Demystifying Containerization Principles for Data Scientists - An introductory tutorial on how Dockers can be used as a development environment for data science projects
Containers vs. VMs: It's All About the Apps!Steve Wilson
There has been much hype about whether Containers will replace Virtual Machines for use in Cloud architectures. We’ll look at the strengths of each technology and how they apply in real-world usage. By taking a top-down (Application-first) approach to requirements analysis, versus a bottoms-up (Infrastructure-first) approach, we can see how unique architectures will emerge that can balance the needs of Developers, DevOps and corporate IT.
Containerization Principles Overview for app development and deploymentDr Ganesh Iyer
This is the slide deck from recent Workshop conducted as part of IEEE INDICON 2018 on Containerization principles for next-generation application development and deployment.
Bare-metal, Docker Containers, and Virtualization: The Growing Choices for Cl...Odinot Stanislas
(FR)
Introduction très sympathique autour des environnements Cloud avec un focus particulier sur la virtualisation et les containers (Docker)
(ENG)
Friendly presentation about Cloud solutions with a focus on virtualization and containers (Docker).
Author: Nicholas Weaver – Principal Architect, Intel Corporation
Containers vs. VMs: It's All About the Apps!Steve Wilson
There has been much hype about whether Containers will replace Virtual Machines for use in Cloud architectures. We’ll look at the strengths of each technology and how they apply in real-world usage. By taking a top-down (Application-first) approach to requirements analysis, versus a bottoms-up (Infrastructure-first) approach, we can see how unique architectures will emerge that can balance the needs of Developers, DevOps and corporate IT.
Containerization Principles Overview for app development and deploymentDr Ganesh Iyer
This is the slide deck from recent Workshop conducted as part of IEEE INDICON 2018 on Containerization principles for next-generation application development and deployment.
Bare-metal, Docker Containers, and Virtualization: The Growing Choices for Cl...Odinot Stanislas
(FR)
Introduction très sympathique autour des environnements Cloud avec un focus particulier sur la virtualisation et les containers (Docker)
(ENG)
Friendly presentation about Cloud solutions with a focus on virtualization and containers (Docker).
Author: Nicholas Weaver – Principal Architect, Intel Corporation
Hypervisor "versus" Linux Containers!
Docker is an open-source engine that automates the deployment of any application as a lightweight, portable, self-sufficient container that will run virtually anywhere.
Less hardware, less pain and more scalability in production, on VMs, bare-metal servers, OpenStack clusters, public instances, or combinations of the above. "Do more with less " and this is all that matters!
Automation of server and applications deployments never had been so easy and fast that ever. Also brings produtivity to a new level, in the DataCenters and Cloud Environments.
Francisco Gonçalves (Dec2013
( francis.goncalves@gmail.com )
As Docker containers become the new standard, learn about what's catapulting them to the head of the pack and how to best protect their assets now and later with the help of Unitrends.
Mit Urs Stephan Alder (CEO Kybernetika), Michael Abmayer (Senior Consultant Opvizor) und Dennis Zimmer (CEO Opvizor) präsentierten gleich 3 hochkarätige Referenten an der vergangenen VMware@Night bei Digicomp. Sie zeigten zusammen auf, welche Auswirkungen Container in der Virtualisierung auf den täglichen Betrieb sowie die Performance- und Kapazitätsplanung haben.
Vor allem Docker ist derzeit in aller Munde und die bekannteste und meist genutzte Container-Technologie. Container werden vielfach in virtuellen Maschinen betrieben und stellen eine neue Herausforderung für VMware- Administratoren, aber auch IT-Manager dar. Gewährleistung und Überwachung der Performance sowie eine möglichst genaue Kapazitätsplanung sind Herausforderungen, denen man sich zügig stellen muss.
Nach einer kurzen Einführung in die Thematik der Container, in der auch die Unterschiede zur Virtualisierung aufgezeigt wurde, widmeten sich die Referenten dem Umgang mit Conteinern am Beispiel von Docker mit VMware vSphere. Zum Abschluss wurde die Performanceüberwachung und Kapazitätsplanung behandelt.
Evolving to serverless
How the applications are transforming
A note on CI/CD
Architecture of Docker
Setting up a docker environment
Deep dive into DockerFile and containers
Tagging and publishing an image to docker hub
A glimpse from session one
Services: scale our application and enable load-balancing
Swarm: Deploying application onto a cluster, running it on multiple machines
Stack: A stack is a group of interrelated services that share dependencies, and can be orchestrated and scaled together.
Deploy your app: Compose file works just as well in production as it does on your machine.
Extras: Containers and VMs together
Developing with Docker for the Arm ArchitectureDocker, Inc.
This virtual meetup introduces the concepts and best practices of using Docker containers for software development for the Arm architecture across a variety of hardware systems. Using Docker Desktop on Windows or Mac, Amazon Web Services (AWS) A1 instances, and embedded Linux, we will demonstrate the latest Docker features to build, share, and run multi-architecture images with transparent support for Arm.
Discussing the difference between docker dontainers and virtual machinesSteven Grzbielok
This presentation is designed to give an overview about differences of both virtualization methods to provide the reader with the fundamental knowledge to decide in each use case which technology is more suitable.
Containers, Docker, and Microservices: the Terrific TrioJérôme Petazzoni
One of the upsides of Microservices is the ability to deploy often,at arbitrary schedules, and independently of other services, instead of requiring synchronized deployments happening on a fixed time.
But to really leverage this advantage, we need fast, efficient, and reliable deployment processes. That's one of the value propositions of Containers in general, and Docker in particular.
