Analysis of user experience is typically done by taking a random sample of users, measuring their experiences and extracting a single number from that sample. In terms of web performance, the experience we need to measure is user perceived page load time, and the single number we need to extract depends on the distribution of measurements across the sample.
There are a few contenders for what the magic number should be. Do you use the mean, median, mode, or something else? How do you determine the correctness of this number or whether your sample size is large enough? Is one number sufficient?
This talk covers some of the statistics behind figuring out which numbers one should be looking at and how to go about extracting it from the sample.
C 04-internet of things - horizon watch trend report (client version) 28jan2015
This document is an internal IBM report on trends related to the Internet of Things (IoT) in 2015. It provides an overview of the IoT trend, lists key trends to watch in 2015, discusses what others are saying about the IoT, outlines the IoT ecosystem, and provides additional resources. The report predicts that the IoT will have major implications for businesses and result in new applications and services, and that security, standards, and managing big data will be significant challenges.
Attobahn is developing a new wireless network called the Quantum Speed Network that will provide ultra-fast internet speeds of up to 20 Gbps per user through a unique architecture of protonic switching nodes, nucleus switches, and V-Rover base stations. The network aims to address the exponential growth in mobile data usage and provide highly secure dedicated bandwidth to support technologies like virtual reality and the internet of things. Attobahn has filed patents on its breakthrough transmission technology and plans to generate revenue through network access fees and partnerships.
This document provides a summary of a presentation on addressing challenges in mobile application testing. It discusses how mobile application testing is different than traditional web testing due to factors like device fragmentation, new capabilities to test, and more network considerations. It also outlines what mobile testers need, including test automation, device cloud access, test planning and reporting tools, and the ability to test various parts of a mobile solution like the backend systems and network. The presentation was given by representatives from IBM and AT&T.
Vectorwise is an extremely fast database that enables quick decision making through real-time analytics. It is multiple times faster than other databases, with some customer queries seeing speed increases of 70x. This speed is due to its innovative vector processing approach. Customers report being able to reduce BI project timelines by 50% using Vectorwise due to its ease of use and lack of need for tuning. It also reduces infrastructure costs through requiring less hardware and IT resources.
MeasureWorks eFinancials - Best practices for a successfull mobile experienc...
Gebruikers van mobiel internet verwachten snelle transacties en betrouwbare sites en/of applicaties. Volgens recent onderzoek haakt meer dan 52% van de klanten af bij een slechte ervaring en overweegt daardoor geen gebruik meer te maken van een mobiele applicatie.
Nu mobiel internet een integraal onderdeel wordt van uw dienstverlening, en de verwachtingen van klanten toenemen, wordt het managen en monitoren van uw mobiele sites en applicaties een voorwaarde voor succes. Het niet tijdig identificeren van langzame, of erger, niet functionerende mobiele diensten zal onherroepelijk resulteren in verlies van klanten, omzet en uiteindelijk reputatie schade.
Aan de hand van praktijkvoorbeelden zullen we u laten zien:
* Wat de impact is van de adoptie van mobiel internet en groeiende klantverwachtingen op uw online dienstverlening
* Op welke wijze Mobiele Web Experience problemen kunnen worden herkend voordat klanten uw website verlaten
* Best practices voor het leveren van een kwalitatief uitstekende Mobile Web Experience
The document discusses the Internet of Things (IoT) and its potential. It describes IoT as the third wave of internet connectivity, following fixed and mobile internet. Basic IoT concepts are explained, such as how IoT connects physical devices to collect and share data. Statistics on current and predicted IoT usage are provided. Examples are given of how IoT can optimize different areas like transportation, healthcare, smart homes and more. The document also outlines the opportunities and challenges of IoT for Malaysia, including the need for IoT professionals and pioneers to help advance IoT.
This document discusses the rapid growth of internet video and adaptive rate technologies. It notes that video will account for 60% of consumer internet traffic by 2013, driven by growth in live streaming and TV services. It also highlights how mobile data traffic is growing even faster, reaching 3.6 exabytes per month by 2014 with 66% being mobile video. The document introduces adaptive rate technologies that allow video quality to adjust based on available bandwidth.
This document discusses Optinera's use of NoSQL tools to build a computer vision platform. It outlines Optinera's services, data needs including CRM, metrics, and computer vision, and solutions using a polyglot approach. It also describes Optinera's architecture with services, caches, search, and SwoopCV pods for computer vision workloads. The document concludes with discussing futures such as improving the CMS, metric processing, and a spoke/hub persistence model.
This document discusses opportunities for wireless network optimization. It notes that mobile data traffic is growing rapidly driven by new services and devices. This is putting pressure on network capacity and quality of experience. The document examines challenges in offering bandwidth at low cost, optimizing network performance, and migrating from legacy to IP networks. It argues that network optimization can help address these challenges by reducing costs, improving quality of experience, and freeing up funds for reinvestment while preparing networks for future growth. The document provides an overview of Alcatel-Lucent's wireless optimization services and their value in helping operators meet these challenges.
The document discusses the results of Forrester's evaluation of 11 enterprise business intelligence platform vendors. It finds that IBM Cognos, SAP BusinessObjects, Oracle, and SAS continue to lead, while Information Builders, Microsoft, and MicroStrategy joined them as Leaders. TIBCO Spotfire and Actuate maintained their Strong Performer status, and QlikTech and Panorama Software moved into the Strong Performer category based on improvements to their analytical capabilities. The evaluation assessed the vendors' current offerings, strategies, and market presences based on 145 criteria.
The Forrester Wave: Enterprise Business Intelligence Platforms, Q4 2010
The document discusses the results of Forrester's evaluation of 11 enterprise business intelligence platform vendors based on 145 criteria. It found that IBM Cognos, SAP BusinessObjects, and Oracle led as Leaders due to the completeness of their BI and overall information management functionality. Actuate and TIBCO Spotfire were Strong Performers for offering comparable BI functionality but relying more on partners for other information management capabilities. QlikTech and Panorama Software moved into the Strong Performers category based on improvements in their analytical capabilities.
The document discusses the results of Forrester's evaluation of 11 enterprise business intelligence platform vendors based on 145 criteria. It found that IBM Cognos, SAP BusinessObjects, and Oracle led as Leaders due to the completeness of their BI and overall information management functionality. Actuate and TIBCO Spotfire were Strong Performers for offering comparable BI functionality but relying more on partners for other information management capabilities. QlikTech and Panorama Software moved into the Strong Performers category based on improvements in their analytical capabilities.
The document discusses the web browser industry. It provides an overview of the industry structure and key players like Internet Explorer and Firefox. It analyzes factors like demographics of Indian internet users, usage patterns, and success factors for browsers. Porter's Five Forces model is applied, examining rivalry, barriers to entry, and other forces. The future of the industry is promising as internet access increases in India through various technologies and policies.
Sandvine Webinar – Making Cents of Internet Phenomena Through Network Busines...
To view the recorded version of the Sandvine webinar held at Computaris' 2 decade anniversary virtual event, please register here: http://webexpo.computaris.com/webinars/sandvine
The Best of Both Worlds - Combining Performance and Functional Mobile App Tes...
We co-hosted a webinar with Neotys to shed some lights on
- How to overcome the challenges in mobile app performance and functional testing
- How to gain granular and actionable insights to measure and improve your app user experience
- Best practices to get the mobile readiness for 2017 Holiday Shopping Season
- A brief demo of the integration between Neoload and Bitbar Testing
Data Pioneers - Roland Haeve (Atos Nederland) - Big data in organisaties
This document discusses big data and its growth. It notes that in 2000, 2 exabytes of new data were produced, while in 2011 1.8 zettabytes of new data were produced. By 2020, data production is expected to grow 40 times to 35 zettabytes. The traditional 3-4 V's of big data (volume, velocity, variety, veracity) are expanding to 5-7 V's with the addition of viscosity, virality, and value. Examples of big data use cases include sensor data from CERN and jet engines, social media data from Twitter, and transactional data from Walmart. Atos provides big data analytics solutions and has implemented projects for smart metering,
The IoT Food Chain – Picking the Right Dining Partner is Important with Dean ...
Download our special report, IoT Tech for the Manager: http://bit.ly/report1-slideshare
The IoT Food Chain – Picking the Right Dining Partner is Important as presented at the IoT Inc Business' fourteenth Meetup. See: http://www.iot-inc.com/internet-of-things-value-chain-meetup/
In our fourteenth Meetup we have Dean Freeman, Research VP at Gartner presenting “The IoT Food Chain – Picking the Right Dining Partner is Important”.
