This is a 1-hr tech talk designed for developers to give a comprehensive, vendor-agnostic overview of cloud computing, primarily targeting educators in the higher education market but is open to any developer. This is followed by an introduction to products in Google Cloud, focusing on the serverless products. The talk ends with several inspirational examples of what can be built with Google Cloud
This document discusses cloud computing and Google Cloud Platform. It provides an overview of cloud concepts like IaaS, PaaS, and SaaS and Google Cloud services including Compute Engine, Cloud Storage, Cloud SQL, and Cloud Functions. It also covers advantages of the cloud like mobility, autoscaling, and APIs/SDKs. Architectures for backup, archiving, and disaster recovery using Google Cloud services are presented. Considerations for administering Google Cloud like regions/zones, pricing models, and dependencies on internet connectivity are also mentioned.
This document discusses Google Cloud Platform and how Google powers its own services. It notes that Google is the fourth largest server manufacturer and would be the second largest internet service provider by traffic. It describes how Google builds customized hardware from cheap commodity parts and manages vast numbers of homogeneous servers at scale with software resilience and horizontal layers rather than hardware resilience and vertical stacks. The document also provides an overview of how Google's global data centers, communications network, data storage and distribution, services and APIs, and compute platforms can be utilized to build and scale applications. It includes several customer stories about how companies have used Google Cloud Platform for applications experiencing peak traffic, global data storage, crowd-sourcing weather data, and syncing notes across devices.
This document provides summaries of Google Cloud Platform services, including Google App Engine, Google BigQuery, Google Cloud Bigtable, Google Cloud Build, Google Cloud Dataflow, Google Cloud Datalab, Google Cloud Dataproc, Google Cloud Datastore, Google Cloud Endpoints, Google Cloud Firestore, Google Cloud Functions, Google Cloud Healthcare, Google Cloud IoT Core, Google Cloud Talent Solution, Google Cloud Hardware Security Module, Google Cloud Key Management Service, Google Cloud Machine Learning Engine, Google Cloud Memorystore, Google Cloud Pub/Sub, Google Cloud Spanner, Google Cloud SQL, Google Cloud Storage, Google Cloud Test Lab, Google Cloud Translation, Google Compute Engine, Google Container Registry, Google Data Loss Prevention API, Google Kubernetes Engine
Introduction to Google Cloud Services / PlatformsNilanchal
The presentation provides a brief Introduction to Google Cloud Services and Platforms. In the course of this slide, we will introduce you the different Google cloud computing options, Compute Engine, App Engine, Cloud function, Databases, file storage and security features of Google cloud platform.
Cloud computing provides dynamically scalable resources as a service over the Internet. It addresses problems with traditional infrastructure like hard-to-scale systems that are costly and complex to manage. Cloud platforms like Google Cloud Platform provide computing services like Compute Engine VMs and App Engine PaaS, as well as storage, networking, databases and other services to build scalable applications without managing physical hardware. These services automatically scale as needed, reducing infrastructure costs and management complexity.
Google Cloud Connect @ Korea
- Google Cloud Vision
- G Suite Product Roadmap
- Google Cloud Security
- Google Cloud Machine Learning
- G suite Customer Stories
MongoDB Days UK: Run MongoDB on Google Cloud PlatformMongoDB
This document discusses MongoDB performance on Google Cloud Platform. It provides benchmarks comparing MongoDB performance on Google Compute Engine virtual machines with different disk configurations. The benchmarks show that dedicating separate disks for the MongoDB database files and journal files significantly improves write performance. The document also describes how the company uses MongoDB on Google Cloud Platform for time-series database workloads, including off-site backups to Google Cloud Storage and automated restore testing.
This document discusses cloud computing and Google Cloud Platform. It provides an overview of cloud concepts like IaaS, PaaS, and SaaS and Google Cloud services including Compute Engine, Cloud Storage, Cloud SQL, and Cloud Functions. It also covers advantages of the cloud like mobility, autoscaling, and APIs/SDKs. Architectures for backup, archiving, and disaster recovery using Google Cloud services are presented. Considerations for administering Google Cloud like regions/zones, pricing models, and dependencies on internet connectivity are also mentioned.
This document discusses Google Cloud Platform and how Google powers its own services. It notes that Google is the fourth largest server manufacturer and would be the second largest internet service provider by traffic. It describes how Google builds customized hardware from cheap commodity parts and manages vast numbers of homogeneous servers at scale with software resilience and horizontal layers rather than hardware resilience and vertical stacks. The document also provides an overview of how Google's global data centers, communications network, data storage and distribution, services and APIs, and compute platforms can be utilized to build and scale applications. It includes several customer stories about how companies have used Google Cloud Platform for applications experiencing peak traffic, global data storage, crowd-sourcing weather data, and syncing notes across devices.
This document provides summaries of Google Cloud Platform services, including Google App Engine, Google BigQuery, Google Cloud Bigtable, Google Cloud Build, Google Cloud Dataflow, Google Cloud Datalab, Google Cloud Dataproc, Google Cloud Datastore, Google Cloud Endpoints, Google Cloud Firestore, Google Cloud Functions, Google Cloud Healthcare, Google Cloud IoT Core, Google Cloud Talent Solution, Google Cloud Hardware Security Module, Google Cloud Key Management Service, Google Cloud Machine Learning Engine, Google Cloud Memorystore, Google Cloud Pub/Sub, Google Cloud Spanner, Google Cloud SQL, Google Cloud Storage, Google Cloud Test Lab, Google Cloud Translation, Google Compute Engine, Google Container Registry, Google Data Loss Prevention API, Google Kubernetes Engine
Introduction to Google Cloud Services / PlatformsNilanchal
The presentation provides a brief Introduction to Google Cloud Services and Platforms. In the course of this slide, we will introduce you the different Google cloud computing options, Compute Engine, App Engine, Cloud function, Databases, file storage and security features of Google cloud platform.
Cloud computing provides dynamically scalable resources as a service over the Internet. It addresses problems with traditional infrastructure like hard-to-scale systems that are costly and complex to manage. Cloud platforms like Google Cloud Platform provide computing services like Compute Engine VMs and App Engine PaaS, as well as storage, networking, databases and other services to build scalable applications without managing physical hardware. These services automatically scale as needed, reducing infrastructure costs and management complexity.
Google Cloud Connect @ Korea
- Google Cloud Vision
- G Suite Product Roadmap
- Google Cloud Security
- Google Cloud Machine Learning
- G suite Customer Stories
MongoDB Days UK: Run MongoDB on Google Cloud PlatformMongoDB
This document discusses MongoDB performance on Google Cloud Platform. It provides benchmarks comparing MongoDB performance on Google Compute Engine virtual machines with different disk configurations. The benchmarks show that dedicating separate disks for the MongoDB database files and journal files significantly improves write performance. The document also describes how the company uses MongoDB on Google Cloud Platform for time-series database workloads, including off-site backups to Google Cloud Storage and automated restore testing.
The document provides information about Google Cloud Platform services including App Engine, Compute Engine, Cloud Storage, BigQuery, and Cloud SQL. It discusses the key features of each service, such as scalability, reliability, cost efficiency, and SQL support for Cloud SQL. Pricing models are outlined for various resources like instances, storage, bandwidth, and database tiers. The document aims to help users understand and utilize Google Cloud Platform's infrastructure and managed services.
