Docker containers provide significantly lower resource usage and higher density than traditional virtual machines when running multiple workloads concurrently on a server.
When booting 15 Ubuntu VMs with MySQL sequentially, Docker containers boot on average 3.5 seconds compared to 5.8 seconds for KVMs. During steady state operation of 15 active VMs, Docker uses on average 0.2% CPU and 49MB RAM per container, while KVMs use 1.9% CPU and 292MB RAM each. Docker maintains low 1-minute load averages of 0.15, while KVMs average 35.9% under load.
KVM and docker LXC Benchmarking with OpenStackBoden Russell
Passive benchmarking with docker LXC and KVM using OpenStack hosted in SoftLayer. These results provide initial incite as to why LXC as a technology choice offers benefits over traditional VMs and seek to provide answers as to the typical initial LXC question -- "why would I consider Linux Containers over VMs" from a performance perspective.
Results here provide insight as to:
- Cloudy ops times (start, stop, reboot) using OpenStack.
- Guest micro benchmark performance (I/O, network, memory, CPU).
- Guest micro benchmark performance of MySQL; OLTP read, read / write complex and indexed insertion.
- Compute node resource consumption; VM / Container density factors.
- Lessons learned during benchmarking.
The tests here were performed using OpenStack Rally to drive the OpenStack cloudy tests and various other linux tools to test the guest performance on a "micro level". The nova docker virt driver was used in the Cloud scenario to realize VMs as docker LXC containers and compared to the nova virt driver for libvirt KVM.
Please read the disclaimers in the presentation as this is only intended to be the "chip of the ice burg".
Linux Container Brief for IEEE WG P2302Boden Russell
A brief into to Linux Containers presented to IEEE working group P2302 (InterCloud standards and portability). This deck covers:
- Definitions and motivations for containers
- Container technology stack
- Containers vs Hypervisor VMs
- Cgroups
- Namespaces
- Pivot root vs chroot
- Linux Container image basics
- Linux Container security topics
- Overview of Linux Container tooling functionality
- Thoughts on container portability and runtime configuration
- Container tooling in the industry
- Container gaps
- Sample use cases for traditional VMs
Overall, a bulk of this deck is covered in other material I have posted here. However there are a few new slides in this deck, most notability some thoughts on container portability and runtime config.
KVM and docker LXC Benchmarking with OpenStackBoden Russell
Passive benchmarking with docker LXC and KVM using OpenStack hosted in SoftLayer. These results provide initial incite as to why LXC as a technology choice offers benefits over traditional VMs and seek to provide answers as to the typical initial LXC question -- "why would I consider Linux Containers over VMs" from a performance perspective.
Results here provide insight as to:
- Cloudy ops times (start, stop, reboot) using OpenStack.
- Guest micro benchmark performance (I/O, network, memory, CPU).
- Guest micro benchmark performance of MySQL; OLTP read, read / write complex and indexed insertion.
- Compute node resource consumption; VM / Container density factors.
- Lessons learned during benchmarking.
The tests here were performed using OpenStack Rally to drive the OpenStack cloudy tests and various other linux tools to test the guest performance on a "micro level". The nova docker virt driver was used in the Cloud scenario to realize VMs as docker LXC containers and compared to the nova virt driver for libvirt KVM.
Please read the disclaimers in the presentation as this is only intended to be the "chip of the ice burg".
Linux Container Brief for IEEE WG P2302Boden Russell
A brief into to Linux Containers presented to IEEE working group P2302 (InterCloud standards and portability). This deck covers:
- Definitions and motivations for containers
- Container technology stack
- Containers vs Hypervisor VMs
- Cgroups
- Namespaces
- Pivot root vs chroot
- Linux Container image basics
- Linux Container security topics
- Overview of Linux Container tooling functionality
- Thoughts on container portability and runtime configuration
- Container tooling in the industry
- Container gaps
- Sample use cases for traditional VMs
Overall, a bulk of this deck is covered in other material I have posted here. However there are a few new slides in this deck, most notability some thoughts on container portability and runtime config.
