This document discusses Puppet, an open source configuration management tool. It can be used to automate system configuration, deployment, and administration tasks across Linux, Unix, and Windows systems. Puppet uses a master-slave architecture with Puppet masters distributing configuration files to Puppet agents. It provides a declarative language to define system configurations and resources.
Kubernetes Jobによるバッチシステムのリソース最適化 / AbemaTV DevCon 2018 TrackB Session B6AbemaTV, Inc.
This document discusses transcoding video files using Kubernetes jobs. It describes creating different job pods for each transcoding task, such as 1080p, 720p, etc. It shows configuring the jobs with specifications for parallelism, completions, and restart policies. The document also discusses using the Kubernetes client API to watch for job status changes in order to manage the transcoding workflow.
Kubernetes Jobによるバッチシステムのリソース最適化 / AbemaTV DevCon 2018 TrackB Session B6AbemaTV, Inc.
This document discusses transcoding video files using Kubernetes jobs. It describes creating different job pods for each transcoding task, such as 1080p, 720p, etc. It shows configuring the jobs with specifications for parallelism, completions, and restart policies. The document also discusses using the Kubernetes client API to watch for job status changes in order to manage the transcoding workflow.
Devoxx 2009 University session Jbpm4 In ActionJoram Barrez
- The document discusses the history and capabilities of jBPM, an open source business process management system.
- It provides biographies of the founders and an agenda for the discussion.
- The main points are that jBPM allows modeling of business processes, provides execution and monitoring of those processes, and has advantages for both business users and technical users.
RabbitMQ with python and ruby RuPy 2009Paolo Negri
The document discusses using RabbitMQ, an open-source message broker based on AMQP, for asynchronous messaging between Python and Ruby applications. It provides an overview of AMQP concepts like producers, consumers, exchanges and queues, and how RabbitMQ implements these using Erlang. Code examples are shown for sending and receiving messages asynchronously in Python and Ruby.
The document discusses using NetApp snapshot technology to improve database refreshes for development, QA, and testing environments. Currently refresh takes over 10 days using RMAN backup and restore. The proposed solution uses FlexVol cloning to create private copies of the production database with minimal storage. This allows frequent refreshes without impacting production performance or other environments. It provides scalability improvements over the existing process.
Rocket Fuelled Cucumbers discusses strategies for dealing with slow cucumber test suites, including:
- Using Spork to preload support code to speed up test runs
- Tagging tests to run focused subsets based on features, filenames, or tags
- Distributing tests across multiple servers using Testjour to parallelize testing
- Looking to cloud providers like EC2 to gain additional hardware resources
- Dividing applications and tests along service boundaries to isolate components
Jamie Winsor and a team of engineers created Berkshelf to help take the sting out of Chef’s learning curve. After encountering numerous challenges while developing Chef cookbooks, Jamie was inspired to create a tool based on criteria that’d be important for a developer’s productivity. Berkshelf, like Rebar, Go, or Mix, is a source code management tool.
This document provides an introduction to using Ansible in a top-down approach. It discusses using Ansible to provision infrastructure including load balancers, application servers, and databases. It covers using ad-hoc commands and playbooks to configure systems. Playbooks can target groups of hosts, apply roles to automate common tasks, and allow variables to customize configurations. Selective execution allows running only certain parts of a playbook. Overall the document demonstrates how Ansible can be used to deploy and manage infrastructure and applications in a centralized, automated way.
1. The document provides instructions for upgrading the image on an 8600 switch, including copying new image and configuration files from a server, formatting the flash memory, and rebooting the switch with the new image.
2. It then lists configurations for various protocols and features including OSPF, MLT, Spanning Tree, DHCP Relay, port mirroring, NTP, Radius, VRRP, MAC security, broadcast/multicast rate limiting, static routes, ATM PVCs with VLAN mapping, and RIP.
3. The document finishes with configurations for access policies, syslog server, port tagging, and global port settings.
The document discusses moving a project from Subversion to Git version control. It describes the typical Subversion workflow with a trunk branch and stable release tags. It then outlines some of the issues this can cause like merge hell and broken builds. The document proposes migrating the codebase to Git, describing how to convert the Subversion repository to Git, mirror changes between the two systems, and migrate tools and developers over to the new Git workflow. It contrasts the new Git workflow with branches for features and bug fixes that can be easily merged into the master branch.
