The document discusses Docker, including what it is, its benefits and architecture. Docker provides an abstraction layer that allows applications to be packaged into lightweight containers that can run on any infrastructure. The key components of Docker include images, which are templates used to create containers that run applications in isolated environments. The document then provides instructions on installing Docker and using basic commands like running containers from images and pulling new images from registries.
an enhanced multi layered cryptosystem based secureIJAEMSJORNAL
As the cloud computing technology develops during the recent days, outsourcing data to cloud service for storage becomes an attractive trend, which benefits in sparing efforts on heavy data maintenance and management. Nevertheless, since the outsourced cloud storage is not fully trustworthy, it raises security concerns on how to realize data deduplication in cloud while achieving integrity auditing. In this work, we study the problem of integrity auditing and secure deduplication on cloud data. Specifically, willing achieving both data integrity and deduplication in cloud, we propose two secure systems, namely SecCloud and SecCloud. SecCloud introduces an auditing entity with maintenance of a Map Reduce cloud, which helps clients generate data tags before uploading still audit the integrity of data having been stored in cloud. Compared with previous work, the computation by user in SecCloud is greatly reduced during the file uploading and auditing phases. SecCloud is designed motivated individually fact that customers always must encrypt their data before uploading, and enables integrity auditing and secure deduplication on encrypted data.
Docker allows creating isolated environments called containers from images. Containers provide a standard way to develop, ship, and run applications. The document discusses how Docker can be used for scientific computing including running different versions of software, automating computations, sharing research environments and results, and providing isolated development environments for users through Docker IaaS tools. K-scope is a code analysis tool that previously required complex installation of its Omni XMP dependency, but could now be run as a containerized application to simplify deployment.
We are the company providing Complete Solution for all Academic Final Year/Semester Student Projects. Our projects are
suitable for B.E (CSE,IT,ECE,EEE), B.Tech (CSE,IT,ECE,EEE),M.Tech (CSE,IT,ECE,EEE) B.sc (IT & CSE), M.sc (IT & CSE),
MCA, and many more..... We are specialized on Java,Dot Net ,PHP & Andirod technologies. Each Project listed comes with
the following deliverable: 1. Project Abstract 2. Complete functional code 3. Complete Project report with diagrams 4.
Database 5. Screen-shots 6. Video File
SERVICE AT CLOUDTECHNOLOGIES
IEEE, WEB, WINDOWS PROJECTS ON DOT NET, JAVA& ANDROID TECHNOLOGIES,EMBEDDED SYSTEMS,MAT LAB,VLSI DESIGN.
ME, M-TECH PAPER PUBLISHING
COLLEGE TRAINING
Thanks&Regards
cloudtechnologies
# 304, Siri Towers,Behind Prime Hospitals
Maitrivanam, Ameerpet.
Contact:-8121953811,8522991105.040-65511811
cloudtechnologiesprojects@gmail.com
http://cloudstechnologies.in/
bulk ieee projects in pondicherry,ieee projects in pondicherry,final year ieee projects in pondicherry
Nexgen Technology Address:
Nexgen Technology
No :66,4th cross,Venkata nagar,
Near SBI ATM,
Puducherry.
Email Id: praveen@nexgenproject.com.
www.nexgenproject.com
Mobile: 9751442511,9791938249
Telephone: 0413-2211159.
NEXGEN TECHNOLOGY as an efficient Software Training Center located at Pondicherry with IT Training on IEEE Projects in Android,IEEE IT B.Tech Student Projects, Android Projects Training with Placements Pondicherry, IEEE projects in pondicherry, final IEEE Projects in Pondicherry , MCA, BTech, BCA Projects in Pondicherry, Bulk IEEE PROJECTS IN Pondicherry.So far we have reached almost all engineering colleges located in Pondicherry and around 90km
Dataservices - Processing Big Data The Microservice WayJosef Adersberger
We see a big data processing pattern emerging using the Microservice approach to build an integrated, flexible, and distributed system of data processing tasks. We call this the Dataservice pattern. In this presentation we'll introduce into Dataservices: their basic concepts, the technology typically in use (like Kubernetes, Kafka, Cassandra and Spring) and some architectures from real-life.
Running Accurate, Scalable, and Reproducible Simulations of Distributed Syste...Rafael Ferreira da Silva
Scientific workflows are used routinely in numerous scientific domains, and Workflow Management Systems (WMSs) have been developed to orchestrate and optimize workflow executions on distributed platforms. WMSs are complex software systems that interact with complex software infrastructures. Most WMS research and development activities rely on empirical experiments conducted with full-fledged software stacks on actual hardware platforms. Such experiments, however, are limited to hardware and software infrastructures at hand and can be labor- and/or time-intensive. As a result, relying solely on real- world experiments impedes WMS research and development. An alternative is to conduct experiments in simulation.
