Poster X-Meeting 2015 - Improving automation, reproducibility and installation of genomic pipelines with Docker.
Authors: Marcel Caraciolo and Felipe Figuereirdo
Toffee – A highly efficient, lossless file format for DIA-MSBrett Tully
The closed nature of vendor file formats in mass spectrometry is a significant barrier to progress in developing robust bioinformatics software. In response, the community has developed the open mzML format, implemented in XML and based on controlled vocabularies [1]. Widely adopted, mzML is an important step forward; however, it suffers from two challenges that are particularly apparent as the field moves to high-throughput proteomics: a) large increase in file size – and corresponding increase in CPU time devoted to I/O, and b) a largely sequential I/O access pattern. Described here is ‘toffee’, an open, random I/O format backed by HDF5, with lossless compression that gives file sizes similar to the original vendor format and can be reconverted back to mzML without penalty. In addition to the file format, there are C++ and python libraries for creating and accessing the file format, along with a wrapper around OpenSWATH [2] that enables SWATH-MS data to be analyzed with standard algorithms. Using this library, the files can be accessed in the same manner as the Vendor file (or mzML) in a scan-by-scan manner; however, by accepting a degree of mass approximation (<5 parts per million) toffee enables data to be extracted as a two-dimensional slice analogous to an image, and thus amenable to deep-learning based peptide identification strategies. Documentation and examples are available at https://toffee.readthedocs.io, and all code is MIT licensed at https://bitbucket.org/cmriprocan/toffee.
Applying the Scientific Method to Simulation ExperimentsFrank Bergmann
In this talk I would like to explore on how to apply the scientific method to in silico experiments. How can we design these experiments, so that they are independent of the software tool that gave rise to them? Over the past decade we have seen the rise of model exchange formats such as the Systems Biology Markup Language (SBML), that enable us to share the models readily with colleagues and between applications.
Here I present the Simulation Experiment Description Markup Language (SED-ML) that aims to do the same thing for in silico experiments. After detailing its history, and where it currently stands, I will give a short overview of the growing tool support.
Geared towards bioinformatics students and taking a somewhat humoristic point of view, this presentation explains what bioinformaticians are and what they do.
Conner Poole has earned a Certificate of Achievement for completing the CRAS requirements and demonstrating proficiency in Pro Tools Tier 2 as of June 29, 2015. The certificate is numbered TAP8kYU8z4.
The document discusses using the pHash library for audio fingerprinting. pHash is a C/C++ library that supports fingerprinting of audio, video, and images. It generates hashes based on the bark scale frequencies that humans can hear and compares the bit error rate between hashes to determine a match. The document outlines a project to use pHash for audio fingerprinting, including a bash script to run the process and an 87 line C++ file to calculate hashes and determine matches. Areas for potential improvement are also discussed.
Reproducible bioinformatics pipelines with Docker and AndurilChristian Frech
Christian Frech presented on using Docker and Anduril to create reproducible bioinformatics pipelines. Anduril is a pipeline framework that aims to make pipelines modular, bundled with their execution environment, and able to be run on clusters. It uses a proprietary scripting language but can embed other languages. Frech demonstrated an RNA-seq analysis pipeline built in Anduril, which generated QC plots, differential expression results, network and enrichment analyses. While adoption of Anduril has been limited by its scripting language, Docker can be used to containerize components and make pipelines fully reproducible and portable.
Kishor S is a VLSI design engineer seeking a challenging position to contribute his 1 year and 7 month experience in RTL design using VHDL and Verilog. He has skills in communication protocols like UART, SPI, I2C, and encryption algorithms. He has experience using tools like Tanner EDA, Xilinx ISE, and Altera FPGA design software. Notable projects include developing clock and control signals for a CCD image sensor, a color sorting algorithm, and an interface for an HMI. He holds a Bachelor's degree in Electronics and Communication Engineering.
Prometheus: From Berlin to Bonanza (Keynote CloudNativeCon+Kubecon Europe 2017)Brian Brazil
Brian Brazil is a founder of Robust Perception and core developer of Prometheus. Prometheus started in 2012 in Berlin and is now used by over 500 companies. It is an open source monitoring system that collects and stores metrics, has a query language, and supports alerting. Prometheus uses client libraries to instrument code and exporters to collect metrics from systems. It can automatically discover services in Kubernetes and is designed for cloud native monitoring.
Toffee – A highly efficient, lossless file format for DIA-MSBrett Tully
The closed nature of vendor file formats in mass spectrometry is a significant barrier to progress in developing robust bioinformatics software. In response, the community has developed the open mzML format, implemented in XML and based on controlled vocabularies [1]. Widely adopted, mzML is an important step forward; however, it suffers from two challenges that are particularly apparent as the field moves to high-throughput proteomics: a) large increase in file size – and corresponding increase in CPU time devoted to I/O, and b) a largely sequential I/O access pattern. Described here is ‘toffee’, an open, random I/O format backed by HDF5, with lossless compression that gives file sizes similar to the original vendor format and can be reconverted back to mzML without penalty. In addition to the file format, there are C++ and python libraries for creating and accessing the file format, along with a wrapper around OpenSWATH [2] that enables SWATH-MS data to be analyzed with standard algorithms. Using this library, the files can be accessed in the same manner as the Vendor file (or mzML) in a scan-by-scan manner; however, by accepting a degree of mass approximation (<5 parts per million) toffee enables data to be extracted as a two-dimensional slice analogous to an image, and thus amenable to deep-learning based peptide identification strategies. Documentation and examples are available at https://toffee.readthedocs.io, and all code is MIT licensed at https://bitbucket.org/cmriprocan/toffee.