Docker offers a new, lightweight approach to application portability.It can build applications using easy-to-write, repeatable, efficient recipes; then it can ship them across environments using a common container format; and it can run them within isolated namespaces which abstract the operating environment, independently of the distribution,versions, network setup, and other details of this environment.
But Docker can do way more than deploy your apps. Docker also enables you to generalize Microservices principles and apply them on operational tasks like logging, remote access, backups, and troubleshooting.This decoupling results in independent, smaller, simpler moving parts.
Docker vs VM | | Containerization or Virtualization - The Differences | DevOp...Edureka!
** Edureka DevOps Training : https://www.edureka.co/devops **
This Edureka Video on Docker vs VM (Virtual Machine) video compares the Major Differences between Docker and VM. Below are the topics covered in the video:
1. What is Virtual Machine?
2. Benefits of Virtual Machine
3. What are Docker Containers
4. Benefits of Docker Containers
5. Docker vs VM – Main Differences
6. Use Case
Check our complete DevOps playlist here (includes all the videos mentioned in the video): http://goo.gl/O2vo13
Follow us to never miss an update in the future.
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Introduction to dockers and kubernetes. Learn how this helps you to build scalable and portable applications with cloud. It introduces the basic concepts of dockers, its differences with virtualization, then explain the need for orchestration and do some hands-on experiments with dockers
Docker 101 - High level introduction to dockerDr Ganesh Iyer
This deck will help you understand the basics of Docker. It introduces dockers and containers, gives a comparison with virtualization and gives some getting started guides.
Learn, Collaborate & Dockerize. Docker is an open platform that helps you build, ship and run applications anytime and anywhere.
Join Docker Jaipur:
Docker Page: events.docker.com/jaipur
Telegram Group: t.me/dockerjaipur
Twitter: @JaipurDocker
The challenge of application distribution - Introduction to Docker (2014 dec ...Sébastien Portebois
Live recording with the demos: https://www.youtube.com/watch?v=0XRcmJEiZOM
Contents
- The application distribution challenge
- The current solutions
- Introduction to Docker, Containers, and the Matrix from Hell
- Why people care: Separation of Concerns
- Technical Discussion
- Ecosystem, momentum
- How to build Docker images
- How to make containers talk to each other, how to handle data persistence
- Demo 1: isolation
- Demo 2: real case - installing Go Math! Academy, tail –f containers, unit tests
Hypervisor "versus" Linux Containers!
Docker is an open-source engine that automates the deployment of any application as a lightweight, portable, self-sufficient container that will run virtually anywhere.
Less hardware, less pain and more scalability in production, on VMs, bare-metal servers, OpenStack clusters, public instances, or combinations of the above. "Do more with less " and this is all that matters!
Automation of server and applications deployments never had been so easy and fast that ever. Also brings produtivity to a new level, in the DataCenters and Cloud Environments.
Francisco Gonçalves (Dec2013
( francis.goncalves@gmail.com )
As Docker containers become the new standard, learn about what's catapulting them to the head of the pack and how to best protect their assets now and later with the help of Unitrends.
Mit Urs Stephan Alder (CEO Kybernetika), Michael Abmayer (Senior Consultant Opvizor) und Dennis Zimmer (CEO Opvizor) präsentierten gleich 3 hochkarätige Referenten an der vergangenen VMware@Night bei Digicomp. Sie zeigten zusammen auf, welche Auswirkungen Container in der Virtualisierung auf den täglichen Betrieb sowie die Performance- und Kapazitätsplanung haben.
Vor allem Docker ist derzeit in aller Munde und die bekannteste und meist genutzte Container-Technologie. Container werden vielfach in virtuellen Maschinen betrieben und stellen eine neue Herausforderung für VMware- Administratoren, aber auch IT-Manager dar. Gewährleistung und Überwachung der Performance sowie eine möglichst genaue Kapazitätsplanung sind Herausforderungen, denen man sich zügig stellen muss.
Nach einer kurzen Einführung in die Thematik der Container, in der auch die Unterschiede zur Virtualisierung aufgezeigt wurde, widmeten sich die Referenten dem Umgang mit Conteinern am Beispiel von Docker mit VMware vSphere. Zum Abschluss wurde die Performanceüberwachung und Kapazitätsplanung behandelt.
Evolving to serverless
How the applications are transforming
A note on CI/CD
Architecture of Docker
Setting up a docker environment
Deep dive into DockerFile and containers
Tagging and publishing an image to docker hub
A glimpse from session one
Services: scale our application and enable load-balancing
Swarm: Deploying application onto a cluster, running it on multiple machines
Stack: A stack is a group of interrelated services that share dependencies, and can be orchestrated and scaled together.
Deploy your app: Compose file works just as well in production as it does on your machine.
Extras: Containers and VMs together
Developing with Docker for the Arm ArchitectureDocker, Inc.
This virtual meetup introduces the concepts and best practices of using Docker containers for software development for the Arm architecture across a variety of hardware systems. Using Docker Desktop on Windows or Mac, Amazon Web Services (AWS) A1 instances, and embedded Linux, we will demonstrate the latest Docker features to build, share, and run multi-architecture images with transparent support for Arm.
Discussing the difference between docker dontainers and virtual machinesSteven Grzbielok
This presentation is designed to give an overview about differences of both virtualization methods to provide the reader with the fundamental knowledge to decide in each use case which technology is more suitable.
Containers, Docker, and Microservices: the Terrific TrioJérôme Petazzoni
One of the upsides of Microservices is the ability to deploy often,at arbitrary schedules, and independently of other services, instead of requiring synchronized deployments happening on a fixed time.