Presentation Abstract
The Internet of Things means many different things to different people. What is key about the IoT is there is a distinct food chain that runs from the silicon devices to the services and then back. The level of success you will have in the IoT is heavily dependent upon where you fit in the food chain, and if you have the capability to move up the chain or across the chain into different verticals. In this presentation we will explore the food chain, what is important and what steps need to be taken to succeed in the world of the IoT.
Improving D3 Performance with CANVAS and other Hacks
This document discusses techniques for improving the performance of D3 visualizations. It begins with an overview of D3 and some basic tutorials. It then describes issues with performance for force-directed layouts and edge-bundled layouts as the number of nodes and links increases. Solutions proposed include using canvas instead of SVG for rendering, reducing unnecessary calculations, and caching repeated drawing states. The document concludes that the number of DOM nodes has major performance implications and techniques like canvas can help when exact mouse interactions are not required.
Frontend Performance: Beginner to Expert to Crazy Person
There’s no such thing as fast enough. You can always make your website faster. This talk will show you how. The very first requirement of a great user experience is actually getting the bytes of that experience to the user before they they get tired and leave.In this talk we’ll start with the basics and get progressively insane. We’ll go over several frontend performance best practices, a few anti-patterns, the reasoning behind the rules, and how they’ve changed over the years. We’ll also look at some great tools to help you.
Frontend Performance: De débutant à Expert à Fou Furieux
Frontend Performance Beginner to Expert to Crazy Person
The very first requirement of a great user experience is actually getting the bytes of that experience to the user before they they get tired and leave.
In this talk we'll start with the basics and get progressively insane. We'll go over several frontend performance best practices, a few anti-patterns, the reasoning behind the rules, and how they've changed over the years. We'll also look at some great tools to help you.
La performance front-end de débutant, à expert, à fou furieux !
La toute première condition nécessaire à une bonne expérience utilisateur est de pouvoir obtenir les octets de cette expérience avant que l'utilisateur ne se lasse et parte.
Nous débuterons cette conférence avec les bases pour progressivement devenir démentiel. Nous aborderons plusieurs des meilleurs pratiques de la performance front-end, quelques anti-patterns à éviter, le raisonnement derrière les règles, et comment ces dernières ont changé au fil des ans. Nous regarderons d'un peu plus près quelques très bon outils qui peuvent vous aider.
The document outlines steps for front-end performance optimization, beginning with basic techniques like caching, compression and domain sharing and progressing to more advanced strategies involving preloading, parallel downloads, and predicting response times. It was presented by Philip Tellis at WebPerfDays New York and includes references for further reading on topics like CDNs, TCP tuning, and the page visibility API.
RUM isn’t just for page level metrics anymore. Thanks to modern browser updates and new techniques we can collect real user data at the object level, finding slow page components and keeping third parties honest.
In this talk we will show you how to use Resource Timing, User Timing, and other browser tricks to time the most important components in your page. We’ll also share recipes for several of the web’s most popular third parties. This will give you a head start on measuring object level performance on your own site.
Frontend Performance: Beginner to Expert to Crazy Person (San Diego Web Perf ...
The document outlines steps web performance experts take to optimize frontend performance, moving from beginner to advanced techniques. It starts with basic optimizations like enabling gzip, caching, and image optimization. It then discusses more advanced strategies like using a CDN, splitting JavaScript, auditing CSS, and parallelizing downloads. Finally it discusses very advanced techniques like pre-loading assets, detecting broken Accept-Encoding headers, and understanding how to optimize for HTTP/2. The document provides references for further information on each topic.
Frontend Performance: Beginner to Expert to Crazy Person
The document discusses front-end web performance optimization from beginner to expert levels. At the beginner level, it recommends starting with basic optimizations like measuring performance, enabling gzip compression, optimizing images, and caching. At the expert level, it discusses more advanced techniques like using a CDN, splitting JavaScript files, auditing CSS, and flushing content early. Finally, it outlines "crazy" optimizations like pre-loading assets, post-load fetching, and understanding round-trip network latency.
Frontend Performance: Beginner to Expert to Crazy Person
Boston Web Performance Meetup, April 22, 2014
The very first requirement of a great user experience is actually getting the bytes of that experience to the user before they they get fed up and leave. In this talk we'll start with the basics and get progressively insane. We'll go over several front-end performance best practices, a few anti-patterns, the reasoning behind the rules, and how they've changed over the years. We'll also look at some great tools to help you.
Schedule: 6:30, pizza
7:15: talk
Frontend Performance: Beginner to Expert to Crazy Person
The very first requirement of a great user experience is actually getting the bytes of that experience to the user before they they get fed up and leave.
In this talk we'll start with the basics and get progressively insane. We'll go over several frontend performance best practices, a few anti-patterns, the reasoning behind the rules, and how they've changed over the years. We'll also look at some great tools to help you.
The document appears to be a presentation on measuring real user experiences using Real User Monitoring (RUM) and analyzing the data. It discusses using RUM tools like Boomerang to collect data on user behavior and performance in real-time. The presentation then examines specific metrics collected like user patience, cache behavior, and how quickly new software versions are distributed based on the RUM data.
Improving 3rd Party Script Performance With IFrames
This document discusses using <IFRAME> tags to improve the performance of third party scripts. It describes how third party scripts normally block page loading and proposes using an iframe to load scripts asynchronously in parallel without blocking. It provides code for creating an iframe targeted to load scripts, handling cross-domain issues, and modifying the Method Queue Pattern to support iframes. The approach allows third party scripts to load without blocking the main page load.
The document discusses Boomerang, an open source tool for measuring real user performance on websites. It measures load times, bandwidth usage, latency and other metrics. Additional functionality can be added through plugins. The presentation encourages developers to use Boomerang to analyze user behavior, identify performance issues, and continuously improve sites based on real user data. It provides several examples of insights that can be gained, such as how performance varies by country, browser, and internet connection speed.
Abusing JavaScript to measure Web Performance, or, "how does boomerang work?"
The document is a presentation about abusing JavaScript to measure web performance. It discusses using JavaScript to measure network latency, TCP handshake time, network throughput, DNS lookup time, IPv6 support and latency, and other performance metrics. It provides code examples for measuring each metric in JavaScript and notes challenges to consider. The presentation encourages the use of the open source Boomerang library for accurate performance measurement.
While building boomerang, we developed many interesting methods to measure network performance characteristics using JavaScript running in the browser. While the W3C's NavigationTiming API provides access to many performance metrics, there's far more you can get at with some creative tweaking and analysis of how the browser reacts to certain requests.
In this talk, I'll go into the details of how boomerang works to measure network throughput, latency, TCP connect time, DNS time and IPv6 connectivity. I'll also touch upon some of the other performance related browser APIs we use to gather useful information. I will NOT be covering the W3C Navigation Timing API since that's been covered by Alois Reitbauer in a previous Boston Web Perf talk.
The document discusses analyzing real user monitoring (RUM) data to gain insights into website performance and user behavior. It describes building plugins to collect navigation and timing data from browsers. Various statistical techniques for analyzing the data are covered, including log-normal distributions, filtering outliers, sampling, and correlating metrics like page load time and bounce rates. The analysis of an example 8 million page dataset suggests very fast or slow page loads are associated with higher bounce rates, and thresholds for user-unfriendly performance are proposed based on bounce rates exceeding 50%.
This document contains slides from a presentation about using JavaScript to analyze network performance. It discusses how to measure latency, TCP handshake time, network throughput, DNS lookup time, IPv6 support and latency, and private network scanning using JavaScript. Code examples are provided for measuring each of these network metrics by making image requests and timing the responses. The presentation emphasizes that accurately measuring network throughput requires requesting resources of different sizes and accounting for TCP slow start. It also notes some challenges around caching and geo-located DNS results.
A Node.JS bag of goodies for analyzing Web Traffic
This document is a presentation about analyzing web traffic using Node.js modules. It introduces Node.js and the npm package manager. It then discusses modules for parsing HTTP logs, including parsing user agents, handling IP addresses, geolocation, and date formatting. It also covers modules for statistical analysis like fast-stats, gauss, and statsd. The presentation provides code examples for using these modules and takes questions at the end.
The document discusses input validation and output encoding to prevent vulnerabilities like XSS and SQL injection. It provides examples of how unexpected input can enable attacks, like special characters or invalid data types being passed to endpoints and rendered unencoded. The key lessons are that input validation is needed to receive clean, expected data, while output encoding is crucial to prevent exploits when displaying data to users. Both techniques are important defenses that address different but related issues.
