Leverage Docker to unlock efficient and rapid container deployments to improve your development workflow Key FeaturesReconfigure Docker hosts to create a logging system with the ElasticSearch-Logstash-Kibana (ELK) stackTackle the challenges of large-scale container deployment with this fast-paced guideBenchmark the performance of your Docker containers using Apache JMeterBook Description Docker is an enterprise-grade container platform that allows you to build and deploy your apps. Its portable format lets you run your code right from your desktop workstations to popular cloud computing providers. This comprehensive guide will improve your Docker workflows and ensure your application's production environment runs smoothly. This book starts with a refresher on setting up and running Docker and details the basic setup for creating a Docker Swarm cluster. You will then learn how to automate this cluster by using Chef Server and Cookbook. After that, you will run the Docker monitoring system with Prometheus and Grafana, and deploy the ELK stack. You will also learn some tips for optimizing Docker images. After deploying containers with the help of Jenkins, you will then move on to a tutorial on using Apache JMeter to analyze your application's performance. You will learn how to use Docker Swarm and NGINX to load-balance your application and how common debugging tools in Linux can be used to troubleshoot Docker containers. By the end of this book, you will be able to integrate all the optimizations that you have learned and put everything into practice in your applications. What you will learnAutomate provisioning and setting up nodes in a Docker Swarm clusterConfigure a monitoring system with Prometheus and GrafanaUse Apache JMeter to create workloads for benchmarking the performance of Docker containersUnderstand how to load-balance an application with Docker Swarm and NginxDeploy strace, tcdump, blktrace, and other Linux debugging tools to troubleshoot containersIntegrate Docker optimizations for DevOps, Site Reliability Engineering, CI, and CDWho this book is for If you are a software developer with a good understanding of managing Docker services and the Linux file system and are looking for ways to optimize working with Docker containers, then this is the book for you. Developers fascinated with containers and workflow automation with benefit from this book.

This book constitutes the refereed post-conference proceedings of 13 workshops held at the 34th International ISC High Performance 2019 Conference, in Frankfurt, Germany, in June 2019: HPC I/O in the Data Center (HPC-IODC), Workshop on Performance & Scalability of Storage Systems (WOPSSS), Workshop on Performance & Scalability of Storage Systems (WOPSSS), 13th Workshop on Virtualization in High-Performance Cloud Computing (VHPC '18), 3rd International Workshop on In Situ Visualization: Introduction and Applications, ExaComm: Fourth International Workshop on Communication Architectures for HPC, Big Data, Deep Learning and Clouds at Extreme Scale, International Workshop on OpenPOWER for HPC (IWOPH18), IXPUG Workshop: Many-core Computing on Intel, Processors: Applications, Performance and Best-Practice Solutions, Workshop on Sustainable Ultrascale Computing Systems, Approximate and Transprecision Computing on Emerging Technologies (ATCET), First Workshop on the Convergence of Large Scale Simulation and Artificial Intelligence, 3rd Workshop for Open Source Supercomputing (OpenSuCo), First Workshop on Interactive High-Performance Computing, Workshop on Performance Portable Programming Models for Accelerators (P^3MA). The 48 full papers included in this volume were carefully reviewed and selected. They cover all aspects of research, development, and application of large-scale, high performance experimental and commercial systems. Topics include HPC computer architecture and hardware; programming models, system software, and applications; solutions for heterogeneity, reliability, power efficiency of systems; virtualization and containerized environments; big data and cloud computing; and artificial intelligence.

Learn how to use Python to create efficient applications About This Book Identify the bottlenecks in your applications and solve them using the best profiling techniques Write efficient numerical code in NumPy, Cython, and Pandas Adapt your programs to run on multiple processors and machines with parallel programming Who This Book Is For The book is aimed at Python developers who want to improve the performance of their application. Basic knowledge of Python is expected What You Will Learn Write efficient numerical code with the NumPy and Pandas libraries Use Cython and Numba to achieve native performance Find bottlenecks in your Python code using profilers Write asynchronous code using Asyncio and RxPy Use Tensorflow and Theano for automatic parallelism in Python Set up and run distributed algorithms on a cluster using Dask and PySpark In Detail Python is a versatile language that has found applications in many industries. The clean syntax, rich standard library, and vast selection of third-party libraries make Python a wildly popular language. Python High Performance is a practical guide that shows how to leverage the power of both native and third-party Python libraries to build robust applications. The book explains how to use various profilers to find performance bottlenecks and apply the correct algorithm to fix them. The reader will learn how to effectively use NumPy and Cython to speed up numerical code. The book explains concepts of concurrent programming and how to implement robust and responsive applications using Reactive programming. Readers will learn how to write code for parallel architectures using Tensorflow and Theano, and use a cluster of computers for large-scale computations using technologies such as Dask and PySpark. By the end of the book, readers will have learned to achieve performance and scale from their Python applications. Style and approach A step-by-step practical guide filled with real-world use cases and examples

