to reuse uploaded extracts to provision new instances. Re-use Existing (that is, historical) Extracts in New Projects: Ability to incorporate existing extracts in new projects via new LOV fields in package construction. Leverages the Setup Manager repository to access point-in-time extracts (snapshots) of configuration data. Allows customer to reuse existing extracts to provision new instances. Allows comparative historical reporting of identical APIs, executed at different times. Support for BR100 formats: Setup Manager can now automatically produce reports in the BR100 format. Native support for industry standard formats. Concurrent Manager API Support: General Foundation now provides an API for management of "Concurrent Manager" configuration data. Ability to migrate Concurrent Managers from one instance to another. Complete the setup once and never again; no need to redefine the Concurrent Managers. User Experience Management Enhancements Application Management Suite for Oracle E-Business Suite includes comprehensive capabilities for user experience management, supporting both real user and synthetic transaction based user monitoring techniques. This latest release of the management suite include numerous improvements in real user monitoring support. KPI Reporting: Configurable decimal precision for reporting of KPI and SLA values. By default, this is two decimal places. KPI numerator and denominator information. It is now possible to view KPI numerator and denominator information, and to have it available for export. Content Messages Processing: The application content message facility has been extended to distinguish between notifications and errors. In addition, it is now possible to specify matching rules that can be used to refine a selected content message specification. Note this is only available for XPath-based (not literal) message contents. Data Export: The Enriched data export facility has been significantly enhanced to provide improved performance and accessibility. Data is no longer stored within XML-based files, but is now stored within the Reporter database. However, it is possible to configure an alternative database for its storage. Access to the export data is through SQL. With this enhancement, it is now more easy than ever to use tools such as Oracle Business Intelligence Enterprise Edition to analyze correlated data collected from real user monitoring and business data sources. SNMP Traps for System Events: Previously, the SNMP notification facility was only available for KPI alerting. It has now been extended to support the generation of SNMP traps for system events, to provide external health monitoring of the RUEI system processes. Performance Improvements: Enhanced dashboard performance. The dashboard facility has been enhanced to support the parallel loading of items. In the case of dashboards containing large numbers of items, this can result in a significant performance improvement. Initial period selection within Data Browser and reports. The User Preferences facility has been extended to allow you to specify the initial period selection when first entering the Data Browser or reports facility. The default is the last hour. Performance improvement when querying the all sessions group. Technical Prerequisites, Download and Installation Instructions The Linux version of the plug-in is available for immediate download from Oracle Technology Network or Oracle eDelivery. For specific information regarding technical prerequisites, product download and installation, please refer to My Oracle Support note 1224313.1. The following certifications are in progress: * Oracle Solaris on SPARC (64-bit) (9, 10) * HP-UX Itanium (11.23, 11.31) * HP-UX PA-RISC (64-bit) (11.23, 11.31) * IBM AIX on Power Systems (64-bit) (5.3, 6.1)