Messing with JavaScript and the DOM to measure network characteristics
This document discusses using JavaScript to analyze network performance. It covers measuring latency, TCP handshake time, DNS lookup time, network throughput, and IPv6 support. The document provides code examples for measuring each of these metrics using JavaScript and analyzing image load times. It notes that network conditions vary and accurate measurements require statistical analysis over many samples.
Measuring the Impact of Network Latency at Twitter
Widya Salim and Victor Ma will outline the causal impact analysis, framework, and key learnings used to quantify the impact of reducing Twitter's network latency.
Sustainability requires ingenuity and stewardship. Did you know Pigging Solutions pigging systems help you achieve your sustainable manufacturing goals AND provide rapid return on investment.
How? Our systems recover over 99% of product in transfer piping. Recovering trapped product from transfer lines that would otherwise become flush-waste, means you can increase batch yields and eliminate flush waste. From raw materials to finished product, if you can pump it, we can pig it.
YOUR RELIABLE WEB DESIGN & DEVELOPMENT TEAM — FOR LASTING SUCCESS
WPRiders is a web development company specialized in WordPress and WooCommerce websites and plugins for customers around the world. The company is headquartered in Bucharest, Romania, but our team members are located all over the world. Our customers are primarily from the US and Western Europe, but we have clients from Australia, Canada and other areas as well.
Some facts about WPRiders and why we are one of the best firms around:
More than 700 five-star reviews! You can check them here.
1500 WordPress projects delivered.
We respond 80% faster than other firms! Data provided by Freshdesk.
We’ve been in business since 2015.
We are located in 7 countries and have 22 team members.
With so many projects delivered, our team knows what works and what doesn’t when it comes to WordPress and WooCommerce.
Our team members are:
- highly experienced developers (employees & contractors with 5 -10+ years of experience),
- great designers with an eye for UX/UI with 10+ years of experience
- project managers with development background who speak both tech and non-tech
- QA specialists
- Conversion Rate Optimisation - CRO experts
They are all working together to provide you with the best possible service. We are passionate about WordPress, and we love creating custom solutions that help our clients achieve their goals.
At WPRiders, we are committed to building long-term relationships with our clients. We believe in accountability, in doing the right thing, as well as in transparency and open communication. You can read more about WPRiders on the About us page.
These fighter aircraft have uses outside of traditional combat situations. They are essential in defending India's territorial integrity, averting dangers, and delivering aid to those in need during natural calamities. Additionally, the IAF improves its interoperability and fortifies international military alliances by working together and conducting joint exercises with other air forces.
Best Practices for Effectively Running dbt in Airflow.pdf
As a popular open-source library for analytics engineering, dbt is often used in combination with Airflow. Orchestrating and executing dbt models as DAGs ensures an additional layer of control over tasks, observability, and provides a reliable, scalable environment to run dbt models.
This webinar will cover a step-by-step guide to Cosmos, an open source package from Astronomer that helps you easily run your dbt Core projects as Airflow DAGs and Task Groups, all with just a few lines of code. We’ll walk through:
- Standard ways of running dbt (and when to utilize other methods)
- How Cosmos can be used to run and visualize your dbt projects in Airflow
- Common challenges and how to address them, including performance, dependency conflicts, and more
- How running dbt projects in Airflow helps with cost optimization
Webinar given on 9 July 2024
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Are you interested in dipping your toes in the cloud native observability waters, but as an engineer you are not sure where to get started with tracing problems through your microservices and application landscapes on Kubernetes? Then this is the session for you, where we take you on your first steps in an active open-source project that offers a buffet of languages, challenges, and opportunities for getting started with telemetry data.
The project is called openTelemetry, but before diving into the specifics, we’ll start with de-mystifying key concepts and terms such as observability, telemetry, instrumentation, cardinality, percentile to lay a foundation. After understanding the nuts and bolts of observability and distributed traces, we’ll explore the openTelemetry community; its Special Interest Groups (SIGs), repositories, and how to become not only an end-user, but possibly a contributor.We will wrap up with an overview of the components in this project, such as the Collector, the OpenTelemetry protocol (OTLP), its APIs, and its SDKs.
Attendees will leave with an understanding of key observability concepts, become grounded in distributed tracing terminology, be aware of the components of openTelemetry, and know how to take their first steps to an open-source contribution!
Key Takeaways: Open source, vendor neutral instrumentation is an exciting new reality as the industry standardizes on openTelemetry for observability. OpenTelemetry is on a mission to enable effective observability by making high-quality, portable telemetry ubiquitous. The world of observability and monitoring today has a steep learning curve and in order to achieve ubiquity, the project would benefit from growing our contributor community.
PublicInsite is a leading web analytics and SEO firm with offices in Boston and Ottawa. They help clients measure their online marketing performance through analytics tools like Google Analytics. They specialize in measuring public sector websites and ensuring metrics are aligned with goals. PublicInsite collects data on website traffic from log files on web servers and page tags to track user behavior and identify trends to improve conversion and retention.
- The document discusses mobile analytics and strategies for tracking mobile traffic. It notes rapid growth in smartphones and changing mobile internet platforms.
- Key challenges for web analytics on mobile include lack of cookies, referrers, and JavaScript support on many platforms. Custom pixel-based solutions are recommended.
- The company implemented a custom pixel-based solution for their mobile websites and apps to track usage across platforms without JavaScript.
- Looking ahead, location services and optimized smartphone sites are important, while SMS and WAP may decline as smartphones grow. Testing solutions on various devices is also advised.
C 04-internet of things - horizon watch trend report (client version) 28jan2015Diane Shimmon
This document is an internal IBM report on trends related to the Internet of Things (IoT) in 2015. It provides an overview of the IoT trend, lists key trends to watch in 2015, discusses what others are saying about the IoT, outlines the IoT ecosystem, and provides additional resources. The report predicts that the IoT will have major implications for businesses and result in new applications and services, and that security, standards, and managing big data will be significant challenges.
Attobahn is developing a new wireless network called the Quantum Speed Network that will provide ultra-fast internet speeds of up to 20 Gbps per user through a unique architecture of protonic switching nodes, nucleus switches, and V-Rover base stations. The network aims to address the exponential growth in mobile data usage and provide highly secure dedicated bandwidth to support technologies like virtual reality and the internet of things. Attobahn has filed patents on its breakthrough transmission technology and plans to generate revenue through network access fees and partnerships.
This document provides a summary of a presentation on addressing challenges in mobile application testing. It discusses how mobile application testing is different than traditional web testing due to factors like device fragmentation, new capabilities to test, and more network considerations. It also outlines what mobile testers need, including test automation, device cloud access, test planning and reporting tools, and the ability to test various parts of a mobile solution like the backend systems and network. The presentation was given by representatives from IBM and AT&T.
Vectorwise is an extremely fast database that enables quick decision making through real-time analytics. It is multiple times faster than other databases, with some customer queries seeing speed increases of 70x. This speed is due to its innovative vector processing approach. Customers report being able to reduce BI project timelines by 50% using Vectorwise due to its ease of use and lack of need for tuning. It also reduces infrastructure costs through requiring less hardware and IT resources.
MeasureWorks eFinancials - Best practices for a successfull mobile experienc...MeasureWorks
Gebruikers van mobiel internet verwachten snelle transacties en betrouwbare sites en/of applicaties. Volgens recent onderzoek haakt meer dan 52% van de klanten af bij een slechte ervaring en overweegt daardoor geen gebruik meer te maken van een mobiele applicatie.
Nu mobiel internet een integraal onderdeel wordt van uw dienstverlening, en de verwachtingen van klanten toenemen, wordt het managen en monitoren van uw mobiele sites en applicaties een voorwaarde voor succes. Het niet tijdig identificeren van langzame, of erger, niet functionerende mobiele diensten zal onherroepelijk resulteren in verlies van klanten, omzet en uiteindelijk reputatie schade.
Aan de hand van praktijkvoorbeelden zullen we u laten zien:
* Wat de impact is van de adoptie van mobiel internet en groeiende klantverwachtingen op uw online dienstverlening
* Op welke wijze Mobiele Web Experience problemen kunnen worden herkend voordat klanten uw website verlaten
* Best practices voor het leveren van een kwalitatief uitstekende Mobile Web Experience
The document discusses the Internet of Things (IoT) and its potential. It describes IoT as the third wave of internet connectivity, following fixed and mobile internet. Basic IoT concepts are explained, such as how IoT connects physical devices to collect and share data. Statistics on current and predicted IoT usage are provided. Examples are given of how IoT can optimize different areas like transportation, healthcare, smart homes and more. The document also outlines the opportunities and challenges of IoT for Malaysia, including the need for IoT professionals and pioneers to help advance IoT.