Applying the Scientific Method to Simulation ExperimentsFrank Bergmann
In this talk I would like to explore on how to apply the scientific method to in silico experiments. How can we design these experiments, so that they are independent of the software tool that gave rise to them? Over the past decade we have seen the rise of model exchange formats such as the Systems Biology Markup Language (SBML), that enable us to share the models readily with colleagues and between applications.
Here I present the Simulation Experiment Description Markup Language (SED-ML) that aims to do the same thing for in silico experiments. After detailing its history, and where it currently stands, I will give a short overview of the growing tool support.
Geared towards bioinformatics students and taking a somewhat humoristic point of view, this presentation explains what bioinformaticians are and what they do.
Conner Poole has earned a Certificate of Achievement for completing the CRAS requirements and demonstrating proficiency in Pro Tools Tier 2 as of June 29, 2015. The certificate is numbered TAP8kYU8z4.
The document discusses using the pHash library for audio fingerprinting. pHash is a C/C++ library that supports fingerprinting of audio, video, and images. It generates hashes based on the bark scale frequencies that humans can hear and compares the bit error rate between hashes to determine a match. The document outlines a project to use pHash for audio fingerprinting, including a bash script to run the process and an 87 line C++ file to calculate hashes and determine matches. Areas for potential improvement are also discussed.
Reproducible bioinformatics pipelines with Docker and AndurilChristian Frech
Christian Frech presented on using Docker and Anduril to create reproducible bioinformatics pipelines. Anduril is a pipeline framework that aims to make pipelines modular, bundled with their execution environment, and able to be run on clusters. It uses a proprietary scripting language but can embed other languages. Frech demonstrated an RNA-seq analysis pipeline built in Anduril, which generated QC plots, differential expression results, network and enrichment analyses. While adoption of Anduril has been limited by its scripting language, Docker can be used to containerize components and make pipelines fully reproducible and portable.
Kishor S is a VLSI design engineer seeking a challenging position to contribute his 1 year and 7 month experience in RTL design using VHDL and Verilog. He has skills in communication protocols like UART, SPI, I2C, and encryption algorithms. He has experience using tools like Tanner EDA, Xilinx ISE, and Altera FPGA design software. Notable projects include developing clock and control signals for a CCD image sensor, a color sorting algorithm, and an interface for an HMI. He holds a Bachelor's degree in Electronics and Communication Engineering.
Prometheus: From Berlin to Bonanza (Keynote CloudNativeCon+Kubecon Europe 2017)Brian Brazil
Brian Brazil is a founder of Robust Perception and core developer of Prometheus. Prometheus started in 2012 in Berlin and is now used by over 500 companies. It is an open source monitoring system that collects and stores metrics, has a query language, and supports alerting. Prometheus uses client libraries to instrument code and exporters to collect metrics from systems. It can automatically discover services in Kubernetes and is designed for cloud native monitoring.
COST-EFFECTIVE LOW-DELAY DESIGN FOR MULTI-PARTY CLOUD VIDEO CONFERENCINGnexgentechnology
GET IEEE BIG DATA,JAVA ,DOTNET,ANDROID ,NS2,MATLAB,EMBEDED AT LOW COST WITH BEST QUALITY PLEASE CONTACT BELOW NUMBER
FOR MORE INFORMATION PLEASE FIND THE BELOW DETAILS:
Nexgen Technology
No :66,4th cross,Venkata nagar,
Near SBI ATM,
Puducherry.
Email Id: praveen@nexgenproject.com
Mobile: 9791938249
Telephone: 0413-2211159
www.nexgenproject.com
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.
Mobile IoT Middleware Interoperability & QoS Analysis - Eclipse IoT Day Paris...Nikolaos Georgantas
Research results by the Inria Paris MiMove Team on Mobile IoT Middleware Interoperability & QoS Analysis. Presentation at Eclipse IoT Day Paris Saclay 2019
Building cloud-enabled genomics workflows with Luigi and DockerJacob Feala
Talk given at Bio-IT 2016, Cloud Computing track
Abstract:
As bioinformatics scientists, we tend to write custom tools for managing our workflows, even when viable, open-source alternatives are available from the tech community. Our field has, however, begun to adopt Docker containers to stabilize compute environments. In this talk, I will introduce Luigi, a workflow system built by engineers at Spotify to manage long-running big data processing jobs with complex dependencies. Focusing on a case study of next generation sequencing analysis in cancer genomics research, I will show how Luigi can connect simple, containerized applications into complex bioinformatics pipelines that can be easily integrated with compute, storage, and data warehousing on the cloud.
The document discusses providing actuator and sensor access as a service over the internet. It proposes an algorithm for resource requisition that creates locks on actuator instances to prevent multiple simultaneous requests. This ensures actuators can only respond to one command at a time. The algorithm also analyzes request volume to optimize traffic to unavailable resources. An API is developed to abstract away hardware details and provide platform-independent parameter retrieval and actuation. This allows developers to focus on application logic rather than hardware integration.