In this work we present WRENCH, a WMS simulation framework, whose objectives are (i) accurate and scalable simula- tions; and (ii) easy simulation software development. WRENCH achieves its first objective by building on the SimGrid framework. While SimGrid is recognized for the accuracy and scalability of its simulation models, it only provides low-level simulation abstractions and thus large software development efforts are required when implementing simulators of complex systems. WRENCH thus achieves its second objective by providing high- level and directly re-usable simulation abstractions on top of SimGrid. After describing and giving rationales for WRENCH’s software architecture and APIs, we present a case study in which we apply WRENCH to simulate the Pegasus production WMS. We report on ease of implementation, simulation accuracy, and simulation scalability so as to determine to which extent WRENCH achieves its two above objectives. We also draw both qualitative and quantitative comparisons with a previously proposed workflow simulator.
This document discusses increasing cloud resilience through fault injection testing. It describes using the Butterfly Effect system to intentionally inject failures like hardware failures, network issues, and software bugs into OpenStack deployments. This allows failures to be tested, repairs to be learned, and future failures to be predicted. Monitoring tools like Monasca and Zabbix are used to detect damages and visualize results. The goal is to automate repair and increase reliability through continuous testing and learning from failures.
Workshop - Openstack, Cloud Computing, VirtualizationJayaprakash R
This document provides an overview of an OpenStack workshop held at Kalasalingam Institute of Technology on September 26th 2015. It defines cloud computing and the different cloud models (IaaS, PaaS, SaaS). It then discusses the core OpenStack components like Compute (Nova), Identity (Keystone), Networking (Neutron), Image (Glance), Block Storage (Cinder), Object Storage (Swift), Orchestration (Heat), and Telemetry (Ceilometer). It also covers concepts like hypervisors, security groups, networking, and provides examples of CLI commands for interacting with the different services.
an enhanced multi layered cryptosystem based secureIJAEMSJORNAL
As the cloud computing technology develops during the recent days, outsourcing data to cloud service for storage becomes an attractive trend, which benefits in sparing efforts on heavy data maintenance and management. Nevertheless, since the outsourced cloud storage is not fully trustworthy, it raises security concerns on how to realize data deduplication in cloud while achieving integrity auditing. In this work, we study the problem of integrity auditing and secure deduplication on cloud data. Specifically, willing achieving both data integrity and deduplication in cloud, we propose two secure systems, namely SecCloud and SecCloud. SecCloud introduces an auditing entity with maintenance of a Map Reduce cloud, which helps clients generate data tags before uploading still audit the integrity of data having been stored in cloud. Compared with previous work, the computation by user in SecCloud is greatly reduced during the file uploading and auditing phases. SecCloud is designed motivated individually fact that customers always must encrypt their data before uploading, and enables integrity auditing and secure deduplication on encrypted data.
Docker allows creating isolated environments called containers from images. Containers provide a standard way to develop, ship, and run applications. The document discusses how Docker can be used for scientific computing including running different versions of software, automating computations, sharing research environments and results, and providing isolated development environments for users through Docker IaaS tools. K-scope is a code analysis tool that previously required complex installation of its Omni XMP dependency, but could now be run as a containerized application to simplify deployment.
We are the company providing Complete Solution for all Academic Final Year/Semester Student Projects. Our projects are
suitable for B.E (CSE,IT,ECE,EEE), B.Tech (CSE,IT,ECE,EEE),M.Tech (CSE,IT,ECE,EEE) B.sc (IT & CSE), M.sc (IT & CSE),
MCA, and many more..... We are specialized on Java,Dot Net ,PHP & Andirod technologies. Each Project listed comes with
the following deliverable: 1. Project Abstract 2. Complete functional code 3. Complete Project report with diagrams 4.
Database 5. Screen-shots 6. Video File
SERVICE AT CLOUDTECHNOLOGIES
IEEE, WEB, WINDOWS PROJECTS ON DOT NET, JAVA& ANDROID TECHNOLOGIES,EMBEDDED SYSTEMS,MAT LAB,VLSI DESIGN.
ME, M-TECH PAPER PUBLISHING
COLLEGE TRAINING
Thanks&Regards
cloudtechnologies
# 304, Siri Towers,Behind Prime Hospitals
Maitrivanam, Ameerpet.
Contact:-8121953811,8522991105.040-65511811
cloudtechnologiesprojects@gmail.com
http://cloudstechnologies.in/
bulk ieee projects in pondicherry,ieee projects in pondicherry,final year ieee projects in pondicherry
Nexgen Technology Address:
Nexgen Technology
No :66,4th cross,Venkata nagar,
Near SBI ATM,
Puducherry.
Email Id: praveen@nexgenproject.com.
www.nexgenproject.com
Mobile: 9751442511,9791938249
Telephone: 0413-2211159.
NEXGEN TECHNOLOGY as an efficient Software Training Center located at Pondicherry with IT Training on IEEE Projects in Android,IEEE IT B.Tech Student Projects, Android Projects Training with Placements Pondicherry, IEEE projects in pondicherry, final IEEE Projects in Pondicherry , MCA, BTech, BCA Projects in Pondicherry, Bulk IEEE PROJECTS IN Pondicherry.So far we have reached almost all engineering colleges located in Pondicherry and around 90km
Dataservices - Processing Big Data The Microservice WayJosef Adersberger
We see a big data processing pattern emerging using the Microservice approach to build an integrated, flexible, and distributed system of data processing tasks. We call this the Dataservice pattern. In this presentation we'll introduce into Dataservices: their basic concepts, the technology typically in use (like Kubernetes, Kafka, Cassandra and Spring) and some architectures from real-life.