This document discusses the rapid growth of internet video and adaptive rate technologies. It notes that video will account for 60% of consumer internet traffic by 2013, driven by growth in live streaming and TV services. It also highlights how mobile data traffic is growing even faster, reaching 3.6 exabytes per month by 2014 with 66% being mobile video. The document introduces adaptive rate technologies that allow video quality to adjust based on available bandwidth.
This document discusses Optinera's use of NoSQL tools to build a computer vision platform. It outlines Optinera's services, data needs including CRM, metrics, and computer vision, and solutions using a polyglot approach. It also describes Optinera's architecture with services, caches, search, and SwoopCV pods for computer vision workloads. The document concludes with discussing futures such as improving the CMS, metric processing, and a spoke/hub persistence model.
This document discusses opportunities for wireless network optimization. It notes that mobile data traffic is growing rapidly driven by new services and devices. This is putting pressure on network capacity and quality of experience. The document examines challenges in offering bandwidth at low cost, optimizing network performance, and migrating from legacy to IP networks. It argues that network optimization can help address these challenges by reducing costs, improving quality of experience, and freeing up funds for reinvestment while preparing networks for future growth. The document provides an overview of Alcatel-Lucent's wireless optimization services and their value in helping operators meet these challenges.
The document discusses the results of Forrester's evaluation of 11 enterprise business intelligence platform vendors. It finds that IBM Cognos, SAP BusinessObjects, Oracle, and SAS continue to lead, while Information Builders, Microsoft, and MicroStrategy joined them as Leaders. TIBCO Spotfire and Actuate maintained their Strong Performer status, and QlikTech and Panorama Software moved into the Strong Performer category based on improvements to their analytical capabilities. The evaluation assessed the vendors' current offerings, strategies, and market presences based on 145 criteria.
The Forrester Wave: Enterprise Business Intelligence Platforms, Q4 2010telcobiaas
The document discusses the results of Forrester's evaluation of 11 enterprise business intelligence platform vendors based on 145 criteria. It found that IBM Cognos, SAP BusinessObjects, and Oracle led as Leaders due to the completeness of their BI and overall information management functionality. Actuate and TIBCO Spotfire were Strong Performers for offering comparable BI functionality but relying more on partners for other information management capabilities. QlikTech and Panorama Software moved into the Strong Performers category based on improvements in their analytical capabilities.
Forrester wave business intelligence platformsdivjeev
The document discusses the results of Forrester's evaluation of 11 enterprise business intelligence platform vendors based on 145 criteria. It found that IBM Cognos, SAP BusinessObjects, and Oracle led as Leaders due to the completeness of their BI and overall information management functionality. Actuate and TIBCO Spotfire were Strong Performers for offering comparable BI functionality but relying more on partners for other information management capabilities. QlikTech and Panorama Software moved into the Strong Performers category based on improvements in their analytical capabilities.
The document discusses the web browser industry. It provides an overview of the industry structure and key players like Internet Explorer and Firefox. It analyzes factors like demographics of Indian internet users, usage patterns, and success factors for browsers. Porter's Five Forces model is applied, examining rivalry, barriers to entry, and other forces. The future of the industry is promising as internet access increases in India through various technologies and policies.
Sandvine Webinar – Making Cents of Internet Phenomena Through Network Busines...Computaris
To view the recorded version of the Sandvine webinar held at Computaris' 2 decade anniversary virtual event, please register here: http://webexpo.computaris.com/webinars/sandvine
The Best of Both Worlds - Combining Performance and Functional Mobile App Tes...Bitbar
We co-hosted a webinar with Neotys to shed some lights on
- How to overcome the challenges in mobile app performance and functional testing
- How to gain granular and actionable insights to measure and improve your app user experience
- Best practices to get the mobile readiness for 2017 Holiday Shopping Season
- A brief demo of the integration between Neoload and Bitbar Testing
Data Pioneers - Roland Haeve (Atos Nederland) - Big data in organisatiesMultiscope
This document discusses big data and its growth. It notes that in 2000, 2 exabytes of new data were produced, while in 2011 1.8 zettabytes of new data were produced. By 2020, data production is expected to grow 40 times to 35 zettabytes. The traditional 3-4 V's of big data (volume, velocity, variety, veracity) are expanding to 5-7 V's with the addition of viscosity, virality, and value. Examples of big data use cases include sensor data from CERN and jet engines, social media data from Twitter, and transactional data from Walmart. Atos provides big data analytics solutions and has implemented projects for smart metering,
The IoT Food Chain – Picking the Right Dining Partner is Important with Dean ...gogo6
Download our special report, IoT Tech for the Manager: http://bit.ly/report1-slideshare
The IoT Food Chain – Picking the Right Dining Partner is Important as presented at the IoT Inc Business' fourteenth Meetup. See: http://www.iot-inc.com/internet-of-things-value-chain-meetup/
In our fourteenth Meetup we have Dean Freeman, Research VP at Gartner presenting “The IoT Food Chain – Picking the Right Dining Partner is Important”.
Presentation Abstract
The Internet of Things means many different things to different people. What is key about the IoT is there is a distinct food chain that runs from the silicon devices to the services and then back. The level of success you will have in the IoT is heavily dependent upon where you fit in the food chain, and if you have the capability to move up the chain or across the chain into different verticals. In this presentation we will explore the food chain, what is important and what steps need to be taken to succeed in the world of the IoT.
Improving D3 Performance with CANVAS and other HacksPhilip Tellis
This document discusses techniques for improving the performance of D3 visualizations. It begins with an overview of D3 and some basic tutorials. It then describes issues with performance for force-directed layouts and edge-bundled layouts as the number of nodes and links increases. Solutions proposed include using canvas instead of SVG for rendering, reducing unnecessary calculations, and caching repeated drawing states. The document concludes that the number of DOM nodes has major performance implications and techniques like canvas can help when exact mouse interactions are not required.
Frontend Performance: Beginner to Expert to Crazy PersonPhilip Tellis
There’s no such thing as fast enough. You can always make your website faster. This talk will show you how. The very first requirement of a great user experience is actually getting the bytes of that experience to the user before they they get tired and leave.In this talk we’ll start with the basics and get progressively insane. We’ll go over several frontend performance best practices, a few anti-patterns, the reasoning behind the rules, and how they’ve changed over the years. We’ll also look at some great tools to help you.
Frontend Performance: De débutant à Expert à Fou FurieuxPhilip Tellis
Frontend Performance Beginner to Expert to Crazy Person
The very first requirement of a great user experience is actually getting the bytes of that experience to the user before they they get tired and leave.
In this talk we'll start with the basics and get progressively insane. We'll go over several frontend performance best practices, a few anti-patterns, the reasoning behind the rules, and how they've changed over the years. We'll also look at some great tools to help you.
La performance front-end de débutant, à expert, à fou furieux !
La toute première condition nécessaire à une bonne expérience utilisateur est de pouvoir obtenir les octets de cette expérience avant que l'utilisateur ne se lasse et parte.
Nous débuterons cette conférence avec les bases pour progressivement devenir démentiel. Nous aborderons plusieurs des meilleurs pratiques de la performance front-end, quelques anti-patterns à éviter, le raisonnement derrière les règles, et comment ces dernières ont changé au fil des ans. Nous regarderons d'un peu plus près quelques très bon outils qui peuvent vous aider.
Frontend Performance: Expert to Crazy PersonPhilip Tellis
The document outlines steps for front-end performance optimization, beginning with basic techniques like caching, compression and domain sharing and progressing to more advanced strategies involving preloading, parallel downloads, and predicting response times. It was presented by Philip Tellis at WebPerfDays New York and includes references for further reading on topics like CDNs, TCP tuning, and the page visibility API.
RUM isn’t just for page level metrics anymore. Thanks to modern browser updates and new techniques we can collect real user data at the object level, finding slow page components and keeping third parties honest.
In this talk we will show you how to use Resource Timing, User Timing, and other browser tricks to time the most important components in your page. We’ll also share recipes for several of the web’s most popular third parties. This will give you a head start on measuring object level performance on your own site.