This document discusses the need for an open source IoT development environment and testbed to allow software developers to create IoT applications without requiring hardware expertise. It notes that existing IoT testbeds often use proprietary hardware and software, limiting interoperability. The proposed solution aims to provide virtual access to sensors and actuators through an API, as well as a microcontroller platform as a service. This would allow developers to write code without worrying about hardware integration and deployment details. The goal is to make IoT development and testing more accessible through an open testbed that addresses issues like sensor availability and cost.
Peter Gervais is a senior systems engineer, architect and programmer with over 25 years of experience spanning various industries including telecommunications, air traffic control, intelligence agencies, web development, and more. He has expertise in languages like Java, C++, PHP, and operating systems like UNIX, Linux, and Windows. He is fluent in both French and English and has held positions at companies such as Nortel, Cisco, General Dynamics, Nav Canada, and Canadian intelligence services.
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.
Outdated training deck for Prometheus monitoring tool - shared as a basis for newer content for potential MeetUp and Conference talks. I'm sharing it since there is some intrinsic value remaining.
Summit 16: Cengn Experience in Opnfv ProjectsOPNFV
CENGN, the first associate member of OPNFV is beginning to contribute to OPNFV projects by way of creating a Pharos Community lab and participating in JOID and Yardstick projects with OPNFV interns. This session will cover our learnings on the design and deployment of the Pharos lab, our experience with student interns contributing to the OPNFV projects and partnerships with innovative companies like Kontron
Evaluation of Container Virtualized MEGADOCK System in Distributed Computing ...Kento Aoyama
This document evaluates the performance of container virtualization using Docker for a bioinformatics application called MEGADOCK. Two experiments were conducted:
1) MEGADOCK was run on a physical machine with and without Docker, showing a 6.32% performance overhead with Docker. With NVIDIA Docker on GPU, performance was comparable to native.
2) MEGADOCK was run on Azure VMs with and without Docker, showing comparable scalability. Docker performance was around 6x faster than VMs.
The results show that Docker introduces small overhead for compute-intensive applications like MEGADOCK. Docker provides advantages of environment isolation and portability without significant performance costs.
Audio/Video Conferencing in Distributed Brokering SystemsVideoguy
This document proposes using a distributed brokering system called NaradaBrokering to support audio/video conferencing. It outlines improvements made over previous work, including eliminating redundant headers from messages and supporting legacy applications. The key contribution is a new event called RTPEvent that compactly encapsulates multimedia content for efficient routing while avoiding echo problems and supporting variable length topic names. Experimental results show NaradaBrokering can effectively support real-time audio/video conferencing among large, heterogeneous clients.
MACHINE LEARNING AUTOMATIONS PIPELINE WITH CI/CDIRJET Journal
This document discusses integrating machine learning pipelines with continuous integration and continuous deployment (CI/CD) tools to automate machine learning workflows. It proposes using DevOps tools like Jenkins, Docker, and GitHub to build a CI/CD pipeline for machine learning. The pipeline would include steps for data preprocessing, model training, evaluation, and deployment. Continuous integration would involve regular code updates and testing. Continuous deployment would push trained models to production for monitoring. The goal is to reduce costs and resources needed for machine learning projects through automation with DevOps practices like CI/CD.
The document discusses the EOSC Test Suite, which provides automated testing of cloud services for research. It outlines the timeline and context of the Test Suite, describing how it deploys scientific workloads and containerized tests across heterogeneous cloud platforms. The document also details the process for including new tests in the Test Suite, lists examples of deployments that have been run, and discusses the benefits of the Test Suite for validating cloud services and providing examples for researchers.
This document discusses cloud native technologies and continuous integration/continuous delivery (CI/CD) practices.
It defines cloud native as using containers, microservices, immutable infrastructure and other techniques to build scalable applications on public, private or hybrid clouds. These allow for loosely coupled, resilient and observable systems.
The document then discusses how containers enable lightweight packaging and isolation which supports modern development practices. It outlines common cloud native tools and how standardizing on these helps with areas like service communication and monitoring.
Finally, it discusses how adopting CI/CD practices like automated testing, deployment and monitoring can significantly reduce the time it takes to develop and release changes from over 100 minutes to potentially just minutes. This allows for much faster
Docker-PPT.pdf for presentation and otheradarsh20cs004
Consistency: With Docker, developers can create Dockerfiles to define the environment and dependencies required for their applications. This ensures consistent development, testing, and production environments, reducing deployment errors and streamlining workflows.
Scalability: Docker's containerization model facilitates horizontal scaling by replicating containers across multiple nodes or instances. This scalability enables applications to handle varying workload demands and ensures optimal performance during peak usage times.
Speed: Docker containers start up quickly and have faster deployment times compared to traditional deployment methods. This speed is especially beneficial for continuous integration/continuous deployment (CI/CD) pipelines, where rapid iteration and deployment are essential.
Complexity: Docker introduces additional complexity, especially for users who are new to containerization concepts. Understanding Dockerfile syntax, image creation, container orchestration, networking, and storage management can be challenging for beginners.
Security Concerns: While Docker provides isolation at the process level, it is still possible for vulnerabilities or misconfigurations to compromise container security. Shared kernel vulnerabilities, improper container configurations, and insecure container images can pose security risks.