Cloud computing provides on-demand access to shared computing resources like networks, servers, storage, applications and services available over the internet. It offers advantages like cost effectiveness, dynamic scaling, on-demand self-service and measured service. There are three main service models - Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS). The document then discusses Google Cloud Platform's IaaS offering called Google Compute Engine and its PaaS offering called Google App Engine.
Google Cloud Platform as a Backend Solution for your ProductSergey Smetanin
This document provides an overview of Google Cloud Platform services that could be used as a backend solution for a product. It discusses Google App Engine as a fully managed platform, Google Cloud Datastore as a NoSQL database, Google Cloud Storage for file storage, and Google BigQuery for analytics. The document then describes how a company called RuBeacon uses these Google Cloud services for their mobile app backend, focusing on App Engine, Datastore, Storage, and related services.
Google Cloud Platform Introduction - 2016Q3Simon Su
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.
Introduction to Google's Cloud TechnologiesChris Schalk
An overview of the different Cloud technologies available from Google including App Engine, Google Storage, Google Prediction API, and BigQuery.
This presentation was given to the San Diego GTUG on Aug 26th, 2011.
Next Generation Cloud Computing With Google - RightScale Compute 2013RightScale
Speaker: Martin Gannholm - Lead Engineer, Google
Google Cloud Platform provides everything you need to build, run, and scale social, mobile, and online applications. Already, tens of thousands of popular applications like Khan Academy, Angry Birds, SnapChat, and Pulse are benefiting from the power of running on top of Google infrastructure. Come join Google as we go deep on how to best leverage our technology with RightScale to build your next masterpiece.
Google Cloud Storage is unified object storage for developers and enterprises, from live data serving to data analytics/ML to data archiving.
High performance, internet-scale, immutable BLOB (binary large object) storage
Simple Abstraction Storage buckets, immutable objects with mutable metadata and Globally unique URI identifiers for buckets, objects
Common storage for Google Cloud Platform services
This document provides an overview of Google Cloud Platform (GCP) services. It begins by explaining why GCP is underpinned by Google's infrastructure and innovation. It then outlines GCP's compute, networking, storage, big data, and machine learning services. These include Compute Engine, Container Engine, App Engine, load balancing, Cloud DNS, Cloud Storage, Cloud Datastore, Cloud Bigtable, Cloud SQL, BigQuery, Dataflow, Pub/Sub, Dataproc, and Cloud Datalab. Machine learning services such as Translate API, Prediction API, Cloud Vision API, and Cloud Speech API are also introduced.
This document provides an overview of Google Cloud Platform (GCP) services. It discusses computing services like App Engine and Compute Engine for hosting applications. It covers storage options like Cloud Storage, Cloud Datastore and Cloud SQL. It also mentions big data services like BigQuery and machine learning services like Prediction API. The document provides brief descriptions of each service and highlights their key features. It includes code samples for using Prediction API to train a model and make predictions on new data.
Google Cloud Platform is a suite of cloud computing services offered by Google that includes compute, storage, and application development services running on Google's hardware. Core services include Google Container Engine for Docker container management, Google Cloud Storage for large unstructured data storage, Google App Engine for scalable hosting, and Google Compute Engine for virtual machine instances. Google Drive is Google's cloud storage and file editing platform that provides 15GB of free storage and collaboration tools integrated with Google Docs, Sheets, Slides, and Forms for documents, spreadsheets, presentations, and surveys.
Google Cloud Platform is a cloud computing platform by Google that offers hosting on the same supporting infrastructure that Google uses internally for end-user products like Google Search and YouTube. Cloud Platform provides developer products to build a range of programs from simple websites to complex applications.
Google Cloud Platform is a part of a suite of enterprise solutions from Google for Work and provides a set of modular cloud-based services with a host of development tools. For example, hosting and computing, cloud storage, data storage, translations APIs and prediction APIs.
Topic Covered
Why Google Cloud Platform ?
Google Cloud Platform Services: First Insight !!!
Here are the key considerations in choosing between public and private clouds for a new service/company:
- Public clouds like AWS provide massive scalability and flexibility with no upfront investment, allowing you to focus resources on your core product. However, you lose some control and security over your infrastructure.
- Private clouds give you more control and security over your infrastructure but require managing and maintaining servers. Upfront investment is needed to set up hardware. Scaling can be more difficult than public clouds.
- A hybrid approach using a public cloud for non-critical loads and a private cloud for sensitive workloads may strike the best balance of cost, control and flexibility for a new company.
- Consider your security, data ownership and compliance
Google Cloud - Scale With A Smile (Dec 2014)Ido Green
"Google's ability to build, organize, and operate a huge network of servers and fiber-optic cables with an efficiency and speed that rocks physics on its heels. This is what makes Google Google: its physical network, its thousands of fiber miles, and those many thousands of servers that, in aggregate, add up to the mother of all clouds.” - Wired
---
Well, Wired hit the nail on the head with this quote about our platform. In this presentation we cover most of the new interesting features that will give you the ability to scale with (a big) smile!
Building Enterprise Applications on Google Cloud Platform Cloud Computing Exp...Chris Schalk
This is a presentation given by Google Developer Advocate Chris Schalk at Cloud Expo in NYC on June 8th 2011 on building enterprise applications with Google's Cloud Platform.
Google provides Infrastructure as a Service (IaaS) through Compute Engine, which allows users to create and run virtual machines on Google's infrastructure. It also provides Platform as a Service (PaaS) through services like App Engine, a fully managed platform for developing and hosting web applications at scale using popular programming languages. Google's cloud services run on the same infrastructure used for its consumer products and offer reliability, security, scalability and pay-as-you-go pricing.
Presentation for Introduction to Google Cloud Platform. This PPT provides basic understanding for services provided by Google Cloud Platform like Compute, Storage, VPC, IAM.
These slides are made for the 2013 DevFest talks. It covers the main blocks of Google cloud platform: App engine, Compute Engine, storage options and more.
Here's an intro to the 30 Days of Google Cloud program to kickstart your career in the cloud as well as earn exciting prizes & digital badges. To start with, your facilitator, Mohini Gupta, will be taking you on board this journey, explaining you these :
1.) Introduction to the program
2.) About GCP Crash Course
3.) A Tour of Qwiklabs and the Google Cloud Platform Lab
4.) Hands-on lab experience
Intro to cloud computing & running your code on Google Cloudwesley chun
This is a 1-hr tech talk designed for developers to give a comprehensive, vendor-agnostic overview of cloud computing, primarily targeting educators in the higher education market but is open to any developer. This is followed by an introduction to products in Google Cloud, focusing on the serverless products. The talk ends with several inspirational examples of what can be built with Google Cloud.
Powerful Google Cloud tools for your hack (2020)wesley chun
You may know Google for search, YouTube, Android, Chrome, and Gmail, but did you know Google has many other cloud services? This session takes hackathon participants on a deeper dive from the opening ceremony lightning intro. In this comprehensive yet still high-level overview of Google Cloud tools & APIs with the purpose of inspiring students for their hacks. We'll look closely at our serverless platforms & machine learning APIs, tools that have an immediate impact on projects, alleviating the need to think about computing infrastructure as well as dispensing with the need to have machine learning expertise. We'll wrap up w/online resources like videos & hands-on tutorials to get you started so you'll know what to do with those Cloud credits you got from MLH!
The document provides information about Google Cloud Platform services including App Engine, Compute Engine, Cloud Storage, BigQuery, and Cloud SQL. It discusses the key features of each service, such as scalability, reliability, cost efficiency, and SQL support for Cloud SQL. Pricing models are outlined for various resources like instances, storage, bandwidth, and database tiers. The document aims to help users understand and utilize Google Cloud Platform's infrastructure and managed services.