Frontend Performance: Beginner to Expert to Crazy Person (San Diego Web Perf ...Philip Tellis
The document outlines steps web performance experts take to optimize frontend performance, moving from beginner to advanced techniques. It starts with basic optimizations like enabling gzip, caching, and image optimization. It then discusses more advanced strategies like using a CDN, splitting JavaScript, auditing CSS, and parallelizing downloads. Finally it discusses very advanced techniques like pre-loading assets, detecting broken Accept-Encoding headers, and understanding how to optimize for HTTP/2. The document provides references for further information on each topic.
Frontend Performance: Beginner to Expert to Crazy PersonPhilip Tellis
The document discusses front-end web performance optimization from beginner to expert levels. At the beginner level, it recommends starting with basic optimizations like measuring performance, enabling gzip compression, optimizing images, and caching. At the expert level, it discusses more advanced techniques like using a CDN, splitting JavaScript files, auditing CSS, and flushing content early. Finally, it outlines "crazy" optimizations like pre-loading assets, post-load fetching, and understanding round-trip network latency.
Frontend Performance: Beginner to Expert to Crazy PersonPhilip Tellis
Boston Web Performance Meetup, April 22, 2014
The very first requirement of a great user experience is actually getting the bytes of that experience to the user before they they get fed up and leave. In this talk we'll start with the basics and get progressively insane. We'll go over several front-end performance best practices, a few anti-patterns, the reasoning behind the rules, and how they've changed over the years. We'll also look at some great tools to help you.
Schedule: 6:30, pizza
7:15: talk
Frontend Performance: Beginner to Expert to Crazy PersonPhilip Tellis
The very first requirement of a great user experience is actually getting the bytes of that experience to the user before they they get fed up and leave.
In this talk we'll start with the basics and get progressively insane. We'll go over several frontend performance best practices, a few anti-patterns, the reasoning behind the rules, and how they've changed over the years. We'll also look at some great tools to help you.
The document appears to be a presentation on measuring real user experiences using Real User Monitoring (RUM) and analyzing the data. It discusses using RUM tools like Boomerang to collect data on user behavior and performance in real-time. The presentation then examines specific metrics collected like user patience, cache behavior, and how quickly new software versions are distributed based on the RUM data.
Improving 3rd Party Script Performance With IFramesPhilip Tellis
This document discusses using <IFRAME> tags to improve the performance of third party scripts. It describes how third party scripts normally block page loading and proposes using an iframe to load scripts asynchronously in parallel without blocking. It provides code for creating an iframe targeted to load scripts, handling cross-domain issues, and modifying the Method Queue Pattern to support iframes. The approach allows third party scripts to load without blocking the main page load.
The document discusses Boomerang, an open source tool for measuring real user performance on websites. It measures load times, bandwidth usage, latency and other metrics. Additional functionality can be added through plugins. The presentation encourages developers to use Boomerang to analyze user behavior, identify performance issues, and continuously improve sites based on real user data. It provides several examples of insights that can be gained, such as how performance varies by country, browser, and internet connection speed.
Abusing JavaScript to measure Web Performance, or, "how does boomerang work?"Philip Tellis
The document is a presentation about abusing JavaScript to measure web performance. It discusses using JavaScript to measure network latency, TCP handshake time, network throughput, DNS lookup time, IPv6 support and latency, and other performance metrics. It provides code examples for measuring each metric in JavaScript and notes challenges to consider. The presentation encourages the use of the open source Boomerang library for accurate performance measurement.
Abusing JavaScript to Measure Web PerformancePhilip Tellis
While building boomerang, we developed many interesting methods to measure network performance characteristics using JavaScript running in the browser. While the W3C's NavigationTiming API provides access to many performance metrics, there's far more you can get at with some creative tweaking and analysis of how the browser reacts to certain requests.
In this talk, I'll go into the details of how boomerang works to measure network throughput, latency, TCP connect time, DNS time and IPv6 connectivity. I'll also touch upon some of the other performance related browser APIs we use to gather useful information. I will NOT be covering the W3C Navigation Timing API since that's been covered by Alois Reitbauer in a previous Boston Web Perf talk.
The document discusses analyzing real user monitoring (RUM) data to gain insights into website performance and user behavior. It describes building plugins to collect navigation and timing data from browsers. Various statistical techniques for analyzing the data are covered, including log-normal distributions, filtering outliers, sampling, and correlating metrics like page load time and bounce rates. The analysis of an example 8 million page dataset suggests very fast or slow page loads are associated with higher bounce rates, and thresholds for user-unfriendly performance are proposed based on bounce rates exceeding 50%.
Analysing network characteristics with JavaScriptPhilip Tellis
This document contains slides from a presentation about using JavaScript to analyze network performance. It discusses how to measure latency, TCP handshake time, network throughput, DNS lookup time, IPv6 support and latency, and private network scanning using JavaScript. Code examples are provided for measuring each of these network metrics by making image requests and timing the responses. The presentation emphasizes that accurately measuring network throughput requires requesting resources of different sizes and accounting for TCP slow start. It also notes some challenges around caching and geo-located DNS results.
A Node.JS bag of goodies for analyzing Web TrafficPhilip Tellis
This document is a presentation about analyzing web traffic using Node.js modules. It introduces Node.js and the npm package manager. It then discusses modules for parsing HTTP logs, including parsing user agents, handling IP addresses, geolocation, and date formatting. It also covers modules for statistical analysis like fast-stats, gauss, and statsd. The presentation provides code examples for using these modules and takes questions at the end.
The document discusses input validation and output encoding to prevent vulnerabilities like XSS and SQL injection. It provides examples of how unexpected input can enable attacks, like special characters or invalid data types being passed to endpoints and rendered unencoded. The key lessons are that input validation is needed to receive clean, expected data, while output encoding is crucial to prevent exploits when displaying data to users. Both techniques are important defenses that address different but related issues.
Messing with JavaScript and the DOM to measure network characteristicsPhilip Tellis
This document discusses using JavaScript to analyze network performance. It covers measuring latency, TCP handshake time, DNS lookup time, network throughput, and IPv6 support. The document provides code examples for measuring each of these metrics using JavaScript and analyzing image load times. It notes that network conditions vary and accurate measurements require statistical analysis over many samples.
Measuring the Impact of Network Latency at TwitterScyllaDB
Widya Salim and Victor Ma will outline the causal impact analysis, framework, and key learnings used to quantify the impact of reducing Twitter's network latency.
Sustainability requires ingenuity and stewardship. Did you know Pigging Solutions pigging systems help you achieve your sustainable manufacturing goals AND provide rapid return on investment.
How? Our systems recover over 99% of product in transfer piping. Recovering trapped product from transfer lines that would otherwise become flush-waste, means you can increase batch yields and eliminate flush waste. From raw materials to finished product, if you can pump it, we can pig it.
YOUR RELIABLE WEB DESIGN & DEVELOPMENT TEAM — FOR LASTING SUCCESS
WPRiders is a web development company specialized in WordPress and WooCommerce websites and plugins for customers around the world. The company is headquartered in Bucharest, Romania, but our team members are located all over the world. Our customers are primarily from the US and Western Europe, but we have clients from Australia, Canada and other areas as well.
Some facts about WPRiders and why we are one of the best firms around:
More than 700 five-star reviews! You can check them here.
1500 WordPress projects delivered.
We respond 80% faster than other firms! Data provided by Freshdesk.
We’ve been in business since 2015.
We are located in 7 countries and have 22 team members.
With so many projects delivered, our team knows what works and what doesn’t when it comes to WordPress and WooCommerce.
Our team members are:
- highly experienced developers (employees & contractors with 5 -10+ years of experience),
- great designers with an eye for UX/UI with 10+ years of experience
- project managers with development background who speak both tech and non-tech
- QA specialists
- Conversion Rate Optimisation - CRO experts
They are all working together to provide you with the best possible service. We are passionate about WordPress, and we love creating custom solutions that help our clients achieve their goals.
At WPRiders, we are committed to building long-term relationships with our clients. We believe in accountability, in doing the right thing, as well as in transparency and open communication. You can read more about WPRiders on the About us page.
INDIAN AIR FORCE FIGHTER PLANES LIST.pdfjackson110191
These fighter aircraft have uses outside of traditional combat situations. They are essential in defending India's territorial integrity, averting dangers, and delivering aid to those in need during natural calamities. Additionally, the IAF improves its interoperability and fortifies international military alliances by working together and conducting joint exercises with other air forces.
Best Practices for Effectively Running dbt in Airflow.pdfTatiana Al-Chueyr
As a popular open-source library for analytics engineering, dbt is often used in combination with Airflow. Orchestrating and executing dbt models as DAGs ensures an additional layer of control over tasks, observability, and provides a reliable, scalable environment to run dbt models.
