Load testing is a continuous process that involves designing tests with a specific purpose in mind, running the tests to saturation using realistic user models, and analyzing the results across different load levels while linking them to production metrics. The goal is to understand how an application performs under various loads and identify any bottlenecks before they impact real users.
Designing and Running Performance ExperimentsJ On The Beach
An accurate understanding of how our systems perform is critical for ensuring good customer service, effective capacity planning and managing the process of optimisation.
Sadly, it's all too rare to see good practice when it comes to analysing and testing the performance of systems. In this talk, we see how to approach performance analysis scientifically.
We’ll discuss how to design, construct, execute, verify and analyse performance experiments to answer these four important questions:
How much load can my system handle before it is saturated?
What service can I expect my customers to see at a given load level?
What are the bottlenecks in my application that cause saturation?
How is my performance varying over time?
Attendees will learn how to collate and process large timeseries datausing InfluxDB. We'll see how to monitor experiments as they execute,how to analyse the results of each experiment and how to compare results across experiments.
Queuing Theory and the Theory of Constraints are two powerful theories that can increase your velocity. This session explains both theories in simple terms then covers how they can be applied in the real world by agile teams. 21 simple velocity increasing experiments are described that you can immediately use.
The effects of Queuing Theory impact our lives on a daily basis. Scrum uses Queuing Theory at its core and you can amplify those effects.
The Theory of Constraints can identify the one constraint that is preventing your team from increasing its velocity. It also shows us how to remove that constraint in the cheapest way possible.
Being productive is a great advantage. So, today, we will give you some tips on how to work faster and be productive with great results. Keep checking our blog for more tips & tricks at http://kanbantool.com/blog.
Designing and Running Performance ExperimentsJ On The Beach
An accurate understanding of how our systems perform is critical for ensuring good customer service, effective capacity planning and managing the process of optimisation.
Sadly, it's all too rare to see good practice when it comes to analysing and testing the performance of systems. In this talk, we see how to approach performance analysis scientifically.
We’ll discuss how to design, construct, execute, verify and analyse performance experiments to answer these four important questions:
How much load can my system handle before it is saturated?
What service can I expect my customers to see at a given load level?
What are the bottlenecks in my application that cause saturation?
How is my performance varying over time?
Attendees will learn how to collate and process large timeseries datausing InfluxDB. We'll see how to monitor experiments as they execute,how to analyse the results of each experiment and how to compare results across experiments.
Queuing Theory and the Theory of Constraints are two powerful theories that can increase your velocity. This session explains both theories in simple terms then covers how they can be applied in the real world by agile teams. 21 simple velocity increasing experiments are described that you can immediately use.
The effects of Queuing Theory impact our lives on a daily basis. Scrum uses Queuing Theory at its core and you can amplify those effects.
The Theory of Constraints can identify the one constraint that is preventing your team from increasing its velocity. It also shows us how to remove that constraint in the cheapest way possible.
Being productive is a great advantage. So, today, we will give you some tips on how to work faster and be productive with great results. Keep checking our blog for more tips & tricks at http://kanbantool.com/blog.
How to Get Automatic Analysis for Load Test ResultsClare Avieli
The ability to fully automate your results analysis is vital in today’s Continuous Integration and Continuous Deployment era. Agile practices like Microservices exacerbate this need, giving you tens of services to test, ten times a day! Analysis by the human eye is impossible - you need automation.
But automating the analysis is extremely difficult due to the ever-increasing complexities of load testing processes and timeline based reports. As such, contemporary load testing tools and services offer excellent ways to present reports but fall short when it comes to the analysis.
In this presentation, Andrey Pokhilko (founder of JMeter-plugins.org and Loadosophia) explores how to take automatic result analysis and decision making to a new level.
Join us and discuss:
• Why is it tough to fully automate analysis and decision making on test results
• How humans analyze the test in practice - which KPIs they look at
• Which decisions can be made automatically during test execution
• Which facts can be automatically concluded post-test
• Practical results from several months of method application
How to successfully load test over a million concurrent users stp con demoApica
Does your company attract millions of visitors, users or even subscribers to your site or application? Whether you answered yes or no, it’s still a great idea to know what it takes to test 2+ million concurrent users, fast. In this presentation, you’ll get a first-hand, live walk-through of Apica Load Test doing a mega test of 2 million concurrent users.
