You can enjoy desktop development with Node.js and HTML5/CSS/WebGL right now. Here we also to announce that Stem project which is a JavaScript operating system, it makes developers be able to make things on embedded system with JavaScript only. There is no need to understand that difficult knowledge about embedded system when you work on Stem OS.
Node.js实践 is a document about Node.js. It discusses how Node.js allows JavaScript to be used for server-side applications by providing a fast, scalable, and flexible environment. Node.js uses a single thread with non-blocking I/O and the V8 JavaScript engine. It also uses an event-driven architecture. This allows JavaScript to be used beyond just client-side applications in the browser. It also discusses how libraries like YUI3 and jQuery can be used in Node.js applications both on the front-end and back-end.
JavaScript is a client-side script language, but we can use it on server side programming now. However, it is still difficult to write server-side application for front-end developer.
Here we try to find a solution to write server-side script that developer only need to understand and have client-side experience.
You can enjoy desktop development with Node.js and HTML5/CSS/WebGL right now. Here we also to announce that Stem project which is a JavaScript operating system, it makes developers be able to make things on embedded system with JavaScript only. There is no need to understand that difficult knowledge about embedded system when you work on Stem OS.
Node.js实践 is a document about Node.js. It discusses how Node.js allows JavaScript to be used for server-side applications by providing a fast, scalable, and flexible environment. Node.js uses a single thread with non-blocking I/O and the V8 JavaScript engine. It also uses an event-driven architecture. This allows JavaScript to be used beyond just client-side applications in the browser. It also discusses how libraries like YUI3 and jQuery can be used in Node.js applications both on the front-end and back-end.
JavaScript is a client-side script language, but we can use it on server side programming now. However, it is still difficult to write server-side application for front-end developer.
Here we try to find a solution to write server-side script that developer only need to understand and have client-side experience.
The cross-browser, cross-device WebSocket API Socket.IO solves differences between browsers to provide a consistent API for real-time applications. It supports bi-directional communication over WebSocket, Flash, AJAX long-polling and other transports. Socket.IO is simple to use, supports older browsers, and adds features like disconnection handling that standard WebSocket does not provide. It has been used successfully in several production applications to handle thousands of simultaneous connections.
Real-time Web Application with Socket.IO, Node.js, and RedisYork Tsai
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This document summarizes a presentation about building real-time web applications using Socket.IO, Node.js, and Redis. It introduces Socket.IO for enabling real-time bidirectional communication across browsers. It then discusses using Redis for data persistence and as a pub/sub messaging system to integrate components and ensure scalability. The document provides code examples and addresses questions about authentication, load balancing, and configurations.
Kubernetes Basics provides an overview of Kubernetes concepts and components. It discusses pods vs deployments, scaling deployments, rolling updates, stateful vs stateless applications, daemon sets, secrets, configmaps, services, ingress, storage classes, network policies, and Kubernetes CLI commands. Hands-on examples are given for running commands, exposing services, deleting resources, executing commands in pods, viewing logs, and getting resource information. YAML files are shown for defining deployments, services, and ingress. Skills discussed include using configmaps as environment variables, sidecar deployments, init containers, labels and node selectors, private registries, taints and tolerations, resource management, and readiness and liveness probes.
Simon Su presented on using Google Cloud Platform for IoT applications. The document discussed key concepts in IoT like connectivity, devices, sensors and cloud infrastructure. It provided examples of using various Google Cloud services for IoT like Cloud PubSub for messaging, BigQuery for data storage, Cloud Functions for serverless computing, Cloud Vision API for image recognition and Cloud IoT Core for connecting devices. Code samples were given to illustrate how to use these services for common IoT tasks.