Cgroups, namespaces, and beyond: what are containers made from? (DockerCon Eu...Jérôme Petazzoni
Linux containers are different from Solaris Zones or BSD Jails: they use discrete kernel features like cgroups, namespaces, SELinux, and more. We will describe those mechanisms in depth, as well as demo how to put them together to produce a container. We will also highlight how different container runtimes compare to each other.
This talk was delivered at DockerCon Europe 2015 in Barcelona.
Anatomy of a Container: Namespaces, cgroups & Some Filesystem Magic - LinuxConJérôme Petazzoni
Containers are everywhere. But what exactly is a container? What are they made from? What's the difference between LXC, butts-nspawn, Docker, and the other container systems out there? And why should we bother about specific filesystems?
In this talk, Jérôme will show the individual roles and behaviors of the components making up a container: namespaces, control groups, and copy-on-write systems. Then, he will use them to assemble a container from scratch, and highlight the differences (and likelinesses) with existing container systems.
Cgroups, namespaces and beyond: what are containers made from?Docker, Inc.
Linux containers are different from Solaris Zones or BSD Jails: they use discrete kernel features like cgroups, namespaces, SELinux, and more. We will describe those mechanisms in depth, as well as demo how to put them together to produce a container. We will also highlight how different container runtimes compare to each other.
Containerization is more than the new Virtualization: enabling separation of ...Jérôme Petazzoni
Docker offers a new, lightweight approach to application
portability. Applications are shipped using a common container format,
and managed with a high-level API. Their processes run within isolated
namespaces which abstract the operating environment, independently of
the distribution, versions, network setup, and other details of this
environment.
This "containerization" has often been nicknamed "the new
virtualization". But containers are more than lightweight virtual
machines. Beyond their smaller footprint, shorter boot times, and
higher consolidation factors, they also bring a lot of new features
and use cases which were not possible with classical virtual machines.
We will focus on one of those features: separation of operational
concerns. Specifically, we will demonstrate how some fundamental tasks
like logging, remote access, backups, and troubleshooting can be
entirely decoupled from the deployment of applications and
services. This decoupling results in independent, smaller, simpler
moving parts; just like microservice architectures break down large
monolithic apps in more manageable components.
Orchestrating Docker containers at scaleMaciej Lasyk
Many of us already poked around Docker. Let's recap what we know and then think what do we know about scaling apps & whole environments which are Docker - based? Should we PaaS, IaaS or go with bare? Which tools to use on a given scale?
Christian Kniep from Docker Inc. gave this talk at the Stanford HPC Conference.
"This talk will recap the history of and what constitutes Linux Containers, before laying out how the technology is employed by various engines and what problems these engines have to solve. Afterward, Christian will elaborate on why the advent of standards for images and runtimes moved the discussion from building and distributing containers to orchestrating containerized applications at scale. In conclusion, attendees will get an update on what problems still hinder the adoption of containers for distributed high performance workloads and how Docker is addressing these issues."
Christian Kniep is a Technical Account Manager at Docker, Inc. With a 10 year journey rooted in the HPC parts of the german automotive industry, Christian Kniep started to support CAE applications and VR installations. When told at a conference that HPC can not learn anything from the emerging Cloud and BigData companies, he became curious and was leading the containerization effort of the cloud-stack at Playstation Now. Christian joined Docker Inc in 2017 to help push the adoption forward and be part of the innovation instead of an external bystander. During the day he helps Docker customers in the EMEA region to fully utilize the power of containers; at night he likes to explore new emerging trends by containerizing them first and seek application in the nebulous world of DevOps.
Watch the video: https://wp.me/p3RLHQ-i4X
Learn more: http://docker.com
and
http://hpcadvisorycouncil.com
Sign up for our insideHPC Newsletter: http://insidehpc.com
Describes what is lightweight virtualization and containers, and the low-level mechanisms in the Linux kernel that it relies on: namespaces, cgroups. It also gives details on AUFS. Those component together are the key to understanding how modern systems like Docker (http://www.docker.io/) work.