Running Accurate, Scalable, and Reproducible Simulations of Distributed Syste...Rafael Ferreira da Silva
Scientific workflows are used routinely in numerous scientific domains, and Workflow Management Systems (WMSs) have been developed to orchestrate and optimize workflow executions on distributed platforms. WMSs are complex software systems that interact with complex software infrastructures. Most WMS research and development activities rely on empirical experiments conducted with full-fledged software stacks on actual hardware platforms. Such experiments, however, are limited to hardware and software infrastructures at hand and can be labor- and/or time-intensive. As a result, relying solely on real- world experiments impedes WMS research and development. An alternative is to conduct experiments in simulation.
In this work we present WRENCH, a WMS simulation framework, whose objectives are (i) accurate and scalable simula- tions; and (ii) easy simulation software development. WRENCH achieves its first objective by building on the SimGrid framework. While SimGrid is recognized for the accuracy and scalability of its simulation models, it only provides low-level simulation abstractions and thus large software development efforts are required when implementing simulators of complex systems. WRENCH thus achieves its second objective by providing high- level and directly re-usable simulation abstractions on top of SimGrid. After describing and giving rationales for WRENCH’s software architecture and APIs, we present a case study in which we apply WRENCH to simulate the Pegasus production WMS. We report on ease of implementation, simulation accuracy, and simulation scalability so as to determine to which extent WRENCH achieves its two above objectives. We also draw both qualitative and quantitative comparisons with a previously proposed workflow simulator.
This document discusses increasing cloud resilience through fault injection testing. It describes using the Butterfly Effect system to intentionally inject failures like hardware failures, network issues, and software bugs into OpenStack deployments. This allows failures to be tested, repairs to be learned, and future failures to be predicted. Monitoring tools like Monasca and Zabbix are used to detect damages and visualize results. The goal is to automate repair and increase reliability through continuous testing and learning from failures.
Workshop - Openstack, Cloud Computing, VirtualizationJayaprakash R
This document provides an overview of an OpenStack workshop held at Kalasalingam Institute of Technology on September 26th 2015. It defines cloud computing and the different cloud models (IaaS, PaaS, SaaS). It then discusses the core OpenStack components like Compute (Nova), Identity (Keystone), Networking (Neutron), Image (Glance), Block Storage (Cinder), Object Storage (Swift), Orchestration (Heat), and Telemetry (Ceilometer). It also covers concepts like hypervisors, security groups, networking, and provides examples of CLI commands for interacting with the different services.
KubeCon EU 2019 "Securing Cloud Native Communication: From End User to Service"Daniel Bryant
Everyone building or operating cloud native applications must understand the fundamentals of security issues and modern threat models. Although this topic is vast, in this talk Nic and Daniel will focus on the end-to-end communication and higher-level networking threats, and explore how the combination of an edge proxy and service mesh using TLS and mTLS can be used to mitigate many man-in-the-middle attacks.
Key takeaways include:
- An understanding of the "three pillars" of service mesh functionality: observability, reliability, and security. A service mesh is in a unique place to enforce security features like mTLS
- Learn how to ensure that there are no exploitable "gaps" within the end-to-end/user-to-service communication path.
- Explore the differences in ingress/mesh control planes, with brief demonstrations using Ambassador and Consul Connect
SecCloudPro: A Novel Secure Cloud Storage System for Auditing and DeduplicationIJCERT
In this paper, we show the trustworthiness evaluating and secure deduplication over cloud data utilizing imaginative secure frameworks .Usually cloud framework outsourced information at cloud storage is semi-trusted because of absence of security at cloud storage while putting away or sharing at cloud level because of weak cryptosystem information may be uncover or adjusted by the hackers keeping in mind the end goal to ensure clients information protection and security We propose novel progressed secure framework i.e SecCloudPro which empower the cloud framework secured and legitimate utilizing Verifier(TPA) benefit of Cloud Server. Additionally our framework performs data deduplication in a Secured way in requested to enhance the cloud Storage space too data transfer capacity i.e bandwidth.
Building and Scaling Internet of Things Applications with Vortex CloudAngelo Corsaro
Cloud Messaging is one of the most critical elements at the core of any Internet of Things and Industrial Internet application. The degree of efficiency and connectivity provided by the cloud messaging technology usually drives the overall efficiency and reach of the entire system.
Vortex Cloud is a Cloud Messaging implementation that targets public as well as private clouds and enables embedded, mobile, web, enterprise and cloud applications to efficiently and securely share data across the Internet. Vortex Cloud has been designed ground up to address easy of connectivity, wire-efficiency, scalability, elasticity and security.
This presentation will (1) introduce the Vortex Cloud architecture and explain how it provides elasticity and fault-tolerance, (2) explain the different deployment models supported for public-cloud, private-cloud and no-cloud (3) get you started developing a simple Internet of Things Application.
