Our tech process, how we make apps using React Native on Gitlab with Gitlab CI (Continuous Integration) and CD (Continuous Delivery)
Reveal JS source on GitHub: https://github.com/Lingvokot/gitlab-and-lingvokot
This document discusses how to break bad habits by using GitLab CI to automate routine tasks. It provides examples of automating tests, packaging code, and deploying artifacts and websites. Specifically, it shows how to:
1. Run automated tests with GitLab CI
2. Package code into downloadable artifacts
3. Deploy packages and websites to AWS S3 and GitLab Pages
4. Separate testing and production using environments
5. Allow multiple developers to work on the same project simultaneously
6. Avoid mistakes by not deploying directly to production
This document discusses GitLab Continuous Integration (GitLab CI/CD). It defines continuous integration, continuous delivery, and continuous deployment. It explains that GitLab CI/CD uses pipelines made up of stages and jobs to test, build, and deploy code. Pipelines are configured using a YAML file. Jobs run on GitLab runners, which can execute jobs locally or using Docker. Benefits of GitLab CI/CD include integrated pipelines, Docker/Kubernetes integration, and not requiring plugins. The downside is that it is only available within GitLab.
Continuous Deployment with Kubernetes, Docker and GitLab CIalexanderkiel
This document discusses continuous deployment of Clojure services to Kubernetes using Docker and GitLab CI. It provides an overview of Docker, Kubernetes, deploying a sample Clojure service, and configuring GitLab CI for continuous integration and deployment. The sample Clojure service is built as a Docker image, tested using GitLab CI, and deployed to Kubernetes clusters for testing and production using configuration files and GitLab CI pipelines.
Continuous Integration/Deployment with Gitlab CIDavid Hahn
This document discusses continuous integration/deployment with Gitlab CI. It provides an introduction and overview of continuous integration, continuous delivery, and deployment. It then discusses Gitlab and Gitlab CI in more detail, including stages and pipelines, the UI, runners, using CI as code, and examples for Node.js + React, Java + Angular, and Electron applications. The sources section lists links and image sources for additional information.
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.
This document discusses using TensorFlow with Golang for machine learning tasks like image recognition. It provides instructions for cloning a GitHub repository containing a sample project that uses a pre-trained TensorFlow model within a Golang application to classify images. The application is built as a Docker image to perform image recognition by taking URLs as arguments and returning potential labels and probabilities. The document also briefly mentions the possibility of training custom models from Golang in TensorFlow.
Our tech process, how we make apps using React Native on Gitlab with Gitlab CI (Continuous Integration) and CD (Continuous Delivery)
Reveal JS source on GitHub: https://github.com/Lingvokot/gitlab-and-lingvokot
This document discusses how to break bad habits by using GitLab CI to automate routine tasks. It provides examples of automating tests, packaging code, and deploying artifacts and websites. Specifically, it shows how to:
1. Run automated tests with GitLab CI
2. Package code into downloadable artifacts
3. Deploy packages and websites to AWS S3 and GitLab Pages
4. Separate testing and production using environments
5. Allow multiple developers to work on the same project simultaneously
6. Avoid mistakes by not deploying directly to production
This document discusses GitLab Continuous Integration (GitLab CI/CD). It defines continuous integration, continuous delivery, and continuous deployment. It explains that GitLab CI/CD uses pipelines made up of stages and jobs to test, build, and deploy code. Pipelines are configured using a YAML file. Jobs run on GitLab runners, which can execute jobs locally or using Docker. Benefits of GitLab CI/CD include integrated pipelines, Docker/Kubernetes integration, and not requiring plugins. The downside is that it is only available within GitLab.
Continuous Deployment with Kubernetes, Docker and GitLab CIalexanderkiel
This document discusses continuous deployment of Clojure services to Kubernetes using Docker and GitLab CI. It provides an overview of Docker, Kubernetes, deploying a sample Clojure service, and configuring GitLab CI for continuous integration and deployment. The sample Clojure service is built as a Docker image, tested using GitLab CI, and deployed to Kubernetes clusters for testing and production using configuration files and GitLab CI pipelines.
Continuous Integration/Deployment with Gitlab CIDavid Hahn
This document discusses continuous integration/deployment with Gitlab CI. It provides an introduction and overview of continuous integration, continuous delivery, and deployment. It then discusses Gitlab and Gitlab CI in more detail, including stages and pipelines, the UI, runners, using CI as code, and examples for Node.js + React, Java + Angular, and Electron applications. The sources section lists links and image sources for additional information.