But to really leverage this advantage, we need fast, efficient, and reliable deployment processes. That's one of the value propositions of Containers in general, and Docker in particular.
Docker offers a new, lightweight approach to application portability.It can build applications using easy-to-write, repeatable, efficient recipes; then it can ship them across environments using a common container format; and it can run them within isolated namespaces which abstract the operating environment, independently of the distribution,versions, network setup, and other details of this environment.
But Docker can do way more than deploy your apps. Docker also enables you to generalize Microservices principles and apply them on operational tasks like logging, remote access, backups, and troubleshooting.This decoupling results in independent, smaller, simpler moving parts.
Docker vs VM | | Containerization or Virtualization - The Differences | DevOp...Edureka!
** Edureka DevOps Training : https://www.edureka.co/devops **
This Edureka Video on Docker vs VM (Virtual Machine) video compares the Major Differences between Docker and VM. Below are the topics covered in the video:
1. What is Virtual Machine?
2. Benefits of Virtual Machine
3. What are Docker Containers
4. Benefits of Docker Containers
5. Docker vs VM – Main Differences
6. Use Case
Check our complete DevOps playlist here (includes all the videos mentioned in the video): http://goo.gl/O2vo13
Follow us to never miss an update in the future.
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Introduction to dockers and kubernetes. Learn how this helps you to build scalable and portable applications with cloud. It introduces the basic concepts of dockers, its differences with virtualization, then explain the need for orchestration and do some hands-on experiments with dockers
Docker 101 - High level introduction to dockerDr Ganesh Iyer
This deck will help you understand the basics of Docker. It introduces dockers and containers, gives a comparison with virtualization and gives some getting started guides.
Learn, Collaborate & Dockerize. Docker is an open platform that helps you build, ship and run applications anytime and anywhere.
Join Docker Jaipur:
Docker Page: events.docker.com/jaipur
Telegram Group: t.me/dockerjaipur
Twitter: @JaipurDocker
The challenge of application distribution - Introduction to Docker (2014 dec ...Sébastien Portebois
Live recording with the demos: https://www.youtube.com/watch?v=0XRcmJEiZOM
Contents
- The application distribution challenge
- The current solutions
- Introduction to Docker, Containers, and the Matrix from Hell
- Why people care: Separation of Concerns
- Technical Discussion
- Ecosystem, momentum
- How to build Docker images
- How to make containers talk to each other, how to handle data persistence
- Demo 1: isolation
- Demo 2: real case - installing Go Math! Academy, tail –f containers, unit tests
My college ppt on topic Docker. Through this ppt, you will understand the following:- What is a container? What is Docker? Why its important for developers? and many more!
Docker - Demo on PHP Application deployment Arun prasath
Docker is an open-source project to easily create lightweight, portable, self-sufficient containers from any application. The same container that a developer builds and tests on a laptop can run at scale, in production, on VMs, bare metal, OpenStack clusters, public clouds and more.
In this demo, I will show how to build a Apache image from a Dockerfile and deploy a PHP application which is present in an external folder using custom configuration files.
Getting Started with Docker - Nick StinematesAtlassian
Docker is an open-source engine that automates the deployment of any application as a lightweight, portable, self-sufficient container that will run virtually anywhere. In this session, you will learn how to get started building your first Docker container, and how to use Docker containers to simplify your CI process.
Docker is the world's leading software containerization platform.
This is a comprehensive introduction to Docker, suitable for delivering in introductory meetups to an audience who does not know about docker.
In case you want to deliver this presentation somewhere, kindly drop me a mail at aditya.konarde@gmail.com
You can contact me at:
Connect with me onLinkedIN: https://www.linkedin.com/in/adityakonarde
Add me on Facebook: https://www.facebook.com/Aditya.Konarde
Tweet to me @aditya_konarde
Docker is a tool designed to make it easier to create, deploy, and run applications
by using containers. Containers allow a developer to package up
an application with all of the parts it needs, such as libraries and other dependencies,
and ship it all out as one package. By doing so, thanks to the
container, the developer can rest assured that the application will run on
any other Linux machine regardless of any customized settings that machine
might have that could differ from the machine used for writing and testing
the code.
In a way, Docker is a bit like a virtual machine. But unlike a virtual
machine, rather than creating a whole virtual operating system, Docker allows
applications to use the same Linux kernel as the system that they’re
running on and only requires applications be shipped with things not already
running on the host computer. This gives a significant performance boost
and reduces the size of the application.
We talk about docker, what it is, why it matters, and how it can benefit us. This presentation is an introduction and delivered to local meetup in Indonesia.
Similar to Demystifying Containerization Principles for Data Scientists (20)
SRE Demystified - 16 - NALSD - Non-Abstract Large System DesignDr Ganesh Iyer
According to Google, SRE is what you get when you treat operations as if it’s a software problem. In this video, I briefly explain what is Non-Abstract Large System Design (NALSD). Video recording can be found at https://youtu.be/barW9f1aNig
According to Google, SRE is what you get when you treat operations as if it’s a software problem. In this video, I briefly explain key SRE processes. Video: https://youtu.be/BdFmRJAnB6A
According to Google, SRE is what you get when you treat operations as if it’s a software problem. In this video, I briefly explain important documents required for running SRE teams, reporting service state, New SRE onboarding and service decommissioning.
Video at: https://youtu.be/FfIiTVwF0pI
SRE Demystified - 12 - Docs that matter -1 Dr Ganesh Iyer
According to Google, SRE is what you get when you treat operations as if it’s a software problem. In this video, I briefly explain important documents required for onboarding new services, running services and production products.