This talk gives a brief introduction to OpenStack and Chef, then outlines the current state of deploying OpenStack with Chef. There was a live demo deploying to a Dell rack during the talk.
SCALE 9x, February 25-27 in Los Angeles.
Docker storage drivers by Jérôme PetazzoniDocker, Inc.
The first release of Docker only supported AUFS, and AUFS was available (out of the box) only on Debian and Ubuntu kernel. Then Red Hat wanted Docker to run on its distros, and contributed the Device Mapper driver, and later the BTRFS driver, and recently the overlayfs driver.
Jérôme presents how those drivers compare from a high-level perspective, explaining their pros and cons.
Then he showed each driver in action, and look at low-level implementation details. We won't dive into the golang implementation code itself, but we will explain the concepts of each driver. This will help to better understand how they work, and give some hints when it comes to troubleshoot their behaviour.
Docker Tips And Tricks at the Docker Beijing MeetupJérôme Petazzoni
This talk was presented in October at the Docker Beijing Meetup, in the VMware offices.
It presents some of the latest features of Docker, discusses orchestration possibilities with Docker, then gives a briefing about the performance of containers; and finally shows how to use volumes to decouple components in your applications.
LXC, Docker, security: is it safe to run applications in Linux Containers?Jérôme Petazzoni
Linux Containers (or LXC) is now a popular choice for development and testing environments. As more and more people use them in production deployments, they face a common question: are Linux Containers secure enough? It is often claimed that containers have weaker isolation than virtual machines. We will explore whether this is true, if it matters, and what can be done about it.
Cgroups, namespaces, and beyond: what are containers made from? (DockerCon Eu...Jérôme Petazzoni
Linux containers are different from Solaris Zones or BSD Jails: they use discrete kernel features like cgroups, namespaces, SELinux, and more. We will describe those mechanisms in depth, as well as demo how to put them together to produce a container. We will also highlight how different container runtimes compare to each other.
This talk was delivered at DockerCon Europe 2015 in Barcelona.
Anatomy of a Container: Namespaces, cgroups & Some Filesystem Magic - LinuxConJérôme Petazzoni
Containers are everywhere. But what exactly is a container? What are they made from? What's the difference between LXC, butts-nspawn, Docker, and the other container systems out there? And why should we bother about specific filesystems?
In this talk, Jérôme will show the individual roles and behaviors of the components making up a container: namespaces, control groups, and copy-on-write systems. Then, he will use them to assemble a container from scratch, and highlight the differences (and likelinesses) with existing container systems.
Cgroups, namespaces and beyond: what are containers made from?Docker, Inc.
Linux containers are different from Solaris Zones or BSD Jails: they use discrete kernel features like cgroups, namespaces, SELinux, and more. We will describe those mechanisms in depth, as well as demo how to put them together to produce a container. We will also highlight how different container runtimes compare to each other.
Containerization is more than the new Virtualization: enabling separation of ...Jérôme Petazzoni
Docker offers a new, lightweight approach to application
portability. Applications are shipped using a common container format,
and managed with a high-level API. Their processes run within isolated
namespaces which abstract the operating environment, independently of
the distribution, versions, network setup, and other details of this
environment.
This "containerization" has often been nicknamed "the new
virtualization". But containers are more than lightweight virtual
machines. Beyond their smaller footprint, shorter boot times, and
higher consolidation factors, they also bring a lot of new features
and use cases which were not possible with classical virtual machines.
We will focus on one of those features: separation of operational
concerns. Specifically, we will demonstrate how some fundamental tasks
like logging, remote access, backups, and troubleshooting can be
entirely decoupled from the deployment of applications and
services. This decoupling results in independent, smaller, simpler
moving parts; just like microservice architectures break down large
monolithic apps in more manageable components.