Cloud computing provides on-demand access to shared computing resources like networks, servers, storage, applications and services available over the internet. It offers advantages like cost effectiveness, dynamic scaling, on-demand self-service and measured service. There are three main service models - Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS). The document then discusses Google Cloud Platform's IaaS offering called Google Compute Engine and its PaaS offering called Google App Engine.
Google Cloud Platform as a Backend Solution for your ProductSergey Smetanin
This document provides an overview of Google Cloud Platform services that could be used as a backend solution for a product. It discusses Google App Engine as a fully managed platform, Google Cloud Datastore as a NoSQL database, Google Cloud Storage for file storage, and Google BigQuery for analytics. The document then describes how a company called RuBeacon uses these Google Cloud services for their mobile app backend, focusing on App Engine, Datastore, Storage, and related services.
Google Cloud Platform Introduction - 2016Q3Simon Su
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.
Introduction to Google's Cloud TechnologiesChris Schalk
An overview of the different Cloud technologies available from Google including App Engine, Google Storage, Google Prediction API, and BigQuery.
This presentation was given to the San Diego GTUG on Aug 26th, 2011.
Next Generation Cloud Computing With Google - RightScale Compute 2013RightScale
Speaker: Martin Gannholm - Lead Engineer, Google
Google Cloud Platform provides everything you need to build, run, and scale social, mobile, and online applications. Already, tens of thousands of popular applications like Khan Academy, Angry Birds, SnapChat, and Pulse are benefiting from the power of running on top of Google infrastructure. Come join Google as we go deep on how to best leverage our technology with RightScale to build your next masterpiece.
Google Cloud Storage is unified object storage for developers and enterprises, from live data serving to data analytics/ML to data archiving.
High performance, internet-scale, immutable BLOB (binary large object) storage
Simple Abstraction Storage buckets, immutable objects with mutable metadata and Globally unique URI identifiers for buckets, objects
Common storage for Google Cloud Platform services
This document provides an overview of Google Cloud Platform (GCP) services. It begins by explaining why GCP is underpinned by Google's infrastructure and innovation. It then outlines GCP's compute, networking, storage, big data, and machine learning services. These include Compute Engine, Container Engine, App Engine, load balancing, Cloud DNS, Cloud Storage, Cloud Datastore, Cloud Bigtable, Cloud SQL, BigQuery, Dataflow, Pub/Sub, Dataproc, and Cloud Datalab. Machine learning services such as Translate API, Prediction API, Cloud Vision API, and Cloud Speech API are also introduced.
This document provides an overview of Google Cloud Platform (GCP) services. It discusses computing services like App Engine and Compute Engine for hosting applications. It covers storage options like Cloud Storage, Cloud Datastore and Cloud SQL. It also mentions big data services like BigQuery and machine learning services like Prediction API. The document provides brief descriptions of each service and highlights their key features. It includes code samples for using Prediction API to train a model and make predictions on new data.
Google Cloud Platform is a suite of cloud computing services offered by Google that includes compute, storage, and application development services running on Google's hardware. Core services include Google Container Engine for Docker container management, Google Cloud Storage for large unstructured data storage, Google App Engine for scalable hosting, and Google Compute Engine for virtual machine instances. Google Drive is Google's cloud storage and file editing platform that provides 15GB of free storage and collaboration tools integrated with Google Docs, Sheets, Slides, and Forms for documents, spreadsheets, presentations, and surveys.
Google Cloud Platform is a cloud computing platform by Google that offers hosting on the same supporting infrastructure that Google uses internally for end-user products like Google Search and YouTube. Cloud Platform provides developer products to build a range of programs from simple websites to complex applications.
Google Cloud Platform is a part of a suite of enterprise solutions from Google for Work and provides a set of modular cloud-based services with a host of development tools. For example, hosting and computing, cloud storage, data storage, translations APIs and prediction APIs.
Topic Covered
Why Google Cloud Platform ?
Google Cloud Platform Services: First Insight !!!
Here are the key considerations in choosing between public and private clouds for a new service/company:
- Public clouds like AWS provide massive scalability and flexibility with no upfront investment, allowing you to focus resources on your core product. However, you lose some control and security over your infrastructure.
- Private clouds give you more control and security over your infrastructure but require managing and maintaining servers. Upfront investment is needed to set up hardware. Scaling can be more difficult than public clouds.
- A hybrid approach using a public cloud for non-critical loads and a private cloud for sensitive workloads may strike the best balance of cost, control and flexibility for a new company.
- Consider your security, data ownership and compliance
Google Cloud - Scale With A Smile (Dec 2014)Ido Green
"Google's ability to build, organize, and operate a huge network of servers and fiber-optic cables with an efficiency and speed that rocks physics on its heels. This is what makes Google Google: its physical network, its thousands of fiber miles, and those many thousands of servers that, in aggregate, add up to the mother of all clouds.” - Wired
---
Well, Wired hit the nail on the head with this quote about our platform. In this presentation we cover most of the new interesting features that will give you the ability to scale with (a big) smile!
Building Enterprise Applications on Google Cloud Platform Cloud Computing Exp...Chris Schalk
This is a presentation given by Google Developer Advocate Chris Schalk at Cloud Expo in NYC on June 8th 2011 on building enterprise applications with Google's Cloud Platform.
Google provides Infrastructure as a Service (IaaS) through Compute Engine, which allows users to create and run virtual machines on Google's infrastructure. It also provides Platform as a Service (PaaS) through services like App Engine, a fully managed platform for developing and hosting web applications at scale using popular programming languages. Google's cloud services run on the same infrastructure used for its consumer products and offer reliability, security, scalability and pay-as-you-go pricing.
Presentation for Introduction to Google Cloud Platform. This PPT provides basic understanding for services provided by Google Cloud Platform like Compute, Storage, VPC, IAM.
These slides are made for the 2013 DevFest talks. It covers the main blocks of Google cloud platform: App engine, Compute Engine, storage options and more.
Here's an intro to the 30 Days of Google Cloud program to kickstart your career in the cloud as well as earn exciting prizes & digital badges. To start with, your facilitator, Mohini Gupta, will be taking you on board this journey, explaining you these :
1.) Introduction to the program
2.) About GCP Crash Course
3.) A Tour of Qwiklabs and the Google Cloud Platform Lab
4.) Hands-on lab experience
Intro to cloud computing & running your code on Google Cloudwesley chun
This is a 1-hr tech talk designed for developers to give a comprehensive, vendor-agnostic overview of cloud computing, primarily targeting educators in the higher education market but is open to any developer. This is followed by an introduction to products in Google Cloud, focusing on the serverless products. The talk ends with several inspirational examples of what can be built with Google Cloud.
Powerful Google Cloud tools for your hack (2020)wesley chun
You may know Google for search, YouTube, Android, Chrome, and Gmail, but did you know Google has many other cloud services? This session takes hackathon participants on a deeper dive from the opening ceremony lightning intro. In this comprehensive yet still high-level overview of Google Cloud tools & APIs with the purpose of inspiring students for their hacks. We'll look closely at our serverless platforms & machine learning APIs, tools that have an immediate impact on projects, alleviating the need to think about computing infrastructure as well as dispensing with the need to have machine learning expertise. We'll wrap up w/online resources like videos & hands-on tutorials to get you started so you'll know what to do with those Cloud credits you got from MLH!