Youtube video here: https://youtu.be/Uq5jvBdox48
According to Google, SRE is what you get when you treat operations as if it’s a software problem. In this video, I briefly explain the term SRE (Site Reliability Engineering) and introduce key metrics for an SRE team SLI, SLO, and SLA.
Youtube Channel here: https://www.youtube.com/playlist?list=PLm_COkBtXzFq5uxmamT0tqXo-aKftLC1U
According to Google, SRE is what you get when you treat operations as if it’s a software problem. In this video, I briefly explain continuous release engineering and configuration management.
Youtube channel here: https://youtu.be/EgpCw15fIK8
According to Google, SRE is what you get when you treat operations as if it’s a software problem. In this video, I briefly explain what is release engineering and important release engineering philosophies.
Youtube channel here: https://youtu.be/EgpCw15fIK8
According to Google, SRE is what you get when you treat operations as if it’s a software problem. In this video, I briefly explain what does simplicity means for an SRE.
Youtube channel here: https://youtu.be/EgpCw15fIK8
According to Google, SRE is what you get when you treat operations as if it’s a software problem. In this video, I briefly explain various practical alerting considerations and views from Google.
Youtube channel here: https://youtu.be/EgpCw15fIK8
According to Google, SRE is what you get when you treat operations as if it’s a software problem. In this video, I briefly explain distributed monitoring concepts.
Youtube channel here: https://youtu.be/EgpCw15fIK8
According to Google, SRE is what you get when you treat operations as if it’s a software problem. In this video, I briefly explain what is and isn't toil, how to identify, measure and eliminate them.
Youtube channel here: https://youtu.be/EgpCw15fIK8
According to Google, SRE is what you get when you treat operations as if it’s a software problem. In this video, I briefly explain how SREs engage with other teams especially service owners / developers.
Youtube channel here: https://youtu.be/EgpCw15fIK8
According to Google, SRE is what you get when you treat operations as if it’s a software problem. In this video, I briefly explain different SLIs typically associated with a system. I will explain Availability, latency and quality SLIs in brief.
Youtube channel here: https://youtu.be/EgpCw15fIK8
Machine Learning for Statisticians - IntroductionDr Ganesh Iyer
Introduction to Machine Learning for Statisticians. From the webinar given for Sacred Hearts College, Tevara, Ernakulam, India on 8/8/2020. It briefly introduces ML concepts and what does it mean for statisticians.
Making Decisions - A Game Theoretic approachDr Ganesh Iyer
Webinar recording of the webinar conducted on 18-07-2020 for Rajagiri School of Engineering and Technology.
Speaker - Dr Ganesh Neelakanta Iyer
Topics:
Overview of Game Theory, Non cooperative games, cooperative games and mechanism design principles.
Game Theory and its engineering applications delivered at ViTECoN 2019 at VIT, Vellore. It gives introduction to types of games, sample from different engineering domains
Half day session on Machine learning and its applications. It introduces Artificial Intelligence, move on Machine Learning, applications, algorithms, types, using Cloud for ML, Deep Learning and some resources to start with
Characteristics of successful entrepreneurs, How to start a business, Habits of successful entrepreneurs, Some highly successful entrepreneurs - Walt Disney, Small kids who are very successful
A comprehensive overview of various Game Theory principles and examples from Engineering and other fields to know how we can use it to solve various research problems.
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
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.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
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.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
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.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...
Demystifying Containerization Principles for Data Scientists
1. Demystifying Containerization
Principles for Data Scientists
A quick preview of Dockers
Dr Ganesh Neelakanta Iyer
Amrita Vishwa Vidyapeetham, Coimbatore
Associate Professor, Dept of Computer Science and Engg
2. About Me • Associate Professor, Amrita Vishwa Vidyapeetham
• Masters & PhD from National University of Singapore (NUS)
• Several years in Industry/Academia
• Sasken Communications, NXP Semiconductors, Progress
Software, IIIT-HYD, NUS (Singapore)
• Architect, Manager, Technology Evangelist, Visiting Faculty
• Talks/workshops in USA, Europe, Australia, Asia
• Cloud/Edge Computing, IoT, Game Theory, Software QA
• Kathakali Artist, Composer, Speaker, Traveler, Photographer
GANESHNIYER http://ganeshniyer.com
5. Tough part is
• Setting them up and running
• Python latest version is 3.7 (as of 24th Oct 2018)
– TensorFlow support only up to Python 3.6
• TensorFlow 1.10 is incompatible with numPy > 1.14.5
• Primary problem is that when we do “pip instal yyy” it installs
latest version always – We may not know all these
dependencies and end up redoing all over again and again
Dr Ganesh Neelakanta Iyer 5
12. and spawned an Intermodal Shipping Container Ecosystem
• 90% of all cargo now shipped in a standard container
• Order of magnitude reduction in cost and time to load and unload ships
• Massive reduction in losses due to theft or damage
• Huge reduction in freight cost as percent of final goods (from >25% to <3%) massive globalizations
• 5000 ships deliver 200M containers per year
13. Static website
Web frontend
User DB
Queue Analytics DB
Background workers
API endpoint
nginx 1.5 + modsecurity + openssl + bootstrap 2
postgresql + pgv8 + v8
hadoop + hive + thrift + OpenJDK
Ruby + Rails + sass + Unicorn
Redis + redis-sentinel
Python 3.0 + celery + pyredis + libcurl + ffmpeg + libopencv + nodejs +
phantomjs
Python 2.7 + Flask + pyredis + celery + psycopg + postgresql-client
Development VM
QA server
Public Cloud
Disaster recovery
Contributor’s laptop
Production Servers
The Challenge
Multiplicityof
Stacks
Multiplicityof
hardware
environments
Production Cluster
Customer Data Center
Doservicesand
appsinteract
appropriately?