This document provides an overview of various Google Cloud Platform services including Compute Engine, Networking, Load Balancing, Cloud Launcher, Cloud Storage, Cloud SQL, Cloud Monitoring, Cloud DNS, and Deployment Manager. It includes descriptions of the basic concepts and functionality for each service. It also outlines several hands-on labs demonstrating how to use specific GCP services like backing up instances to Cloud Storage snapshots, exporting Cloud SQL databases to Cloud Storage, enabling Cloud Logging, and deploying a VM instance using Deployment Manager.
This document provides instructions for enabling and using the serial console on a Windows machine. It outlines connecting to the VM from port 3, using "?" to check available commands, running "cmd" to start a new command session, and "ch -sn [session name]" to switch sessions. Finally, it notes you can reset the password using "Create or reset Windows password" and login to access the Windows command prompt for troubleshooting.
Cloud Spanner is a fully managed relational database that provides global scale, SQL support, and strong consistency across multiple regions. It is horizontally scalable, provides automatic replication and maintenance, and supports transactions with ACID semantics. Spanner offers high availability, enterprise-grade security with encryption and IAM controls, and supports multiple programming languages through client libraries. Performance scales based on the number of nodes provisioned, with a minimum of 3 nodes recommended for production workloads.
Google Cloud Computing compares GCE, GAE and GKESimon Su
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Google Cloud Computing compares GCE, GKE and GAE. GCE provides raw compute, storage and networking resources and requires more management overhead. GAE focuses on application logic and requires less management. GKE offers managed Kubernetes infrastructure and services. Each option has different strengths for workloads like microservices, containerized services, or large-scale applications requiring quick scaling. Monitoring and management features like Stackdriver are also compared.
The document provides information about Simon Su and his expertise in Google Dataflow. It includes Simon's contact information and links to his online profiles. It then discusses Simon's areas of specialization including data scientist, data engineer, and frontend engineer. The document proceeds to provide information about preparing for a Google Dataflow workshop, including documents and labs to review. It also discusses Google Cloud services for data processing and analysis like Dataflow, BigQuery, Pub/Sub, and Dataproc. Finally, it outlines the agenda for the workshop, which will include hands-on labs to deploy users' first Dataflow project and create a streaming Dataflow model.
This document outlines labs for Google Cloud Dataflow workshops. Lab 1 covers setting up the Dataflow environment and building a first project. Lab 2 focuses on deploying the first project to Google Cloud Platform. Lab 3 builds streaming Dataflow by creating PubSub topics/subscriptions and deploying streaming samples that read from PubSub and write to BigQuery.
GCPUG meetup 201610 - Dataflow IntroductionSimon Su
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This document provides information about Simon Su and Sunny Hu, who will be presenting on Google's BigData solution. It includes their contact information and backgrounds. Simon's areas of focus include Node.js and blogging. Sunny's skills include project management, system analysis, and Java. The document also advertises a Facebook and Google+ group for the Google Cloud Platform User Group Taiwan, where people can share experiences using GCP. It poses trivia questions about Google's infrastructure and provides timelines of Google's BigData innovations.
使用 Raspberry pi + fluentd + gcp cloud logging, big query 做iot 資料搜集與分析Simon Su
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This is a short training for introduce Pi to use fluentd to collect data and use Google Cloud Logging and BigQuery as backend and then use Apps Script and Google Sheet as presentation layer.
This document provides an overview of Docker concepts and commands for building, running, and managing Docker containers. It demonstrates how to run a simple Node.js application as a Docker container using commands like docker run, docker build, docker ps, and docker-compose. It also shows how to link containers, mount folders, push images to Docker Hub, and remove containers.
Google Cloud Platform Introduction - 2016Q3Simon Su
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The document summarizes news and services from Google Cloud Platform, including free GCE machine types, preemptible VMs, IAM project management, and new APIs for Machine Learning, Vision, and Speech. It also provides an overview of various GCP computing, storage, database and analytics services like Compute Engine, App Engine, Cloud SQL, Cloud Storage, BigQuery, and Dataflow. Join the Google Cloud Platform User Group Taiwan Facebook group for more information on GCP services and events.