Powerful Google Cloud tools for your hackwesley chun
This 1-hour presentation is meant to give univeresity hackathoners a deeper yes still high-level overview of Google Cloud and its developer APIs with the purpose of inspiring students to consider these products for their hacks. It follows and dives deeper into the products introduced at the opening ceremony lightning talk. Of particular focus are the serverless and machine learning platforms & APIs... tools that have an immediate impact on projects, alleviating the need to manage VMs, operating systems, etc., as well as dispensing with the need to have expertise with machine learning.
Cloud computing overview & running your code on Google Cloud (Jun 2019)wesley chun
This is a 1-hr tech talk designed for developers to give a comprehensive, vendor-agnostic overview of cloud computing, primarily targeting educators in the higher education market but is open to any developer. This is followed by an introduction to products in Google Cloud, focusing on the serverless products. The talk ends with several inspirational examples of what can be built with Google Cloud.
How Google Cloud Platform can help in the classroom/labwesley chun
This is a 90-min tech talk along with hands-on exercises gives a comprehensive, vendor-agnostic overview of cloud computing, primarily targeting educators in the higher education market but is open to any developer. This is followed by an introduction to products in Google Cloud Platform, focusing on its serverless and machine learning products. .
Cloud computing overview & running your code on Google Cloudwesley chun
This is a half-hr tech talk designed for developers to give a comprehensive, vendor-agnostic overview of cloud computing, primarily targeting educators in the higher education market but is open to any developer. This is followed by an introduction to products in Google Cloud, focusing on the serverless products. The talk ends with several inspirational examples of what can be built with Google Cloud
Cloud computing overview & Technical intro to Google Cloudwesley chun
The document provides an overview of cloud computing and an introduction to Google Cloud. It discusses the different types of cloud services including Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS). It then introduces various Google Cloud Platform (GCP) and G Suite products and services that fall under each category. Examples of code snippets using GCP and G Suite APIs in Python are also provided to demonstrate interacting with these cloud services programmatically.
Powerful Google developer tools for immediate impact! (2023-24 B)wesley chun
This is one of two presentations to students or working professionals. You may know Google for search, YouTube, Android, Chrome, and Gmail, but did you know Google has many other cloud services? In this comprehensive yet still high-level overview of Google Cloud tools & APIs with the purpose of inspiring you as to what's possible. The session introduces Google's serverless platforms and machine learning & other APIs, tools that have an immediate impact on projects, alleviating the need to think about computing infrastructure as well as dispensing with the need to have machine learning expertise. We'll wrap up w/online resources like videos & hands-on tutorials to get you started! The main takeaways are where to run your code, store your data, and analyze your data, all in the cloud!
This talk is 1-hr in length.
The other version of this talk ("A") is an 45-mins long and focuses more on APIs platforms.
This is a half-hour technical talk on serverless computing with Python featuring products from the Google Cloud Platform. It starts with a review of all of cloud computing then dives into serverless computing, demonstrates multiple products, then shows inspirational examples of apps built using these technologies.
Serverless computing with Google Cloud (2023-24)wesley chun
This is a half-hour technical talk on serverless computing with Google Cloud (Platform). It starts with a review of all of cloud computing then dives into serverless computing, demonstrates multiple products, and shows inspirational examples of apps built using these technologies.
Cloud computing overview & running your code on Google Cloudwesley chun
This is a half-hr tech talk designed for developers to give a comprehensive, vendor-agnostic overview of cloud computing, primarily targeting educators in the higher education market but is open to any developer. This is followed by an introduction to products in Google Cloud, focusing on the serverless products. The talk ends with several inspirational examples of what can be built with Google Cloud.
- The speaker discusses serverless computing platforms on Google Cloud like Cloud Functions and Cloud Run. These platforms allow developers to focus on writing code without worrying about managing servers.
- Serverless computing is growing rapidly due to its ability to auto-scale applications and only charge for compute resources when code is running. This "pay-per-use" model avoids costs from idle servers.
- Popular serverless platforms on Google Cloud include Cloud Functions for running code in response to events, and Cloud Run for deploying containerized applications that are triggered by HTTP requests.
Google Cloud is an organization producing 2 well-know product groups, GCP & G Suite. Most think they don't go nor work well together. This 90-minute session busts that myth and exposes developers to some of the more well-known APIs from both GCP & G Suite as well as highlights several novel solutions that have already been built as sample apps but also serve as inspiration into what's possible. The goal is to show developers the potential of building with ALL of Google Cloud.
Powerful Google developer tools for immediate impact! (2023-24 A)wesley chun
This is one of two 45-60-min presentations to students or working professionals. You may know Google for search, YouTube, Android, Chrome, and Gmail, but did you know Google has many other cloud services? In this comprehensive yet still high-level overview of Google Cloud tools & APIs with the purpose of inspiring you as to what's possible. The session introduces Google's machine learning & other APIs, tools that have an immediate impact on projects, alleviating the need to think about computing infrastructure as well as dispensing with the need to have machine learning expertise. We'll wrap up w/online resources like videos & hands-on tutorials to get you started! The main takeaways are where to run your code, store your data, and analyze your data, all in the cloud!
The other version of this talk ("B") focuses more on serverless platforms.
This is an inspirational lightning talk on how developers can take on the future with Google Cloud and other non-Cloud Google tools. It presents various application ideas that are meant to both inspire what's possible as well as show what some of those tools could be.
Introduction to serverless computing on Google Cloudwesley chun
This is a 15-20 minute tech talk designed for those who wish to get a broad high-level introduction to serverless computing. Tech featured includes Google App Engine, Google Cloud Functions, and Google Apps Script.
Exploring Google (Cloud) APIs & Cloud Computing overviewwesley chun
This is a 100-minute tech talk designed for developers to give a comprehensive overview of using Google APIs, primarily those from Google Cloud (G Suite and Google Cloud Platform)
Run your code serverlessly on Google's open cloudwesley chun
This is a half-hour technical seminar on Google support of the open source ecosystem, a quick high-level overview/review of cloud computing in general, and then focuses on serverless compute products in Google Cloud and how the platforms are more open than ever!
This is a one hour technical talk on serverless computing with Google Cloud (Platform). It starts with a review of all of cloud computing then dives into serverless computing, demonstrates multiple products, and shows inspirational examples of apps built using these technologies.
Powerful Google developer tools for immediate impact! (2023-24 C)wesley chun
This presentations targets students or working professionals. You may know Google for search, YouTube, Android, Chrome, and Gmail, but did you know Google has many developer tools, platforms & APIs? This comprehensive yet still high-level overview outlines the most impactful tools for where to run your code, store & analyze your data. It will also inspire you as to what's possible. This talk is 50 minutes in length.
Easy path to machine learning (2023-2024)wesley chun
1-hr tech talk introducing Machine Learning and the GCP ML APIs and other Google Cloud developer tools to a technical audience:
Easier onramp to getting into AI/ML by using GCP AI/ML APIs (Vision, Video Intelligence, Natural Language, Speech-to-Text, Text-to-Speech, Translation) backed by single-task pre-trained models found in Vertex AI, AutoML for finetuning those pre-trained models, and other "friends of AI/ML" Google dev tools & platforms that can help: BigQuery (data warehouse & analysis), Cloud SQL+AlloyDB & Firestore (SQL & NoSQL databases), serverless platforms (App Engine, Cloud Functions, Cloud Run), and introducing the Gemini API (from both Google AI and GCP Vertex AI)
30-45-min tech talk given at user groups or technical conferences to introducing developers to integrating with Google APIs from Python .