Survey on Data Security with Time Constraint in CloudsIRJET Journal
This document discusses a proposed key-policy attribute-based encryption scheme with time-specified attributes (KP-TSABE) that aims to provide secure self-destructing of sensitive data stored in the cloud. The KP-TSABE scheme labels each ciphertext with a time interval and associates each private key with a time instant. A ciphertext can only be decrypted if the time instant falls within the specified time interval and if the attributes associated with the ciphertext satisfy the key's access structure. This allows fine-grained access control for a user-defined authorization period and ensures sensitive data is securely destroyed after an expiration time. The scheme is proven secure under cryptographic assumptions and is intended to address privacy and security challenges with sharing
FedRAMP Compliant FlexPod architecture from NetApp, Cisco, HyTrust and CoalfireEric Chiu
The FlexPod Datacenter solution combines NetApp storage systems, Cisco Unified Computing System (Cisco UCS) servers, and Cisco Nexus fabric into a single flexible architecture. The FlexPod integrated infrastructure leads in efficiency and flexibility, scaling and flexing as needed, with validated designs that reduce deployment time, project risk, and the cost of IT.
In this deployment, the FlexPod Datacenter solution is treated as the core infrastructure-as-a-service component. In addition, the HyTrust CloudControl and HyTrust DataControl software suites enable FlexPod readiness for FedRAMP environments.
Hybrid Cloud Approach for Secure Authorized DeduplicationPrem Rao
This document proposes a hybrid cloud approach for secure authorized data deduplication. It discusses existing systems that use data deduplication to reduce storage usage but lack security features. The proposed system uses convergent encryption for data confidentiality while allowing deduplication. It also aims to support authorized duplicate checks by encrypting files with differential privilege keys. The system design involves data owner, encryption/decryption, private cloud, public cloud, and cloud server modules. Cryptographic techniques like hashing and encryption are used along with communication via HTTP. The development follows a waterfall model with phases for requirements analysis, design, implementation, testing, and maintenance.
The document provides an overview of containers and Docker. It discusses why containers are important for organizing software, improving portability, and protecting infrastructure. It describes key Docker concepts like images, containers, Dockerfile for building images, and tools like Docker Compose and Docker Swarm for defining and running multi-container apps. The document recommends reading "The Art of War" and scanning systems without being detected before potentially more intrusive activities. It also briefly introduces network security pillars and buffer overflows as an attack technique.
What is Docker & Why is it Getting Popular?Mars Devs
Docker and containerization, in general, are now causing quite a stir But what is Docker, and how does it relate to containerization. Today, in this blog we will walk you through the nitty-gritty of Docker and why it is getting adopted rapidly.
Click here to know more: https://www.marsdevs.com/blogs/what-is-docker-why-is-it-getting-popular
This document provides an introduction to Docker. It discusses how Docker benefits both developers and operations staff by providing application isolation and portability. Key Docker concepts covered include images, containers, and features like swarm and routing mesh. The document also outlines some of the main benefits of Docker deployment such as cost savings, standardization, and rapid deployment. Some pros of Docker include consistency, ease of debugging, and community support, while cons include documentation gaps and performance issues on non-native environments.
Many of the advantages of using Docker containers include fast development, testing, and server deployments of your application. This PPT explains some of the Docker use cases that will help you to improve software development, application portability & deployment, and agility for your business
This document discusses Docker technology in cloud computing. It defines cloud computing and containerization using Docker. Docker is an open-source platform that allows developers to package applications with dependencies into standardized units called containers that can run on any infrastructure. The key components of Docker include images, containers, registries, and a daemon. Containers offer benefits over virtual machines like faster deployment, portability, and scalability. The document also discusses applications of Docker in cloud platforms and public registries like Docker Hub.
ASP.NET 5 es la nueva versión de .NET Framework rediseñada por completo, open source y multiplataforma.
Docker es una plataforma abierta que simplifica la creación, despliegue y ejecución de aplicaciones distribuidas usando tecnologías de virtualización de contenedores, consiguiendo entornos de ejecución aislados, mas seguros y flexibles.
Presentación de la charla sobre ASP.NET 5 y Docker que di en Betabeers Zaragoza.
En esta charla vimos en que consisten ambas tecnologías y como trabajar con ellas para crear y desplegar aplicaciones web flexibles de una forma sencilla.
Kubernetes Vs. Docker Swarm: Comparing the Best Container Orchestration Tool ...Katy Slemon
Let's see, the major advantages and disadvantages of the two most powerful and most popular container orchestration tools: Kubernetes and Docker Swarm.
This document discusses containers and container orchestration on Azure. It begins with an introduction to containers and their advantages over virtual machines. It then covers building Dockerfiles, container commands, and hosting container registries and applications on Azure. Container orchestration with Kubernetes is discussed as a way to deploy and scale containerized applications on the cloud, providing capabilities like auto-scaling, self-healing, service discovery and load balancing. The document points to additional future content on using Azure Kubernetes Service.
Early adopters report "easier replication, faster deployment and lower configuration and operating costs" of applications that involve Docker containers - an open platform that allows developers and sysadmins to build, ship and execute distributed applications.