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.
This document discusses using TensorFlow with Golang for machine learning tasks like image recognition. It provides instructions for cloning a GitHub repository containing a sample project that uses a pre-trained TensorFlow model within a Golang application to classify images. The application is built as a Docker image to perform image recognition by taking URLs as arguments and returning potential labels and probabilities. The document also briefly mentions the possibility of training custom models from Golang in TensorFlow.
Gitlab ci e kubernetes, build test and deploy your projects like a prosparkfabrik
This document discusses using GitLab CI and Kubernetes together for continuous integration, delivery, and deployment. It provides an overview of Kubernetes and GitLab, describes how to set up a GitLab runner using the Kubernetes executor, and provides an example YAML configuration. It also covers continuous deployment workflows, running GitLab on Kubernetes, and some tips and tricks as well as techniques for troubleshooting Kubernetes and GitLab CI/CD pipelines.
1. The document summarizes the topics covered in an advanced Docker workshop, including Docker Machine, Docker Swarm, networking, services, GitLab integration, IoT applications, Moby/LinuxKit, and a call to action to learn more about Docker on their own.
2. Specific topics included how to create Docker Machines on Azure, build a Swarm cluster, configure networking and services, integrate with GitLab for continuous integration/delivery, develop IoT applications using Docker on Raspberry Pi, and introduce Moby and LinuxKit for building customized container-based operating systems.
3. The workshop concluded by emphasizing business models, microservices, infrastructure as code, container design, DevOps, and
This document summarizes a company's two year journey migrating their infrastructure to Kubernetes on AWS. It describes their stack including tools like Terraform, AWS, CoreOS, Kubernetes and Docker. It outlines their architecture with masters, workers and stateful/stateless nodes. It discusses their lifecycles for development, testing and production. It also covers some struggles they faced around node availability and networking issues. Finally, it provides lessons learned around costs, using Terraform with Kubernetes, separating concerns, and prioritizing automation and testing in their workflows.
This document discusses Docker containers as a toolset to standardize build environments. It outlines motivations for using containers due to issues with manually installing dependencies. The approach taken was to build Docker images for common build tools and applications. Examples are provided of Dockerfiles for CloudFormation and Ansible containers. Implementation in a CI pipeline and lessons learned are also covered.
How to Achieve Canary Deployment on KubernetesHanLing Shen
This document provides an overview of how to achieve canary deployments on Kubernetes. It begins with background on AWS Elastic Beanstalk and Kubernetes. It then explains blue/green deployments and canary deployments. The remainder of the document demonstrates how to set up canary deployments on Kubernetes using multiple deployments, services, and labels to route a portion of traffic to a new version. It also discusses tools like Helm and Jenkins that can help automate the canary deployment process.
This document discusses Node.js, continuous integration, continuous delivery, and Jenkins pipelines. It provides code examples for setting up a Node.js project with Sequelize, Mocha testing, and a Makefile for building, packaging, and deploying the project. It also shows a Jenkinsfile for integrating the project with Jenkins for continuous integration and delivery to production.
Whose Job Is It Anyway? Kubernetes, CRI, & Container RuntimesPhil Estes
A talk given at Cloud Native London meetup, February 6, 2018 on the role of container runtimes in Kubernetes, the introduction of the Container Runtime Interface (CRI), and the history of containerd and it's use as a CRI implementing container runtime for Kubernetes.
The document summarizes BlaBlaCar's journey to migrating 100% of their production services to containers. It describes how they started with bare metal servers and evolved to using configuration management tools like Chef. They then standardized on CoreOS and rkt as their container platform. Key tools they developed include dgr for building container images and ggn for managing services running in containers. They also implemented service discovery using custom tools like Nerve and Synapse. The document shares many lessons learned from their large scale production container deployment.
"Yahoo! JAPAN の Kubernetes-as-a-Service" で加速するアプリケーション開発Yahoo!デベロッパーネットワーク
This document discusses automating Kubernetes deployments using Kubernetes-as-a-Service. It defines a CustomResourceDefinition for Kubernetes clusters that includes specifications for the Kubernetes version, number of master and worker nodes, and hardware flavors. It also includes an example KubernetesCluster resource definition.
The document provides instructions for getting started with Okteto Cloud, a platform for developing and deploying containerized applications. It summarizes how to install the Okteto CLI, configure access to an Okteto Cloud namespace, and deploy sample applications written in Go, Python, Node.js, and Ruby by applying Kubernetes manifest files and using Okteto commands. It also lists credentials and links for the service.