Networking Complexity: Docker's networking capabilities, while powerful, can be complex to configure and manage, especially in distributed or multi-container environments. Issues such as container-to-container communication, network segmentation, and service discovery may require additional expertise
Fake general image detection refers to the process of identifying whether an image has been manipulated or altered in some way to create a deceptive or false representation of reality. This type of detection is commonly used in fields such as forensics, journalism, and social media moderation to identify images that have been doctored or manipulated for malicious purposes, such as spreading fake news, propaganda, or misinformation. Fake general image detection techniques can include analyzing the image's metadata, examining inconsistencies in the lighting and shadows, identifying anomalies in the image's pixel patterns, and comparing the image to known authentic images or reference images. Some algorithms use machine learning techniques to analyze large datasets of both authentic and fake images to improve the accuracy of their detection.
However, it's important to note that no single method or algorithm can detect all types of fake images with 100% accuracy, and as technology advances, so do the techniques for creating convincing fake images. Therefore, it's essential to use a combination of techniques and human expertise to identify fake images and prevent them from spreading.
There are several techniques that can be used to detect fake images on social media. Here are a few examples: Done it
Containers, the next wave of virtualization, are changing everything! As companies learn about the value of DevOps practices and containerization they are flocking to containers. Now with Docker running on Windows and Docker Containers built into both Azure and Windows Server, containers are poised to take over the virtualization landscape. Come to the session to learn all about containers and how you can put these technologies to use in your organization. You will learn about DevOps, Docker Containers, Running Containers on Windows 10, Windows Server 2016 and Linux on-premises or in the Azure cloud. You will learn about the tools and practices for leveraging containers, deploying containers as well as how you can continue on your journey to becoming a container expert as you grow your technical career.
The document provides an overview of the DevOps training program offered by Edureka. It covers topics such as introduction to DevOps, DevOps tools and lifecycle phases including continuous integration with Jenkins, containerization with Docker, version control with Git and GitHub, continuous deployment with Puppet, continuous testing with Selenium, and continuous monitoring with Nagios. The document also discusses career guidance and top DevOps interview questions. It aims to help readers master DevOps concepts and tools to become DevOps professionals.
The document discusses DevOps tools and concepts. It introduces DevOps and its benefits, then describes the DevOps lifecycle which includes continuous development, integration, testing, deployment, and monitoring. It also discusses specific DevOps tools, including Git and GitHub for version control, Jenkins for continuous integration, and Docker for containerization. The document provides overviews and examples of using these tools at different stages of the DevOps process.
O documento descreve o desenvolvimento de um aplicativo móvel chamado MamaRisk para auxiliar médicos e pacientes na avaliação do risco hereditário de câncer de mama através de perguntas e respostas simples. O aplicativo cruza as respostas dos usuários com as diretrizes da NCCN para determinar a indicação de teste genético e fornecer contexto educacional. Testes com usuários resultaram em melhorias na usabilidade e compreensão do aplicativo.
COST-EFFECTIVE LOW-DELAY DESIGN FOR MULTI-PARTY CLOUD VIDEO CONFERENCINGnexgentechnology
GET IEEE BIG DATA,JAVA ,DOTNET,ANDROID ,NS2,MATLAB,EMBEDED AT LOW COST WITH BEST QUALITY PLEASE CONTACT BELOW NUMBER
FOR MORE INFORMATION PLEASE FIND THE BELOW DETAILS:
Nexgen Technology
No :66,4th cross,Venkata nagar,
Near SBI ATM,
Puducherry.
Email Id: praveen@nexgenproject.com
Mobile: 9791938249
Telephone: 0413-2211159
www.nexgenproject.com
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.
Mobile IoT Middleware Interoperability & QoS Analysis - Eclipse IoT Day Paris...Nikolaos Georgantas
Research results by the Inria Paris MiMove Team on Mobile IoT Middleware Interoperability & QoS Analysis. Presentation at Eclipse IoT Day Paris Saclay 2019
Building cloud-enabled genomics workflows with Luigi and DockerJacob Feala
Talk given at Bio-IT 2016, Cloud Computing track
Abstract:
As bioinformatics scientists, we tend to write custom tools for managing our workflows, even when viable, open-source alternatives are available from the tech community. Our field has, however, begun to adopt Docker containers to stabilize compute environments. In this talk, I will introduce Luigi, a workflow system built by engineers at Spotify to manage long-running big data processing jobs with complex dependencies. Focusing on a case study of next generation sequencing analysis in cancer genomics research, I will show how Luigi can connect simple, containerized applications into complex bioinformatics pipelines that can be easily integrated with compute, storage, and data warehousing on the cloud.
The document discusses providing actuator and sensor access as a service over the internet. It proposes an algorithm for resource requisition that creates locks on actuator instances to prevent multiple simultaneous requests. This ensures actuators can only respond to one command at a time. The algorithm also analyzes request volume to optimize traffic to unavailable resources. An API is developed to abstract away hardware details and provide platform-independent parameter retrieval and actuation. This allows developers to focus on application logic rather than hardware integration.
This document discusses the need for an open source IoT development environment and testbed to allow software developers to create IoT applications without requiring hardware expertise. It notes that existing IoT testbeds often use proprietary hardware and software, limiting interoperability. The proposed solution aims to provide virtual access to sensors and actuators through an API, as well as a microcontroller platform as a service. This would allow developers to write code without worrying about hardware integration and deployment details. The goal is to make IoT development and testing more accessible through an open testbed that addresses issues like sensor availability and cost.