Orchestrating Docker containers at scaleMaciej Lasyk
Many of us already poked around Docker. Let's recap what we know and then think what do we know about scaling apps & whole environments which are Docker - based? Should we PaaS, IaaS or go with bare? Which tools to use on a given scale?
Christian Kniep from Docker Inc. gave this talk at the Stanford HPC Conference.
"This talk will recap the history of and what constitutes Linux Containers, before laying out how the technology is employed by various engines and what problems these engines have to solve. Afterward, Christian will elaborate on why the advent of standards for images and runtimes moved the discussion from building and distributing containers to orchestrating containerized applications at scale. In conclusion, attendees will get an update on what problems still hinder the adoption of containers for distributed high performance workloads and how Docker is addressing these issues."
Christian Kniep is a Technical Account Manager at Docker, Inc. With a 10 year journey rooted in the HPC parts of the german automotive industry, Christian Kniep started to support CAE applications and VR installations. When told at a conference that HPC can not learn anything from the emerging Cloud and BigData companies, he became curious and was leading the containerization effort of the cloud-stack at Playstation Now. Christian joined Docker Inc in 2017 to help push the adoption forward and be part of the innovation instead of an external bystander. During the day he helps Docker customers in the EMEA region to fully utilize the power of containers; at night he likes to explore new emerging trends by containerizing them first and seek application in the nebulous world of DevOps.
Watch the video: https://wp.me/p3RLHQ-i4X
Learn more: http://docker.com
and
http://hpcadvisorycouncil.com
Sign up for our insideHPC Newsletter: http://insidehpc.com
Describes what is lightweight virtualization and containers, and the low-level mechanisms in the Linux kernel that it relies on: namespaces, cgroups. It also gives details on AUFS. Those component together are the key to understanding how modern systems like Docker (http://www.docker.io/) work.
This talk gives a brief introduction to OpenStack and Chef, then outlines the current state of deploying OpenStack with Chef. There was a live demo deploying to a Dell rack during the talk.
SCALE 9x, February 25-27 in Los Angeles.
Docker storage drivers by Jérôme PetazzoniDocker, Inc.
The first release of Docker only supported AUFS, and AUFS was available (out of the box) only on Debian and Ubuntu kernel. Then Red Hat wanted Docker to run on its distros, and contributed the Device Mapper driver, and later the BTRFS driver, and recently the overlayfs driver.
Jérôme presents how those drivers compare from a high-level perspective, explaining their pros and cons.
Then he showed each driver in action, and look at low-level implementation details. We won't dive into the golang implementation code itself, but we will explain the concepts of each driver. This will help to better understand how they work, and give some hints when it comes to troubleshoot their behaviour.
Docker Tips And Tricks at the Docker Beijing MeetupJérôme Petazzoni
This talk was presented in October at the Docker Beijing Meetup, in the VMware offices.
It presents some of the latest features of Docker, discusses orchestration possibilities with Docker, then gives a briefing about the performance of containers; and finally shows how to use volumes to decouple components in your applications.
LXC, Docker, security: is it safe to run applications in Linux Containers?Jérôme Petazzoni
Linux Containers (or LXC) is now a popular choice for development and testing environments. As more and more people use them in production deployments, they face a common question: are Linux Containers secure enough? It is often claimed that containers have weaker isolation than virtual machines. We will explore whether this is true, if it matters, and what can be done about it.
CERN OpenStack Cloud Control Plane - From VMs to K8sBelmiro Moreira
CERN is the home of the Large Hadron Collider (LHC), a 27km circular proton accelerator that generates petabytes of physics data every year. To process all this data, CERN runs an OpenStack Cloud (>300K cores) that helps scientists all around the world to unveil the mysteries of the Universe. The Infrastructure is also used to run all the IT services of the Organization.
Delivering these services, with high performance and reliable service levels has been one of the major challenges for the CERN Cloud engineering team. We have been constantly iterating the architecture and deployment model of the Cloud control plane.
