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Docker allows developers to easily deploy applications in lightweight sandbox containers that run on the host operating system. Containers package an application and its dependencies into a standardized unit, and have less overhead than virtual machines. Docker images are read-only templates used to create container instances that can be run, started, stopped, moved and deleted. Images are stored in Docker registries, while containers are isolated and secured instances created from images. Docker tools like the client, machine, and compose help manage images, machines, and multi-container applications.
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Containerization (docker)
Containerization with Docker allows applications to run in isolated containers that share computing resources. Docker containers bundle applications and dependencies together, making them portable across different environments. The Docker architecture uses a client-server model, with a Docker daemon managing the execution of containers on a host. Images contain the files and metadata needed to run applications, and are built from layers to optimize disk usage and deployment. Docker provides lightweight containers that start faster and use less memory than virtual machines.
Docker presentation
Docker is an open source containerization platform that allows developers to package applications and dependencies into standardized containers. Containers allow applications to be run consistently across different computing environments using operating system-level virtualization. Docker makes it easier to build, deploy, and manage containers using simple commands. It provides benefits like application isolation, cost-effectiveness, scalability, disposability, and improved developer productivity compared to traditional virtual machines. Docker images contain the executable application code and dependencies needed to run as containers. The Dockerfile automates the creation of Docker images from a base image. Running a Docker image creates a container instance where the application code is executed.
Docker for Professionals: The Practical Guide
Docker is a container that wraps a piece of software into a complete file system, including everything the file would require to run (code, runtime, system tools, etc.). It then allows you to ship and use this container on any environment, regardless of the system requirements or the operating system.
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Docker is a container technology that allows applications and their dependencies to be packaged into standardized units called containers that can run on any infrastructure regardless of environment. Key Docker tools include Docker Engine for running containers, Docker Machine for provisioning hosts, Docker Swarm for clustering hosts, Docker Compose for defining multi-container apps, and Docker Registry for storing images. Containers allow developers to focus on code by ensuring consistency across environments and enabling microservices architectures through modularization of applications into independent containers that can scale individually.
Docker container
This document discusses Docker containers and how they compare to virtual machines. It explains that Docker containers are lightweight software packages that bundle code and dependencies and allow applications to run in isolation on a shared operating system kernel. Containers take up less space than virtual machines and start almost instantly. The document provides examples of Dockerfiles used to build container images and Docker commands to build, run, and execute commands inside containers.
Introduction to Dockers and containers
Docker is an open platform for developing, shipping, and running applications. docker container, its main benefit is to package applications in “containers” allowing them to be portable among any system running the Linux operating system (OS).
Docker
Docker is a containerization platform that allows applications and their dependencies to be packaged into standardized units called containers that can run on any infrastructure regardless of the underlying operating system. The key components of Docker include images which serve as templates for building containers, a daemon that manages the containers, a client to interact with the daemon, and a registry to store and distribute images. Containers offer isolation, portability and scalability compared to virtual machines.
Docker
Containers allow multiple isolated user space instances to run on a single host operating system. Containers are seen as less flexible than virtual machines since they generally can only run the same operating system as the host. Docker adds an application deployment engine on top of a container execution environment. Docker aims to provide a lightweight way to model applications and a fast development lifecycle by reducing the time between code writing and deployment. Docker has components like the client/server, images used to create containers, and public/private registries for storing images.
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Containerization (docker)
Containerization with Docker allows applications to run in isolated containers that share computing resources. Docker containers bundle applications and dependencies together, making them portable across different environments. The Docker architecture uses a client-server model, with a Docker daemon managing the execution of containers on a host. Images contain the files and metadata needed to run applications, and are built from layers to optimize disk usage and deployment. Docker provides lightweight containers that start faster and use less memory than virtual machines.