This document discusses how to use Docker to containerize and deploy Python web applications. It provides steps to install Docker, build a sample Flask application into a Docker image, run the container locally, and deploy the containerized application to AWS. Key points covered include using Dockerfiles to create images, the Docker index for sharing images, and port mapping when running containers.
Behind the Scenes at LiveJournal: Scaling StorytimeSergeyChernyshev
Brad talks about clustering setups using MySQL and DRDB and their Open Source software most of which he wrote initially and continues to develop.
A lot of these techniques and/or software is used by many other companies as well - among them Flickr/Yahoo! and Facebook.
Lorsque la quantité de données est très grande et que l'architecture de votre réseau de neurones est complexe, la question du temps d'entraînement et de la capacité de votre machine deviennent primordiales. Un entraînement de modèle peut vite prendre plusieurs heures voire jours, ou même ne pas tenir en mémoire. Il est alors temps de parler de Deep Learning distribué !
Au cours de cette présentation, nous allons voir différentes solutions et bonnes pratiques pour accélérer l'entraînement de modèles de Deep Learning en les distribuant sur un cluster ou sur des plateformes multi-GPUs.
Par Yoann Benoit, Data Scientist et Technical Officer chez Xebia
Toutes les informations sur xebicon.fr
The document discusses speculation and speculative execution in modern microprocessors. It explains that processors predict upcoming instructions and speculatively execute them to improve performance. If the prediction is correct, the results are committed, but if not the results are discarded. The document also discusses how transistor counts have increased quadratically compared to linear speed increases, enabling more complex superscalar and pipeline designs to exploit instruction level parallelism.
Infrastructure as data with Ansible: systems and cloud
deployment and management for the lazy developer
Abstract: Great programmers and sysadmins are lazy people: rightly,
they prefer avoiding manual, time consuming and error-prone tasks such
as installing and configuring a Linux/Apache/Tomcat cluster for the
tenth time.
Ansible, an infrastructure (server, cloud) deployment automation &
configuration both powerful AND simple (in most cases simpler than
shell scripts and maven poms!), will make developers and it staff more
productive and effective.
http://www.ansible.cc
Infrastructure as data with Ansible: systems and cloud deployment and managem...Codemotion
Great programmers and sysadmins are lazy people: rightly, they prefer avoiding manual, time consuming and error-prone tasks such as installing and configuring a Linux, Apache, Tomcat cluster for the tenth time.
With Ansible, an infrastructure (server, cloud) deployment automation & configuration both powerful AND simple (in most cases simpler than shell scripts and maven poms!), you can enjoy your coffee while it does all the work.
The talk is very practical: I will set up a whole cluster in real time before the talk ends.
Devoxx 2009 University session Jbpm4 In ActionJoram Barrez
- The document discusses the history and capabilities of jBPM, an open source business process management system.
- It provides biographies of the founders and an agenda for the discussion.
- The main points are that jBPM allows modeling of business processes, provides execution and monitoring of those processes, and has advantages for both business users and technical users.
RabbitMQ with python and ruby RuPy 2009Paolo Negri
The document discusses using RabbitMQ, an open-source message broker based on AMQP, for asynchronous messaging between Python and Ruby applications. It provides an overview of AMQP concepts like producers, consumers, exchanges and queues, and how RabbitMQ implements these using Erlang. Code examples are shown for sending and receiving messages asynchronously in Python and Ruby.
The document discusses using NetApp snapshot technology to improve database refreshes for development, QA, and testing environments. Currently refresh takes over 10 days using RMAN backup and restore. The proposed solution uses FlexVol cloning to create private copies of the production database with minimal storage. This allows frequent refreshes without impacting production performance or other environments. It provides scalability improvements over the existing process.
Rocket Fuelled Cucumbers discusses strategies for dealing with slow cucumber test suites, including:
- Using Spork to preload support code to speed up test runs
- Tagging tests to run focused subsets based on features, filenames, or tags
- Distributing tests across multiple servers using Testjour to parallelize testing
- Looking to cloud providers like EC2 to gain additional hardware resources
- Dividing applications and tests along service boundaries to isolate components
Jamie Winsor and a team of engineers created Berkshelf to help take the sting out of Chef’s learning curve. After encountering numerous challenges while developing Chef cookbooks, Jamie was inspired to create a tool based on criteria that’d be important for a developer’s productivity. Berkshelf, like Rebar, Go, or Mix, is a source code management tool.