In this presentation we will describe the different control plane architecture models that we relied over the years. Finally, we will describe all the work done to move the OpenStack Cloud control plane from VMs into a kubernetes cluster. We will report about our experience running this architecture at scale, its advantages and challenges.
Metal-k8s presentation by Julien Girardin @ Paris Kubernetes MeetupLaure Vergeron
Julien Girardin presents metal-k8s, an opinionated Kubernetes distribution designed for bare-metal deployments. Julien explains why we chose certain Kubespray plugins over others for Zenko's needs of scalability and petabyte-scale storage over multiple public and private clouds.
KubeCon EU 2016: Leveraging ephemeral namespaces in a CI/CD pipelineKubeAcademy
One of the most underrated features of Kubernetes is namespaces. In the market, instead of using this feature, people are still stuck with having different clusters for their environments. This talk will try to break this approach, and will introduce how we end up using ephemeral namespaces within our CI/CD pipeline. It will cover the architecture of our system for running the user acceptance tests on isolated ephemeral namespaces with every bits and pieces running within pods. While doing this, we will set up our CI/CD pipeline on top of TravisCI, GoCD, and Selenium that is controlled by Nightwatch.js.
Sched Link: http://sched.co/6Bcb
Presentation at March 2019 Dutch Postgres User Group Meetup on lessons learnt while migrating from Oracle to Postgres, demo'ed via vagrant test environments and using generic pgbench datasets.
DCSF 19 Accelerating Docker Containers with NVIDIA GPUsDocker, Inc.
Using the NVIDIA Container Runtime, many developers and enterprises have been developing, benchmarking and deploying deep learning (DL) frameworks, HPC and other GPU accelerated containers at scale for the last two years. In this talk, we will go over the architecture of the NVIDIA Container Runtime and discuss our recent close collaboration with Docker. The result of our collaboration with Docker is a seamless native integration of the runtime enabling Docker Engine 19.03 CE and the forthcoming Docker Enterprise release to run GPU accelerated containers. We will also highlight containerized NVIDIA drivers. This new feature eliminates the overhead of provisioning GPU machines and brings GPU support on container optimized operating systems, which either lack package managers for installing software or require all applications to run in containers. In this session, you will learn how GPU accelerated containers can be easily built and deployed through the use of driver containers and native support for GPUs in Docker 19.03. The session will include a demo of running a GPU accelerated deep learning container using the new CLI options in Docker 19.03 and containerized drivers. Running NVIDIA GPU accelerated containers with Docker has never been this easy!
OpenNebulaConf 2016 - OpenNebula, a story about flexibility and technological...OpenNebula Project
Cloud providers are constantly addressing the technology limitations on their infrastructures, which must be overcome to meet customer needs. On this presentation, we will demonstrate how technological agnosticism and management flexibility of OpenNebula has allowed Todoencloud to provide the most efficient open source solution to the needs of its customers, choosing the most appropriate virtualization technology (Xen and KVM), storage approach (ZFS vs CEPH), Cloud Bursting solutions (Azure, Amazon) and customized networking topologies.
Cumulus Linux supports great networking, what’s next? Matt Peterson (@dorkmatt) our resident expert from the office of the CTO shares his previous experience, his views on devops, and how Cumulus Networks makes it easier to manage networks with ONIE, ZTP and no CLI! “Devops is a lifestyle, shared responsibility”. With Linux as the networks OS, “it’s all just one apt-get away!”
Drupaljam 2017 - Deploying Drupal 8 onto Hosted Kubernetes in Google CloudDropsolid
In this presentation I explain using video examples how kubernetes works and how this can be used to host your Drupal 7 or 8 site. There are obviously also gotcha's and I'd like to warn you to not use this in production until you've verified it
Docker Engine 1.12 can be rightly called ” A Next Generation Docker Clustering & Distributed System”. Though Docker Engine 1.12 Final Release is around corner but the recent RC3 brings lots of improvements and exciting features. One of the major highlight of this release is Docker Swarm Mode which provides powerful yet optional ability to create coordinated groups of decentralized Docker Engines. Swarm Mode combines your engine in swarms of any scale. It’s self-organizing and self-healing. It enables infrastructure-agnostic topology.The newer version democratizes orchestration with out-of-box capabilities for multi-container on multi-host app deployments.