Overview
1. The main goals of performance testing
2. The Advantages of Performance Tests
3. The Disadvantages of Performance Tests
4. Types of performance tests
5. Determining a successful performance testing project
Enjoy!
QConSF 2014 talk on Netflix Mantis, a stream processing systemDanny Yuan
Justin and I gave this talk in QCon SF 2014 about the Mantis, a stream processing system that features a reactive programming API, auto scaling, and stream locality
Provisioning and Capacity Planning Workshop (Dogpatch Labs, September 2015)Brian Brazil
If you’ve ever worried that you may have an outage someday due to your production servers not being able to handle increased user traffic, then this workshop will help put you at ease. Learn the foundations and how to apply it to your services.
Contact me at brian.brazil@robustperception.io if you'd like to learn more.
How to Get Automatic Analysis for Load Test ResultsClare Avieli
The ability to fully automate your results analysis is vital in today’s Continuous Integration and Continuous Deployment era. Agile practices like Microservices exacerbate this need, giving you tens of services to test, ten times a day! Analysis by the human eye is impossible - you need automation.
But automating the analysis is extremely difficult due to the ever-increasing complexities of load testing processes and timeline based reports. As such, contemporary load testing tools and services offer excellent ways to present reports but fall short when it comes to the analysis.
In this presentation, Andrey Pokhilko (founder of JMeter-plugins.org and Loadosophia) explores how to take automatic result analysis and decision making to a new level.
Join us and discuss:
• Why is it tough to fully automate analysis and decision making on test results
• How humans analyze the test in practice - which KPIs they look at
• Which decisions can be made automatically during test execution
• Which facts can be automatically concluded post-test
• Practical results from several months of method application
How to successfully load test over a million concurrent users stp con demoApica
Does your company attract millions of visitors, users or even subscribers to your site or application? Whether you answered yes or no, it’s still a great idea to know what it takes to test 2+ million concurrent users, fast. In this presentation, you’ll get a first-hand, live walk-through of Apica Load Test doing a mega test of 2 million concurrent users.
Overview
1. The main goals of performance testing
2. The Advantages of Performance Tests
3. The Disadvantages of Performance Tests
4. Types of performance tests
5. Determining a successful performance testing project
Enjoy!
QConSF 2014 talk on Netflix Mantis, a stream processing systemDanny Yuan
Justin and I gave this talk in QCon SF 2014 about the Mantis, a stream processing system that features a reactive programming API, auto scaling, and stream locality
Provisioning and Capacity Planning Workshop (Dogpatch Labs, September 2015)Brian Brazil
If you’ve ever worried that you may have an outage someday due to your production servers not being able to handle increased user traffic, then this workshop will help put you at ease. Learn the foundations and how to apply it to your services.
Contact me at brian.brazil@robustperception.io if you'd like to learn more.
London web performance WPO Lessons from the field June 2013Stephen Thair
Web Performance - random lessons learnt from delivering WPO, Load testing and APM consulting in the UK. PLus a bit about WebPageTest Private Instances etc
Provisioning and Capacity Planning (Travel Meets Big Data)Brian Brazil
Ever worried that you’ll have an outage someday because your production servers can’t handle increased user traffic?
Then this workshop will help put you at ease! Learn the foundations and how to apply it to your services.
At the end of the workshop you will be able to:
– Estimate how much spare capacity you have in less than 5 minutes
– Estimate how much runway that capacity provides
– Determine how many servers you need
– Spot common potential problems as you scale
A lot of effort has gone into cloud storage peformance benchmarking, both of swift and other cloud stacks and part of the result is a lot of confusion in the numbers, in large part because there is no standard. This is further complicated because some implementations are written in java, some in python and some in raw curl. Furthermore, the underlying libraries themselves can cause variances as they do not all use the same buffer sizes, enable/disable ssl-compression and probably other parameters as well.
I would like to talk about our benchmarking methodologies at HP as well as describe a tool suite I've developed that implements them and share some results of benchmarking our own OpenStack implementation. One thing I've discovered over previous months of testing is that both latency and cpu overhead can have a major impact on performance and those are captured as well, something most tools typically don't report.
The tools are written in python and use the OpenStack python-swiftclient library.
