Talk for USENIX LISA17: "Containers pose interesting challenges for performance monitoring and analysis, requiring new analysis methodologies and tooling. Resource-oriented analysis, as is common with systems performance tools and GUIs, must now account for both hardware limits and soft limits, as implemented using cgroups. A reverse diagnosis methodology can be applied to identify whether a container is resource constrained, and by which hard or soft resource. The interaction between the host and containers can also be examined, and noisy neighbors identified or exonerated. Performance tooling can need special usage or workarounds to function properly from within a container or on the host, to deal with different privilege levels and name spaces. At Netflix, we're using containers for some microservices, and care very much about analyzing and tuning our containers to be as fast and efficient as possible. This talk will show you how to identify bottlenecks in the host or container configuration, in the applications by profiling in a container environment, and how to dig deeper into kernel and container internals."
How to test infrastructure code: automated testing for Terraform, Kubernetes,...Yevgeniy Brikman
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This talk is a step-by-step, live-coding class on how to write automated tests for infrastructure code, including the code you write for use with tools such as Terraform, Kubernetes, Docker, and Packer. Topics covered include unit tests, integration tests, end-to-end tests, test parallelism, retries, error handling, static analysis, and more.
Jessica Deen, Microsoft -
Helm 3 is here; let's go hands-on! In this demo-fueled session, I'll walk you through the differences between Helm 2 and Helm 3. I'll offer tips for a successful rollout or upgrade, go over how to easily use charts created for Helm 2 with Helm 3 (without changing your syntax), and review opportunities where you can participate in the project's future.
ATF(ARM Trusted Firmware)は、ARMv8では嶷勣なソフトウェア。
畠悶を旋喘するのではなく、その匯何を旋喘辛嬬。
このY創では、BL31(EL3 Runtime Firmware)をg悶で聞う栽、どうすればいいのかを、Xilinx芙のZynq UltraScale+ MPSoCを箭にh苧しています。
ATF (ARM Trusted Firmware) is an important software in ARMv8.
Instead of using the whole, part of it is available.
This document explains how to do when using BL31 (EL3 Runtime Firmware) alone, for example, with Xilinx's Zynq UltraScale + MPSoC.
This document discusses methods for reducing Linux boot times, focusing on hardware architecture, the boot process, kernel optimizations, and the init system. It recommends using faster storage like SSDs, optimizing bootloaders like GRUB, improving kernel decompression with LZ4, disabling unnecessary processes, and switching to systemd for network configuration to reduce boot times to as little as 2 seconds.
This document provides an introduction to Git and GitHub. It discusses key features of Git including being a distributed version control system designed for speed and efficiency. It covers setting up Git locally and on GitHub, including configuring user information, initializing and cloning repositories, and pushing and pulling changes. The document also provides some basic Git commands and points to additional learning resources for beginners.
This document provides an overview of DevOps with Swapnil Jain. It introduces Swapnil and his background, then covers an agenda on Ansible including an introduction, use cases, architecture, modules demo, playbook demo, Ansible Tower features, and Tower demo. Ansible is introduced as an open source configuration management and orchestration tool that can automate and standardize remote host configuration. Common use cases include provisioning, configuration management, application deployment, continuous delivery, security and compliance, and orchestration.
syzkaller is an unsupervised, coverage-guided Linux syscall fuzzer.
The presentation covers basic of operation of the fuzzer, gives tutorial on how to run it and how to extend it to fuzz new drivers.
This document discusses Veriloggen, a Python framework for generating Verilog HDL code from Python. It allows designing hardware at the register-transfer level using Python by mapping Python constructs to Verilog modules, always blocks, wires, and other Verilog constructs. Veriloggen includes modules for RTL generation (Core), connecting Python threads to finite state machines (Thread), and defining streaming hardware (Stream). It aims to support a "Veriloggen for DSL X" approach to create domain-specific hardware description languages in Python.
This document provides an introduction to Gitlab CI and continuous integration/continuous delivery (CI/CD) workflows. It discusses DevOps practices and the benefits of Gitlab CI. It then covers how to set up Gitlab runners, write a basic Gitlab CI configuration file, define jobs, stages, variables and environments. The document demonstrates concepts like Docker integration, artifacts, auto and manual deployments, and stopping deployments. It concludes with a live demo of a Gitlab CI configuration.
My talk at FullStackFest, 4.9.2017. Become more familiar with managing infrastructure using Terraform, Packer and deployment pipeline. Code repository - https://github.com/antonbabenko/terraform-deployment-pipeline-talk
Introduction to Gitlab | Gitlab 101 | Training SessionAnwarul Islam
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I actually described in this slide how to use Gitlab with git. I explained what is git, push, pull, clone, commit etc. so, you can use this slide to learn or tech someone.
Git submodules allow a repository to include a checkout of an external project as a subdirectory. Submodules maintain their own identity and commit information, so other developers cloning the main project can also easily clone the submodules. Partial checkouts are possible, allowing developers to choose which submodules to clone. When other developers clone a repository with submodules, they need to run additional commands to initialize and update the submodules.
This presentation starts with an introduction to the rationale behind automated deployments in Continuous Delivery and DevOps. Then, I compare agent-based architectures, such as Chef and Puppet with the agentless architecture of the server orchestration engine Ansible. The presentation concludes with an automated deployment of Dynatrace into a simulated production environment.
Lessons learned from writing over 300,000 lines of infrastructure codeYevgeniy Brikman
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This talk is a concise masterclass on how to write infrastructure code. I share key lessons from the ^Infrastructure Cookbook ̄ we developed at Gruntwork while creating and maintaining a library of over 300,000 lines of infrastructure code that¨s used in production by hundreds of companies. Come and hear our war stories, laugh about all the mistakes we¨ve made along the way, and learn what Terraform, Packer, Docker, and Go look like in the wild.