ABSTRACT
Want to integrate Google technologies into the web+mobile apps that you build? Google has various open source libraries & developer tools that help you do exactly that. Users who have run into roadblocks like authentication or found our APIs confusing/challenging, are welcome to come and make these non-issues moving forward. Learn how to leverage the power of Google technologies in the next apps you build!!
Build an AI/ML-driven image archive processing workflow: Image archive, analy...wesley chun
Google provides a diverse array of services to realize the ambition of solving real business problems, like constrained resources. An image archive & analysis plus report generation use-case can be realized with just GWS (Google Workspace) & GCP (Google Cloud) APIs. The principle of mixing-and-matching Google technologies is applicable to many other challenges faced by you, your organization, or your customers. These slides are from the half-hour presentation about this case study.
Exploring Google APIs 102: Cloud vs. non-GCP Google APIswesley chun
As a follow-up to his "Exploring Google APIs" talk in 2019 (https://www.youtube.com/watch?v=ri8Bfptgo9Q) on Google APIs and running code on Google Cloud, tech consultant Wesley Chun dives deeper into using the REST APIs available for many Google services, Cloud and otherwise. While developers should expect a common user experience across all Google APIs, this isn't the case, so Wesley, who has spent 13+ years working on different Google API teams, will walk you through the differences you need to know if any of your current or future projects plan on using any Google API, esp. Cloud vs. non-GCP Google APIs. Two of the key topics in this session include an overview of the different client libraries available as well as what's required for authorizing your app's access to Google APIs. Knowledge of accessing APIs from Python or Javascript may be helpful but not necessary.
You may know Google for search, YouTube, Android, Chrome, and Gmail, but that's only as an end-user of OUR apps. Did you know you can also integrate Google technologies into YOUR apps? We have many APIs and open source libraries that help you do that! If you have tried and found it challenging, didn't find not enough examples, run into roadblocks, got confused, or just curious about what Google APIs can offer, join us to resolve any blockers. Code samples will be in Python and/or Node.js/JavaScript. This session focuses on showing you how to access Google Cloud APIs from one of Google Cloud's compute platforms, whether serverless or otherwise.
This is a one hour technical talk by @wescpy on serverless computing with Google Cloud (Platform). It starts with a review of all of cloud computing then dives into serverless computing, demonstrates multiple products, and shows inspirational examples of apps built using these technologies. There is a bonus section covering serverless in-practice featuring how to think about app development, common use cases, flexibility, best practices, and local dev & testing.
Designing flexible apps deployable to App Engine, Cloud Functions, or Cloud Runwesley chun
Many people ask, "Which one is better for me: App Engine, Cloud Functions, or Cloud Run?" To help you learn more about them, understand their differences, appropriate use cases, etc., why not deploy the same app to all 3? With this "test drive," you only need to make minor config changes between platforms. You'll also learn one of Google Cloud's AI/ML "building block" APIs as a bonus as the sample app is a simple "mini" Google Translate "MVP". This is a 45- 60-minute talk that reviews the Google Cloud serverless compute platforms then walks through the same app and its deployments. The code is maintained at https://github.com/googlecodelabs/cloud-nebulous-serverless-python
Image archive, analysis & report generation with Google Cloudwesley chun
Google Cloud provides a diverse array of services to realize the ambition of solving real business problems, like constrained resources. An image archive & analysis plus report generation use-case can be realized with just Google Workspace & GCP APIs. The principle of mixing-and-matching Google technologies is applicable to many other challenges faced by you, your organization, or your customers. These slides are from a half- to 1-hour presentation about this case study.
Half-hour tech talk given at user groups or technical conferences to introducing developers to integrating with Google (Cloud) APIs from Python .
ABSTRACT
Want to integrate Google technologies into the web+mobile apps that you build? Google has various open source libraries & developer tools that help you do exactly that. Users who have run into roadblocks like authentication or found our APIs confusing/challenging, are welcome to come and make these non-issues moving forward. Learn how to leverage the power of Google technologies in the next apps you build!!
This is a half-hour technical talk on serverless computing with Google Cloud (Platform). It starts with a review of all of cloud computing then dives into serverless computing, demonstrates multiple products, and shows inspirational examples of apps built using these technologies.
Introduction to Cloud Computing with Google Cloudwesley chun
This is a 20-30 minute technical talk introducing developers to cloud computing including an overview of Google Cloud computing products. There is a special focus on serverless tools as a convenient way for developers to run code. The talk ends with several inspirational apps showcasing what is possible with Google Cloud tools meant to plant a seed as to consider what is possible.
Exploring Google (Cloud) APIs with Python & JavaScriptwesley chun
Half-hour tech talk given at user groups or technical conferences to introducing developers to integrating with Google (Cloud) APIs from Python or JavaScript.
ABSTRACT
Want to integrate Google technologies into the web+mobile apps that you build? Google has various open source libraries & developer tools that help you do exactly that. Users who have run into roadblocks like authentication or found our APIs confusing/challenging, are welcome to come and make these non-issues moving forward. Learn how to leverage the power of Google technologies in the next apps you build!!
Hackathon opening ceremony 2-5 minute lightning talk introducing Google Cloud tools that students can use for their hacks, whetting their appetites for a more detailed longer tech talk later.
Google Apps Script: Accessing G Suite & other Google services with JavaScriptwesley chun
This document provides an overview of Google Apps Script, including its capabilities, use cases, and coding examples. Some key points:
- Google Apps Script is a JavaScript runtime that allows automation of G Suite applications and integration with other Google and external services.
- It can be used to extend functionality within G Suite editors like Sheets, Docs and Slides through add-ons, or to build standalone web apps and microservices.
- Examples demonstrate how to access APIs to integrate with services like Google Maps, Gmail, Calendar and Natural Language, as well as build bots for Hangouts Chat.
- The document also shows how Apps Script can be used to "glue" together Google Cloud Platform
The document provides an overview of a presentation about Google Cloud developer tools and an easier path to machine learning. It introduces the speaker and their background and experience. It then outlines the agenda which includes introductions to machine learning and Google Cloud, Google APIs, Cloud ML APIs, and other APIs to consider. It provides examples of using various Cloud ML APIs like Vision, Natural Language, and Speech for tasks like image labeling, text analysis, and speech recognition. The goal is to demonstrate how APIs powered by machine learning can help ease the burden of learning machine learning by allowing users to leverage pre-built models if they can call APIs.
Software Engineering and Project Management - Introduction, Modeling Concepts...Prakhyath Rai
Introduction, Modeling Concepts and Class Modeling: What is Object orientation? What is OO development? OO Themes; Evidence for usefulness of OO development; OO modeling history. Modeling
as Design technique: Modeling, abstraction, The Three models. Class Modeling: Object and Class Concept, Link and associations concepts, Generalization and Inheritance, A sample class model, Navigation of class models, and UML diagrams
Building the Analysis Models: Requirement Analysis, Analysis Model Approaches, Data modeling Concepts, Object Oriented Analysis, Scenario-Based Modeling, Flow-Oriented Modeling, class Based Modeling, Creating a Behavioral Model.
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024Sinan KOZAK
Sinan from the Delivery Hero mobile infrastructure engineering team shares a deep dive into performance acceleration with Gradle build cache optimizations. Sinan shares their journey into solving complex build-cache problems that affect Gradle builds. By understanding the challenges and solutions found in our journey, we aim to demonstrate the possibilities for faster builds. The case study reveals how overlapping outputs and cache misconfigurations led to significant increases in build times, especially as the project scaled up with numerous modules using Paparazzi tests. The journey from diagnosing to defeating cache issues offers invaluable lessons on maintaining cache integrity without sacrificing functionality.
artificial intelligence and data science contents.pptxGauravCar
What is artificial intelligence? Artificial intelligence is the ability of a computer or computer-controlled robot to perform tasks that are commonly associated with the intellectual processes characteristic of humans, such as the ability to reason.