Speakers
Mark Seger
Session ID: SFO17-307
Session Name: WALT vs PELT : Redux
- SFO17-307
Speaker: Pavan Kumar Kondeti
Track: LMG
★ Session Summary ★
New data on the comparison of the WALT and PELT load tracking schemes in the scheduler
---------------------------------------------------
★ Resources ★
Event Page: http://connect.linaro.org/resource/sfo17/sfo17-307/
Presentation:
Video: https://www.youtube.com/watch?v=r3QKEYpyetU
---------------------------------------------------
★ Event Details ★
Linaro Connect San Francisco 2017 (SFO17)
25-29 September 2017
Hyatt Regency San Francisco Airport
---------------------------------------------------
Keyword:
'http://www.linaro.org'
'http://connect.linaro.org'
---------------------------------------------------
Follow us on Social Media
https://www.facebook.com/LinaroOrg
https://twitter.com/linaroorg
https://www.youtube.com/user/linaroorg?sub_confirmation=1
https://www.linkedin.com/company/1026961
A lean automation blueprint for testing in continuous deliverySauce Labs
Testing in Continuous Delivery changes test automation. It demands more automation but also requires immediate feedback. Many test teams today suffer from two extremes. Too little or no automation to organizations with hundreds of thousands of tests constantly running all kinds of VMs takes multiple days to execute. Any hope of Continuous Delivery or Pipeline Automation makes these states unsustainable.
Applying the power of Continuous Delivery to performance testing. Process, techniques, best practices. This talk describes a pragmatic approach to building a robust performance testing strategy.
On the way to low latency (2nd edition)Artem Orobets
This is the second edition of the story about how we struggled to implement strict latency requirements in a service implemented with Java and how we managed to do that.
The most common latency contributors are an in-process locking, thread scheduling, I/O, algorithmic inefficiencies and, of course, garbage collector.
I will share our experience of dealing with the causes. And tell what you can do to prevent them from affecting the production.
Queuing Theory and the Theory of Constraints are two powerful theories that can increase your velocity. This session explains both theories in simple terms then covers how they can be applied in the real world by agile teams. 21 simple velocity increasing experiments are described that you can immediately use.
The effects of Queuing Theory impact our lives on a daily basis. Scrum uses Queuing Theory at its core and you can amplify those effects.
The Theory of Constraints can identify the one constraint that is preventing your team from increasing its velocity. It also shows us how to remove that constraint in the cheapest way possible.
Presented at Scrum Australia (@auscrum), Melbourne, 29 April 2016
May Marketo Masterclass, London MUG May 22 2024.pdfAdele Miller
Can't make Adobe Summit in Vegas? No sweat because the EMEA Marketo Engage Champions are coming to London to share their Summit sessions, insights and more!
This is a MUG with a twist you don't want to miss.
How to Position Your Globus Data Portal for Success Ten Good PracticesGlobus
Science gateways allow science and engineering communities to access shared data, software, computing services, and instruments. Science gateways have gained a lot of traction in the last twenty years, as evidenced by projects such as the Science Gateways Community Institute (SGCI) and the Center of Excellence on Science Gateways (SGX3) in the US, The Australian Research Data Commons (ARDC) and its platforms in Australia, and the projects around Virtual Research Environments in Europe. A few mature frameworks have evolved with their different strengths and foci and have been taken up by a larger community such as the Globus Data Portal, Hubzero, Tapis, and Galaxy. However, even when gateways are built on successful frameworks, they continue to face the challenges of ongoing maintenance costs and how to meet the ever-expanding needs of the community they serve with enhanced features. It is not uncommon that gateways with compelling use cases are nonetheless unable to get past the prototype phase and become a full production service, or if they do, they don't survive more than a couple of years. While there is no guaranteed pathway to success, it seems likely that for any gateway there is a need for a strong community and/or solid funding streams to create and sustain its success. With over twenty years of examples to draw from, this presentation goes into detail for ten factors common to successful and enduring gateways that effectively serve as best practices for any new or developing gateway.
Check out the webinar slides to learn more about how XfilesPro transforms Salesforce document management by leveraging its world-class applications. For more details, please connect with sales@xfilespro.com
If you want to watch the on-demand webinar, please click here: https://www.xfilespro.com/webinars/salesforce-document-management-2-0-smarter-faster-better/
Listen to the keynote address and hear about the latest developments from Rachana Ananthakrishnan and Ian Foster who review the updates to the Globus Platform and Service, and the relevance of Globus to the scientific community as an automation platform to accelerate scientific discovery.
Graspan: A Big Data System for Big Code AnalysisAftab Hussain
We built a disk-based parallel graph system, Graspan, that uses a novel edge-pair centric computation model to compute dynamic transitive closures on very large program graphs.