This webinar will cover a step-by-step guide to Cosmos, an open source package from Astronomer that helps you easily run your dbt Core projects as Airflow DAGs and Task Groups, all with just a few lines of code. We’ll walk through:
- Standard ways of running dbt (and when to utilize other methods)
- How Cosmos can be used to run and visualize your dbt projects in Airflow
- Common challenges and how to address them, including performance, dependency conflicts, and more
- How running dbt projects in Airflow helps with cost optimization
Webinar given on 9 July 2024
Choose our Linux Web Hosting for a seamless and successful online presencerajancomputerfbd
Our Linux Web Hosting plans offer unbeatable performance, security, and scalability, ensuring your website runs smoothly and efficiently.
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Are you interested in dipping your toes in the cloud native observability waters, but as an engineer you are not sure where to get started with tracing problems through your microservices and application landscapes on Kubernetes? Then this is the session for you, where we take you on your first steps in an active open-source project that offers a buffet of languages, challenges, and opportunities for getting started with telemetry data.
The project is called openTelemetry, but before diving into the specifics, we’ll start with de-mystifying key concepts and terms such as observability, telemetry, instrumentation, cardinality, percentile to lay a foundation. After understanding the nuts and bolts of observability and distributed traces, we’ll explore the openTelemetry community; its Special Interest Groups (SIGs), repositories, and how to become not only an end-user, but possibly a contributor.We will wrap up with an overview of the components in this project, such as the Collector, the OpenTelemetry protocol (OTLP), its APIs, and its SDKs.
Attendees will leave with an understanding of key observability concepts, become grounded in distributed tracing terminology, be aware of the components of openTelemetry, and know how to take their first steps to an open-source contribution!
Key Takeaways: Open source, vendor neutral instrumentation is an exciting new reality as the industry standardizes on openTelemetry for observability. OpenTelemetry is on a mission to enable effective observability by making high-quality, portable telemetry ubiquitous. The world of observability and monitoring today has a steep learning curve and in order to achieve ubiquity, the project would benefit from growing our contributor community.
Transcript: Details of description part II: Describing images in practice - T...BookNet Canada
This presentation explores the practical application of image description techniques. Familiar guidelines will be demonstrated in practice, and descriptions will be developed “live”! If you have learned a lot about the theory of image description techniques but want to feel more confident putting them into practice, this is the presentation for you. There will be useful, actionable information for everyone, whether you are working with authors, colleagues, alone, or leveraging AI as a collaborator.
Link to presentation recording and slides: https://bnctechforum.ca/sessions/details-of-description-part-ii-describing-images-in-practice/
Presented by BookNet Canada on June 25, 2024, with support from the Department of Canadian Heritage.
Understanding Insider Security Threats: Types, Examples, Effects, and Mitigat...Bert Blevins
Today’s digitally connected world presents a wide range of security challenges for enterprises. Insider security threats are particularly noteworthy because they have the potential to cause significant harm. Unlike external threats, insider risks originate from within the company, making them more subtle and challenging to identify. This blog aims to provide a comprehensive understanding of insider security threats, including their types, examples, effects, and mitigation techniques.
Implementations of Fused Deposition Modeling in real worldEmerging Tech
The presentation showcases the diverse real-world applications of Fused Deposition Modeling (FDM) across multiple industries:
1. **Manufacturing**: FDM is utilized in manufacturing for rapid prototyping, creating custom tools and fixtures, and producing functional end-use parts. Companies leverage its cost-effectiveness and flexibility to streamline production processes.
2. **Medical**: In the medical field, FDM is used to create patient-specific anatomical models, surgical guides, and prosthetics. Its ability to produce precise and biocompatible parts supports advancements in personalized healthcare solutions.
3. **Education**: FDM plays a crucial role in education by enabling students to learn about design and engineering through hands-on 3D printing projects. It promotes innovation and practical skill development in STEM disciplines.
4. **Science**: Researchers use FDM to prototype equipment for scientific experiments, build custom laboratory tools, and create models for visualization and testing purposes. It facilitates rapid iteration and customization in scientific endeavors.
5. **Automotive**: Automotive manufacturers employ FDM for prototyping vehicle components, tooling for assembly lines, and customized parts. It speeds up the design validation process and enhances efficiency in automotive engineering.
6. **Consumer Electronics**: FDM is utilized in consumer electronics for designing and prototyping product enclosures, casings, and internal components. It enables rapid iteration and customization to meet evolving consumer demands.
7. **Robotics**: Robotics engineers leverage FDM to prototype robot parts, create lightweight and durable components, and customize robot designs for specific applications. It supports innovation and optimization in robotic systems.
8. **Aerospace**: In aerospace, FDM is used to manufacture lightweight parts, complex geometries, and prototypes of aircraft components. It contributes to cost reduction, faster production cycles, and weight savings in aerospace engineering.
9. **Architecture**: Architects utilize FDM for creating detailed architectural models, prototypes of building components, and intricate designs. It aids in visualizing concepts, testing structural integrity, and communicating design ideas effectively.
Each industry example demonstrates how FDM enhances innovation, accelerates product development, and addresses specific challenges through advanced manufacturing capabilities.
Best Programming Language for Civil EngineersAwais Yaseen
The integration of programming into civil engineering is transforming the industry. We can design complex infrastructure projects and analyse large datasets. Imagine revolutionizing the way we build our cities and infrastructure, all by the power of coding. Programming skills are no longer just a bonus—they’re a game changer in this era.
Technology is revolutionizing civil engineering by integrating advanced tools and techniques. Programming allows for the automation of repetitive tasks, enhancing the accuracy of designs, simulations, and analyses. With the advent of artificial intelligence and machine learning, engineers can now predict structural behaviors under various conditions, optimize material usage, and improve project planning.
Advanced Techniques for Cyber Security Analysis and Anomaly DetectionBert Blevins
Cybersecurity is a major concern in today's connected digital world. Threats to organizations are constantly evolving and have the potential to compromise sensitive information, disrupt operations, and lead to significant financial losses. Traditional cybersecurity techniques often fall short against modern attackers. Therefore, advanced techniques for cyber security analysis and anomaly detection are essential for protecting digital assets. This blog explores these cutting-edge methods, providing a comprehensive overview of their application and importance.
How RPA Help in the Transportation and Logistics Industry.pptxSynapseIndia
Revolutionize your transportation processes with our cutting-edge RPA software. Automate repetitive tasks, reduce costs, and enhance efficiency in the logistics sector with our advanced solutions.
Details of description part II: Describing images in practice - Tech Forum 2024BookNet Canada
This presentation explores the practical application of image description techniques. Familiar guidelines will be demonstrated in practice, and descriptions will be developed “live”! If you have learned a lot about the theory of image description techniques but want to feel more confident putting them into practice, this is the presentation for you. There will be useful, actionable information for everyone, whether you are working with authors, colleagues, alone, or leveraging AI as a collaborator.
Link to presentation recording and transcript: https://bnctechforum.ca/sessions/details-of-description-part-ii-describing-images-in-practice/
Presented by BookNet Canada on June 25, 2024, with support from the Department of Canadian Heritage.
Details of description part II: Describing images in practice - Tech Forum 2024
The Statistics of Web Performance
1. Introduction
Statistics - I
Statistics - II
The Statistics of Web Performance
Philip Tellis / philip@bluesmoon.info
ConFoo / 2010-03-12
ConFoo / 2010-03-12 The Statistics of Web Performance
2. Introduction
Statistics - I
Statistics - II
$ finger philip
Philip Tellis
philip@bluesmoon.info
@bluesmoon
yahoo
geek
ConFoo / 2010-03-12 The Statistics of Web Performance
3. Introduction
The goal
Statistics - I
Performance Measurement
Statistics - II
Introduction
ConFoo / 2010-03-12 The Statistics of Web Performance
4. Introduction
The goal
Statistics - I
Performance Measurement
Statistics - II
Accurately measure page performance
At least, as accurately as possible
ConFoo / 2010-03-12 The Statistics of Web Performance
5. Introduction
The goal
Statistics - I
Performance Measurement
Statistics - II
Accurately measure page performance
At least, as accurately as possible
ConFoo / 2010-03-12 The Statistics of Web Performance
6. Introduction
The goal
Statistics - I
Performance Measurement
Statistics - II
Be unintrusive
If you try to measure something accurately, you will change
something related
– Heisenberg’s uncertainty principle
ConFoo / 2010-03-12 The Statistics of Web Performance
7. Introduction
The goal
Statistics - I
Performance Measurement
Statistics - II
And one number to rule them all
ConFoo / 2010-03-12 The Statistics of Web Performance
8. Introduction
The goal
Statistics - I
Performance Measurement
Statistics - II
Bandwidth
Real bandwidth v/s advertised bandwidth
Bandwidth to your server, not to the ISP
Bandwidth during normal internet usage
If the user’s always watching movies, you’re not winning
ConFoo / 2010-03-12 The Statistics of Web Performance
9. Introduction
The goal
Statistics - I
Performance Measurement
Statistics - II
Bandwidth
Real bandwidth v/s advertised bandwidth
Bandwidth to your server, not to the ISP
Bandwidth during normal internet usage
If the user’s always watching movies, you’re not winning
ConFoo / 2010-03-12 The Statistics of Web Performance
10. Introduction
The goal
Statistics - I
Performance Measurement
Statistics - II
Latency
How long does it take a byte to get to the user?