Generating Visual Studio Code Extensions for Xtext DSLsKarsten Thoms
This short talk was held in the Eclipse Modeling Symposium at EclipseCon Europe 2016. It shows a new Xtext Generator fragment that produces an extension for VS Code.
What's Running My Containers? A review of runtimes and standards.Phil Estes
A talk given at Open Source Leadership Summit (OSLS) on Thursday, March 14th in Half Moon Bay, CA. In this talk the current status of the Open Container Initiative (OCI) standards as well as the Kubernetes Container Runtime Interface (CRI) were presented, with a view towards how these components have provided a level playing field with significant choice when it comes to container runtimes for use in Kubernetes, as well as interoperability per the OCI standards.
This document discusses the app container runtime rkt. It provides an overview of rkt, including what it is, its goals, and how it differs from Docker. Key points include:
- Rkt implements the Application Container (appc) specification and allows running containerized applications.
- Its goals are fast downloads/starts, verifiable/cacheable images, composability, and using common technologies like DNS for discovery.
- It differs from Docker in being more composable without a central daemon, focusing more on security through image verification, and using an open standard for images instead of Docker's format.
- The document demonstrates downloading images, verifying signatures, running containers in pods with options like
Automated Serverless Pipelines with #GitOps on CodefreshCodefresh
**Watch the full presentation here: https://codefresh.io/automated-serverless-pipelines-with-gitops-on-codefresh/
Dan Van Brunt introduces you to Serverless, talks about common misconceptions and challenges, and then demos how he uses the Serverless Framework effectively alongside containers. He shares some of the advanced pipelines he's developed so you can replicate his workflow without building a pipeline from scratch!
Try Codefresh for FREE (120 builds/month) and get a free custom demo at Codefresh.io
[OpenInfra Days Korea 2018] Day 2 - E3-2: "핸즈온 워크샵: Kubespray, Helm, Armada를 ...OpenStack Korea Community
This document discusses running OpenStack on Kubernetes. It provides instructions for logging into the Kubernetes cluster and OpenStack dashboard. It also summarizes the logging, monitoring, and alerting tools used, including Prometheus for monitoring, Kibana and Elasticsearch for logging, and Alertmanager for alerts. Grafana is used for visualizing metrics and Prometheus is configured to monitor the OpenStack and Kubernetes components.
DevOps Fest 2020. Дмитрий Кудрявцев. Реализация GitOps на Kubernetes. ArgoCDDevOps_Fest
The document discusses GitOps and ArgoCD for managing Kubernetes applications. It defines GitOps as storing the desired state of systems in Git repositories and using continuous delivery tools to ensure the live systems match that state. ArgoCD is introduced as a GitOps tool that monitors applications and ensures the running state matches the target state defined in Git. Key features of ArgoCD include a web UI, automated deployments, support for different config formats, and rollback capabilities. The document provides an example of using Kustomize to customize Kubernetes resources through overlays.
Gitlab ci e kubernetes, build test and deploy your projects like a prosparkfabrik
This document discusses using GitLab CI and Kubernetes together for continuous integration, delivery, and deployment. It provides an overview of Kubernetes and GitLab, describes how to set up a GitLab runner using the Kubernetes executor, and provides an example YAML configuration. It also covers continuous deployment workflows, running GitLab on Kubernetes, and some tips and tricks as well as techniques for troubleshooting Kubernetes and GitLab CI/CD pipelines.
1. The document summarizes the topics covered in an advanced Docker workshop, including Docker Machine, Docker Swarm, networking, services, GitLab integration, IoT applications, Moby/LinuxKit, and a call to action to learn more about Docker on their own.
2. Specific topics included how to create Docker Machines on Azure, build a Swarm cluster, configure networking and services, integrate with GitLab for continuous integration/delivery, develop IoT applications using Docker on Raspberry Pi, and introduce Moby and LinuxKit for building customized container-based operating systems.
3. The workshop concluded by emphasizing business models, microservices, infrastructure as code, container design, DevOps, and
This document summarizes a company's two year journey migrating their infrastructure to Kubernetes on AWS. It describes their stack including tools like Terraform, AWS, CoreOS, Kubernetes and Docker. It outlines their architecture with masters, workers and stateful/stateless nodes. It discusses their lifecycles for development, testing and production. It also covers some struggles they faced around node availability and networking issues. Finally, it provides lessons learned around costs, using Terraform with Kubernetes, separating concerns, and prioritizing automation and testing in their workflows.