We implement context-sensitive pointer/alias and dataflow analyses on Graspan. An evaluation of these analyses on large codebases such as Linux shows that their Graspan implementations scale to millions of lines of code and are much simpler than their original implementations.
These analyses were used to augment the existing checkers; these augmented checkers found 132 new NULL pointer bugs and 1308 unnecessary NULL tests in Linux 4.4.0-rc5, PostgreSQL 8.3.9, and Apache httpd 2.2.18.
- Accepted in ASPLOS ‘17, Xi’an, China.
- Featured in the tutorial, Systemized Program Analyses: A Big Data Perspective on Static Analysis Scalability, ASPLOS ‘17.
- Invited for presentation at SoCal PLS ‘16.
- Invited for poster presentation at PLDI SRC ‘16.
Atelier - Innover avec l’IA Générative et les graphes de connaissancesNeo4j
Atelier - Innover avec l’IA Générative et les graphes de connaissances
Allez au-delà du battage médiatique autour de l’IA et découvrez des techniques pratiques pour utiliser l’IA de manière responsable à travers les données de votre organisation. Explorez comment utiliser les graphes de connaissances pour augmenter la précision, la transparence et la capacité d’explication dans les systèmes d’IA générative. Vous partirez avec une expérience pratique combinant les relations entre les données et les LLM pour apporter du contexte spécifique à votre domaine et améliorer votre raisonnement.
Amenez votre ordinateur portable et nous vous guiderons sur la mise en place de votre propre pile d’IA générative, en vous fournissant des exemples pratiques et codés pour démarrer en quelques minutes.
Unleash Unlimited Potential with One-Time Purchase
BoxLang is more than just a language; it's a community. By choosing a Visionary License, you're not just investing in your success, you're actively contributing to the ongoing development and support of BoxLang.
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I ...Juraj Vysvader
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I didn't get rich from it but it did have 63K downloads (powered possible tens of thousands of websites).
Understanding Globus Data Transfers with NetSageGlobus
NetSage is an open privacy-aware network measurement, analysis, and visualization service designed to help end-users visualize and reason about large data transfers. NetSage traditionally has used a combination of passive measurements, including SNMP and flow data, as well as active measurements, mainly perfSONAR, to provide longitudinal network performance data visualization. It has been deployed by dozens of networks world wide, and is supported domestically by the Engagement and Performance Operations Center (EPOC), NSF #2328479. We have recently expanded the NetSage data sources to include logs for Globus data transfers, following the same privacy-preserving approach as for Flow data. Using the logs for the Texas Advanced Computing Center (TACC) as an example, this talk will walk through several different example use cases that NetSage can answer, including: Who is using Globus to share data with my institution, and what kind of performance are they able to achieve? How many transfers has Globus supported for us? Which sites are we sharing the most data with, and how is that changing over time? How is my site using Globus to move data internally, and what kind of performance do we see for those transfers? What percentage of data transfers at my institution used Globus, and how did the overall data transfer performance compare to the Globus users?
Developing Distributed High-performance Computing Capabilities of an Open Sci...Globus
COVID-19 had an unprecedented impact on scientific collaboration. The pandemic and its broad response from the scientific community has forged new relationships among public health practitioners, mathematical modelers, and scientific computing specialists, while revealing critical gaps in exploiting advanced computing systems to support urgent decision making. Informed by our team’s work in applying high-performance computing in support of public health decision makers during the COVID-19 pandemic, we present how Globus technologies are enabling the development of an open science platform for robust epidemic analysis, with the goal of collaborative, secure, distributed, on-demand, and fast time-to-solution analyses to support public health.
Code reviews are vital for ensuring good code quality. They serve as one of our last lines of defense against bugs and subpar code reaching production.
Yet, they often turn into annoying tasks riddled with frustration, hostility, unclear feedback and lack of standards. How can we improve this crucial process?
In this session we will cover:
- The Art of Effective Code Reviews
- Streamlining the Review Process
- Elevating Reviews with Automated Tools
By the end of this presentation, you'll have the knowledge on how to organize and improve your code review proces
OpenMetadata Community Meeting - 5th June 2024OpenMetadata
The OpenMetadata Community Meeting was held on June 5th, 2024. In this meeting, we discussed about the data quality capabilities that are integrated with the Incident Manager, providing a complete solution to handle your data observability needs. Watch the end-to-end demo of the data quality features.