Citrix TechEdge 2014 - Advanced Tools and Techniques for Troubleshooting NetS...David McGeough
This session will cover advanced techniques in troubleshooting the Citrix NetScaler Appliance using tools such as Citrix TaaS, IPMI, nsconmsg, wireshark and log analysis. We will review usages of these tools along with case studies showing how to best troubleshoot common issues seen in operating Citrix NetScaler Appliances.
What you will learn
- Various tools available to troubleshoot issues and how to use them to isolate NetScaler Issues
- Common deployment problems and how to isolate the causes
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
4. Increasing Revenue: Do More With Less
Reduce Total Cost of Ownership (TCO) and increase Return On Investment (ROI)
6/11/2014 4
Category Factors Scope
CAPEX
Hardware costs - VM density (consolidation ratio)
- Soft device integration
- Broad vendor compatibility
- Hypervisor
- Cloud manager
Software licensing costs - Software purchase price
- Support contracts
- Hypervisor
- Cloud manager
OPEX
Disaster recovery - Hypervisor
- Cloud manager
Upgrade / maintenance expenses - Hypervisor
- Cloud manager
Power & cooling costs - Reduced HW footprint - Hypervisor
- Cloud manager
Administration efficiency - Automated operations
- Performance / response time
- Hypervisor
- Cloud manager
Support & training costs - Hypervisor
- Cloud manager
AGILITY
Application delivery time - Workflow complexity
- Toolset costs
- Skillset
- Hypervisor
- Cloud manager
Planned / unplanned downtime - Hypervisor
- Cloud manager
*Not a complete or extensive list
5. About This Benchmark
Use case perspective
– As an OpenStack Cloud user I want a Ubuntu based VM with MySQL… Why would I choose
docker LXC vs a traditional hypervisor?
OpenStack “Cloudy” perspective
– LXC vs. traditional VM from a Cloudy (OpenStack) perspective
– VM operational times (boot, start, stop, snapshot)
– Compute node resource usage (per VM penalty); density factor
Guest runtime perspective
– CPU, memory, file I/O, MySQL OLTP, etc.
Why KVM?
– Exceptional performance
DISCLAIMERS
The tests herein are semi-active litmus tests – no in depth tuning,
analysis, etc. More active testing is warranted. These results do not
necessary reflect your workload or exact performance nor are they
guaranteed to be statistically sound.
6/11/2014 5
6. Docker in OpenStack
Havana
– Nova virt driver which integrates with docker REST API on backend
– Glance translator to integrate docker images with Glance
Icehouse
– Heat plugin for docker
Both options are still under development
6/11/2014 6
nova-docker virt driver docker heat plugin
DockerInc::Docke
r::Container
(plugin)
7. Benchmark Environment Topology @ SoftLayer
6/11/2014 7
glance api / reg
nova api / cond / etc
keystone
…
rally
nova api / cond / etc
cinder api / sch / vol
docker lxc
dstat
controller compute node
glance api / reg
nova api / cond / etc
keystone
…
rally
nova api / cond / etc
cinder api / sch / vol
KVM
dstat
controller compute node
+
Awesome!
+
Awesome!