Docker allows packaging applications and dependencies into virtual containers that can run on any Linux server. This provides flexibility and portability. Docker images are lighter than virtual machines and use less storage. Docker Compose is a tool that defines and runs multi-container Docker applications using a YAML file to automate building, running, and linking containers together. It handles dependencies and startup order of containers to simplify running complex applications with multiple services.
Faster and Easier Software Development using Docker Platformmsyukor
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Faster and Easier Software Development using Docker Platform presentation for Workshop with Open Source Community 1/2019 organized by MAMPU Malaysia under project Open Source Development and Capabilities Program (OSDeC) for Public Sector in Malaysia on January 29, 2019 at Port Dickson, Negeri Sembilan, Malaysia.
This document provides an overview of DevOps with Swapnil Jain. It introduces Swapnil and his background, then covers an agenda on Ansible including an introduction, use cases, architecture, modules demo, playbook demo, Ansible Tower features, and Tower demo. Ansible is introduced as an open source configuration management and orchestration tool that can automate and standardize remote host configuration. Common use cases include provisioning, configuration management, application deployment, continuous delivery, security and compliance, and orchestration.
syzkaller is an unsupervised, coverage-guided Linux syscall fuzzer.
The presentation covers basic of operation of the fuzzer, gives tutorial on how to run it and how to extend it to fuzz new drivers.
This document discusses Veriloggen, a Python framework for generating Verilog HDL code from Python. It allows designing hardware at the register-transfer level using Python by mapping Python constructs to Verilog modules, always blocks, wires, and other Verilog constructs. Veriloggen includes modules for RTL generation (Core), connecting Python threads to finite state machines (Thread), and defining streaming hardware (Stream). It aims to support a "Veriloggen for DSL X" approach to create domain-specific hardware description languages in Python.
This document provides an introduction to Gitlab CI and continuous integration/continuous delivery (CI/CD) workflows. It discusses DevOps practices and the benefits of Gitlab CI. It then covers how to set up Gitlab runners, write a basic Gitlab CI configuration file, define jobs, stages, variables and environments. The document demonstrates concepts like Docker integration, artifacts, auto and manual deployments, and stopping deployments. It concludes with a live demo of a Gitlab CI configuration.
My talk at FullStackFest, 4.9.2017. Become more familiar with managing infrastructure using Terraform, Packer and deployment pipeline. Code repository - https://github.com/antonbabenko/terraform-deployment-pipeline-talk
Introduction to Gitlab | Gitlab 101 | Training SessionAnwarul Islam
?
I actually described in this slide how to use Gitlab with git. I explained what is git, push, pull, clone, commit etc. so, you can use this slide to learn or tech someone.
Git submodules allow a repository to include a checkout of an external project as a subdirectory. Submodules maintain their own identity and commit information, so other developers cloning the main project can also easily clone the submodules. Partial checkouts are possible, allowing developers to choose which submodules to clone. When other developers clone a repository with submodules, they need to run additional commands to initialize and update the submodules.
This presentation starts with an introduction to the rationale behind automated deployments in Continuous Delivery and DevOps. Then, I compare agent-based architectures, such as Chef and Puppet with the agentless architecture of the server orchestration engine Ansible. The presentation concludes with an automated deployment of Dynatrace into a simulated production environment.
Lessons learned from writing over 300,000 lines of infrastructure codeYevgeniy Brikman
?
This talk is a concise masterclass on how to write infrastructure code. I share key lessons from the ^Infrastructure Cookbook ̄ we developed at Gruntwork while creating and maintaining a library of over 300,000 lines of infrastructure code that¨s used in production by hundreds of companies. Come and hear our war stories, laugh about all the mistakes we¨ve made along the way, and learn what Terraform, Packer, Docker, and Go look like in the wild.
Docker allows packaging applications and dependencies into virtual containers that can run on any Linux server. This provides flexibility and portability. Docker images are lighter than virtual machines and use less storage. Docker Compose is a tool that defines and runs multi-container Docker applications using a YAML file to automate building, running, and linking containers together. It handles dependencies and startup order of containers to simplify running complex applications with multiple services.
Faster and Easier Software Development using Docker Platformmsyukor
?
Faster and Easier Software Development using Docker Platform presentation for Workshop with Open Source Community 1/2019 organized by MAMPU Malaysia under project Open Source Development and Capabilities Program (OSDeC) for Public Sector in Malaysia on January 29, 2019 at Port Dickson, Negeri Sembilan, Malaysia.
The document describes an unsupervised representation learning technique using deep convolutional generative adversarial networks (DCGANs). It proposes using strided convolutions and fractional-strided convolutions instead of pooling layers, batch normalization in the generator and discriminator, and removing fully connected hidden layers. ReLU is used for all layers except the generator's output uses tanh, and LeakyReLU is used for all layers in the discriminator. This architecture learning representations from images without manually labeled examples.
Generative adversarial nets are a type of neural network that use two models - a generative model G that captures the data distribution, and a discriminative model D that estimates the probability that a sample came from the training data rather than G. The two models are trained simultaneously in an adversarial process, with the generative model trying to fool the discriminative model, and vice versa.
This document provides an introduction to convolutional neural networks (CNNs). It explains that CNNs have sparse connections, parameter sharing, and are translationally invariant. CNNs use convolutional and pooling layers to extract features from input images through activation maps of increasing depth. The convolutional layer filters the input image with kernels to produce feature maps, while the pooling layer downsamples the data to reduce parameters. Padding and stride size affect the output size. Pretrained CNN models can be used for feature extraction and machine learning tasks.