This document discusses Docker containers as a toolset to standardize build environments. It outlines motivations for using containers due to issues with manually installing dependencies. The approach taken was to build Docker images for common build tools and applications. Examples are provided of Dockerfiles for CloudFormation and Ansible containers. Implementation in a CI pipeline and lessons learned are also covered.
How to Achieve Canary Deployment on KubernetesHanLing Shen
This document provides an overview of how to achieve canary deployments on Kubernetes. It begins with background on AWS Elastic Beanstalk and Kubernetes. It then explains blue/green deployments and canary deployments. The remainder of the document demonstrates how to set up canary deployments on Kubernetes using multiple deployments, services, and labels to route a portion of traffic to a new version. It also discusses tools like Helm and Jenkins that can help automate the canary deployment process.
This document discusses Node.js, continuous integration, continuous delivery, and Jenkins pipelines. It provides code examples for setting up a Node.js project with Sequelize, Mocha testing, and a Makefile for building, packaging, and deploying the project. It also shows a Jenkinsfile for integrating the project with Jenkins for continuous integration and delivery to production.
Whose Job Is It Anyway? Kubernetes, CRI, & Container RuntimesPhil Estes
A talk given at Cloud Native London meetup, February 6, 2018 on the role of container runtimes in Kubernetes, the introduction of the Container Runtime Interface (CRI), and the history of containerd and it's use as a CRI implementing container runtime for Kubernetes.
The document summarizes BlaBlaCar's journey to migrating 100% of their production services to containers. It describes how they started with bare metal servers and evolved to using configuration management tools like Chef. They then standardized on CoreOS and rkt as their container platform. Key tools they developed include dgr for building container images and ggn for managing services running in containers. They also implemented service discovery using custom tools like Nerve and Synapse. The document shares many lessons learned from their large scale production container deployment.
"Yahoo! JAPAN の Kubernetes-as-a-Service" で加速するアプリケーション開発Yahoo!デベロッパーネットワーク
This document discusses automating Kubernetes deployments using Kubernetes-as-a-Service. It defines a CustomResourceDefinition for Kubernetes clusters that includes specifications for the Kubernetes version, number of master and worker nodes, and hardware flavors. It also includes an example KubernetesCluster resource definition.
The document provides instructions for getting started with Okteto Cloud, a platform for developing and deploying containerized applications. It summarizes how to install the Okteto CLI, configure access to an Okteto Cloud namespace, and deploy sample applications written in Go, Python, Node.js, and Ruby by applying Kubernetes manifest files and using Okteto commands. It also lists credentials and links for the service.
Generating Visual Studio Code Extensions for Xtext DSLsKarsten Thoms
This short talk was held in the Eclipse Modeling Symposium at EclipseCon Europe 2016. It shows a new Xtext Generator fragment that produces an extension for VS Code.
What's Running My Containers? A review of runtimes and standards.Phil Estes
A talk given at Open Source Leadership Summit (OSLS) on Thursday, March 14th in Half Moon Bay, CA. In this talk the current status of the Open Container Initiative (OCI) standards as well as the Kubernetes Container Runtime Interface (CRI) were presented, with a view towards how these components have provided a level playing field with significant choice when it comes to container runtimes for use in Kubernetes, as well as interoperability per the OCI standards.
This document discusses the app container runtime rkt. It provides an overview of rkt, including what it is, its goals, and how it differs from Docker. Key points include:
- Rkt implements the Application Container (appc) specification and allows running containerized applications.
- Its goals are fast downloads/starts, verifiable/cacheable images, composability, and using common technologies like DNS for discovery.
- It differs from Docker in being more composable without a central daemon, focusing more on security through image verification, and using an open standard for images instead of Docker's format.
- The document demonstrates downloading images, verifying signatures, running containers in pods with options like
Automated Serverless Pipelines with #GitOps on CodefreshCodefresh
**Watch the full presentation here: https://codefresh.io/automated-serverless-pipelines-with-gitops-on-codefresh/
Dan Van Brunt introduces you to Serverless, talks about common misconceptions and challenges, and then demos how he uses the Serverless Framework effectively alongside containers. He shares some of the advanced pipelines he's developed so you can replicate his workflow without building a pipeline from scratch!
Try Codefresh for FREE (120 builds/month) and get a free custom demo at Codefresh.io
[OpenInfra Days Korea 2018] Day 2 - E3-2: "핸즈온 워크샵: Kubespray, Helm, Armada를 ...OpenStack Korea Community
This document discusses running OpenStack on Kubernetes. It provides instructions for logging into the Kubernetes cluster and OpenStack dashboard. It also summarizes the logging, monitoring, and alerting tools used, including Prometheus for monitoring, Kibana and Elasticsearch for logging, and Alertmanager for alerts. Grafana is used for visualizing metrics and Prometheus is configured to monitor the OpenStack and Kubernetes components.