  Read the article

• Interesting articles and blogs on SPARC T4

  - by mv

  Interesting articles and blogs on SPARC T4 processor   I have consolidated all the interesting information I could get on SPARC T4 processor and its hardware cryptographic capabilities.  Hope its useful. 1. Advantages of SPARC T4 processor  Most important points in this T4 announcement are : "The SPARC T4 processor was designed from the ground up for high speed security and has a cryptographic stream processing unit (SPU) integrated directly into each processor core. These accelerators support 16 industry standard security ciphers and enable high speed encryption at rates 3 to 5 times that of competing processors. By integrating encryption capabilities directly inside the instruction pipeline, the SPARC T4 processor eliminates the performance and cost barriers typically associated with secure computing and makes it possible to deliver high security levels without impacting the user experience." Data Sheet has more details on these  : "New on-chip Encryption Instruction Accelerators with direct non-privileged support for 16 industry-standard cryptographic algorithms plus random number generation in each of the eight cores: AES, Camellia, CRC32c, DES, 3DES, DH, DSA, ECC, Kasumi, MD5, RSA, SHA-1, SHA-224, SHA-256, SHA-384, SHA-512" I ran "isainfo -v" command on Solaris 11 Sparc T4-1 system. It shows the new instructions as expected  : $ isainfo -v 64-bit sparcv9 applications crc32c cbcond pause mont mpmul sha512 sha256 sha1 md5 camellia kasumi des aes ima hpc vis3 fmaf asi_blk_init vis2 vis popc 32-bit sparc applications crc32c cbcond pause mont mpmul sha512 sha256 sha1 md5 camellia kasumi des aes ima hpc vis3 fmaf asi_blk_init vis2 vis popc v8plus div32 mul32  2.  Dan Anderson's Blog have some interesting points about how these can be used : "New T4 crypto instructions include: aes_kexpand0, aes_kexpand1, aes_kexpand2,         aes_eround01, aes_eround23, aes_eround01_l, aes_eround_23_l, aes_dround01, aes_dround23, aes_dround01_l, aes_dround_23_l.       Having SPARC T4 hardware crypto instructions is all well and good, but how do we access it ?      The software is available with Solaris 11 and is used automatically if you are running Solaris a SPARC T4.  It is used internally in the kernel through kernel crypto modules.  It is available in user space through the PKCS#11 library." 3.   Dans' Blog on Where's the Crypto Libraries? Although this was written in 2009 but still is very useful  "Here's a brief tour of the major crypto libraries shown in the digraph:   The libpkcs11 library contains the PKCS#11 API (C_\*() functions, such as C_Initialize()). That in turn calls library pkcs11_softtoken or pkcs11_kernel, for userland or kernel crypto providers. The latter is used mostly for hardware-assisted cryptography (such as n2cp for Niagara2 SPARC processors), as that is performed more efficiently in kernel space with the "kCF" module (Kernel Crypto Framework). Additionally, for Solaris 10, strong crypto algorithms were split off in separate libraries, pkcs11_softtoken_extra libcryptoutil contains low-level utility functions to help implement cryptography. libsoftcrypto (OpenSolaris and Solaris Nevada only) implements several symmetric-key crypto algorithms in software, such as AES, RC4, and DES3, and the bignum library (used for RSA). libmd implements MD5, SHA, and SHA2 message digest algorithms" 4. Difference in T3 and T4 Diagram in this blog is good and self explanatory. Jeff's blog also highlights the differences  "The T4 servers have improved crypto acceleration, described at https://blogs.oracle.com/DanX/entry/sparc_t4_openssl_engine. It is "just built in" so administrators no longer have to assign crypto accelerator units to domains - it "just happens". Every physical or virtual CPU on a SPARC-T4 has full access to hardware based crypto acceleration at all times. .... For completeness sake, it's worth noting that the T4 adds more crypto algorithms, and accelerates Camelia, CRC32c, and more SHA-x." 5. About performance counters In this blog, performance counters are explained : "Note that unlike T3 and before, T4 crypto doesn't require kernel modules like ncp or n2cp, there is no visibility of crypto hardware with kstats or cryptoadm. T4 does provide hardware counters for crypto operations.  