Wired, wireless, mobile, satellite?
How many hops in between?
Speed of light is constant
This is not a battle we will soon win.
When was the last time you heard latency mentioned in a
TV ad?
http://www.stuartcheshire.org/rants/Latency.html
ConFoo / 2010-03-12 The Statistics of Web Performance
11. Introduction
The goal
Statistics - I
Performance Measurement
Statistics - II
Latency
How long does it take a byte to get to the user?
Wired, wireless, mobile, satellite?
How many hops in between?
Speed of light is constant
This is not a battle we will soon win.
When was the last time you heard latency mentioned in a
TV ad?
http://www.stuartcheshire.org/rants/Latency.html
ConFoo / 2010-03-12 The Statistics of Web Performance
12. Introduction
The goal
Statistics - I
Performance Measurement
Statistics - II
Latency
How long does it take a byte to get to the user?
Wired, wireless, mobile, satellite?
How many hops in between?
Speed of light is constant
This is not a battle we will soon win.
When was the last time you heard latency mentioned in a
TV ad?
http://www.stuartcheshire.org/rants/Latency.html
ConFoo / 2010-03-12 The Statistics of Web Performance
13. Introduction
The goal
Statistics - I
Performance Measurement
Statistics - II
User perceived page load time
Time from “click on a link” to “spinner stops spinning”
This is what users notice
Depends on how long your page takes to build
Depends on what’s in your page
Depends on how long components take to load
Depends on how long the browser takes to execute and
render
ConFoo / 2010-03-12 The Statistics of Web Performance
14. Introduction
The goal
Statistics - I
Performance Measurement
Statistics - II
We need to measure real user data
ConFoo / 2010-03-12 The Statistics of Web Performance
15. Introduction
The goal
Statistics - I
Performance Measurement
Statistics - II
The statistics apply to any kind of performance data though
ConFoo / 2010-03-12 The Statistics of Web Performance
16. Introduction Random Sampling
Statistics - I Margin of Error
Statistics - II Central Tendency
Statistics - I
ConFoo / 2010-03-12 The Statistics of Web Performance
17. Introduction Random Sampling
Statistics - I Margin of Error
Statistics - II Central Tendency
Disclaimer
I am not a statistician
ConFoo / 2010-03-12 The Statistics of Web Performance
18. Introduction Random Sampling
Statistics - I Margin of Error
Statistics - II Central Tendency
Population
All possible users of your system
ConFoo / 2010-03-12 The Statistics of Web Performance
19. Introduction Random Sampling
Statistics - I Margin of Error
Statistics - II Central Tendency
Sample
Representative subset of the population
ConFoo / 2010-03-12 The Statistics of Web Performance
20. Introduction Random Sampling
Statistics - I Margin of Error
Statistics - II Central Tendency
Bad sample
Sometimes it’s not
ConFoo / 2010-03-12 The Statistics of Web Performance
21. Introduction Random Sampling
Statistics - I Margin of Error
Statistics - II Central Tendency
How to randomize?
Pick 10% of users at random and always test them
OR
For each user, decide at random if they should be tested
http://tech.bluesmoon.info/2010/01/statistics-of-performance-measurement.html
ConFoo / 2010-03-12 The Statistics of Web Performance
22. Introduction Random Sampling
Statistics - I Margin of Error
Statistics - II Central Tendency
Select 10% of users - I
if($sessionid % 10 === 0) {
// instrument code for measurement
}
Once a user enters the measurement bucket, they stay
there until they log out
Fixed set of users, so tests may be more consistent
Error in the sample results in positive feedback
ConFoo / 2010-03-12 The Statistics of Web Performance
23. Introduction Random Sampling
Statistics - I Margin of Error
Statistics - II Central Tendency
Select 10% of users - II
if(rand() < 0.1 * getrandmax()) {
// instrument code for measurement
}
For every request, a user has a 10% chance of being
tested
Gets rid of positive feedback errors, but sample size !=
10% of population
ConFoo / 2010-03-12 The Statistics of Web Performance
24. Introduction Random Sampling
Statistics - I Margin of Error
Statistics - II Central Tendency
How big a sample is representative?
Select n such that
σ
1.96 √n ≤ 5%µ
ConFoo / 2010-03-12 The Statistics of Web Performance
25. Introduction Random Sampling
Statistics - I Margin of Error
Statistics - II Central Tendency
Standard Deviation
Standard deviation tells you the spread of the curve
The narrower the curve, the more confident you can be
ConFoo / 2010-03-12 The Statistics of Web Performance
26. Introduction Random Sampling
Statistics - I Margin of Error
Statistics - II Central Tendency
MoE at 95% confidence
σ
±1.96 √n
ConFoo / 2010-03-12 The Statistics of Web Performance
27. Introduction Random Sampling
Statistics - I Margin of Error
Statistics - II Central Tendency
MoE & Sample size
There is an inverse square root correlation between sample
size and margin of error
ConFoo / 2010-03-12 The Statistics of Web Performance
28. Introduction Random Sampling
Statistics - I Margin of Error
Statistics - II Central Tendency
But wait... it’s not complicated enough.
We have different types of margins of error
...more about that later
ConFoo / 2010-03-12 The Statistics of Web Performance
29. Introduction Random Sampling
Statistics - I Margin of Error
Statistics - II Central Tendency
But wait... it’s not complicated enough.
We have different types of margins of error
...more about that later
ConFoo / 2010-03-12 The Statistics of Web Performance
30. Introduction Random Sampling
Statistics - I Margin of Error
Statistics - II Central Tendency
But wait... it’s not complicated enough.
We have different types of margins of error
...more about that later
ConFoo / 2010-03-12 The Statistics of Web Performance
31. Introduction Random Sampling
Statistics - I Margin of Error
Statistics - II Central Tendency
Ding dong
ConFoo / 2010-03-12 The Statistics of Web Performance
32. Introduction Random Sampling
Statistics - I Margin of Error
Statistics - II Central Tendency
One number
Mean (Arithmetic)
Good for symmetric curves
Affected by outliers
Mean(10, 11, 12, 11, 109) = 30
ConFoo / 2010-03-12 The Statistics of Web Performance
33. Introduction Random Sampling
Statistics - I Margin of Error
Statistics - II Central Tendency
One number
Median
Middle value measures central tendency well
Not trivial to pull out of a DB
Median(10, 11, 12, 11, 109) = 11
ConFoo / 2010-03-12 The Statistics of Web Performance
34. Introduction Random Sampling
Statistics - I Margin of Error
Statistics - II Central Tendency
One number
Mode
Not often used
Multi-modal distributions suggest problems
Mode(10, 11, 12, 11, 109) = 11
ConFoo / 2010-03-12 The Statistics of Web Performance
35. Introduction Random Sampling
Statistics - I Margin of Error
Statistics - II Central Tendency
Other numbers
A percentile point in the distribution: 95th , 98.5th or 99th
Used to find out the worst user experience
Makes more sense if you filter data first
P95th (10, 11, 12, 11, 109) = 12
ConFoo / 2010-03-12 The Statistics of Web Performance
36. Introduction Random Sampling
Statistics - I Margin of Error
Statistics - II Central Tendency
Other means
Geometric mean
Good if your data is exponential in nature
(with the tail on the right)
GMean(10, 11, 12, 11, 109) = 16.68
ConFoo / 2010-03-12 The Statistics of Web Performance
37. Introduction Random Sampling
Statistics - I Margin of Error
Statistics - II Central Tendency
Wait... how did I get that?
N
ΠN xi — could lead to overflow
i=1
ΣN loge (xi )
i=1
N
e — computationally simpler
ConFoo / 2010-03-12 The Statistics of Web Performance
38. Introduction Random Sampling
Statistics - I Margin of Error
Statistics - II Central Tendency
Wait... how did I get that?