CanImigrate
smoothlyand
quickly?
14. Results in M x N compatibility nightmare
Static website
Web frontend
Background workers
User DB
Analytics DB
Queue
Development
VM
QA Server
Single Prod
Server
Onsite
Cluster
Public Cloud
Contributor’s
laptop
Customer
Servers
? ? ? ? ? ? ?
? ? ? ? ? ? ?
? ? ? ? ? ? ?
? ? ? ? ? ? ?
? ? ? ? ? ? ?
? ? ? ? ? ? ?
15. Static website Web frontendUser DB Queue Analytics DB
Development
VM
QA server Public Cloud Contributor’s
laptop
Docker is a shipping container system for
code
Multiplicityof
Stacks
Multiplicityof
hardware
environments
Production
Cluster
Customer Data
Center
Doservicesand
appsinteract
appropriately?
CanImigrate
smoothlyand
quickly
…that can be manipulated using
standard operations and run
consistently on virtually any
hardware platform
An engine that enables any
payload to be encapsulated
as a lightweight, portable,
self-sufficient container…
16. Static website Web frontendUser DB Queue Analytics DB
Development
VM
QA server Public Cloud Contributor’s
laptop
Or…put more simply
Multiplicityof
Stacks
Multiplicityof
hardware
environments
Production
Cluster
Customer Data
Center
Doservicesand
appsinteract
appropriately?
CanImigrate
smoothlyand
quickly
Operator: Configure Once, Run
Anything
Developer: Build Once, Run
Anywhere (Finally)
17. Static website
Web frontend
Background workers
User DB
Analytics DB
Queue
Development
VM
QA Server
Single Prod
Server
Onsite
Cluster
Public Cloud
Contributor’s
laptop
Customer
Servers
Docker solves the M x N problem
18. Docker containers
• Wrap up a piece of software in a
complete file system that contains
everything it needs to run:
– Code, runtime, system tools, system
libraries
– Anything you can install on a server
• This guarantees that it will always
run the same, regardless of the
environment it is running in
19. Why containers matter
Physical Containers Docker
Content Agnostic The same container can hold almost
any type of cargo
Can encapsulate any payload and its
dependencies
Hardware Agnostic Standard shape and interface allow
same container to move from ship to
train to semi-truck to warehouse to
crane without being modified or
opened
Using operating system primitives (e.g.
LXC) can run consistently on virtually
any hardware—VMs, bare metal,
openstack, public IAAS, etc.—without
modification
Content Isolation and
Interaction
No worry about anvils crushing
bananas. Containers can be stacked
and shipped together
Resource, network, and content
isolation. Avoids dependency hell
Automation Standard interfaces make it easy to
automate loading, unloading, moving,
etc.
Standard operations to run, start, stop,
commit, search, etc. Perfect for devops:
CI, CD, autoscaling, hybrid clouds
Highly efficient No opening or modification, quick to
move between waypoints
Lightweight, virtually no perf or start-up
penalty, quick to move and manipulate
Separation of duties Shipper worries about inside of box,
carrier worries about outside of box
Developer worries about code. Ops
worries about infrastructure.
20. Docker containers
Lightweight
• Containers running on
one machine all share
the same OS kernel
• They start instantly
and make more
efficient use of RAM
• Images are
constructed from
layered file systems
• They can share
common files, making
disk usage and image
downloads much
more efficient
Open
• Based on open
standards
• Allowing containers to
run on all major Linux
distributions and
Microsoft OS with
support for every
infrastructure
Secure
• Containers isolate
applications from
each other and the
underlying
infrastructure while
providing an added
layer of protection for
the application
21. Docker / Containers vs. Virtual Machine
https://www.docker.com/whatisdocker/
Containers have similar resource
isolation and allocation benefits as
VMs but a different architectural
approach allows them to be much
more portable and efficient
22. Virtual Machines
Virtual machines run guest operating systems—note the OS
layer in each box. This is resource intensive, and the
resulting disk image and application state is an entanglement
of OS settings, system-installed dependencies, OS security
patches, and other easy-to-lose, hard-to-replicate ephemera
Containers vs Virtual Machines
Containers
Containers can share a single kernel, and the only
information that needs to be in a container image is the
executable and its package dependencies, which never need
to be installed on the host system. These processes run like
native processes, and you can manage them individually
23. Why are Docker containers lightweight?
Bins/
Libs
App
A
Original App
(No OS to take
up space, resources,
or require restart)
AppΔ
Bins
/
App
A
Bins/
Libs
App
A’
Gues
t
OS
Bins/
Libs
Modified App
Union file system allows
us to only save the diffs
Between container A
and container
A’
VMs
Every app, every copy of an
app, and every slight modification
of the app requires a new virtual server
App
A
Guest
OS
Bins/
Libs
Copy of
App
No OS. Can
Share bins/libs
App
A
Guest
OS
Guest
OS
VMs Containers
24. What are the basics of the Docker system?
Source
Code
Repository
Dockerfile
For
A
Docker Engine
Docker
Container
Image
Registry
Build
Docker Engine
Host 2 OS 2 (Windows / Linux)
Container
A
Container
B
Container
C
ContainerA
Push
Search
Pull
Run
Host 1 OS (Linux)
25. Changes and Updates
Docker Engine
Docker
Container
Image
Registry
Docker Engine
Push
Update
Bins/
Libs
App
A
AppΔ
Bins
/
Base
Container
Image
Host is now running A’’
Container
Mod A’’
AppΔ
Bins
/
Bins/
Libs
App
A
Bins
/
Bins/
Libs
App
A’’
Host running A wants to upgrade to A’’.