DevOps Fest 2020. Дмитрий Кудрявцев. Реализация GitOps на Kubernetes. ArgoCDDevOps_Fest
The document discusses GitOps and ArgoCD for managing Kubernetes applications. It defines GitOps as storing the desired state of systems in Git repositories and using continuous delivery tools to ensure the live systems match that state. ArgoCD is introduced as a GitOps tool that monitors applications and ensures the running state matches the target state defined in Git. Key features of ArgoCD include a web UI, automated deployments, support for different config formats, and rollback capabilities. The document provides an example of using Kustomize to customize Kubernetes resources through overlays.
Take your CI to the next level! Learn how to optimize your pipelines for faster and more efficient builds through parallelization, caching, failing early, and more.
GitLab CI/CD is a built-in continuous integration and delivery tool in GitLab. It allows for automated testing, building, and deploying of applications. It supports various languages and tools through configuration files. Pipelines can be triggered on code pushes or manually to run tests and deploy code. The tool aims to speed up development workflows through automation while providing visibility into builds.
Dmytro Patkovskyi "Practical tips regarding build optimization for those who ...Fwdays
This talk is about build optimization mechanisms available in three developer tools that are often used together (Gitlab, Gradle, and Docker). Dmytro will describe the possibilities of each instrument and advise which functions you should use and how. Additional attention will be paid to the most common pitfalls, along with handy tips and tricks. The talk will also be useful for those who use just one or two out of the tools.
GitLab CI is a continuous integration service fully integrated with GitLab. It allows users to define build and test workflows directly in the GitLab repository using a .gitlab-ci.yml file. GitLab CI runs jobs defined in the YAML file on GitLab-hosted runners which can be Docker containers. It supports features like artifacts, dependencies between jobs, stages, and secret variables to securely pass credentials to builds.
Доклад Евгения Кузьмина для "Съесть собаку" #14: PHP, 20/092018
Тезисы:
Построение процесса continuous integration/delivery на примере Laravel-приложения;
Структура организации авто-тестирования;
Интеграция запуска тестов и деплоя на CI сервере Jenkins;
Применение Docker в связке с AWS ElasticBeanstalk для blue-green деплоя.
This document provides information about developing and deploying Magento applications on Magento Cloud. It describes the development workflow including working in local, integration, and branch environments. It also outlines the build, deploy, and post-deploy phases of the deployment process. Additionally, it covers static content deployment, configuration files, patches and hotfixes, Fastly configuration, and potential improvements to Magento Cloud.
Continuous Integration/ Continuous Delivery of web applicationsEvgeniy Kuzmin
Smart Gamma use case of implementation Continuous Integration/ Continuous Delivery for Laravel web app, tested by phpunit and Behat, build automation with Jenkins, blue-green deploy on AWS Beanstalk
This document provides an overview of Node.js including its history, key features, and common questions. Node.js is a JavaScript runtime environment for building server-side and networking applications. It is based on Google's V8 JavaScript engine and uses an event-driven, non-blocking I/O model that makes it lightweight and efficient, especially for real-time applications that require high throughput and scalability. The Node.js package ecosystem and large developer community help make it a full-stack JavaScript platform for building fast and scalable network applications.
Kubernetes is making the promise of changing the datacenter from being a group of computer to "a computer" itself. This presentation outlines the new features in K8S with 1.1 and 1.2 release.
Vinted uses GitOps to deploy thousands of pods to Kubernetes. Some key points:
- Vinted infrastructure has grown to 2000 deployments per day and over 10,000 running pods across 480+ physical nodes.
- GitOps is a DevOps process using Git for deployment and management of containerized applications. It promotes repeatability, reliability, and efficiency.
- Vinted uses Helm charts stored in Git to define application manifests and environments. Jenkins jobs trigger on commits to update image tags and deploy applications.
Continuous integration / continuous delivery of web applications, Eugen Kuzmi...Evgeniy Kuzmin
What will be discussed:
- Building the process of continuous integration/delivery on the example of a Laravel application;
- The structure of the auto-testing organization;
- Integration of running tests and deploy on Jenkins CI server;
- Employment of Docker in conjunction with AWS ElasticBeanstalk for blue-green deployment.