N
ΠN xi — could lead to overflow
i=1
ΣN loge (xi )
i=1
N
e — computationally simpler
ConFoo / 2010-03-12 The Statistics of Web Performance
39. Introduction Random Sampling
Statistics - I Margin of Error
Statistics - II Central Tendency
Wait... how did I get that?
N
ΠN xi — could lead to overflow
i=1
ΣN loge (xi )
i=1
N
e — computationally simpler
ConFoo / 2010-03-12 The Statistics of Web Performance
40. Introduction Random Sampling
Statistics - I Margin of Error
Statistics - II Central Tendency
Wait... how did I get that?
N
ΠN xi — could lead to overflow
i=1
ΣN loge (xi )
i=1
N
e — computationally simpler
ConFoo / 2010-03-12 The Statistics of Web Performance
41. Introduction Random Sampling
Statistics - I Margin of Error
Statistics - II Central Tendency
Other means
And there is also the Harmonic mean, but forget about that
ConFoo / 2010-03-12 The Statistics of Web Performance
42. Introduction Random Sampling
Statistics - I Margin of Error
Statistics - II Central Tendency
...though consequently
We have other margins of error
Geometric margin of error
Uses geometric standard deviation
Median margin of error
Uses ranges of actual values from data set
Stick to the arithmetic MoE
– simpler to calculate, simpler to read and not incorrect
ConFoo / 2010-03-12 The Statistics of Web Performance
43. Introduction Random Sampling
Statistics - I Margin of Error
Statistics - II Central Tendency
...though consequently
We have other margins of error
Geometric margin of error
Uses geometric standard deviation
Median margin of error
Uses ranges of actual values from data set
Stick to the arithmetic MoE
– simpler to calculate, simpler to read and not incorrect
ConFoo / 2010-03-12 The Statistics of Web Performance
44. Introduction
Filtering
Statistics - I
The Log-Normal distribution
Statistics - II
Statistics - II
ConFoo / 2010-03-12 The Statistics of Web Performance
45. Introduction
Filtering
Statistics - I
The Log-Normal distribution
Statistics - II
Outliers
Out of range data points
Nothing you can fix here
There’s even a book about
them
ConFoo / 2010-03-12 The Statistics of Web Performance
46. Introduction
Filtering
Statistics - I
The Log-Normal distribution
Statistics - II
Outliers
Out of range data points
Nothing you can fix here
There’s even a book about
them
ConFoo / 2010-03-12 The Statistics of Web Performance
47. Introduction
Filtering
Statistics - I
The Log-Normal distribution
Statistics - II
Outliers
Out of range data points
Nothing you can fix here
There’s even a book about
them
ConFoo / 2010-03-12 The Statistics of Web Performance
48. Introduction
Filtering
Statistics - I
The Log-Normal distribution
Statistics - II
Outliers
Out of range data points
Nothing you can fix here
There’s even a book about
them
ConFoo / 2010-03-12 The Statistics of Web Performance
49. Introduction
Filtering
Statistics - I
The Log-Normal distribution
Statistics - II
DNS problems can cause outliers
2 or 3 DNS servers for an ISP
30 second timeout if first fails
... 30 second increase in page load time
Maybe measure both and fix what you can
http://nms.lcs.mit.edu/papers/dns-ton2002.pdf
ConFoo / 2010-03-12 The Statistics of Web Performance
50. Introduction
Filtering
Statistics - I
The Log-Normal distribution
Statistics - II
Band-pass filtering
ConFoo / 2010-03-12 The Statistics of Web Performance
51. Introduction
Filtering
Statistics - I
The Log-Normal distribution
Statistics - II
Band-pass filtering
Strip everything outside a reasonable range
Bandwidth range: 4kbps - 4Gbps
Page load time: 50ms - 120s
You may need to relook at the ranges all the time
ConFoo / 2010-03-12 The Statistics of Web Performance
52. Introduction
Filtering
Statistics - I
The Log-Normal distribution
Statistics - II
IQR filtering
ConFoo / 2010-03-12 The Statistics of Web Performance
53. Introduction
Filtering
Statistics - I
The Log-Normal distribution
Statistics - II
IQR filtering
Here, we derive the range from the data
ConFoo / 2010-03-12 The Statistics of Web Performance
54. Introduction
Filtering
Statistics - I
The Log-Normal distribution
Statistics - II
Let’s look at some real charts
ConFoo / 2010-03-12 The Statistics of Web Performance
55. Introduction
Filtering
Statistics - I
The Log-Normal distribution
Statistics - II
Bandwidth distribution for web devs
x-axis is linear
ConFoo / 2010-03-12 The Statistics of Web Performance
56. Introduction
Filtering
Statistics - I
The Log-Normal distribution
Statistics - II
Now let’s use log(kbps) instead of kbps
x-axis is exponential
ConFoo / 2010-03-12 The Statistics of Web Performance
57. Introduction
Filtering
Statistics - I
The Log-Normal distribution
Statistics - II
Exponential == Geometric
Categories/Buckets grow exponentially
Data is related geometrically
Use the geometric mean and geometric margin of error
gmean
Error _range = /gmoe , gmean ∗ gmoe
Non-linear ranges are hard for humans to grok
ConFoo / 2010-03-12 The Statistics of Web Performance
58. Introduction
Filtering
Statistics - I
The Log-Normal distribution
Statistics - II
Exponential == Geometric
Categories/Buckets grow exponentially
Data is related geometrically
Use the geometric mean and geometric margin of error
gmean
Error _range = /gmoe , gmean ∗ gmoe
Non-linear ranges are hard for humans to grok
ConFoo / 2010-03-12 The Statistics of Web Performance
59. Introduction
Filtering
Statistics - I
The Log-Normal distribution
Statistics - II
Exponential == Geometric
Categories/Buckets grow exponentially
Data is related geometrically
Use the geometric mean and geometric margin of error
gmean
Error _range = /gmoe , gmean ∗ gmoe
Non-linear ranges are hard for humans to grok
ConFoo / 2010-03-12 The Statistics of Web Performance
60. Introduction
Statistics - I
Statistics - II
So...
ConFoo / 2010-03-12 The Statistics of Web Performance
61. Introduction
Statistics - I
Statistics - II
Further reading
Web Performance - Not a Simple Number
http://www.netforecast.com/Articles/BCR+C25+Web+Performance+-+Not+A+Simple+Number.pdf
Revisiting statistics for web performance (introduction to
Log-Normal)
http://home.pacbell.net/ciemo/statistics/WhatDoYouMean.pdf
Random Sampling
http://tech.bluesmoon.info/2010/01/statistics-of-performance-measurement.html
Khan Academy’s tutorials on statistics
http://khanacademy.com/
Learning about Statistical Learning
http://measuringmeasures.blogspot.com/2010/01/learning-about-statistical-learning.html
Wikipedia articles on Random Sampling, Central Tendency,
Standard Error, Confounding, Means and IQR
ConFoo / 2010-03-12 The Statistics of Web Performance
62. Introduction
Statistics - I
Statistics - II
Summary
Choose a reasonable sample size and sampling factor
Tune sample size for minimal margin of error
Decide based on your data whether to use mode, median
or one of the means
Figure out whether your data is Normal, Log-Normal or
something else
Filter out anomalous outliers
ConFoo / 2010-03-12 The Statistics of Web Performance
63. Introduction
Statistics - I
Statistics - II
contact me
Philip Tellis
philip@bluesmoon.info
bluesmoon.info
@bluesmoon
ConFoo / 2010-03-12 The Statistics of Web Performance
64. Introduction
Statistics - I
Statistics - II
Photo credits
http://www.flickr.com/photos/leoffreitas/332360959/ by leoffreitas
http://www.flickr.com/photos/cobalt/56500295/ by cobalt123
http://www.flickr.com/photos/sophistechate/4264466015/ by Lisa
Brewster
http://www.flickr.com/photos/nchoz/243216008/ by nchoz
ConFoo / 2010-03-12 The Statistics of Web Performance
65. Introduction
Statistics - I
Statistics - II
List of figures
http://en.wikipedia.org/wiki/File:Standard_deviation_diagram.svg
http://en.wikipedia.org/wiki/File:Normal_Distribution_PDF.svg
http://en.wikipedia.org/wiki/File:KilroySchematic.svg
http://en.wikipedia.org/wiki/File:Boxplot_vs_PDF.png
ConFoo / 2010-03-12 The Statistics of Web Performance