Not surprisingly then, a groundswell of organizations are interested in evaluating Docker containers in proof-of-concept initiatives and/or pilot projects. The transition to production use, however, introduces additional requirements as Docker containers need to be incorporated into existing IT infrastructures and (ultimately) integrated into application workflows.
In answering the 5 Ws and one H, the aim of this webinar is to provide a technical overview and demonstration of Docker and to frame its use within the context of High Performance Computing and Big Data Analytics.
Learn all about Docker.
Agenda:
• What are Docker containers - relative to physical machines, VMs and other containers?
• Who is responsible for Docker containers?
• Why and when were Docker containers created?
• What is the container ecosystem?
• Where is use of containers appropriate and not appropriate?
▸ HPC applications?
▸ Big Data Analytics? Specifically, Spark-based applications?
▸ On premise and in the cloud?
▸ Is running Docker different in HPC versus microservice-based applications?
• How can I make use of Docker containers?
▸ How can I containerize my application?
▸ How can I create, or make use of, a Docker image?
▸ How can I run Docker containers as I do other types of workloads?
• Getting Started and Next Steps
Speaker:
Ian Lumb, System Architect, Univa Corporation.
As an HPC specialist, Ian Lumb has spent about two decades at the global intersection of IT and science. Ian received his B.Sc. from Montreal's McGill University, and then an M.Sc. from York University in Toronto. Although his undergraduate and graduate studies emphasized geophysics, Ian's current interests include workload orchestration and container optimization for HPC to Big Data Analytics in clusters and clouds.
Video Download
Video is available in .mp4 format from http://www.univa.com/resources/webinar-docker101.php.
The document discusses Docker and how it can benefit .NET developers. It begins with an introduction of the presenter and their background. It then outlines the agenda which includes explaining what Docker is, benefits of Docker for developers, using Docker on Windows, and how Docker can be used for ASP.NET development. The document proceeds to explain key Docker concepts such as images, containers, and layers. It also discusses how Docker can provide benefits like write once deploy anywhere, agility, control, portability, and enabling continuous integration and continuous delivery workflows. Lastly it covers using Docker with .NET on Windows and tools for developing and debugging ASP.NET applications in Docker containers.
Docker for .net developer, Container, Hyper-V, Docker Tool for VS, Windows Container, Images, Layer, Docker architecture, What is Docker, Docker Engine
The document discusses the architecture of Docker, including its core components like Docker Engine, Docker Hub, Docker Machine, Docker Compose, Kitematic, Docker Swarm, and Docker Registry. Docker Engine runs on Linux to build and run containers. Docker Hub is a hosted registry service for managing images. Docker Machine sets up Docker Engine on computers and in data centers. Docker Compose defines multi-container applications in a single file. Kitematic provides a GUI for building and running containers. Docker Swarm turns Docker engines into a clustered virtual engine. Docker Registry stores and distributes Docker images.
Docker is an open source tool that allows developers to package applications into containers to deliver software quickly. It solves problems with slow innovation, inconsistent environments ("works on my machine"), and high support costs by allowing developers to build once and run anywhere. Docker uses containers as a lightweight alternative to virtual machines, allowing applications and their dependencies to run reliably and be isolated from other containers and the underlying infrastructure. Key benefits of Docker include accelerated development, consistency across environments, increased security, easy scaling, and quick remediation of issues.
KubeCon EU 2019 "Securing Cloud Native Communication: From End User to Service"Daniel Bryant
Everyone building or operating cloud native applications must understand the fundamentals of security issues and modern threat models. Although this topic is vast, in this talk Nic and Daniel will focus on the end-to-end communication and higher-level networking threats, and explore how the combination of an edge proxy and service mesh using TLS and mTLS can be used to mitigate many man-in-the-middle attacks.
Key takeaways include:
- An understanding of the "three pillars" of service mesh functionality: observability, reliability, and security. A service mesh is in a unique place to enforce security features like mTLS
- Learn how to ensure that there are no exploitable "gaps" within the end-to-end/user-to-service communication path.
- Explore the differences in ingress/mesh control planes, with brief demonstrations using Ambassador and Consul Connect
SecCloudPro: A Novel Secure Cloud Storage System for Auditing and DeduplicationIJCERT
In this paper, we show the trustworthiness evaluating and secure deduplication over cloud data utilizing imaginative secure frameworks .Usually cloud framework outsourced information at cloud storage is semi-trusted because of absence of security at cloud storage while putting away or sharing at cloud level because of weak cryptosystem information may be uncover or adjusted by the hackers keeping in mind the end goal to ensure clients information protection and security We propose novel progressed secure framework i.e SecCloudPro which empower the cloud framework secured and legitimate utilizing Verifier(TPA) benefit of Cloud Server. Additionally our framework performs data deduplication in a Secured way in requested to enhance the cloud Storage space too data transfer capacity i.e bandwidth.