This document provides an overview of Kubernetes 101. It begins with asking why Kubernetes is needed and provides a brief history of the project. It describes containers and container orchestration tools. It then covers the main components of Kubernetes architecture including pods, replica sets, deployments, services, and ingress. It provides examples of common Kubernetes manifest files and discusses basic Kubernetes primitives. It concludes with discussing DevOps practices after adopting Kubernetes and potential next steps to learn more advanced Kubernetes topics.
This document compares GitLab CI and Jenkins for continuous integration. It discusses how GitLab CI is integrated directly into GitLab while Jenkins is a separate product. It also covers differences in programming languages used, configuration approaches, and extensibility through plugins. The document then demonstrates how to set up a sample CI/CD pipeline in GitLab CI to package and deploy code and websites for different environments.
Introduction to Git for Network Engineers (Lab Guide)Joel W. King
This document provides an introduction to using Git and GitHub for network engineers to manage network configuration files. It describes setting up a GitHub account and installing Git locally. It then walks through various Git commands like configuring global settings, creating a repository, adding and committing files, branching, merging, undoing changes, and cleaning up. The goal is to provide hands-on experience with revision control of network configuration files using Git and GitHub.
How often have you heard "it's gonna be hard or impossible to cover this part of our backend application"? I've heard a lot. Because our modern application always involve databases, message queues, 3rd party services. What if I tell you, that I can cover even logs with tests, values of custom application metrics, apps that involve Google Cloud Storage, Google Data Storage, Kafka, Redis, Lambdas, DynamoDB, Aerospike, S3. I work in highload project without manual QA's at all. And I'm confident in my everyday releases, so should be you.
This document contains questions and answers related to DevOps concepts. It begins with definitions of DevOps and explains that DevOps aims to automate infrastructure and integrate development and operations teams. Key DevOps principles like infrastructure as code, continuous integration, deployment and monitoring are outlined. Popular DevOps tools like Git, Jenkins, Ansible, Docker and Nagios are listed. The document also includes questions on version control systems, Git, Ansible, Docker, Scrum methodology and more DevOps related topics.
Neo4j - Product Vision and Knowledge Graphs - GraphSummit ParisNeo4j
Dr. Jesús Barrasa, Head of Solutions Architecture for EMEA, Neo4j
Découvrez les dernières innovations de Neo4j, et notamment les dernières intégrations cloud et les améliorations produits qui font de Neo4j un choix essentiel pour les développeurs qui créent des applications avec des données interconnectées et de l’IA générative.
Hand Rolled Applicative User ValidationCode KataPhilip Schwarz
Could you use a simple piece of Scala validation code (granted, a very simplistic one too!) that you can rewrite, now and again, to refresh your basic understanding of Applicative operators <*>, <*, *>?
The goal is not to write perfect code showcasing validation, but rather, to provide a small, rough-and ready exercise to reinforce your muscle-memory.
Despite its grandiose-sounding title, this deck consists of just three slides showing the Scala 3 code to be rewritten whenever the details of the operators begin to fade away.
The code is my rough and ready translation of a Haskell user-validation program found in a book called Finding Success (and Failure) in Haskell - Fall in love with applicative functors.
Measures in SQL (SIGMOD 2024, Santiago, Chile)Julian Hyde
SQL has attained widespread adoption, but Business Intelligence tools still use their own higher level languages based upon a multidimensional paradigm. Composable calculations are what is missing from SQL, and we propose a new kind of column, called a measure, that attaches a calculation to a table. Like regular tables, tables with measures are composable and closed when used in queries.
SQL-with-measures has the power, conciseness and reusability of multidimensional languages but retains SQL semantics. Measure invocations can be expanded in place to simple, clear SQL.
To define the evaluation semantics for measures, we introduce context-sensitive expressions (a way to evaluate multidimensional expressions that is consistent with existing SQL semantics), a concept called evaluation context, and several operations for setting and modifying the evaluation context.
A talk at SIGMOD, June 9–15, 2024, Santiago, Chile
Authors: Julian Hyde (Google) and John Fremlin (Google)
https://doi.org/10.1145/3626246.3653374
Atelier - Innover avec l’IA Générative et les graphes de connaissancesNeo4j
Atelier - Innover avec l’IA Générative et les graphes de connaissances
Allez au-delà du battage médiatique autour de l’IA et découvrez des techniques pratiques pour utiliser l’IA de manière responsable à travers les données de votre organisation. Explorez comment utiliser les graphes de connaissances pour augmenter la précision, la transparence et la capacité d’explication dans les systèmes d’IA générative. Vous partirez avec une expérience pratique combinant les relations entre les données et les LLM pour apporter du contexte spécifique à votre domaine et améliorer votre raisonnement.