This document provides an introduction to using Ansible in a top-down approach. It discusses using Ansible to provision infrastructure including load balancers, application servers, and databases. It covers using ad-hoc commands and playbooks to configure systems. Playbooks can target groups of hosts, apply roles to automate common tasks, and allow variables to customize configurations. Selective execution allows running only certain parts of a playbook. Overall the document demonstrates how Ansible can be used to deploy and manage infrastructure and applications in a centralized, automated way.
1. The document provides instructions for upgrading the image on an 8600 switch, including copying new image and configuration files from a server, formatting the flash memory, and rebooting the switch with the new image.
2. It then lists configurations for various protocols and features including OSPF, MLT, Spanning Tree, DHCP Relay, port mirroring, NTP, Radius, VRRP, MAC security, broadcast/multicast rate limiting, static routes, ATM PVCs with VLAN mapping, and RIP.
3. The document finishes with configurations for access policies, syslog server, port tagging, and global port settings.
The document discusses moving a project from Subversion to Git version control. It describes the typical Subversion workflow with a trunk branch and stable release tags. It then outlines some of the issues this can cause like merge hell and broken builds. The document proposes migrating the codebase to Git, describing how to convert the Subversion repository to Git, mirror changes between the two systems, and migrate tools and developers over to the new Git workflow. It contrasts the new Git workflow with branches for features and bug fixes that can be easily merged into the master branch.
This document discusses how to use Docker to containerize and deploy Python web applications. It provides steps to install Docker, build a sample Flask application into a Docker image, run the container locally, and deploy the containerized application to AWS. Key points covered include using Dockerfiles to create images, the Docker index for sharing images, and port mapping when running containers.
Behind the Scenes at LiveJournal: Scaling StorytimeSergeyChernyshev
Brad talks about clustering setups using MySQL and DRDB and their Open Source software most of which he wrote initially and continues to develop.
A lot of these techniques and/or software is used by many other companies as well - among them Flickr/Yahoo! and Facebook.
Lorsque la quantité de données est très grande et que l'architecture de votre réseau de neurones est complexe, la question du temps d'entraînement et de la capacité de votre machine deviennent primordiales. Un entraînement de modèle peut vite prendre plusieurs heures voire jours, ou même ne pas tenir en mémoire. Il est alors temps de parler de Deep Learning distribué !
Au cours de cette présentation, nous allons voir différentes solutions et bonnes pratiques pour accélérer l'entraînement de modèles de Deep Learning en les distribuant sur un cluster ou sur des plateformes multi-GPUs.
Par Yoann Benoit, Data Scientist et Technical Officer chez Xebia
Toutes les informations sur xebicon.fr
The document discusses speculation and speculative execution in modern microprocessors. It explains that processors predict upcoming instructions and speculatively execute them to improve performance. If the prediction is correct, the results are committed, but if not the results are discarded. The document also discusses how transistor counts have increased quadratically compared to linear speed increases, enabling more complex superscalar and pipeline designs to exploit instruction level parallelism.
Infrastructure as data with Ansible: systems and cloud
deployment and management for the lazy developer
Abstract: Great programmers and sysadmins are lazy people: rightly,
they prefer avoiding manual, time consuming and error-prone tasks such
as installing and configuring a Linux/Apache/Tomcat cluster for the
tenth time.
Ansible, an infrastructure (server, cloud) deployment automation &
configuration both powerful AND simple (in most cases simpler than
shell scripts and maven poms!), will make developers and it staff more
productive and effective.
http://www.ansible.cc
Infrastructure as data with Ansible: systems and cloud deployment and managem...Codemotion
Great programmers and sysadmins are lazy people: rightly, they prefer avoiding manual, time consuming and error-prone tasks such as installing and configuring a Linux, Apache, Tomcat cluster for the tenth time.
With Ansible, an infrastructure (server, cloud) deployment automation & configuration both powerful AND simple (in most cases simpler than shell scripts and maven poms!), you can enjoy your coffee while it does all the work.
The talk is very practical: I will set up a whole cluster in real time before the talk ends.
This document discusses the evolution of data center networks from routing to switching. It introduces FabricPath, a technology that brings routing capabilities like equal-cost multipathing to layer 2 switching networks. FabricPath uses IS-IS for its control plane and encapsulates frames with MAC-in-MAC headers to implement multi-destination trees and distributed forwarding across the fabric. This allows large layer 2 domains with fast convergence and scalability comparable to routing networks, while maintaining simplicity of configuration and operation of traditional switching.