Docker presentation
Docker is an open source containerization platform that allows developers to package applications and dependencies into standardized containers. Containers allow applications to be run consistently across different computing environments using operating system-level virtualization. Docker makes it easier to build, deploy, and manage containers using simple commands. It provides benefits like application isolation, cost-effectiveness, scalability, disposability, and improved developer productivity compared to traditional virtual machines. Docker images contain the executable application code and dependencies needed to run as containers. The Dockerfile automates the creation of Docker images from a base image. Running a Docker image creates a container instance where the application code is executed.
Docker for Professionals: The Practical Guide
Docker is a container that wraps a piece of software into a complete file system, including everything the file would require to run (code, runtime, system tools, etc.). It then allows you to ship and use this container on any environment, regardless of the system requirements or the operating system.
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Docker is a container technology that allows applications and their dependencies to be packaged into standardized units called containers that can run on any infrastructure regardless of environment. Key Docker tools include Docker Engine for running containers, Docker Machine for provisioning hosts, Docker Swarm for clustering hosts, Docker Compose for defining multi-container apps, and Docker Registry for storing images. Containers allow developers to focus on code by ensuring consistency across environments and enabling microservices architectures through modularization of applications into independent containers that can scale individually.
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Docker is an open platform for developing, shipping, and running applications. docker container, its main benefit is to package applications in “containers” allowing them to be portable among any system running the Linux operating system (OS).
Docker
Docker is a containerization platform that allows applications and their dependencies to be packaged into standardized units called containers that can run on any infrastructure regardless of the underlying operating system. The key components of Docker include images which serve as templates for building containers, a daemon that manages the containers, a client to interact with the daemon, and a registry to store and distribute images. Containers offer isolation, portability and scalability compared to virtual machines.
Docker
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8 good reasons to learn docker
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https://www.gangboard.com/operating-system-training/docker-training
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This document discusses Docker, including what it is, why it is useful, and how it can be used at different stages of development and deployment. Docker allows packaging applications and dependencies into standardized containers that can run on any infrastructure. It helps manage different environments, platforms and targets. The document outlines Docker tools like Docker Engine, Docker Compose, Docker Machine and Swarm that can be used for local development, CI/testing, and production deployment of containerized applications.
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Docker üzerinde Jupyter Notebooks kullanımından bahsedeceğiz. Docker konteynırının run komutu ile yüklenip başlatıldıktan sonra durdurulması ve tekrardan başlatılması. Ayrıca Jupyter Notebooks üzerine önceden hazırlanmış kodların yüklenmesi, klasör yapısı ve 5.0 versiyonu ile yeni gelen özelliklerinden bahsedilecektir. Son olarak ise Jupyter Notebooks Viewerdan bahsedilecektir.
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Docker is an open source platform that allows developers to package applications with dependencies into standardized units called containers that can run on any system with Docker installed. Containers isolate applications from one another and the underlying infrastructure using resource isolation provided by Linux kernel features like namespaces and cgroups. This allows developers to easily deploy and run distributed applications without having to rebuild them for each platform.
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24 23 jun17 2may17 16231 ijeecs latest_version (1) edit septian
Server virtualization is a fundamental technological innovation that is used extensively in IT enterprises. Server virtualization enables creation of multiple virtual machines on single underlying physical machine. It is realized either in form of hypervisors or containers. Hypervisor is an extra layer of abstraction between the hardware and virtual machines that emulates underlying hardware. In contrast, the more recent container-based virtualization technology runs on host kernel without additional layer of abstraction. Thus container technology is expected to provide near native performance compared to hypervisor based technology. We have conducted a series of experiments to measure and compare the performance of workloads over hypervisor based virtual machines, Docker containers and native bare metal machine. We use a standard benchmark workload suite that stresses CPU, memory, disk IO and system. The results obtained show that Docker containers provide better or similar performance compared to traditional hypervisor based virtual machines in almost all the tests. However as expected the native system still provides the best performance as compared to either containers or hypervisors.
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This document discusses Docker, including what it is, why it is useful, and how it can be used at different stages of development and deployment. Docker allows packaging applications and dependencies into standardized containers that can run on any infrastructure. It helps manage different environments, platforms and targets. The document outlines Docker tools like Docker Engine, Docker Compose, Docker Machine and Swarm that can be used for local development, CI/testing, and production deployment of containerized applications.