You can see these using cpustat: cpustat -c pic0=Instr_FGU_crypto 5 You can check the general crypto support of the hardware and OS with the command "isainfo -v". Since T4 crypto's implementation now allows direct userland access, there are no "crypto units" visible to cryptoadm.  " For more details refer Martin's blog as well. 6. How to turn off  SPARC T4 or Intel AES-NI crypto acceleration  I found this interesting blog from Darren about how to turn off  SPARC T4 or Intel AES-NI crypto acceleration. "One of the new Solaris 11 features of the linker/loader is the ability to have a single ELF object that has multiple different implementations of the same functions that are selected at runtime based on the capabilities of the machine.   The alternate to this is having the application coded to call getisax(2) system call and make the choice itself.  We use this functionality of the linker/loader when we build the userland libraries for the Solaris Cryptographic Framework (specifically libmd.so and libsoftcrypto.so) The Solaris linker/loader allows control of a lot of its functionality via environment variables, we can use that to control the version of the cryptographic functions we run.  To do this we simply export the LD_HWCAP environment variable with values that tell ld.so.1 to not select the HWCAP section matching certain features even if isainfo says they are present.  This will work for consumers of the Solaris Cryptographic Framework that use the Solaris PKCS#11 libraries or use libmd.so interfaces directly.  For SPARC T4 : export LD_HWCAP="-aes -des -md5 -sha256 -sha512 -mont -mpul" .. For Intel systems with AES-NI support: export LD_HWCAP="-aes"" Note that LD_HWCAP is explained in  http://docs.oracle.com/cd/E23823_01/html/816-5165/ld.so.1-1.html "LD_HWCAP, LD_HWCAP_32, and LD_HWCAP_64 -  Identifies an alternative hardware capabilities value... A “-” prefix results in the capabilities that follow being removed from the alternative capabilities." 7. Whitepaper on SPARC T4 Servers—Optimized for End-to-End Data Center Computing This Whitepaper on SPARC T4 Servers—Optimized for End-to-End Data Center Computing explains more details.  It has DTrace scripts which may come in handy : "To ensure the hardware-assisted cryptographic acceleration is configured to use and working with the security scenarios, it is recommended to use the following Solaris DTrace script. #!/usr/sbin/dtrace -s pid$1:libsoftcrypto:yf*:entry, pid$target:libsoftcrypto:rsa*:entry, pid$1:libmd:yf*:entry { @[probefunc] = count(); } tick-1sec { printa(@ops); trunc(@ops); }" Note that I have slightly modified the D Script to have RSA "libsoftcrypto:rsa*:entry" as well as per recommendations from Chi-Chang Lin. 8. References http://www.oracle.com/us/corporate/features/sparc-t4-announcement-494846.html http://www.oracle.com/us/products/servers-storage/servers/sparc-enterprise/t-series/sparc-t4-1-ds-487858.pdf https://blogs.oracle.com/DanX/entry/sparc_t4_openssl_engine https://blogs.oracle.com/DanX/entry/where_s_the_crypto_libraries https://blogs.oracle.com/darren/entry/howto_turn_off_sparc_t4 http://docs.oracle.com/cd/E23823_01/html/816-5165/ld.so.1-1.html   https://blogs.oracle.com/hardware/entry/unleash_the_power_of_cryptography https://blogs.oracle.com/cmt/entry/t4_crypto_cheat_sheet https://blogs.oracle.com/martinm/entry/t4_performance_counters_explained  https://blogs.oracle.com/jsavit/entry/no_mau_required_on_a http://www.oracle.com/us/products/servers-storage/servers/sparc-enterprise/t-series/sparc-t4-business-wp-524472.pdf