Peter Gervais is a senior systems engineer, architect and programmer with over 25 years of experience spanning various industries including telecommunications, air traffic control, intelligence agencies, web development, and more. He has expertise in languages like Java, C++, PHP, and operating systems like UNIX, Linux, and Windows. He is fluent in both French and English and has held positions at companies such as Nortel, Cisco, General Dynamics, Nav Canada, and Canadian intelligence services.
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.
Outdated training deck for Prometheus monitoring tool - shared as a basis for newer content for potential MeetUp and Conference talks. I'm sharing it since there is some intrinsic value remaining.
Summit 16: Cengn Experience in Opnfv ProjectsOPNFV
CENGN, the first associate member of OPNFV is beginning to contribute to OPNFV projects by way of creating a Pharos Community lab and participating in JOID and Yardstick projects with OPNFV interns. This session will cover our learnings on the design and deployment of the Pharos lab, our experience with student interns contributing to the OPNFV projects and partnerships with innovative companies like Kontron
Evaluation of Container Virtualized MEGADOCK System in Distributed Computing ...Kento Aoyama
This document evaluates the performance of container virtualization using Docker for a bioinformatics application called MEGADOCK. Two experiments were conducted:
1) MEGADOCK was run on a physical machine with and without Docker, showing a 6.32% performance overhead with Docker. With NVIDIA Docker on GPU, performance was comparable to native.
2) MEGADOCK was run on Azure VMs with and without Docker, showing comparable scalability. Docker performance was around 6x faster than VMs.
The results show that Docker introduces small overhead for compute-intensive applications like MEGADOCK. Docker provides advantages of environment isolation and portability without significant performance costs.
Audio/Video Conferencing in Distributed Brokering SystemsVideoguy
This document proposes using a distributed brokering system called NaradaBrokering to support audio/video conferencing. It outlines improvements made over previous work, including eliminating redundant headers from messages and supporting legacy applications. The key contribution is a new event called RTPEvent that compactly encapsulates multimedia content for efficient routing while avoiding echo problems and supporting variable length topic names. Experimental results show NaradaBrokering can effectively support real-time audio/video conferencing among large, heterogeneous clients.
MACHINE LEARNING AUTOMATIONS PIPELINE WITH CI/CDIRJET Journal
This document discusses integrating machine learning pipelines with continuous integration and continuous deployment (CI/CD) tools to automate machine learning workflows. It proposes using DevOps tools like Jenkins, Docker, and GitHub to build a CI/CD pipeline for machine learning. The pipeline would include steps for data preprocessing, model training, evaluation, and deployment. Continuous integration would involve regular code updates and testing. Continuous deployment would push trained models to production for monitoring. The goal is to reduce costs and resources needed for machine learning projects through automation with DevOps practices like CI/CD.
The document discusses the EOSC Test Suite, which provides automated testing of cloud services for research. It outlines the timeline and context of the Test Suite, describing how it deploys scientific workloads and containerized tests across heterogeneous cloud platforms. The document also details the process for including new tests in the Test Suite, lists examples of deployments that have been run, and discusses the benefits of the Test Suite for validating cloud services and providing examples for researchers.
This document discusses cloud native technologies and continuous integration/continuous delivery (CI/CD) practices.
It defines cloud native as using containers, microservices, immutable infrastructure and other techniques to build scalable applications on public, private or hybrid clouds. These allow for loosely coupled, resilient and observable systems.
The document then discusses how containers enable lightweight packaging and isolation which supports modern development practices. It outlines common cloud native tools and how standardizing on these helps with areas like service communication and monitoring.
Finally, it discusses how adopting CI/CD practices like automated testing, deployment and monitoring can significantly reduce the time it takes to develop and release changes from over 100 minutes to potentially just minutes. This allows for much faster
Docker-PPT.pdf for presentation and otheradarsh20cs004
Consistency: With Docker, developers can create Dockerfiles to define the environment and dependencies required for their applications. This ensures consistent development, testing, and production environments, reducing deployment errors and streamlining workflows.
Scalability: Docker's containerization model facilitates horizontal scaling by replicating containers across multiple nodes or instances. This scalability enables applications to handle varying workload demands and ensures optimal performance during peak usage times.
Speed: Docker containers start up quickly and have faster deployment times compared to traditional deployment methods. This speed is especially beneficial for continuous integration/continuous deployment (CI/CD) pipelines, where rapid iteration and deployment are essential.
Complexity: Docker introduces additional complexity, especially for users who are new to containerization concepts. Understanding Dockerfile syntax, image creation, container orchestration, networking, and storage management can be challenging for beginners.
Security Concerns: While Docker provides isolation at the process level, it is still possible for vulnerabilities or misconfigurations to compromise container security. Shared kernel vulnerabilities, improper container configurations, and insecure container images can pose security risks.
Networking Complexity: Docker's networking capabilities, while powerful, can be complex to configure and manage, especially in distributed or multi-container environments. Issues such as container-to-container communication, network segmentation, and service discovery may require additional expertise
Fake general image detection refers to the process of identifying whether an image has been manipulated or altered in some way to create a deceptive or false representation of reality. This type of detection is commonly used in fields such as forensics, journalism, and social media moderation to identify images that have been doctored or manipulated for malicious purposes, such as spreading fake news, propaganda, or misinformation. Fake general image detection techniques can include analyzing the image's metadata, examining inconsistencies in the lighting and shadows, identifying anomalies in the image's pixel patterns, and comparing the image to known authentic images or reference images. Some algorithms use machine learning techniques to analyze large datasets of both authentic and fake images to improve the accuracy of their detection.