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Docker - the what why and hows
Docker is an open source platform that allows developers to package applications with dependencies into standardized units called containers that can run on any system with Docker installed. Containers isolate applications from one another and the underlying infrastructure using resource isolation provided by Linux kernel features like namespaces and cgroups. This allows developers to easily deploy and run distributed applications without having to rebuild them for each platform.
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Containerization is a lightweight alternative to full machine virtualization that involves encapsulating an application in a container with its own operating environment. This provides many of the benefits of loading an application onto a virtual machine, as the application can be run on any suitable physical machine without any worries about dependencies.
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The document discusses evaluating the use of microservices and container technologies like Docker in an academic environment. It begins by explaining the limitations of traditional monolithic applications and how microservices address these issues. The key aspects of microservices architecture are defined. It then provides details on how Docker containerization works and the various Docker tools like Docker Engine, Docker Hub, Docker Machine, Docker Swarm, and Docker Compose. The document discusses implementing microservices using these Docker technologies and tools in an academic research computing cluster with multiple versions of services running in isolated containers. It includes steps and examples for installing Docker on Linux, Windows, and configuring a Docker server and clients.
Docker
Docker allows running applications in isolated Linux containers. It packages an application and its dependencies into a virtual container that uses features of the Linux kernel like namespaces and control groups to isolate the container's view of the operating system. Docker images contain the instructions to launch containers from templates called images. Containers are instantiated forms of images that contain the operating system, files, and metadata needed to run the application. Docker uses namespaces to isolate processes, networking, filesystem mounts, and other resources for each container.
Docker In Brief
This document provides information about Docker and how it compares to virtual machines. It defines key Docker concepts like containers, images, and layers. It explains that Docker allows applications to be packaged with all their dependencies and shipped as standardized units called containers that can run on any Linux server that has Docker installed. Containers are more lightweight than virtual machines and provide greater performance and portability. The document also provides examples of how to build Docker images using Dockerfiles and deploy containers.
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The document provides an overview of Docker basics, including an introduction to containers, why containers are needed, how Docker differs from virtual machines, and explanations of common Docker commands like build, run, push and pull. It also includes examples demonstrating how to build a Python app into a Docker image and run/deploy it as a container, as well as an example using Nginx.
VS Code tools for docker
The document discusses Docker and Kubernetes tools for Visual Studio code. It provides an overview of Docker, how to build Docker images using Dockerfiles, and how to use the Docker extension in VS Code. It also covers developing applications inside Docker containers using the Remote - Containers extension. Finally, it gives a basic introduction to Kubernetes, including nodes, pods, deployments, and services. The presenter demonstrates creating a Dockerfile and deploying to Kubernetes.
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Virtualization refers to creating virtual versions of hardware, operating systems, storage or network resources. Docker uses virtualization techniques like namespaces and control groups to virtualize operating systems and applications. Docker allows building, shipping and running applications securely isolated in containers. Developers can package applications with all dependencies into standardized units called containers that can run on any Linux server.
24 23 jun17 2may17 16231 ijeecs latest_version (1) edit septian
Server virtualization is a fundamental technological innovation that is used extensively in IT enterprises. Server virtualization enables creation of multiple virtual machines on single underlying physical machine. It is realized either in form of hypervisors or containers. Hypervisor is an extra layer of abstraction between the hardware and virtual machines that emulates underlying hardware. In contrast, the more recent container-based virtualization technology runs on host kernel without additional layer of abstraction. Thus container technology is expected to provide near native performance compared to hypervisor based technology. We have conducted a series of experiments to measure and compare the performance of workloads over hypervisor based virtual machines, Docker containers and native bare metal machine. We use a standard benchmark workload suite that stresses CPU, memory, disk IO and system. The results obtained show that Docker containers provide better or similar performance compared to traditional hypervisor based virtual machines in almost all the tests. However as expected the native system still provides the best performance as compared to either containers or hypervisors.