* How to run your own data quality framework
* What is the performance impact of running data quality frameworks
* How to run the test cases in your own ETL pipelines
* How the Incident Manager is integrated
* Get notified with alerts when test cases fail
Watch the meeting recording here - https://www.youtube.com/watch?v=UbNOje0kf6E
Providing Globus Services to Users of JASMIN for Environmental Data AnalysisGlobus
JASMIN is the UK’s high-performance data analysis platform for environmental science, operated by STFC on behalf of the UK Natural Environment Research Council (NERC). In addition to its role in hosting the CEDA Archive (NERC’s long-term repository for climate, atmospheric science & Earth observation data in the UK), JASMIN provides a collaborative platform to a community of around 2,000 scientists in the UK and beyond, providing nearly 400 environmental science projects with working space, compute resources and tools to facilitate their work. High-performance data transfer into and out of JASMIN has always been a key feature, with many scientists bringing model outputs from supercomputers elsewhere in the UK, to analyse against observational or other model data in the CEDA Archive. A growing number of JASMIN users are now realising the benefits of using the Globus service to provide reliable and efficient data movement and other tasks in this and other contexts. Further use cases involve long-distance (intercontinental) transfers to and from JASMIN, and collecting results from a mobile atmospheric radar system, pushing data to JASMIN via a lightweight Globus deployment. We provide details of how Globus fits into our current infrastructure, our experience of the recent migration to GCSv5.4, and of our interest in developing use of the wider ecosystem of Globus services for the benefit of our user community.
Gamify Your Mind; The Secret Sauce to Delivering Success, Continuously Improv...Shahin Sheidaei
Games are powerful teaching tools, fostering hands-on engagement and fun. But they require careful consideration to succeed. Join me to explore factors in running and selecting games, ensuring they serve as effective teaching tools. Learn to maintain focus on learning objectives while playing, and how to measure the ROI of gaming in education. Discover strategies for pitching gaming to leadership. This session offers insights, tips, and examples for coaches, team leads, and enterprise leaders seeking to teach from simple to complex concepts.
Climate Science Flows: Enabling Petabyte-Scale Climate Analysis with the Eart...Globus
The Earth System Grid Federation (ESGF) is a global network of data servers that archives and distributes the planet’s largest collection of Earth system model output for thousands of climate and environmental scientists worldwide. Many of these petabyte-scale data archives are located in proximity to large high-performance computing (HPC) or cloud computing resources, but the primary workflow for data users consists of transferring data, and applying computations on a different system. As a part of the ESGF 2.0 US project (funded by the United States Department of Energy Office of Science), we developed pre-defined data workflows, which can be run on-demand, capable of applying many data reduction and data analysis to the large ESGF data archives, transferring only the resultant analysis (ex. visualizations, smaller data files). In this talk, we will showcase a few of these workflows, highlighting how Globus Flows can be used for petabyte-scale climate analysis.
Prosigns: Transforming Business with Tailored Technology SolutionsProsigns
Unlocking Business Potential: Tailored Technology Solutions by Prosigns
Discover how Prosigns, a leading technology solutions provider, partners with businesses to drive innovation and success. Our presentation showcases our comprehensive range of services, including custom software development, web and mobile app development, AI & ML solutions, blockchain integration, DevOps services, and Microsoft Dynamics 365 support.
Custom Software Development: Prosigns specializes in creating bespoke software solutions that cater to your unique business needs. Our team of experts works closely with you to understand your requirements and deliver tailor-made software that enhances efficiency and drives growth.
Web and Mobile App Development: From responsive websites to intuitive mobile applications, Prosigns develops cutting-edge solutions that engage users and deliver seamless experiences across devices.
AI & ML Solutions: Harnessing the power of Artificial Intelligence and Machine Learning, Prosigns provides smart solutions that automate processes, provide valuable insights, and drive informed decision-making.
Blockchain Integration: Prosigns offers comprehensive blockchain solutions, including development, integration, and consulting services, enabling businesses to leverage blockchain technology for enhanced security, transparency, and efficiency.
DevOps Services: Prosigns' DevOps services streamline development and operations processes, ensuring faster and more reliable software delivery through automation and continuous integration.
Microsoft Dynamics 365 Support: Prosigns provides comprehensive support and maintenance services for Microsoft Dynamics 365, ensuring your system is always up-to-date, secure, and running smoothly.