8. Benchmark Specs
6/11/2014 8
Spec Controller Node (4CPU x 8G RAM) Compute Node (16CPU x 96G RAM)
Environment Bare Metal @ SoftLayer Bare Metal @ SoftLayer
Mother Board SuperMicro X8SIE-F Intel Xeon QuadCore SingleProc SATA
[1Proc]
SuperMicro X8DTU-F_R2 Intel Xeon HexCore DualProc [2Proc]
CPU Intel Xeon-Lynnfield 3470-Quadcore [2.93GHz] (Intel Xeon-Westmere 5620-Quadcore [2.4GHz]) x 2
Memory (Kingston 4GB DDR3 2Rx8 4GB DDR3 2Rx8 [4GB]) x2 (Kingston 16GB DDR3 2Rx4 16GB DDR3 2Rx4 [16GB]) x 6
HDD (LOCAL) Digital WD Caviar RE3 WD5002ABYS [500GB]; SATAII Western Digital WD Caviar RE4 WD5003ABYX [500GB]; SATAII
NIC eth0/eth1 @ 100 Mbps eth0/eth1 @100 Mbps
Operating System Ubuntu 12.04 LTS 64bit Ubuntu 12.04 LTS 64bit
Kernel 3.5.0-48-generic 3.8.0-38-generic
IO Scheduler deadline deadline
Hypervisor tested NA - KVM 1.0 + virtio + KSM (memory deduplication)
- docker 0.10.0 + go1.2.1 + commit dc9c28f + AUFS
OpenStack Trunk master via devstack Trunk master via devstack. Libvirt KVM nova driver / nova-docker
virt driver
OpenStack Benchmark
Client
OpenStack project rally NA
Metrics Collection NA dstat
Guest Benchmark Driver NA - Sysbench 0.4.12
- mbw 1.1.1.-2
- iibench (py)
- netperf 2.5.0-1
- Blogbench 1.1
- cpu_bench.py
VM Image NA - Scenario 1 (KVM): official ubuntu 12.04 image + mysql
snapshotted and exported to qcow2 – 1080 MB
- Scenario 2 (docker): guillermo/mysql -- 381.5 MB
Hosted @
9. STEADY STATE VM PACKING
OpenStack Cloudy Benchmark
6/11/2014 9
10. Cloudy Performance: Steady State Packing
Benchmark scenario overview
– Pre-cache VM image on compute node prior to test
– Boot 15 VM asynchronously in succession
– Wait for 5 minutes (to achieve steady-state on the
compute node)
– Delete all 15 VMs asynchronously in succession
Benchmark driver
– cpu_bench.py
High level goals
– Understand compute node characteristics under
steady-state conditions with 15 packed / active VMs
6/11/2014 10
0
2
4
6
8
10
12
14
16
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47
ActiveVMs
Time
Benchmark Visualization
VMs
17. Cloudy Performance: Serial VM Boot
Benchmark scenario overview
– Pre-cache VM image on compute node prior to test
– Boot VM
– Wait for VM to become ACTIVE
– Repeat the above steps for a total of 15 VMs
– Delete all VMs
Benchmark driver
– OpenStack Rally
High level goals
– Understand compute node characteristics under
sustained VM boots
6/11/2014 17
0
2
4
6
8
10
12
14
16
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
ActiveVMs
Time
Benchmark Visualization
VMs
18. Cloudy Performance: Serial VM Boot
6/11/2014 18
3.529113102
5.781662448
0
1
2
3
4
5
6
7
docker KVM
TimeInSeconds
Average Server Boot Time
docker
KVM
25. SERIAL VM SOFT REBOOT
OpenStack Cloudy Benchmark
6/11/2014 25
26. Cloudy Performance: Serial VM Reboot
Benchmark scenario overview
– Pre-cache VM image on compute node prior to test
– Boot a VM & wait for it to become ACTIVE
– Soft reboot the VM and wait for it to become ACTIVE
• Repeat reboot a total of 5 times
– Delete VM
– Repeat the above for a total of 5 VMs
Benchmark driver
– OpenStack Rally
High level goals
– Understand compute node characteristics under sustained VM reboots
6/11/2014 26
0
1
2
3
4
5
6
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55
ActiveVMs
Time
Benchmark Visualization
Active VMs
27. Cloudy Performance: Serial VM Reboot
6/11/2014 27
2.577879581
124.433239
0
20
40
60
80
100
120
140
docker KVM
TimeInSeconds
Average Server Reboot Time
docker
KVM
28. Cloudy Performance: Serial VM Reboot
6/11/2014 28
3.567586041
3.479760051
0
0.5
1
1.5
2
2.5
3
3.5
4
docker KVM
TimeInSeconds
Average Server Delete Time
docker
KVM
32. SNAPSHOT VM TO IMAGE
OpenStack Cloudy Benchmark
6/11/2014 32
33. Cloudy Performance: Snapshot VM To Image
Benchmark scenario overview