Your Python code may run correctly, but you need it to run faster. Updated for Python 3, this expanded edition shows you how to locate performance bottlenecks and significantly speed up your code in high-data-volume programs. By exploring the fundamental theory behind design choices, High Performance Python helps you gain a deeper understanding of Python’s implementation. How do you take advantage of multicore architectures or clusters? Or build a system that scales up and down without losing reliability? Experienced Python programmers will learn concrete solutions to many issues, along with war stories from companies that use high-performance Python for social media analytics, productionized machine learning, and more. Get a better grasp of NumPy, Cython, and profilers Learn how Python abstracts the underlying computer architecture Use profiling to find bottlenecks in CPU time and memory usage Write efficient programs by choosing appropriate data structures Speed up matrix and vector computations Use tools to compile Python down to machine code Manage multiple I/O and computational operations concurrently Convert multiprocessing code to run on local or remote clusters Deploy code faster using tools like Docker

This book constitutes revised selected papers from 7 workshops that were held in conjunction with the ISC High Performance 2016 conference in Frankfurt, Germany, in June 2016. The 45 papers presented in this volume were carefully reviewed and selected for inclusion in this book. They stem from the following workshops: Workshop on Exascale Multi/Many Core Computing Systems, E-MuCoCoS; Second International Workshop on Communication Architectures at Extreme Scale, ExaComm; HPC I/O in the Data Center Workshop, HPC-IODC; International Workshop on OpenPOWER for HPC, IWOPH; Workshop on the Application Performance on Intel Xeon Phi – Being Prepared for KNL and Beyond, IXPUG; Workshop on Performance and Scalability of Storage Systems, WOPSSS; and International Workshop on Performance Portable Programming Models for Accelerators, P3MA.

This book constitutes the refereed proceedings of the 31st International Conference, ISC High Performance 2016 [formerly known as the International Supercomputing Conference] held in Frankfurt, Germany, in June 2016. The 25 revised full papers presented in this book were carefully reviewed and selected from 60 submissions. The papers cover the following topics: Autotuning and Thread Mapping; Data Locality and Decomposition; Scalable Applications; Machine Learning; Datacenters andCloud; Communication Runtime; Intel Xeon Phi; Manycore Architectures; Extreme-scale Computations; and Resilience.

60 practical recipes that help you gain expertise with Docker networking and understand the underlying constructs that make it all work About This Book Enhance your Docker networking skills and protect your organization using advanced networking functions Learn how to use third party tools to extend Docker networking This practical and recipe-based book demonstrates the different ways in which you can network containers leveraging the Docker engine. Who This Book Is For The book is for system administrators as well as developers who are well versed with the concepts of Docker and have basic knowledge of Docker networking. You should also have sound knowledge of networking in general. What You Will Learn Configure Linux networking primitives used by Docker networking Build and deploy user-defined Docker networks Examine the different options for resolving and linking containers Implement custom networks for Docker to consume Discover third-party networking plugins such as Weave and Flannel Work through solutions to secure Docker containers and networks Observe methodologies for troubleshooting container networks Explore advanced and experimental Docker networking features In Detail Networking functionality in Docker has changed considerably since its first release, evolving to offer a rich set of built-in networking features, as well as an extensible plugin model allowing for a wide variety of networking functionality. This book explores Docker networking capabilities from end to end. Begin by examining the building blocks used by Docker to implement fundamental containing networking before learning how to consume built-in networking constructs as well as custom networks you create on your own. Next, explore common third-party networking plugins, including detailed information on how these plugins inter-operate with the Docker engine. Consider available options for securing container networks, as well as a process for troubleshooting container connectivity. Finally, examine advanced Docker networking functions and their relevant use cases, tying together everything you need to succeed with your own projects. Style and approach This practical recipe-based book will take readers to next level of Docker networking. It covers relevant use cases and the advanced features of Docker