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Evaluating Docker in the Enterprise - Getting Started
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24 23 jun17 2may17 16231 ijeecs latest_version (1) edit septian
24 23 jun17 2may17 16231 ijeecs latest_version (1) edit septian
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Conversational agents, or chatbots, are increasingly used to access all sorts of services using natural language. While open-domain chatbots - like ChatGPT - can converse on any topic, task-oriented chatbots - the focus of this paper - are designed for specific tasks, like booking a flight, obtaining customer support, or setting an appointment. Like any other software, task-oriented chatbots need to be properly tested, usually by defining and executing test scenarios (i.e., sequences of user-chatbot interactions). However, there is currently a lack of methods to quantify the completeness and strength of such test scenarios, which can lead to low-quality tests, and hence to buggy chatbots.
To fill this gap, we propose adapting mutation testing (MuT) for task-oriented chatbots. To this end, we introduce a set of mutation operators that emulate faults in chatbot designs, an architecture that enables MuT on chatbots built using heterogeneous technologies, and a practical realisation as an Eclipse plugin. Moreover, we evaluate the applicability, effectiveness and efficiency of our approach on open-source chatbots, with promising results.
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdf
A Mix Chart displays historical data of numbers in a graphical or tabular form. The Kalyan Rajdhani Mix Chart specifically shows the results of a sequence of numbers over different periods.
[OReilly Superstream] Occupy the Space: A grassroots guide to engineering (an...
The typical problem in product engineering is not bad strategy, so much as “no strategy”. This leads to confusion, lack of motivation, and incoherent action. The next time you look for a strategy and find an empty space, instead of waiting for it to be filled, I will show you how to fill it in yourself. If you’re wrong, it forces a correction. If you’re right, it helps create focus. I’ll share how I’ve approached this in the past, both what works and lessons for what didn’t work so well.
Dandelion Hashtable: beyond billion requests per second on a commodity server
This slide deck presents DLHT, a concurrent in-memory hashtable. Despite efforts to optimize hashtables, that go as far as sacrificing core functionality, state-of-the-art designs still incur multiple memory accesses per request and block request processing in three cases. First, most hashtables block while waiting for data to be retrieved from memory. Second, open-addressing designs, which represent the current state-of-the-art, either cannot free index slots on deletes or must block all requests to do so. Third, index resizes block every request until all objects are copied to the new index. Defying folklore wisdom, DLHT forgoes open-addressing and adopts a fully-featured and memory-aware closed-addressing design based on bounded cache-line-chaining. This design offers lock-free index operations and deletes that free slots instantly, (2) completes most requests with a single memory access, (3) utilizes software prefetching to hide memory latencies, and (4) employs a novel non-blocking and parallel resizing. In a commodity server and a memory-resident workload, DLHT surpasses 1.6B requests per second and provides 3.5x (12x) the throughput of the state-of-the-art closed-addressing (open-addressing) resizable hashtable on Gets (Deletes).
Crafting Excellence: A Comprehensive Guide to iOS Mobile App Development Serv...
Crafting Excellence: A Comprehensive Guide to iOS Mobile App Development Serv...Pitangent Analytics & Technology Solutions Pvt. Ltd
Discover top-tier mobile app development services, offering innovative solutions for iOS and Android. Enhance your business with custom, user-friendly mobile applications.zkStudyClub - LatticeFold: A Lattice-based Folding Scheme and its Application...
Folding is a recent technique for building efficient recursive SNARKs. Several elegant folding protocols have been proposed, such as Nova, Supernova, Hypernova, Protostar, and others. However, all of them rely on an additively homomorphic commitment scheme based on discrete log, and are therefore not post-quantum secure. In this work we present LatticeFold, the first lattice-based folding protocol based on the Module SIS problem. This folding protocol naturally leads to an efficient recursive lattice-based SNARK and an efficient PCD scheme. LatticeFold supports folding low-degree relations, such as R1CS, as well as high-degree relations, such as CCS. The key challenge is to construct a secure folding protocol that works with the Ajtai commitment scheme. The difficulty, is ensuring that extracted witnesses are low norm through many rounds of folding. We present a novel technique using the sumcheck protocol to ensure that extracted witnesses are always low norm no matter how many rounds of folding are used. Our evaluation of the final proof system suggests that it is as performant as Hypernova, while providing post-quantum security.