  Read the article

• Cloud Based Load Testing Using TF Service &amp; VS 2013

  - by Tarun Arora [Microsoft MVP]

  Originally posted on: http://geekswithblogs.net/TarunArora/archive/2013/06/30/cloud-based-load-testing-using-tf-service-amp-vs-2013.aspx One of the new features announced as part of the Visual Studio 2013 Ultimate Preview is ‘Cloud Based Load Testing’. In this blog post I’ll walk you through, What is Cloud Based Load Testing? How have I been using this feature? – Success story! Where can you find more resources on this feature? What is Cloud Based Load Testing? It goes without saying that performance testing your application not only gives you the confidence that the application will work under heavy levels of stress but also gives you the ability to test how scalable the architecture of your application is. It is important to know how much is too much for your application! Working with various clients in the industry I have realized that the biggest barriers in Load Testing & Performance Testing adoption are, High infrastructure and administration cost that comes with this phase of testing Time taken to procure & set up the test infrastructure Finding use for this infrastructure investment after completion of testing Is cloud the answer? 100% Visual Studio Compatible Scalable and Realistic Start testing in < 2 minutes Intuitive Pay only for what you need Use existing on premise tests on cloud There are a lot of vendors out there offering Cloud Based Load Testing, to name a few, Load Storm Soasta Blaze Meter Blitz And others… The question you may want to ask is, why should you go with Microsoft’s Cloud based Load Test offering. If you are a Microsoft shop or already have investments in Microsoft technologies, you’ll see great benefit in the natural integration this offers with existing Microsoft products such as Visual Studio and Windows Azure. For example, your existing Web tests authored in Visual Studio 2010 or Visual Studio 2012 will run on the cloud without requiring any modifications what so ever. Microsoft’s cloud test rig also supports API based testing, for example, if you are building a WPF application which consumes WCF services, you can write unit tests to invoke the WCF service, these tests can be run on the cloud test rig and loaded with ‘N’ concurrent users for performance testing. If you have your assets already hosted in the Azure and possibly in the same data centre as the Cloud test rig, your Azure app will not incur a usage cost because of the generated traffic since the traffic is coming from the same data centre. The licensing or pricing information on Microsoft’s cloud based Load test service is yet to be announced, but I would expect this to be priced attractively to match the market competition.   The only additional configuration required for running load tests on Microsoft Cloud based Load Tests service is to select the Test run location as Run tests using Visual Studio Team Foundation Service, How have I been using Microsoft’s Cloud based Load Test Service? I have been part of the Microsoft Cloud Based Load Test Service advisory council for the last 7 months. This gave the opportunity to see the product shape up from concept to working solution. I was also the first person outside of Microsoft to try this offering out. This gave me the opportunity to test real world application at various clients using the Microsoft Load Test Service and provide real world feedback to the Microsoft product team. One of the most recent systems I tested using the Load Test Service has been an insurance quote generation engine. This insurance quote generation engine is,   hosted in Windows Azure expected to get quote requests from across the globe expected to handle 5 Million quote requests in a day (not clear how this load will be distributed across the day) There was no way, I could simulate such kind of load from on premise without standing up additional hardware. But Microsoft’s Cloud based Load Test service allowed me to test my key performance testing scenarios, i.e. Simulate expected Load, Endurance Testing, Threshold Testing and Testing for Latency. Simulating expected load: approach to devising a load pattern My approach to devising a load test pattern has been to run the test scenario with 1 user to figure out the response time. Then work out how many users are required to reach the target load. So, for example, to invoke 1 quote from the quote engine software takes 0.5 seconds. Now if you do the math,   1 quote request by 1 user = 0.5 seconds   quotes generated by 1 user in 24 hour = 1 * (((2 * 60) * 60) * 24) = 172,800   quotes generated by 30 users in 24 hours = 172,800 * 30 =  5,184,000 This was a very simple example, if your application requires more concurrent users to test scenario’s such as caching, etc then you can devise your own load pattern, some examples of load test patterns can be found here.  Endurance Testing To test for endurance, I loaded the quote generation engine with an expected fixed user load and ran the test for very long duration such as over 48 hours and observed the affect of the long running test on the Azure infrastructure. Currently Microsoft Load Test service does not support metrics from the machine under test. I used Azure diagnostics to begin with, but later started using Cerebrata Azure Diagnostics Manager to capture the metrics of the machine under test. Threshold Testing To figure out how much user load the application could cope with before falling on its belly, I opted to step load the quote generation engine by incrementing user load with different variations of incremental user load per minute till the application crashed out and forced an IIS reset. Testing for Latency Currently the Microsoft Load Test service does not support generating geographically distributed load, I however, deployed the insurance quote generation engine in different Azure data centres and ran the same set of performance tests to measure for latency. Because I could compare load test results from different runs by exporting the results to excel (this feature is provided out of the box right from Visual Studio 2010) I could see the different in response times. More resources on Microsoft Cloud based Load Test Service A few important links to get you started, Download Visual Studio Ultimate 2013 Preview Getting started guide for load testing using Team Foundation Service Troubleshooting guide for FAQs and known issues Team Foundation Service forum for questions and support Detailed demo and presentation (link to Tech-Ed session recording) Detailed demo and presentation (link to Build session recording) There a few limits on the usage of Microsoft Cloud based Load Test service that you can read about here. If you have any feedback on Microsoft Cloud based Load Test service, feel free to share it with the product team via the Visual Studio User Voice forum. I hope you found this useful. Thank you for taking the time out and reading this blog post. If you enjoyed the post, remember to subscribe to http://feeds.feedburner.com/TarunArora. Stay tuned!

  Read the article

< Previous Page | 198 199 200 201 202 203 204 205 206 207 208 209  | Next Page >