› ...
Artificial intelligence (AI) | Definitio
Applications of artificial Intelligence in Mechanical Engineering.pdfAtif Razi
Historically, mechanical engineering has relied heavily on human expertise and empirical methods to solve complex problems. With the introduction of computer-aided design (CAD) and finite element analysis (FEA), the field took its first steps towards digitization. These tools allowed engineers to simulate and analyze mechanical systems with greater accuracy and efficiency. However, the sheer volume of data generated by modern engineering systems and the increasing complexity of these systems have necessitated more advanced analytical tools, paving the way for AI.
AI offers the capability to process vast amounts of data, identify patterns, and make predictions with a level of speed and accuracy unattainable by traditional methods. This has profound implications for mechanical engineering, enabling more efficient design processes, predictive maintenance strategies, and optimized manufacturing operations. AI-driven tools can learn from historical data, adapt to new information, and continuously improve their performance, making them invaluable in tackling the multifaceted challenges of modern mechanical engineering.
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
1. Build with all of
Google Cloud
Wesley Chun
Developer Advocate, Google
Adjunct CS Faculty, Foothill College
G Suite Dev Show
goo.gl/JpBQ40
About the speaker
● Developer Advocate, Google Cloud
● Mission: enable current and future developers to be successful using
Google Cloud and other Google developer tools, APIs, and platforms
● Videos: host of the G Suite Dev Show on YouTube
● Blogs: developers.googleblog.com &
gsuite-developers.googleblog.com
● Twitters: @wescpy, @GCPcloud, @GoogleDevs, @GSuiteDevs
● Background
● Software engineer & architect for 20+ years
● One of the original Yahoo!Mail engineers
● Author of bestselling "Core Python" books (corepython.com)
● Teacher and technical instructor since 1983 (all ages)
● Fellow of the Python Software Foundation
● AB Mathematics & CMP Music, UC Berkeley; MSCS UC Santa Barbara
2. Agenda and Why
● Not enough cloud computing in engineering curriculum
● Need to prep next-generation cloud-ready workforce
● Introduction to cloud computing
● Introduction to Google Cloud
● Run your code on Google Cloud serverless
● Build with all of Google Cloud (inspiration)
● Resources and summary
Cloud computing overview
All you need to know about the cloud1
3. What is Cloud Computing?
spar
Google Compute Engine, Google Cloud Storage
AWS EC2 & S3; Rackspace; Joyent
Cloud service levels/"pillars"
SaaS
Software as a Service
PaaS
Platform as a Service
IaaS
Infrastructure as a Service
Google BigQuery, Cloud SQL,
Cloud Datastore, NL, Vision, Pub/Sub
AWS Kinesis, RDS; Windows Azure SQL Database
Google Apps Script, App Maker
Salesforce1/force.com
G Suite (Google Apps)
Yahoo!Mail, Hotmail, Salesforce, Netsuite
Google App Engine, Cloud Functions
Heroku, Cloud Foundry, Engine Yard, AWS Lambda
4. Google Compute Engine, Google Cloud Storage
AWS EC2 & S3; Rackspace; Joyent
Outsourcing of apps (SaaS)
SaaS
Software as a Service
PaaS
Platform as a Service
IaaS
Infrastructure as a Service
Google BigQuery, Cloud SQL,
Cloud Datastore, NL, Vision, Pub/Sub
AWS Kinesis, RDS; Windows Azure SQL Database
Google Apps Script, App Maker
Salesforce1/force.com
Google App Engine, Cloud Functions
Heroku, Cloud Foundry, Engine Yard, AWS Lambda
G Suite (Google Apps)
Yahoo!Mail, Hotmail, Salesforce, Netsuite
Google Compute Engine, Google Cloud Storage
AWS EC2 & S3; Rackspace; Joyent
Outsourcing of hardware (IaaS)
SaaS
Software as a Service
PaaS
Platform as a Service
IaaS
Infrastructure as a Service
Google BigQuery, Cloud SQL,
Cloud Datastore, NL, Vision, Pub/Sub
AWS Kinesis, RDS; Windows Azure SQL Database
Google Apps Script, App Maker
Salesforce1/force.com
G Suite (Google Apps)
Yahoo!Mail, Hotmail, Salesforce, Netsuite
Google App Engine, Cloud Functions
Heroku, Cloud Foundry, Engine Yard, AWS Lambda
5. Google Compute Engine, Google Cloud Storage
AWS EC2 & S3; Rackspace; Joyent
Outsourcing of logic-hosting (PaaS)
SaaS
Software as a Service
PaaS
Platform as a Service
IaaS
Infrastructure as a Service
Google BigQuery, Cloud SQL,
Cloud Datastore, NL, Vision, Pub/Sub
AWS Kinesis, RDS; Windows Azure SQL Database
Google Apps Script, App Maker
Salesforce1/force.com
G Suite (Google Apps)
Yahoo!Mail, Hotmail, Salesforce, Netsuite
Google App Engine, Cloud Functions
Heroku, Cloud Foundry, Engine Yard, AWS Lambda
Google Compute Engine, Google Cloud Storage
AWS EC2 & S3; Rackspace; Joyent
IaaS/PaaS gray area (DataB/S/P-aaS?)
SaaS
Software as a Service
PaaS
Platform as a Service
IaaS
Infrastructure as a Service
Google Apps Script, App Maker
Salesforce1/force.com
G Suite (Google Apps)
Yahoo!Mail, Hotmail, Salesforce, Netsuite
Google App Engine, Cloud Functions
Heroku, Cloud Foundry, Engine Yard, AWS Lambda
Google BigQuery, Cloud SQL,
Cloud Datastore, NL, Vision, Pub/Sub
AWS Kinesis, RDS; Windows Azure SQL Database
6. Google Compute Engine, Google Cloud Storage
AWS EC2 & S3; Rackspace; Joyent
SaaS/PaaS gray area
SaaS
Software as a Service
PaaS
Platform as a Service
IaaS
Infrastructure as a Service
Google BigQuery, Cloud SQL,
Cloud Datastore, NL, Vision, Pub/Sub
AWS Kinesis, RDS; Windows Azure SQL Database
G Suite (Google Apps)