However, it's important to note that no single method or algorithm can detect all types of fake images with 100% accuracy, and as technology advances, so do the techniques for creating convincing fake images. Therefore, it's essential to use a combination of techniques and human expertise to identify fake images and prevent them from spreading.
There are several techniques that can be used to detect fake images on social media. Here are a few examples: Done it
Containers, the next wave of virtualization, are changing everything! As companies learn about the value of DevOps practices and containerization they are flocking to containers. Now with Docker running on Windows and Docker Containers built into both Azure and Windows Server, containers are poised to take over the virtualization landscape. Come to the session to learn all about containers and how you can put these technologies to use in your organization. You will learn about DevOps, Docker Containers, Running Containers on Windows 10, Windows Server 2016 and Linux on-premises or in the Azure cloud. You will learn about the tools and practices for leveraging containers, deploying containers as well as how you can continue on your journey to becoming a container expert as you grow your technical career.
The document provides an overview of the DevOps training program offered by Edureka. It covers topics such as introduction to DevOps, DevOps tools and lifecycle phases including continuous integration with Jenkins, containerization with Docker, version control with Git and GitHub, continuous deployment with Puppet, continuous testing with Selenium, and continuous monitoring with Nagios. The document also discusses career guidance and top DevOps interview questions. It aims to help readers master DevOps concepts and tools to become DevOps professionals.
The document discusses DevOps tools and concepts. It introduces DevOps and its benefits, then describes the DevOps lifecycle which includes continuous development, integration, testing, deployment, and monitoring. It also discusses specific DevOps tools, including Git and GitHub for version control, Jenkins for continuous integration, and Docker for containerization. The document provides overviews and examples of using these tools at different stages of the DevOps process.
O documento descreve o desenvolvimento de um aplicativo móvel chamado MamaRisk para auxiliar médicos e pacientes na avaliação do risco hereditário de câncer de mama através de perguntas e respostas simples. O aplicativo cruza as respostas dos usuários com as diretrizes da NCCN para determinar a indicação de teste genético e fornecer contexto educacional. Testes com usuários resultaram em melhorias na usabilidade e compreensão do aplicativo.
Detecção de CNVs por NGS: validação de pipeline de bioinformática para painéi...Genomika Diagnósticos
O documento descreve o desenvolvimento de um pipeline bioinformático para detecção de variações no número de cópias (CNVs) usando sequenciamento de próxima geração (NGS). O uso do software UMItools para extrair apenas barcodes moleculares únicos melhorou a precisão do pipeline, reduzindo a taxa de falsos positivos de 2% para 0%. Validou-se com sucesso o pipeline para identificar CNVs em painéis genéticos e exomas, melhorando o diagnóstico de doenças genéticas.
API-Centric Data Integration for Human Genomics Reference Databases: Achieve...Genomika Diagnósticos
API-Centric Data Integration for Human Genomics Reference Databases: Achievements, Lessons Learned and Challenges
X-Meeting 2015
Authors: Jamisson Freitas, Marcel Caraciolo, Victor Diniz, Rodrigo Alexandre and João Bosco Oliveira
The importance of an adequate soft-clip based approach on bioinformatics pipe...Genomika Diagnósticos
The importance of an adequate soft-clip based approach on bioinformatics pipelines for multiplex targeted next generation sequencing X-Meeting 2016 POSTER
Authors: George Carvalho, Renata Correira, Marcel Caraciolo, Rodrigo Alexandre and João Bosco Oliveira.
Best Practices for Bioinformatics Pipelines for Molecular-Barcoded Targeted S...Genomika Diagnósticos
Poster Best Practices for Bioinformatics Pipelines for Molecular-Barcoded Targeted Sequencing
Authors: Marcel Caraciolo, Murilo Cervato, George Carvalho and Wilder Galvão.
Como seu DNA com a Bioinformática pode revolucionar o diagnóstico clínico no ...Genomika Diagnósticos
O documento descreve como a análise do DNA de um paciente com bioinformática pode revolucionar o diagnóstico clínico, permitindo um melhor entendimento do corpo humano. A empresa Genomika é um laboratório de genética clínica que oferece testes genéticos para diagnóstico e tratamento personalizado de doenças usando fusão de especialistas em biologia molecular e tecnologia da informação.
Construindo softwares de bioinformática para análises clínicas (Introdução) Genomika Diagnósticos
O documento apresenta um laboratório de genética clínica brasileiro que desenvolve softwares de bioinformática para análises clínicas. O laboratório oferece testes genéticos para diagnóstico e tratamento de doenças hereditárias e tumores, e é liderado por especialistas em biologia molecular e tecnologia da informação. A bioinformática é importante para analisar e entender os grandes volumes de dados genéticos.
QR Secure: A Hybrid Approach Using Machine Learning and Security Validation F...AlexanderRichford
QR Secure: A Hybrid Approach Using Machine Learning and Security Validation Functions to Prevent Interaction with Malicious QR Codes.
Aim of the Study: The goal of this research was to develop a robust hybrid approach for identifying malicious and insecure URLs derived from QR codes, ensuring safe interactions.
This is achieved through:
Machine Learning Model: Predicts the likelihood of a URL being malicious.
Security Validation Functions: Ensures the derived URL has a valid certificate and proper URL format.
This innovative blend of technology aims to enhance cybersecurity measures and protect users from potential threats hidden within QR codes 🖥 🔒
This study was my first introduction to using ML which has shown me the immense potential of ML in creating more secure digital environments!