Requests update. Gets only diffs
Container
Mod A’
26. Easily Share and Collaborate on Applications
• Distribute and share content
– Store, distribute and manage your Docker images in your Docker
Hub with your team
– Image updates, changes and history are automatically shared
across your organization.
• Simply share your application with others
– Ship your containers to others without worrying about different
environment dependencies creating issues with your application.
– Other teams can easily link to or test against your app without
having to learn or worry about how it works.
Docker creates a common framework for developers and sysadmins to work together on distributed
applications
27. Get Started with Docker
• Install Docker
• Run a software image in a container
• Browse for an image on Docker Hub
• Create your own image and run it in a
container
• Create a Docker Hub account and an
image repository
• Create an image of your own
• Push your image to Docker Hub for
others to use
https://www.docker.com/products/docker
https://www.docker.com/products/docker-toolbox
28. Docker Container as a Service (CaaS)
Deliver an IT secured and managed application environment for developers to build and deploy
applications in a self service manner
31. Continuous Integration and Deployment (CI / CD)
• The modern development pipeline is fast, continuous and automated
with the goal of more reliable software
• CI/CD allows teams to integrate new code as often as every time
code is checked in by developers and passes testing
• A cornerstone of devops methodology, CI/CD creates a real time
feedback loop with a constant stream of small iterative changes that
accelerates change and improves quality
• CI environments are often fully automated to trigger a test at git push
and to automatically build a new image if the test is successful and
push to a Docker Registry
• Further automation and scripting can deploy a container from the
new image to staging for further testing.
32. Microservices
• App architecture is changing from monolithic code bases with waterfall development
methodologies to loosely coupled services that are developed and deployed
independently
• Tens to thousands of these services can be connected to form an app
• Docker allows developers are able to choose the best tool or stack for each service
and isolates them to eliminate any potential conflicts and avoids the “matrix from
hell.”
• These containers can be easily shared, deployed, updated and scaled instantly and
independently of the other services that make up the app
• Docker’s end to end security features allow teams to build and operate a least
privilege microservices model where services only get access to the resources
(other apps, secrets, compute) they need to run at just the right time to create.
33. IT Infrastructure optimization
• Docker and containers help optimize the utilization and cost
of your IT infrastructure
• Optimization not just cost reduction, it is ensuring the right
amount of resources are available at the right time and
used efficiently
• Because containers are lightweight ways of packaging and
isolating app workloads, Docker allows multiple workloads
to run on the same physical or virtual server without conflict
• Businesses can consolidate datacenters, integrate IT from
mergers and acquisitions and enable portability to cloud
while reducing the footprint of operating systems and
servers to maintain
34. Hybrid Cloud
• Docker guarantees apps are cloud enabled - ready
to move across private and public clouds with a
higher level of control and guarantee apps will
operate as designed
• The Docker platform is infrastructure independent
and ensures everything the app needs to run is
packaged and transported together from one site to
another
• Docker uniquely provides flexibility and choice for
businesses to adopt a single, multi or hybrid cloud
environment without conflict
35. How does this help you build better software?
• Stop wasting hours trying to setup developer environments
• Spin up new instances and make copies of production code to run locally
• With Docker, you can easily take copies of your live environment and run on any new
endpoint running Docker.
Accelerate Developer Onboarding
• The isolation capabilities of Docker containers free developers from the worries of using
“approved” language stacks and tooling
• Developers can use the best language and tools for their application service without
worrying about causing conflict issues
Empower Developer Creativity
• By packaging up the application with its configs and dependencies together and shipping
as a container, the application will always work as designed locally, on another machine,
in test or production
• No more worries about having to install the same configs into a different environment
Eliminate Environment Inconsistencies
38. Setting up
• Before we get started, make sure your system has the latest version of
Docker installed.
• Docker is available in two editions: Community Edition
(CE) and Enterprise Edition (EE).
• Docker Community Edition (CE) is ideal for developers and small teams
looking to get started with Docker and experimenting with container-based
apps. Docker CE has two update channels, stable and edge:
– Stable gives you reliable updates every quarter
– Edge gives you new features every month
• Docker Enterprise Edition (EE) is designed for enterprise development
and IT teams who build, ship, and run business critical applications in
production at scale.
42. If your windows is not in latest version…
https://docs.docker.com/docker-for-windows/release-notes/#docker-community-edition-17062-ce-win27-2017-09-06-stable
43. Docker for Windows
When the whale in the status
bar stays steady, Docker is up-
and-running, and accessible
from any terminal window.
44. Hello-world
• Open command prompt / windows power shell and run
docker run hello-world
Now would also be a good time to make sure you are using
version 1.13 or higher. Run docker --version to check it out.