Yahoo!Mail, Hotmail, Salesforce, Netsuite
Google App Engine, Cloud Functions
Heroku, Cloud Foundry, Engine Yard, AWS Lambda
Google Apps Script, App Maker
Salesforce1/force.com
Summary of responsibility
SaaS
Software as a Service
Applications
Data
Runtime
Middleware
OS
Virtualization
Servers
Storage
Networking
Applications
Data
Runtime
Middleware
OS
Virtualization
Servers
Storage
Networking
IaaS
Infrastructure as a Service
Applications
Data
Runtime
Middleware
OS
Virtualization
Servers
Storage
Networking
PaaS
Platform as a Service
Managed by YOU Managed by cloud vendor
Applications
Data
Runtime
Middleware
OS
Virtualization
Servers
Storage
Networking
on-prem
all you, no cloud
7. Imagine you’re hosting a party...
Photo by Annie Spratt on Unsplash
On-Prem
(DIY)
IaaS
(Compute Engine)
PaaS
(App Engine)
SaaS
(Cloud Functions)
Pick theme
Plan party
Find space
Cook
On call
Pick theme
Plan party
Rent hall
Cook
On call
Pick theme
Plan party
Rent hall
Hire Caterer
Hire manager
Pick theme
Hire planner
Rent hall
Hire caterer
Hire manager
Theme -
Logistics -
Space -
Food -
Manage -
Spec/Reqs
Design app
Provision HW
Build & Serve app
Manage app
IaaS++
(Cloud Launcher)
Pick theme
Plan party
Rent hall
Hire Caterer
On call
9. Google Compute Engine, Google Cloud Storage
AWS EC2 & S3; Rackspace; Joyent
SaaS
Software as a Service
PaaS
Platform as a Service
IaaS
Infrastructure as a Service
Google Apps Script, App Maker
Salesforce1/force.com
G Suite (Google Apps)
Yahoo!Mail, Hotmail, Salesforce, Netsuite
Google App Engine, Cloud Functions
Heroku, Cloud Foundry, Engine Yard, AWS Lambda
Google BigQuery, Cloud SQL,
Cloud Datastore, NL, Vision, Pub/Sub
AWS Kinesis, RDS; Windows Azure SQL Database
Google Cloud Platform vs. G Suite
G Suite
APIs
GCP
APIs
Compute
(running code)
10. Running Code: Compute Engine
>
Google Compute Engine
cloud
Running Code: App Engine
Google App Engine
we
>
cloud
11. Running Code: Cloud Functions
Google Cloud Functions
cloud
Storage
(where to put your data)
15. Storing and Analyzing Data: BigQuery
Google BigQuery
cloud
Machine Learning: Cloud Vision
Google Cloud Vision
cloud
16. Machine Learning: Cloud Speech
Google Cloud Speech
cloud
Machine Learning: Cloud Natural Language
Google Cloud Natural Language
cloud
17. Machine Learning: Cloud Video Intelligence
Google Cloud Video Intelligence
cloud
Machine Learning: AutoML
AutoML:
cloud
18. G Suite
(collaborate & communicate)
G Suite: Gmail
Gmail API
read &
send messages labels
search manage settings
developers
19. G Suite: Google Drive
Drive API read
write permissions/sharing
import/export
developers
G Suite: Google Calendar
Calendar API
access modify create
events
developers
20. G Suite: Google Sheets
Sheets API
developers
G Suite: Google Slides
Slide API
create
manage
developers
21. What about Google Classroom?
● Originally announced May 2014
● LMS integrated with G Suite (Google Docs, Sheets, Slides, etc.)
● Helps teachers manage coursework, create classes, distribute
assignments, grade & send feedback, manage students &
guardians, manage discussion forums, give & grade quizzes
● Suitable for higher ed; more likely to be used in K-12
○ Higher ed generally already using dedicated LMS
● Resources
○ edu.google.com/products/classroom
○ blog.google/outreach-initiatives/education/previewing-new-classroom
○ developers.google.com/classroom
○ developers.google.com/apps-script/advanced/classroom
What about Google Course Kit?
● Originally announced Jul 2018
● More suitable in higher ed due to dedicated LMS
● Integrate your LMS with G Suite (Google Docs, Sheets, Slides, etc.)
○ Blackboard, Canvas, Moodle, Sakai supported
○ Integrate w/your LMS at no cost
○ Compliant with Learning Tools Interoperability (LTI) standard
● Create assignments & manage coursework from within your LMS
● Built-in grading tool; manage feedback in one central place
● Resources
○ edu.google.com/products/course-kit
○ blog.google/outreach-initiatives/education/introducing-course-kit-
new-ways-collaborate-g-suite-your-lms-designed-higher-ed
○ support.google.com/edu/coursekit/answer/9069054
○ support.google.com/edu/coursekit/answer/9069147
22. REST API examples
Short Python code snippets using GCP & G Suite APIs
API key (public data) vs. OAuth2 access (private data)
List (first 100) files/folders in Google Drive
from __future__ import print_function
from apiclient import discovery
from httplib2 import Http
from oauth2client import file, client, tools
SCOPES = 'https://www.googleapis.com/auth/drive.readonly.metadata'
store = file.Storage('storage.json')
creds = store.get()
if not creds or creds.invalid:
flow = client.flow_from_clientsecrets('client_secret.json', SCOPES)
creds = tools.run_flow(flow, store)
DRIVE = discovery.build('drive', 'v3', http=creds.authorize(Http()))
files = DRIVE.files().list().execute().get('files', [])
for f in files:
print(f['name'], f['mimeType'])
Listing your files
goo.gl/ZIgf8k
23. Back up your file archives
Write your own or see github.com/gsuitedevs/drive-zipextractor (JS)
Automate photo albums
OR
24. Import/Export: Customized reports, “database,” or both!
Try our Node.js customized reporting tool codelab:
g.co/codelabs/sheets
Migrate SQL data to a Sheet
# read SQL data then create new spreadsheet & add rows into it
FIELDS = ('ID', 'Customer Name', 'Product Code',
'Units Ordered', 'Unit Price', 'Status')
cxn = sqlite3.connect('db.sqlite')
cur = cxn.cursor()
rows = cur.execute('SELECT * FROM orders').fetchall()
cxn.close()
rows.insert(0, FIELDS)
DATA = {'properties': {'title': 'Customer orders'}}
SHEET_ID = SHEETS.spreadsheets().create(body=DATA,
fields='spreadsheetId').execute().get('spreadsheetId')
SHEETS.spreadsheets().values().update(spreadsheetId=SHEET_ID, range='A1',
body={'values': rows}, valueInputOption='RAW').execute()
Migrate SQL
data to Sheets
goo.gl/N1RPwC
28. [simple API/API key sample]
Search YouTube for videos
from __future__ import print_function
from apiclient import discovery
from settings import API_KEY
QUERY = 'python -snake'
trim = lambda x, ct: ('%s%s' % (x[:ct],
'...' if len(x)>ct else '')).ljust(ct+3)
print('n** Searching for %r videos...' % QUERY)
YOUTUBE = discovery.build('youtube', 'v3', developerKey=API_KEY)
res = YOUTUBE.search().list(q=QUERY, type='video',
part='id,snippet').execute().get('items', [])
for item in res:
print('http://youtu.be/%st%s' % (
trim(item['id']['videoId'], 24),
trim(item['snippet']['title'], 48)))
BigQuery: querying Shakespeare words
TITLE = "The top 10 most common words in all of Shakespeare's works"
QUERY = '''
SELECT LOWER(word) AS word, sum(word_count) AS count
FROM [bigquery-public-data:samples.shakespeare]
GROUP BY word ORDER BY count DESC LIMIT 10
'''
rsp = BQ.query(body={'query': QUERY}, projectId=PROJ_ID).execute()
print('n*** Results for %r:n' % TITLE)
for col in rsp['schema']['fields']: # HEADERS
print(col['name'].upper(), end='t')
print()
for row in rsp['rows']: # DATA
for col in row['f']:
print(col['v'], end='t')
print()
29. Top 10 most common Shakespeare words
$ python3 bq_shake.py
*** Results for "The most common words in all of Shakespeare's works":
WORD COUNT
the 29801
and 27529
i 21029
to 20957
of 18514
a 15370
you 14010
my 12936
in 11722
that 11519
[simple API/API key sample]
Simple sentiment & classification analysis
text = '''
Google, headquartered in Mountain View, unveiled the new Android
phone at the Consumer Electronics Show. Sundar Pichai said in
his keynote that users love their new Android phones.'''
data = {'type': 'PLAIN_TEXT', 'content': text}
NL = discovery.build('language', 'v1', developerKey=API_KEY)
sentiment = NL.documents().analyzeSentiment(
body={'document': data}).execute().get('documentSentiment')
print('TEXT:', text)
print('nSENTIMENT: score (%s), magnitude (%s)' % (
sentiment['score'], sentiment['magnitude']))
print('nCATEGORIES:')
categories = NL.documents().classifyText(
body={'document': data}).execute().get('categories')
for c in categories:
print ('* %s (%s)' % (c['name'][1:], c['confidence']))
PY
30. Sentiment & classification analysis output
$ python3 nl_sent_class.py
TEXT: Google, headquartered in Mountain View, unveiled the new Android
phone at the Consumer Electronics Show. Sundar Pichai said in
his keynote that users love their new Android phones.