Learn how our collaborative approach and dedication to excellence help businesses achieve their goals and stay ahead in today's digital landscape. From concept to deployment, Prosigns is your trusted partner for transforming ideas into reality and unlocking the full potential of your business.
Join us on a journey of innovation and growth. Let's partner for success with Prosigns.
GraphSummit Paris - The art of the possible with Graph TechnologyNeo4j
Sudhir Hasbe, Chief Product Officer, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
2. Agenda
● Who am I?
● Why bother load testing?
● Load Testing Process
○ Designing load tests like a pro
○ Running load tests like a pro
○ Analysing load tests like a pro
18. Recap
● Your organisation (likely) exists to make money
● Application performance has a big impact on revenue
● The magnitude of this impact far outweighs the
investment you will make to maintain and improve
performance
23. ● Once designed, a load test is good for multiple runs
● How many runs depends on:
○ How often you run
○ How often your code changes
○ How often your audience changes
● You must revisit the design as the landscape changes
27. ● What latency do I see with X concurrent users?
● How many concurrent users can I handle before latency
exceeds Xms?
● How many concurrent users can I handle before my system
is saturated?
28. ● Average latency is mostly useless as a metric
● Later percentiles are better: 90th, 95th, 99th, 99.9th
● Max is a useful measure but is highly susceptible to
measurement error
● For best results, consider whole distribution analysis
Measuring Latency
43. ● Wait times are typically non-zero
● Wait times are drawn from a distribution
● If you don’t know the distribution, exponential is a good
fallback
44. ● Google Analytics, MixPanel, Kiss Metrics
● Log files
● OpenZipkin, AWS X-Ray
● NewRelic, AppDynamics, Instana
Source Model Parameters From Real Data
45. Recap
● Design with a purpose in mind
● Each user is different, capture this difference in your model
● Probabilistic models are better than prescriptive plans
● Production data is the best source of model parameters
47. Step One: Create a high-fidelity load test environment
Step Two: Provision enough load generation capacity
Step Three: Instrument the System Under Test
Step Four: Implement the test model for your load generator of choice
Step Five: Go!
48. ● The closer to production the better
● Ideally, you’re already automating production provisioning
● Stubbing is acceptable, but you must do it well
The System Under Test
49. ● Stubs must exhibit service times like real systems
● Service times and wait times are modelled the same way
● github.com/spectolabs/hoverfly
Hoverfly
50. ● Laptops are not load generators
● Less is not more
● If in doubt, over provision
● Make sure that you’re tracking metrics from the load
generators
Load Generators
51. ● CPU, memory, I/O
● Usage, Saturation and Errors (USE)
● Background reading: Systems Performance by Brendan
Gregg
Instrumentation
52. USE Metrics
Resource Utilisation Saturation Errors
CPU CPU % Run Queue Length ECC events/Failed CPUs
Memory Free/Used %
Anon. Paging/Thread
Swapping
Failed mallocs?
Network I/O RX/TX throughput
NIC events
(drops/overruns)
Disk I/O Busy % Wait Queue Length Device Errors
56. ● Super low tech: check the results by hand
● Low tech: check a plot of the results
● High tech: fit a curve to the plot and check that
● Super high tech: take the derivative of the fitted curve
Detecting Saturation
62. Recap
● Testing to saturation provides you with plenty of data
● Detecting saturation is relatively simple from the outside
● Tracking internal performance metrics helps to track
saturation
71. Labelled QoS
Label Load Level 50%ile 90%ile 95%ile 99%ile 99.9%ile 100%ile
Home 60 93 96.0 99.00 374.00 1187.021 1772
Home 70 93 96.0 101.00 463.03 1359.006 1817
Home 80 93 97.0 107.00 515.04 1422.002 4793
Home 90 93 97.0 122.00 705.04 1642.509 4478
Home 100 93 99.0 129.00 715.05 1671.005 5158
Home 110 93 100.0 140.00 864.00 1675.503 5485
Home 120 94 116.0 176.00 852.01 1474.000 5599
Home 130 94 176.0 181.00 1135.00 6176.000 9204
Home 140 94 178.0 187.00 1192.03 5879.001 7523
Home 150 96 180.0 201.00 1384.00 5658.000 9713
72. Recap
● Experiment with different visualisations
● A simple table might be the best visualisation you have
● Segment analysis by endpoint
● Understand your load in the context of your production
metrics