Building and Scaling Internet of Things Applications with Vortex CloudAngelo Corsaro
Cloud Messaging is one of the most critical elements at the core of any Internet of Things and Industrial Internet application. The degree of efficiency and connectivity provided by the cloud messaging technology usually drives the overall efficiency and reach of the entire system.
Vortex Cloud is a Cloud Messaging implementation that targets public as well as private clouds and enables embedded, mobile, web, enterprise and cloud applications to efficiently and securely share data across the Internet. Vortex Cloud has been designed ground up to address easy of connectivity, wire-efficiency, scalability, elasticity and security.
This presentation will (1) introduce the Vortex Cloud architecture and explain how it provides elasticity and fault-tolerance, (2) explain the different deployment models supported for public-cloud, private-cloud and no-cloud (3) get you started developing a simple Internet of Things Application.
Survey on Data Security with Time Constraint in CloudsIRJET Journal
This document discusses a proposed key-policy attribute-based encryption scheme with time-specified attributes (KP-TSABE) that aims to provide secure self-destructing of sensitive data stored in the cloud. The KP-TSABE scheme labels each ciphertext with a time interval and associates each private key with a time instant. A ciphertext can only be decrypted if the time instant falls within the specified time interval and if the attributes associated with the ciphertext satisfy the key's access structure. This allows fine-grained access control for a user-defined authorization period and ensures sensitive data is securely destroyed after an expiration time. The scheme is proven secure under cryptographic assumptions and is intended to address privacy and security challenges with sharing
FedRAMP Compliant FlexPod architecture from NetApp, Cisco, HyTrust and CoalfireEric Chiu
The FlexPod Datacenter solution combines NetApp storage systems, Cisco Unified Computing System (Cisco UCS) servers, and Cisco Nexus fabric into a single flexible architecture. The FlexPod integrated infrastructure leads in efficiency and flexibility, scaling and flexing as needed, with validated designs that reduce deployment time, project risk, and the cost of IT.
In this deployment, the FlexPod Datacenter solution is treated as the core infrastructure-as-a-service component. In addition, the HyTrust CloudControl and HyTrust DataControl software suites enable FlexPod readiness for FedRAMP environments.
Hybrid Cloud Approach for Secure Authorized DeduplicationPrem Rao
This document proposes a hybrid cloud approach for secure authorized data deduplication. It discusses existing systems that use data deduplication to reduce storage usage but lack security features. The proposed system uses convergent encryption for data confidentiality while allowing deduplication. It also aims to support authorized duplicate checks by encrypting files with differential privilege keys. The system design involves data owner, encryption/decryption, private cloud, public cloud, and cloud server modules. Cryptographic techniques like hashing and encryption are used along with communication via HTTP. The development follows a waterfall model with phases for requirements analysis, design, implementation, testing, and maintenance.
The document provides an overview of containers and Docker. It discusses why containers are important for organizing software, improving portability, and protecting infrastructure. It describes key Docker concepts like images, containers, Dockerfile for building images, and tools like Docker Compose and Docker Swarm for defining and running multi-container apps. The document recommends reading "The Art of War" and scanning systems without being detected before potentially more intrusive activities. It also briefly introduces network security pillars and buffer overflows as an attack technique.
What is Docker & Why is it Getting Popular?Mars Devs
Docker and containerization, in general, are now causing quite a stir But what is Docker, and how does it relate to containerization. Today, in this blog we will walk you through the nitty-gritty of Docker and why it is getting adopted rapidly.
Click here to know more: https://www.marsdevs.com/blogs/what-is-docker-why-is-it-getting-popular
This document provides an introduction to Docker. It discusses how Docker benefits both developers and operations staff by providing application isolation and portability. Key Docker concepts covered include images, containers, and features like swarm and routing mesh. The document also outlines some of the main benefits of Docker deployment such as cost savings, standardization, and rapid deployment. Some pros of Docker include consistency, ease of debugging, and community support, while cons include documentation gaps and performance issues on non-native environments.
Many of the advantages of using Docker containers include fast development, testing, and server deployments of your application. This PPT explains some of the Docker use cases that will help you to improve software development, application portability & deployment, and agility for your business
This document discusses Docker technology in cloud computing. It defines cloud computing and containerization using Docker. Docker is an open-source platform that allows developers to package applications with dependencies into standardized units called containers that can run on any infrastructure. The key components of Docker include images, containers, registries, and a daemon. Containers offer benefits over virtual machines like faster deployment, portability, and scalability. The document also discusses applications of Docker in cloud platforms and public registries like Docker Hub.
ASP.NET 5 es la nueva versión de .NET Framework rediseñada por completo, open source y multiplataforma.
Docker es una plataforma abierta que simplifica la creación, despliegue y ejecución de aplicaciones distribuidas usando tecnologías de virtualización de contenedores, consiguiendo entornos de ejecución aislados, mas seguros y flexibles.
Presentación de la charla sobre ASP.NET 5 y Docker que di en Betabeers Zaragoza.
En esta charla vimos en que consisten ambas tecnologías y como trabajar con ellas para crear y desplegar aplicaciones web flexibles de una forma sencilla.