Amenez votre ordinateur portable et nous vous guiderons sur la mise en place de votre propre pile d’IA générative, en vous fournissant des exemples pratiques et codés pour démarrer en quelques minutes.
WhatsApp offers simple, reliable, and private messaging and calling services for free worldwide. With end-to-end encryption, your personal messages and calls are secure, ensuring only you and the recipient can access them. Enjoy voice and video calls to stay connected with loved ones or colleagues. Express yourself using stickers, GIFs, or by sharing moments on Status. WhatsApp Business enables global customer outreach, facilitating sales growth and relationship building through showcasing products and services. Stay connected effortlessly with group chats for planning outings with friends or staying updated on family conversations.
E-Invoicing Implementation: A Step-by-Step Guide for Saudi Arabian CompaniesQuickdice ERP
Explore the seamless transition to e-invoicing with this comprehensive guide tailored for Saudi Arabian businesses. Navigate the process effortlessly with step-by-step instructions designed to streamline implementation and enhance efficiency.
AI Fusion Buddy Review: Brand New, Groundbreaking Gemini-Powered AI AppGoogle
AI Fusion Buddy Review: Brand New, Groundbreaking Gemini-Powered AI App
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https://sumonreview.com/ai-fusion-buddy-review
AI Fusion Buddy Review: Key Features
✅Create Stunning AI App Suite Fully Powered By Google's Latest AI technology, Gemini
✅Use Gemini to Build high-converting Converting Sales Video Scripts, ad copies, Trending Articles, blogs, etc.100% unique!
✅Create Ultra-HD graphics with a single keyword or phrase that commands 10x eyeballs!
✅Fully automated AI articles bulk generation!
✅Auto-post or schedule stunning AI content across all your accounts at once—WordPress, Facebook, LinkedIn, Blogger, and more.
✅With one keyword or URL, generate complete websites, landing pages, and more…
✅Automatically create & sell AI content, graphics, websites, landing pages, & all that gets you paid non-stop 24*7.
✅Pre-built High-Converting 100+ website Templates and 2000+ graphic templates logos, banners, and thumbnail images in Trending Niches.
✅Say goodbye to wasting time logging into multiple Chat GPT & AI Apps once & for all!
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✅Risk-Free: 30-Day Money-Back Guarantee!
✅Commercial License included!
See My Other Reviews Article:
(1) AI Genie Review: https://sumonreview.com/ai-genie-review
(2) SocioWave Review: https://sumonreview.com/sociowave-review
(3) AI Partner & Profit Review: https://sumonreview.com/ai-partner-profit-review
(4) AI Ebook Suite Review: https://sumonreview.com/ai-ebook-suite-review
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#HowDoesAIFusionBuddyWorks
Revolutionizing Visual Effects Mastering AI Face Swaps.pdfUndress Baby
The quest for the best AI face swap solution is marked by an amalgamation of technological prowess and artistic finesse, where cutting-edge algorithms seamlessly replace faces in images or videos with striking realism. Leveraging advanced deep learning techniques, the best AI face swap tools meticulously analyze facial features, lighting conditions, and expressions to execute flawless transformations, ensuring natural-looking results that blur the line between reality and illusion, captivating users with their ingenuity and sophistication.
Web:- https://undressbaby.com/
UI5con 2024 - Keynote: Latest News about UI5 and it’s EcosystemPeter Muessig
Learn about the latest innovations in and around OpenUI5/SAPUI5: UI5 Tooling, UI5 linter, UI5 Web Components, Web Components Integration, UI5 2.x, UI5 GenAI.
Recording:
https://www.youtube.com/live/MSdGLG2zLy8?si=INxBHTqkwHhxV5Ta&t=0
OpenMetadata Community Meeting - 5th June 2024OpenMetadata
The OpenMetadata Community Meeting was held on June 5th, 2024. In this meeting, we discussed about the data quality capabilities that are integrated with the Incident Manager, providing a complete solution to handle your data observability needs. Watch the end-to-end demo of the data quality features.
* How to run your own data quality framework
* What is the performance impact of running data quality frameworks
* How to run the test cases in your own ETL pipelines
* How the Incident Manager is integrated
* Get notified with alerts when test cases fail
Watch the meeting recording here - https://www.youtube.com/watch?v=UbNOje0kf6E
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
E-commerce Development Services- Hornet DynamicsHornet Dynamics
For any business hoping to succeed in the digital age, having a strong online presence is crucial. We offer Ecommerce Development Services that are customized according to your business requirements and client preferences, enabling you to create a dynamic, safe, and user-friendly online store.