– Pre-cache VM image on compute node prior to test
– Boot a VM
– Wait for it to become ACTIVE
– Snapshot the VM
– Wait for image to become ACTIVE
– Delete VM
Benchmark driver
– OpenStack Rally
High level goals
– Understand cloudy ops times from a user perspective
6/11/2014 33
34. Cloudy Performance: Snapshot VM To Image
6/11/2014 34
36.88756394
48.02313805
0
10
20
30
40
50
60
docker KVM
TimeInSeconds
Average Snapshot Server Time
docker
KVM
45. Cloud Management Impacts on docker LXC
0.17
3.529113102
0
0.5
1
1.5
2
2.5
3
3.5
4
docker cli nova-docker
Seconds
Docker: Boot Container - CLI vs Nova Virt
docker cli
nova-docker
6/11/2014 45
Cloud management often caps true ops performance of LXC
46. Ubuntu MySQL Image Size
381.5
1080
0
200
400
600
800
1000
1200
docker kvm
SizeInMB
Docker / KVM: Ubuntu MySQL
docker
kvm
6/11/2014 46
Out of the box JeOS images for docker are lightweight
47. In Summary
Near bare metal performance in the guest
Fast operations in the Cloud
– Often capped by Cloud management framework
Reduced resource consumption (CPU, MEM) on the compute
node – greater density
Out of the box smaller image footprint
6/11/2014 47
Let me start off by saying– it’s very exciting to be here at the 1st dockercon and I hope this is the start of many more
Welcome, before getting started a little about me and containers and in particular about docker
Boden Russell , IBM GTS – advanced cloud solutions & innovation team
SL engagenments including customre PoCs, managed and as a service realizations
One of my favoritate parts of this job – nextgen technology evals and recommend to broader IBM community
In about nov of last year we started evaluating LXC
Tried vairous lxc user toolsets.. .kept coming back to docker
Since then we’ve done some other research with LXC including SAP HANA for education purposes as well as other things
Looking across the industry appeared to be a gap in docs talking about LXC from a Cloud perspective vs hypers
I set out to do some semi-active testing using OpenStack with KVM and docker --- the results we’ll talk about today
Before getting started on the technicals, lets take a mintue to step back and consider why these results are import
What motivates me from a technology / industry perspective…
Consider myself a technologist / scientist, as a result of this I strive to work on projects which have a certain degree of awesomness… obviously docker has a massive degress of awesomeness
I strive for projects and technologies which allow me to use creativity and innovation
Revenue is important to me in that I must support my family
However, I’m willing to consider less revenue as long as I can support my familiy to work on something which is innovate / creative / exciting
Why am I telling you this…. I believe there are a number of people in the community and even in this room who follow these values.. They prioritize working on things they are passionate about above revenue (to a degree).
So what motivates larger companies say those who are making key tech decisions in the enterprise space??...
What do you think movitvates technical decisions in industry?
If you ask and transparent exec making key tech decisions in enterprise, they will tell you: revenue, revenue, revenue
You might argue otherwise – our goal is provide the best use experience possible, or all the features our customers wants, etc..
I would argue All of these are directly related to revenue.
So, how can we increase revenue in this space??
In a nutshell – do more with less
More specifically you will see the benefits of virt and cloud discussed within the context of reducing TCO and increasing the ROI
There are various aspects which impact TCO and ROI and this chart briefly outlines some of the more common categories.
Let’s just cover a few of these which I believe