45. Building an app the Docker way
• In the past, if you were to start writing a Python app, your first order
of business was to install a Python runtime onto your machine
• But, that creates a situation where the environment on your machine
has to be just so in order for your app to run as expected; ditto for
the server that runs your app
• With Docker, you can just grab a portable Python runtime as an
image, no installation necessary
• Then, your build can include the base Python image right alongside
your app code, ensuring that your app, its dependencies, and the
runtime, all travel together
• These portable images are defined by something called a Dockerfile
46. Define a container with a Dockerfile
• Dockerfile will define what goes on in the environment
inside your container
• Access to resources like networking interfaces and disk
drives is virtualized inside this environment, which is
isolated from the rest of your system, so you have to map
ports to the outside world, and be specific about what files
you want to “copy in” to that environment
• However, after doing that, you can expect that the build of
your app defined in this Dockerfile will behave exactly
the same wherever it runs
47. Dockerfile
• Create an empty directory
• Change directories (cd) into the new directory, create a
file called Dockerfile
48. Dockerfile
• In windows, open notepad, copy the content below, click on Save as, type “Dockerfile”
This Dockerfile refers to a couple of files we
haven’t created yet, namely app.py and
requirements.txt. Let’s create those next.
49. The app itself
• Create two more files,
requirements.txt and app.py, and
put them in the same folder with the
Dockerfile
• This completes our app, which as you
can see is quite simple
• When the above Dockerfile is built
into an image, app.py and
requirements.txt will be present
because of that Dockerfile’s ADD
command, and the output from app.py
will be accessible over HTTP thanks to
the EXPOSE command.
50. The App itself
Requirements.txt
app.py
That’s it! You don’t need Python
or anything in
requirements.txt on your
system, nor will building or
running this image install them
on your system. It doesn’t seem
like you’ve really set up an
environment with Python and
Flask, but you have.
51. Building the app
• We are ready to build the app. Make sure you are still at the
top level of your new directory. Here’s what ls should show
• Now run the build command. This creates a Docker image,
which we’re going to tag using -t so it has a friendly name.
54. Run the app
• Run the app, mapping your machine’s port 4000 to the container’s
published port 80 using –p
• docker run -p 4000:80 friendlyhello
• You should see a notice that Python is serving your app at
http://0.0.0.0:80. But that message is coming from inside the
container, which doesn’t know you mapped port 80 of that container to
4000, making the correct URL http://localhost:4000
• Go to that URL in a web browser to see the display content served up on
a web page, including “Hello World” text, the container ID, and the Redis
error message
55.
56. End the process
• Hit CTRL+C in your terminal to quit
• Now use docker stop to end the process, using the
CONTAINER ID, like so
57. • Now let’s run the app in the background, in detached mode:
• docker run -d -p 4000:80 friendlyhello
• You get the long container ID for your app and then are kicked back
to your terminal. Your container is running in the background. You
can also see the abbreviated container ID with docker container ls
(and both work interchangeably when running commands):
• docker container ls
58. Share image
• To demonstrate the portability of what we just created, let’s
upload our built image and run it somewhere else
• After all, you’ll need to learn how to push to registries when you
want to deploy containers to production
• A registry is a collection of repositories, and a repository is a
collection of images—sort of like a GitHub repository, except the
code is already built. An account on a registry can create many
repositories. The docker CLI uses Docker’s public registry by
default
• If you don’t have a Docker account, sign up for one at
cloud.docker.com. Make note of your username.
59.
60.
61. Login with your docker id
• Log in to the Docker public registry on your local machine.
• docker login
62. Tag the image
• The notation for associating a local image with a repository on a
registry is username/repository:tag. The tag is optional, but
recommended, since it is the mechanism that registries use to give
Docker images a version. Give the repository and tag meaningful
names for the context, such as get-started:part1. This will put
the image in the get-started repository and tag it as part1.
• Now, put it all together to tag the image. Run docker tag image
with your username, repository, and tag names so that the image will
upload to your desired destination. The syntax of the command is:
64. Publish the image
• Upload your tagged image to the repository
• docker push username/repository:tag
• Once complete, the results of this upload are publicly available. If
you log in to Docker Hub, you will see the new image there, with its
pull command
65. Publish the image
• Upload your tagged image to the repository
• docker push username/repository:tag
• Once complete, the results of this upload are publicly available. If
you log in to Docker Hub, you will see the new image there, with its
pull command
66.
67. Pull and run the image from the remote
repository
• From now on, you can use docker run and run your app on any
machine with this command:
• docker run -p 4000:80 username/repository:tag
• If the image isn’t available locally on the machine, Docker will pull it
from the repository.
• If you don’t specify the :tag portion of these commands, the tag of
:latest will be assumed, both when you build and when you run
images. Docker will use the last version of the image that ran without
a tag specified (not necessarily the most recent image).
No matter where executes, it pulls your image, along with Python and all the dependencies
from , and runs your code. It all travels together in a neat little package, and the host machine
doesn’t have to install anything but Docker to run it.
68. What have you seen so far?
• Basics of Docker
• How to create your first app in the Docker way
• Building the app
• Run the app
• Sharing and Publishing images
• Pull and run images
70. Docker for Data scientists
If you have tried to install and set up a deep learning framework (e.g. CNTK,
Tensorflow etc.) on your machine you will agree that it is challenging
The proverbial stars need to align to make sure the dependencies and requirements
are satisfied for all the different frameworks that you want to explore and experiment
with
Getting the right anaconda distribution, the correct version of Python, setting up the
paths, the correct versions of different packages, ensuring the installation does not
interfere with other Python-based installations on your system is not a trivial exercise
71. Docker for Data scientists
Using a Docker image saves us this trouble as it provides a pre-
configured environment ready to start work in
Even if you manage to get the framework installed and running in
your machine, every time there’s a new release, something could
inadvertently break
Making Docker your development environment shields your project
from these version changes until you are ready to upgrade your code
to make it compatible with the newer version
Dr Ganesh Neelakanta Iyer 71
72. Docker for Data scientists
Using Docker also makes sharing projects with others a painless process
You don’t have to worry about environments not being compatible, missing dependencies or
even platform conflicts
When sharing a project via a container you are not only sharing your code but your
development environment as well ensuring that your script can be reliably executed, and your
work faithfully reproduced
Furthermore, since you work is already containerized, you can easily deploy it using services
such as Kubernetes, Swarm etc.