"Choosing proper type of scaling", Olena SyrotaFwdays
Imagine an IoT processing system that is already quite mature and production-ready and for which client coverage is growing and scaling and performance aspects are life and death questions. The system has Redis, MongoDB, and stream processing based on ksqldb. In this talk, firstly, we will analyze scaling approaches and then select the proper ones for our system.
Northern Engraving | Nameplate Manufacturing Process - 2024Northern Engraving
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 2 – CoE RolesDianaGray10
In this session, we will review the players involved in the CoE and how each role impacts opportunities.
Topics covered:
• What roles are essential?
• What place in the automation journey does each role play?
Speaker:
Chris Bolin, Senior Intelligent Automation Architect Anika Systems
ScyllaDB is making a major architecture shift. We’re moving from vNode replication to tablets – fragments of tables that are distributed independently, enabling dynamic data distribution and extreme elasticity. In this keynote, ScyllaDB co-founder and CTO Avi Kivity explains the reason for this shift, provides a look at the implementation and roadmap, and shares how this shift benefits ScyllaDB users.
AI in the Workplace Reskilling, Upskilling, and Future Work.pptxSunil Jagani
Discover how AI is transforming the workplace and learn strategies for reskilling and upskilling employees to stay ahead. This comprehensive guide covers the impact of AI on jobs, essential skills for the future, and successful case studies from industry leaders. Embrace AI-driven changes, foster continuous learning, and build a future-ready workforce.
Read More - https://bit.ly/3VKly70
AppSec PNW: Android and iOS Application Security with MobSFAjin Abraham
Mobile Security Framework - MobSF is a free and open source automated mobile application security testing environment designed to help security engineers, researchers, developers, and penetration testers to identify security vulnerabilities, malicious behaviours and privacy concerns in mobile applications using static and dynamic analysis. It supports all the popular mobile application binaries and source code formats built for Android and iOS devices. In addition to automated security assessment, it also offers an interactive testing environment to build and execute scenario based test/fuzz cases against the application.
This talk covers:
Using MobSF for static analysis of mobile applications.
Interactive dynamic security assessment of Android and iOS applications.
Solving Mobile app CTF challenges.
Reverse engineering and runtime analysis of Mobile malware.
How to shift left and integrate MobSF/mobsfscan SAST and DAST in your build pipeline.
Introducing BoxLang : A new JVM language for productivity and modularity!Ortus Solutions, Corp
Just like life, our code must adapt to the ever changing world we live in. From one day coding for the web, to the next for our tablets or APIs or for running serverless applications. Multi-runtime development is the future of coding, the future is to be dynamic. Let us introduce you to BoxLang.
Dynamic. Modular. Productive.
BoxLang redefines development with its dynamic nature, empowering developers to craft expressive and functional code effortlessly. Its modular architecture prioritizes flexibility, allowing for seamless integration into existing ecosystems.
Interoperability at its Core
With 100% interoperability with Java, BoxLang seamlessly bridges the gap between traditional and modern development paradigms, unlocking new possibilities for innovation and collaboration.
Multi-Runtime
From the tiny 2m operating system binary to running on our pure Java web server, CommandBox, Jakarta EE, AWS Lambda, Microsoft Functions, Web Assembly, Android and more. BoxLang has been designed to enhance and adapt according to it's runnable runtime.
The Fusion of Modernity and Tradition
Experience the fusion of modern features inspired by CFML, Node, Ruby, Kotlin, Java, and Clojure, combined with the familiarity of Java bytecode compilation, making BoxLang a language of choice for forward-thinking developers.
Empowering Transition with Transpiler Support
Transitioning from CFML to BoxLang is seamless with our JIT transpiler, facilitating smooth migration and preserving existing code investments.
Unlocking Creativity with IDE Tools
Unleash your creativity with powerful IDE tools tailored for BoxLang, providing an intuitive development experience and streamlining your workflow. Join us as we embark on a journey to redefine JVM development. Welcome to the era of BoxLang.
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.
"Frontline Battles with DDoS: Best practices and Lessons Learned", Igor IvaniukFwdays
At this talk we will discuss DDoS protection tools and best practices, discuss network architectures and what AWS has to offer. Also, we will look into one of the largest DDoS attacks on Ukrainian infrastructure that happened in February 2022. We'll see, what techniques helped to keep the web resources available for Ukrainians and how AWS improved DDoS protection for all customers based on Ukraine experience
Northern Engraving | Modern Metal Trim, Nameplates and Appliance PanelsNorthern Engraving
What began over 115 years ago as a supplier of precision gauges to the automotive industry has evolved into being an industry leader in the manufacture of product branding, automotive cockpit trim and decorative appliance trim. Value-added services include in-house Design, Engineering, Program Management, Test Lab and Tool Shops.
Dandelion Hashtable: beyond billion requests per second on a commodity serverAntonios Katsarakis
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).
"$10 thousand per minute of downtime: architecture, queues, streaming and fin...Fwdays
Direct losses from downtime in 1 minute = $5-$10 thousand dollars. Reputation is priceless.
As part of the talk, we will consider the architectural strategies necessary for the development of highly loaded fintech solutions. We will focus on using queues and streaming to efficiently work and manage large amounts of data in real-time and to minimize latency.