Kubernetes Vs. Docker Swarm: Comparing the Best Container Orchestration Tool ...Katy Slemon
Let's see, the major advantages and disadvantages of the two most powerful and most popular container orchestration tools: Kubernetes and Docker Swarm.
This document discusses containers and container orchestration on Azure. It begins with an introduction to containers and their advantages over virtual machines. It then covers building Dockerfiles, container commands, and hosting container registries and applications on Azure. Container orchestration with Kubernetes is discussed as a way to deploy and scale containerized applications on the cloud, providing capabilities like auto-scaling, self-healing, service discovery and load balancing. The document points to additional future content on using Azure Kubernetes Service.
Early adopters report "easier replication, faster deployment and lower configuration and operating costs" of applications that involve Docker containers - an open platform that allows developers and sysadmins to build, ship and execute distributed applications.
Not surprisingly then, a groundswell of organizations are interested in evaluating Docker containers in proof-of-concept initiatives and/or pilot projects. The transition to production use, however, introduces additional requirements as Docker containers need to be incorporated into existing IT infrastructures and (ultimately) integrated into application workflows.
In answering the 5 Ws and one H, the aim of this webinar is to provide a technical overview and demonstration of Docker and to frame its use within the context of High Performance Computing and Big Data Analytics.
Learn all about Docker.
Agenda:
• What are Docker containers - relative to physical machines, VMs and other containers?
• Who is responsible for Docker containers?
• Why and when were Docker containers created?
• What is the container ecosystem?
• Where is use of containers appropriate and not appropriate?
▸ HPC applications?
▸ Big Data Analytics? Specifically, Spark-based applications?
▸ On premise and in the cloud?
▸ Is running Docker different in HPC versus microservice-based applications?
• How can I make use of Docker containers?
▸ How can I containerize my application?
▸ How can I create, or make use of, a Docker image?
▸ How can I run Docker containers as I do other types of workloads?
• Getting Started and Next Steps
Speaker:
Ian Lumb, System Architect, Univa Corporation.
As an HPC specialist, Ian Lumb has spent about two decades at the global intersection of IT and science. Ian received his B.Sc. from Montreal's McGill University, and then an M.Sc. from York University in Toronto. Although his undergraduate and graduate studies emphasized geophysics, Ian's current interests include workload orchestration and container optimization for HPC to Big Data Analytics in clusters and clouds.
Video Download
Video is available in .mp4 format from http://www.univa.com/resources/webinar-docker101.php.
The document discusses Docker and how it can benefit .NET developers. It begins with an introduction of the presenter and their background. It then outlines the agenda which includes explaining what Docker is, benefits of Docker for developers, using Docker on Windows, and how Docker can be used for ASP.NET development. The document proceeds to explain key Docker concepts such as images, containers, and layers. It also discusses how Docker can provide benefits like write once deploy anywhere, agility, control, portability, and enabling continuous integration and continuous delivery workflows. Lastly it covers using Docker with .NET on Windows and tools for developing and debugging ASP.NET applications in Docker containers.
Docker for .net developer, Container, Hyper-V, Docker Tool for VS, Windows Container, Images, Layer, Docker architecture, What is Docker, Docker Engine
The document discusses the architecture of Docker, including its core components like Docker Engine, Docker Hub, Docker Machine, Docker Compose, Kitematic, Docker Swarm, and Docker Registry. Docker Engine runs on Linux to build and run containers. Docker Hub is a hosted registry service for managing images. Docker Machine sets up Docker Engine on computers and in data centers. Docker Compose defines multi-container applications in a single file. Kitematic provides a GUI for building and running containers. Docker Swarm turns Docker engines into a clustered virtual engine. Docker Registry stores and distributes Docker images.
Docker is an open source tool that allows developers to package applications into containers to deliver software quickly. It solves problems with slow innovation, inconsistent environments ("works on my machine"), and high support costs by allowing developers to build once and run anywhere. Docker uses containers as a lightweight alternative to virtual machines, allowing applications and their dependencies to run reliably and be isolated from other containers and the underlying infrastructure. Key benefits of Docker include accelerated development, consistency across environments, increased security, easy scaling, and quick remediation of issues.
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.
This document introduces Docker. It discusses that Docker uses containerization rather than virtualization, allowing applications and their dependencies to run in isolated containers that share the host operating system's kernel. It describes Docker's client-server architecture with containers built from images and run by the Docker daemon. Benefits of Docker include low overhead, speed, and portability of applications, while disadvantages include potential backup and management challenges for large numbers of containers.
Using Docker container technology with F5 Networks products and servicesF5 Networks
This document discusses how Docker containerization technology can be used with F5 products and services. It provides an overview of Docker, comparing it to virtual machines. Docker allows for higher resource utilization and faster application deployment than VMs. The document outlines how F5 supports using containers and integrating with Docker for application delivery and security services. It describes Docker networking and how F5 solutions can provide services like load balancing within Docker container environments.
This document provides an overview of Docker and containers for data science. It begins with definitions of containers and discusses the history and benefits of containers. It then explains how Docker containers work using namespaces, cgroups, and union file systems. Key Docker concepts are introduced like Dockerfiles, images, containers, and the Docker architecture. Practical examples are given for building simple machine learning models and databases in containers. Advanced topics covered include Docker Compose, DevOps workflows, continuous delivery, and Kubernetes. The document is intended to provide data scientists with an introduction to using Docker for their work.