Dr Ganesh Neelakanta Iyer 72
73. The right image
• Go to Docker hub
https://hub.docker.com/r/
microsoft/cntk/
• Download your preferred
version of the CNTK
image
Dr Ganesh Neelakanta Iyer 73
74. The right image
• The command will download the CNTK 2.2 CPU runtime
configuration set up for Python 3.5
• After pulling the image if we execute the docker images command,
the image that was just pulled should be listed in the output
Dr Ganesh Neelakanta Iyer 74
75. Image to containers
• Use this image to start a container
• To create a new container, we must specify an image
name from which to derive the container from and an
optional command to run (/bin/bash here to access the
bash shell).
docker run [OPTIONS] microsoft/cntk:2.2-cpu-
python3.5 /bin/bash
Dr Ganesh Neelakanta Iyer 75
76. Inside the container
Transfer these to our working directory in the container
The training and test data along with our script are on the local machine
pip install lightgbm inside the container as the CNTK image does not come with lightgbm
Create a working directory called mylightgbmex as we want to train a lightgbm model
To start the deep learning project, lets jump inside the container in a bash shell and use it as our development environment
Dr Ganesh Neelakanta Iyer 76
77. Inside the container
• To run an interactive shell in the image, the docker run command can be executed
using the following options
• docker run -i -t –name mycntkdemo microsoft/cntk:2.2-cpu-
Python3.5 /bin/bash
• -t, –tty=false Allocate a pseudo-TTY
• -i, –interactive Keep STDIN open even if not attached
• The above command starts the container in an interactive mode and puts us in
a bash shell as though we were working directly in our terminal. Once inside the
shell, we can use any editor (the CNTK image comes with vi editor) to write our
code. We can start the Python interpreter by typing Python on the command line.
Dr Ganesh Neelakanta Iyer 77
79. Inside the container
• Next, copy the training and
test data along with Python
script from local machine to
the working folder in the
container mycntkdemo using
the docker cp command
• With the files available
inside the container I will
jump back inside and
execute my script
• Once we have the output
from running our script, we
could transfer it back to our
local machine using the
docker cp command again
Dr Ganesh Neelakanta Iyer 79
80. • Alternatively we could map the
folder C:dockertut on the host
machine to the directory
mylightgbmex in the Docker
container when starting the
container by using the -v flag with
docker run command
• docker run -it –name
mycntkdemo -v
C:dockertut:/root/myligh
tgbmex
microsoft/cntk:2.2-cpu-
python3.5 /bin/bash
• When inside the container, we will
see a directory mylightgbmex
with the contents of the folder
C:dockertut in it.
Dr Ganesh Neelakanta Iyer 80
81. Custom Image
• In the exercise above we installed lightgbm in our container and by doing
so we added another layer to the image we started with
• If we want to save these changes, we need to commit the container’s file
changes or settings into a new image
• docker commit mycntkdemo mycntkwlgbm:version1
• The above command will create a new image called mycntkwlgbm and
should be listed in the output of Docker images command
• This new image will contain everything that the CNTK image came with
plus lightgbm, all the files we transferred from our machine and the output
from executing our script
• We can continue using this new image by starting a container with it.
Dr Ganesh Neelakanta Iyer 81
83. Jupyter Notebook
• Jupyter notebook is a favorite tool of data scientists
• Both CNTK and Tensorflow images come with Jupyter
installed
• In Docker, the containers themselves can have
applications running on ports
• To access these applications, we need to expose the
containers internal port and bind the exposed port to a
specified port on the host
Dr Ganesh Neelakanta Iyer 83
84. Jupyter Notebook
• In the example below, we will access the Jupyter notebook
application running inside my container
• Starting a container with -p flag will explicitly map the port of
the Docker host to the port number on our localhost to access
the application running on that port in the container (port 8888
is default for Jupyter notebook application)
docker run -it -p 8888:8888 –name mycntkdemo2
microsoft/cntk:2.2-cpu-python3.5 /bin/bash
Dr Ganesh Neelakanta Iyer 84
85. Jupyter Notebook
• Once in the container shell, the Jupyter notebook application can be
started using the command
jupyter-notebook –no-browser –ip=0.0.0.0 –notebook-
dir=/cntk/Tutorials –allow-root
Dr Ganesh Neelakanta Iyer 85
86. Type the url with the
token above
http://localhost:8888/?tok
en=************* in your
favorite browser to see
the notebook dashboard
Dr Ganesh Neelakanta Iyer 86
87. Repeat
• In the examples above we used the CNTK framework
• To work with other frameworks, we can simply repeat the
above exercises with the appropriate image
• For example, to work on a Tensorflow project, we can access
the Jupyter notebook application running in the container as:
docker run -it -p 8888:8888 tensorflow/tensorflow
• The command above will get the latest image for CPU only
container and start the Jupyter notebook application
Dr Ganesh Neelakanta Iyer 87
89. Dr Ganesh Neelakanta Iyer 89
Type the url with the token above http://localhost:8888/?token=*************
in your favorite browser to see the notebook dashboard
90. Takeaways
With Docker containers as the development environment for your
deep learning projects, you can hit the ground running
You are spared the overhead of installing and setting up the
environment for the various frameworks and can start working on your
deep learning projects right away
Scripts are guaranteed to run everywhere and will run the same every
time
Dr Ganesh Neelakanta Iyer 90