Paper Link: https://eprint.iacr.org/2024/257
Essentials of Automations: Exploring Attributes & Automation Parameters
Building automations in FME Flow can save time, money, and help businesses scale by eliminating data silos and providing data to stakeholders in real-time. One essential component to orchestrating complex automations is the use of attributes & automation parameters (both formerly known as “keys”). In fact, it’s unlikely you’ll ever build an Automation without using these components, but what exactly are they?
Attributes & automation parameters enable the automation author to pass data values from one automation component to the next. During this webinar, our FME Flow Specialists will cover leveraging the three types of these output attributes & parameters in FME Flow: Event, Custom, and Automation. As a bonus, they’ll also be making use of the Split-Merge Block functionality.
You’ll leave this webinar with a better understanding of how to maximize the potential of automations by making use of attributes & automation parameters, with the ultimate goal of setting your enterprise integration workflows up on autopilot.
Northern Engraving | Nameplate Manufacturing Process - 2024
Manufacturing custom quality metal nameplates and badges involves several standard operations. Processes include sheet prep, lithography, screening, coating, punch press and inspection. All decoration is completed in the flat sheet with adhesive and tooling operations following. The possibilities for creating unique durable nameplates are endless. How will you create your brand identity? We can help!
What is an RPA CoE? Session 1 – CoE Vision
In the first session, we will review the organization's vision and how this has an impact on the COE Structure.
Topics covered:
• The role of a steering committee
• How do the organization’s priorities determine CoE Structure?
Speaker:
Chris Bolin, Senior Intelligent Automation Architect Anika Systems
GraphRAG for LifeSciences Hands-On with the Clinical Knowledge Graph
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Introduction of Cybersecurity with OSS at Code Europe 2024
I develop the Ruby programming language, RubyGems, and Bundler, which are package managers for Ruby. Today, I will introduce how to enhance the security of your application using open-source software (OSS) examples from Ruby and RubyGems.
The first topic is CVE (Common Vulnerabilities and Exposures). I have published CVEs many times. But what exactly is a CVE? I'll provide a basic understanding of CVEs and explain how to detect and handle vulnerabilities in OSS.
Next, let's discuss package managers. Package managers play a critical role in the OSS ecosystem. I'll explain how to manage library dependencies in your application.
I'll share insights into how the Ruby and RubyGems core team works to keep our ecosystem safe. By the end of this talk, you'll have a better understanding of how to safeguard your code.
LF Energy Webinar: Carbon Data Specifications: Mechanisms to Improve Data Acc...
This LF Energy webinar took place June 20, 2024. It featured:
-Alex Thornton, LF Energy
-Hallie Cramer, Google
-Daniel Roesler, UtilityAPI
-Henry Richardson, WattTime
In response to the urgency and scale required to effectively address climate change, open source solutions offer significant potential for driving innovation and progress. Currently, there is a growing demand for standardization and interoperability in energy data and modeling. Open source standards and specifications within the energy sector can also alleviate challenges associated with data fragmentation, transparency, and accessibility. At the same time, it is crucial to consider privacy and security concerns throughout the development of open source platforms.
This webinar will delve into the motivations behind establishing LF Energy’s Carbon Data Specification Consortium. It will provide an overview of the draft specifications and the ongoing progress made by the respective working groups.
Three primary specifications will be discussed:
-Discovery and client registration, emphasizing transparent processes and secure and private access
-Customer data, centering around customer tariffs, bills, energy usage, and full consumption disclosure
-Power systems data, focusing on grid data, inclusive of transmission and distribution networks, generation, intergrid power flows, and market settlement data
Skybuffer SAM4U tool for SAP license adoption
Manage and optimize your license adoption and consumption with SAM4U, an SAP free customer software asset management tool.