This document provides an overview of containers and Docker. It discusses how containers can help modernize applications and infrastructure by increasing performance and flexibility compared to traditional virtual machines. The document then demonstrates how to use basic Docker commands like pull, run, stop, and remove to build and run an Apache container on Docker. It shows the benefits of containers for enterprises looking to adopt cloud-native applications and DevOps.
This document provides an overview of using Arquillian to test Java EE applications. It discusses creating test archives using ShrinkWrap or Maven, configuring Arquillian to run in managed or embedded mode, and including persistence functionality to generate test data from SQL scripts, XML/JSON, or manually in test code. The document contains code samples and dependencies needed to set up an Arquillian test.
The document discusses the relationships between various concepts related to data analysis including big data, machine learning, business intelligence, and knowledge discovery in databases (KDD). It states that KDD refers to the overall process of discovering useful knowledge from data and focuses on how data is stored, accessed, and analyzed. Data mining is a part of the KDD process that uses techniques from artificial intelligence, statistics, and machine learning to extract and transform information from datasets. Machine learning develops the algorithms used in data mining to learn from data. Big data refers to analyzing huge, unstructured data using distributed computing and new tools. Business intelligence uses analytical techniques to present actionable information for business decision making.
This document provides information about OPC connectivity using Java. It discusses what OPC is, why it was developed, and provides examples of companies using OPC like Bosch and ABB. It then describes a case study of implementing an OPC client in Java using the Utgard library and connecting to a Matrikon OPC server for simulation. It outlines the steps to configure DCOM and Eclipse, and includes code examples for reading and writing tags.
This document provides an introduction to machine learning, including definitions, applications, and types of problems. It discusses how machine learning can be applied to data from sensors in industrial settings for tasks like risk prevention in real-time, searching historical data for patterns related to failures, estimating machine lifespan and product quality, and enabling more automated intelligent systems. Large amounts of data are generated every day from various sources, making it impossible for humans to analyze, but machine learning can find hidden patterns in this data.
This document discusses Java EE architecture and patterns. It provides an overview of the latest Java EE technologies, including the Entity, Control, and Boundary (ECB) pattern. It also covers concepts like convention over configuration, annotations, dependency injection, bean validation, and interceptors/aspect-oriented programming in Java EE. The document includes examples and labs/exercises for attendees to implement these techniques in Java EE applications.
This document discusses Industry 4.0 and what it means for the partnership between Tekniker/ES and Brockhaus Group. It defines Industry 4.0 as the fourth industrial revolution focused on software and information processing. It describes how Industry 4.0 will enable decentralized production through smart objects, autonomous products, and real-time decision making. For the partnership, Industry 4.0 means opportunities to improve production quality through data analysis, optimize maintenance through equipment prognostics, and enable new ways of interacting with equipment via mobile devices and augmented reality. Example reference projects are described that apply predictive maintenance, anomaly detection, and big data analysis to wind turbines, machine tools, and automotive production lines.
10.000 ft. overview about the options of storing values of 250.000 sensors from a paint shop in automotive sector; presentation for the management of one of our customers.
The document discusses the architectural process that a software architect undertakes. It begins with gathering information such as reviewing existing solutions and patterns. The architect then develops an initial idea of the system, identifies important drivers and boundaries, and risks. Key aspects of quality are defined using scenarios. The architect then develops strategies to address the identified risks and quality aspects.
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Enhanced data collection methods can help uncover the true extent of child abuse and neglect. This includes Integrated Data Systems from various sources (e.g., schools, healthcare providers, social services) to identify patterns and potential cases of abuse and neglect.
Discovering Digital Process Twins for What-if Analysis: a Process Mining Appr...Marlon Dumas
This webinar discusses the limitations of traditional approaches for business process simulation based on had-crafted model with restrictive assumptions. It shows how process mining techniques can be assembled together to discover high-fidelity digital twins of end-to-end processes from event data.
24.
Step 6: Containerize Application
Docker can build images automatically by reading the instructions from a Dockerfile, a text file that
contains all the commands, in order, needed to build a given image. Dockerfiles adhere to a specific
format and use a specific set of instructions. We can learn the basics on the Dockerfile Reference
page.
Docker has a simple Dockerfile file format that it uses to specify the "layers" of an image. So let’s go
ahead and create a Dockerfile in our Spring Cassandra Example Project:
Dockerfile
FROM java:8
# Install maven
RUN apt‐get update
RUN apt‐get install ‐y maven
WORKDIR /code
# Prepare by downloading dependencies
ADD pom.xml /code/pom.xml
RUN ["mvn", "dependency:resolve"]
RUN ["mvn", "verify"]
# Adding source to WORKDIR
ADD src /code/src
RUN ["mvn", "package"]
EXPOSE 8080
CMD ["java", "‐jar", "target/demo‐0.0.1‐SNAPSHOT.jar"]
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