We will focus special attention on the architectural patterns used in the design of the fintech system, microservices and event-driven architecture, which ensure scalability, fault tolerance, and consistency of the entire system.
"NATO Hackathon Winner: AI-Powered Drug Search", Taras KlobaFwdays
This is a session that details how PostgreSQL's features and Azure AI Services can be effectively used to significantly enhance the search functionality in any application.
In this session, we'll share insights on how we used PostgreSQL to facilitate precise searches across multiple fields in our mobile application. The techniques include using LIKE and ILIKE operators and integrating a trigram-based search to handle potential misspellings, thereby increasing the search accuracy.
We'll also discuss how the azure_ai extension on PostgreSQL databases in Azure and Azure AI Services were utilized to create vectors from user input, a feature beneficial when users wish to find specific items based on text prompts. While our application's case study involves a drug search, the techniques and principles shared in this session can be adapted to improve search functionality in a wide range of applications. Join us to learn how PostgreSQL and Azure AI can be harnessed to enhance your application's search capability.
"NATO Hackathon Winner: AI-Powered Drug Search", Taras Kloba
Docker poster bsb2015-print
1. Picard
Target coverage
SamTools
Bamfile statistics
Statistics
SamTools
Variant calling
" VCF
GATK
Variant calling
" VCF
Variant detection
M. P. Caraciolo1
, F. V. Fiqueiredo1
, V. Monteiro1
1
Genomika Diagnósticos
Improving automation, reproducibility and
installation of genomic analysis pipelines with Docker
ABSTRACT
Bioinformatics pipelines usually rely on a combination of several components and
deploying them incurs substantial configuration and maintenance burden.
Genomics and variant analysis pipeline is normally difficult to install, configure and
deploy. We tackled this issue with a scalable and repeatable approach using Docker
containers (lightweight virtualization). Encapsulating NGS workflows working in
containers, a user can quickly deploy any pipeline version in any environment and
overcomes several issues from common used approaches with virtual machines.
The goal is to share our experiences for developing, distributing and running
pipelines encapsulated in containers using Docker.
bioinfo@genomika.com.br | genomika.com.br
Rua Senador José Henrique, 224, Alfred Nobel, Sala 1301 | Recife, PE | Brazil
INTRODUCTION AND MOTIVATION
The current approach using VM's lack portability, have substantial
overhead (disk, CPU, RAM) and require allocated resources to be
provisioned statically. The tools used in the pipelines generally are
installed using automatic scripts that may break due to no longer exist
tools or incorrect versions. For the biologists the problem is more
critical, since the adversities of finding and installing the required
softwares or limited documentation and obtaining good results requires
experiences.
WHAT IS DOCKER?
REFERENCES Benchmarks
Dockerized Pipeline Approach 1 Dockerized Pipeline Approach (in progress)
Boettiger C. 2015. An introduction to Docker for reproducible research. ACM SIGOPS Operating Systems
Review, Special Issue on Repeatability and Sharing of Experimental Artifacts 49(1):71-79
Di Tommaso P, Chatzou M, Baraja P, Notredame C. 2014. Nextflow: a novel tool for highly scalable
computational pipelines.
Di Tommaso P, Palumbo E, Chatzou M, Prieto P, Heuer ML, Notredame C. The impact of Docker containers
on the performance of genomic pipelines. PeerJ PrePrints. 2015;3:e1428.
doi:10.7287/peerj.preprints.1171v2.
Felter W, Ferreira A, Rajamony R, Rubio J. 2014. An updated performance comparison of virtual machines
and linux contain. IBM Research Available at http://ibm.co/V55Otq (accessed 1 June 2015)
PIPELINE ARCHITECTURE BEFORE CONTAINERS
OUR APPROACH
Time is expressed in minutes. The mean and the standard deviation were estimated from 10
separate runs. Slowdown represents the ratio of the mean execution time with Docker to the
mean execution time when Docker was not used.
Mean execution times for pipelines and tasks with and without Docker.
Docker is a open-source software, it isolates the tools
and software involved in processing, and makes easier
to recreate a snapshot of the current environment of
the pipeline for reproducibility without manual
re-installation of specific versions of software.
mounted volume
or
volume container
BWA
Hypervisor
Host OS
Server
App A
Bins/Libs
Guest OS
App B
Bins/Libs
Guest OS
Docker Engine
Host OS
Server
App A
Bins/Libs
App B
Bins/Libs
...
...
SamTools
Workflow
Base Container Base Container
mount
mount
input/output
Pros: Single container, easy to maintain
Cons: VM-like approach; huge, monolithic container,
difficult to share (against Docker philosophy)
Pros: Completely modularized,
easy to re-use/share workflow components
Cons: “Container hell”?
Mean task time
Native Docker
Mean execution
time
Native Docker
Execution time
std. deviation
Native Docker
SlowdownTasksPipeline
48Variant calling
Pipeline for WES
26.5 27.1 1254.4 4.9 2.6 1.0221293.8
VM Container
BWA
Mapping &
Pairing
SamTools
Format
conversion
" BAM
Picard
Remove
duplicates
" BAM
SamTools
Remove reads
with mapQV=0
" BAM
IGV
GATK
Local realignment around indels
Quality score recalibration
" BAM
Tool
Final alignment
in BAM format
config
file
input
fastq
mounted volume
or
volume container
Container A
BWA
Container B
SamTools
Workflow
mount
mount
input/output
containerized apps
Container C
Tool
config
file
input
fastq