SAM4U, an SAP complimentary software asset management tool for customers, delivers a detailed and well-structured overview of license inventory and usage with a user-friendly interface. We offer a hosted, cost-effective, and performance-optimized SAM4U setup in the Skybuffer Cloud environment. You retain ownership of the system and data, while we manage the ABAP 7.58 infrastructure, ensuring fixed Total Cost of Ownership (TCO) and exceptional services through the SAP Fiori interface.
Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectors
Join us to learn how UiPath Apps can directly and easily interact with prebuilt connectors via Integration Service--including Salesforce, ServiceNow, Open GenAI, and more.
The best part is you can achieve this without building a custom workflow! Say goodbye to the hassle of using separate automations to call APIs. By seamlessly integrating within App Studio, you can now easily streamline your workflow, while gaining direct access to our Connector Catalog of popular applications.
We’ll discuss and demo the benefits of UiPath Apps and connectors including:
Creating a compelling user experience for any software, without the limitations of APIs.
Accelerating the app creation process, saving time and effort
Enjoying high-performance CRUD (create, read, update, delete) operations, for
seamless data management.
Speakers:
Russell Alfeche, Technology Leader, RPA at qBotic and UiPath MVP
Charlie Greenberg, host
5th LF Energy Power Grid Model Meet-up Slides
5th Power Grid Model Meet-up
It is with great pleasure that we extend to you an invitation to the 5th Power Grid Model Meet-up, scheduled for 6th June 2024. This event will adopt a hybrid format, allowing participants to join us either through an online Mircosoft Teams session or in person at TU/e located at Den Dolech 2, Eindhoven, Netherlands. The meet-up will be hosted by Eindhoven University of Technology (TU/e), a research university specializing in engineering science & technology.
Power Grid Model
The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services.
Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.
Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization.
What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
-Insightful presentations covering two practical applications of the Power Grid Model.
-An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024.
-An interactive brainstorming session to discuss and propose new feature requests.
-An opportunity to connect with fellow Power Grid Model enthusiasts and users.
Astute Business Solutions | Oracle Cloud Partner |
Your goto partner for Oracle Cloud, PeopleSoft, E-Business Suite, and Ellucian Banner. We are a firm specialized in managed services and consulting.
Leveraging the Graph for Clinical Trials and Standards
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Docker slide
- 2. What is Docker ??? In simpler words, Docker is a tool that allows developers, sys- admins etc. to easily deploy their applications in sandbox (called containers) to run on the host operating system i.e. Linux. The key benefit of Docker is that it allows users to package an application with all of its dependencies into a standardized unit for software development. Unlike virtual machines, containers do not have the high overhead and hence enable more efficient usage of the underlying system and resources.
- 3. The role of image and containers Example : Ubuntu with Node.js and Application Code Created by using image. Runs your application
- 4. Image & container A read-only template composed of layered filesystems used to share common files and create Docker container instance An isolated and secured shipping container created from an image that can be run,started,stopped,moved and deleted Image Container
- 5. Do Not Confuse between Image and Container Docker images themselves are never “started” and never “running”. The docker run command takes the Docker image as a template and produces a container from it. Images are stored in a Docker registry, such as Docker Hub.
- 6. Where does docker run ?
- 7. Docker container Vs Virtual machine
- 9. Docker toolsbox - Docker Client : manages images and containers - Docker Machine : create and manages machines - Docker Compose : Manage multi container - Docker Kitematic : GUI
- 10. Install Docker - https://docs.docker.com/toolbox/overview/ Install Dockertoolbox for Mac & Windows Install Docker on linux Run install-docker.sh file and you must run it as root
- 11. Docker Client docker pull [image name] docker images docker rmi [image id] docker rm [container id] docker run [image name] docker ps -a
- 12. Docker Machine Docker-machine ls Docker-machine start [machine name] Docker-machine ip [machine name] Docker-machine status [machine name] Docker-machine stop [machine name] Docker-machine env [machine name]
- 13. Thank you :)