Transform Your Communication with Cloud-Based IVR SolutionsTheSMSPoint
Discover the power of Cloud-Based IVR Solutions to streamline communication processes. Embrace scalability and cost-efficiency while enhancing customer experiences with features like automated call routing and voice recognition. Accessible from anywhere, these solutions integrate seamlessly with existing systems, providing real-time analytics for continuous improvement. Revolutionize your communication strategy today with Cloud-Based IVR Solutions. Learn more at: https://thesmspoint.com/channel/cloud-telephony
Microservice Teams - How the cloud changes the way we workSven Peters
A lot of technical challenges and complexity come with building a cloud-native and distributed architecture. The way we develop backend software has fundamentally changed in the last ten years. Managing a microservices architecture demands a lot of us to ensure observability and operational resiliency. But did you also change the way you run your development teams?
Sven will talk about Atlassian’s journey from a monolith to a multi-tenanted architecture and how it affected the way the engineering teams work. You will learn how we shifted to service ownership, moved to more autonomous teams (and its challenges), and established platform and enablement teams.
DDS Security Version 1.2 was adopted in 2024. This revision strengthens support for long runnings systems adding new cryptographic algorithms, certificate revocation, and hardness against DoS attacks.
What is Augmented Reality Image Trackingpavan998932
Augmented Reality (AR) Image Tracking is a technology that enables AR applications to recognize and track images in the real world, overlaying digital content onto them. This enhances the user's interaction with their environment by providing additional information and interactive elements directly tied to physical images.
2. “ Continuous Integration is a software development practice where
members of a team integrate their work frequently, usually each person
integrates at least daily - leading to multiple integrations per day. ”
- Martin Fowler
3. Why GitLab CI?
Integration
Fully integrated with GitLab
Easy to start
A few lines in yml (YAML) inside of .gitlab-ci.yml and a bit clicks
Scalable
Concurrent jobs (in parallel), many runners, tagged runners
Isolated test environment
Using Docker containers
6. Runners
This is an application that processes builds. It receives commands
from GitLab CI.
It's possible to tag runners so jobs run on runners which can process
them (e.g. di erent OS)
8. Stages
Used to group your jobs in stages to create multiple pipelines
Builds of next stage are run after success
9. Repo cleaning
By default, GitLab CI cleans build dir between builds for the sake of
concurrency
But we can preserve builds between builds (Hello, npm and
node_modules !)
12. Get runner first
A simple Ubuntu Server VDS can play this role.
Provision it via script:
# Gitlab CI multi runner
curl -L https://packages.gitlab.com/install/repositories/runner/gitlab-ci-multi-runner/script.
apt-get install -y gitlab-ci-multi-runner
echo 'run "gitlab-ci-multi-runner register"'
Run gitlab-ci-multi-runner register and answer questions.
You can nd your unique registration token under Settings ---> Runners
section.
22. How to get your info
Collect your test coverage with istanbul (GH: )
(or isparta, GH: )
gotwarlost/istanbul
douglasduteil/isparta
Get your mocha test stats in HTML with reporter (GH:
)
mochawesome
adamgruber/mochawesome
Catch your static analysis with plato (GH: )es-analysis/plato
23. But how to export this info to
my static web server?
Use scriptsomekind bash
Use it like that (line in your .gitlab-ci.yml). npm test should generate
istanbul, mocha and plato reports.
my_gitlab_ci_job:
script:
- npm test
...
- /my/path/to/build-export.sh $CI_BUILD_ID $CI_PROJECT_DIR my-project-name
Why not use GitLab CI Web hooks? Because we need access to repository les
24. What about badges?
Use to generate SVG image (via bash script), then ...shields.io
... use bash script to save it into public web space
You can use private nginx server, but exclude is from auth for sure:
location ~* ((badge_maintainability.svg)|(badge_tests.svg)|(badge_coverage.svg))$ {
auth_basic off;
}
Add badge to your README.md. Example for mochawesome:
[![test status](http://path/to/latest/badge_tests.svg)](http://path/to/latest/mochawesome-reports
26. THE END
Useful links:
-
-
-
-
- My email:
- Our organization on GitHub:
Docs for .gitlab-ci.yml
GitLab Runner repository README.md
Installation on linux
Our custom bash scripts
maxim.sysoev@lingvokot.com
github.com/Lingvokot