SENTIMENT: score (0.3), magnitude (0.6)
CATEGORIES:
* Internet & Telecom (0.76)
* Computers & Electronics (0.64)
* News (0.56)
3
Run your code on
Google Cloud serverless
GCP: Google App Engine , Google Cloud Functions
G Suite: Google Apps Script , Google App Maker
31. Serverless: what & why
● What is serverless?
○ Misnomer: of course there's a server somewhere
○ You just don't have to worry about it!
○ Forbes (May 2018): Serverless... [helps] developers focus on writing code without having to
worry about infrastructure... servers (physical & virtual) completely abstracted away from the
user. [Developers] ... focused on solving business problems (e.g., faster app deployment)
● Why serverless?
○ Fastest growing segment of cloud... per 2 analysts*:
■ $1.9B (2016) and $4.25B (2018) ⇒ $7.7B (2021) and $14.93B (2023)
○ Unless focused on DevOps... VMs, networking, load balancing, web servers,
database servers, frontends/proxies, etc. less relevant for app-builders
○ What if you go viral? Autoscaling: your new best friend
○ What if you don't? Code not running? You're not paying. (No VMs to shutdown.)
* in USD; source: MarketsandMarkets™ & CB Insights (Aug 2018)
Google Compute Engine, Google Cloud Storage
AWS EC2 & S3; Rackspace; Joyent
SaaS
Software as a Service
PaaS
Platform as a Service
IaaS
Infrastructure as a Service
G Suite (Google Apps)
Yahoo!Mail, Hotmail, Salesforce, Netsuite
Google App Engine, Cloud Functions
Heroku, Cloud Foundry, Engine Yard, AWS Lambda
Google BigQuery, Cloud SQL,
Cloud Datastore, NL, Vision, Pub/Sub
AWS Kinesis, RDS; Windows Azure SQL Database
Serverless: PaaS-y compute/processing
Google Apps Script, App Maker
Salesforce1/force.com
33. Hello World (3 files)
app.yaml
runtime: python37
main.py
from flask import Flask
app = Flask(__name__)
@app.route('/')
def hello():
return 'Hello World!'
requirements.txt
Flask==1.0.2
App hosting plus a domain name!
$ gcloud app deploy
browser URL:
https://APP_ID.appspot.com
Ex: https://wescpy-apitest.appspot.com
Languages supported
Languages
● Python 2.7 & 3.6
● Node.js
● Ruby
● Java 8 / Servlet 3.1
● Jetty 9
● PHP 5.6, 7
● Go 1.8, 1.9, 1.10
● C#/.NET
● custom
Open Capabilities
Flexible Runtime
Languages
● Python 2.7, 3.7
● Java 7, 8
● PHP 5.5, 7.2
● Go 1.6, 1.8, 1.11
● Node.js 8
"Constrained" Capabilities
Incredibly rapid scale
Bold == 2nd generation
Standard Runtime
34. Google Cloud Functions
Function-hosting in the cloud
"Hello World" Python Cloud Function
main.py
def hello_world(request):
return 'Hello World!'
$ gcloud functions deploy hello --runtime python37 --trigger-http
cmd-line (curl):
curl -X POST https://[GCP_REGION]-[PROJECT_ID].cloudfunctions.net/hello
-H "Content-Type:application/json" --data '{"value": "123"}'
browser URL:
http://[GCP_REGION]-[PROJECT_ID].cloudfunctions.net/hello?value=123
Ex: https://us-central1-myproject-ccsc.cloudfunctions.net/hello
35. Google Cloud Functions
Languages Supported
● Node.js 6, 8 (JavaScript)
● Python 3.7
Deploying Cloud Functions
● Create locally then deploy on cmd-line OR
● Edit and deploy from developer web console
Triggering Cloud Functions (response to events)
● HTTP — via HTTP request
● Cloud Storage — bucket object/metadata CRUD
● Cloud Pub/Sub — new message
● Firebase (DB, Storage, Analytics, Auth)
Google Apps Script (and App Maker)
Customized JS runtime for G Suite automation, extension, and integration
37. What can you do with this?
Accessing maps from
spreadsheets?!?
goo.gl/oAzBN9
This… with help from Google Maps & Gmail
function sendMap() {
var sheet = SpreadsheetApp.getActiveSheet();
var address = sheet.getRange("A2").getValue();
var map = Maps.newStaticMap().addMarker(address);
MailApp.sendEmail(EMAIL, "Map", map.getMapUrl());
}
JS
39. var NAME = "My favorite images";
var deck = SlidesApp.getActivePresentation();
function addImageSlide(link, index) {
var slide = deck.appendSlide(SlidesApp.PredefinedLayout.BLANK);
var image = slide.insertImage(link);
}
function main() {
var images = [
"http://www.google.com/services/images/phone-animation-results_2x.png",
"http://www.google.com/services/images/section-work-card-img_2x.jpg",
"http://gsuite.google.com/img/icons/product-lockup.png",
"http://gsuite.google.com/img/home-hero_2x.jpg",
];
var [title, subtitle] = deck.getSlides()[0].getPageElements();
title.asShape().getText().setText(NAME);
subtitle.asShape().getText().setText("Google Apps ScriptnSlides Service demo");
images.forEach(addImageSlide);
}
Introducing
Slides Add-ons
goo.gl/sYL5AM
Generating Google Slides from images
Gmail
Add-ons
● Expense reports
● Can't we do them
without leaving Gmail?
● On Web AND mobile?
40. ● Expense report app
● Process in Gmail…
● One place to do your
expense report
Gmail Add-ons
Expediting expense
reports
goo.gl/KUVCDu
● Not just for conversations
● Create microservice utilities
● Build chat bots to...
○ Automate workflows
○ Query for information
○ Other heavy-lifting
Hangouts Chat bots
(bot framework and API)
41. function onMessage(e) {
return createMessage(e.user.displayName, 0);
}
function onCardClick(e) {
// Create a new vote card when 'NEW' button is clicked.
if (e.action.actionMethodName === 'newvote') {
return createMessage(e.user.displayName, 0);
}
// Updates the card in-place when '+1' or '-1' button is clicked.
var voteCount = +e.action.parameters[0].value;
e.action.actionMethodName === 'upvote' ? ++voteCount : --voteCount;
return createMessage(e.user.displayName, voteCount, true);
}
Simple vote bot
Hangouts Chat bots
goo.gl/jt3FqK
● Low-code assistive
development
environment
● Go from idea to app
in minutes
● Drag-n-drop
app building
● Generates Apps
Script code
Google App Maker
developers.google.com/appmaker
50. Supercharge G Suite with GCP
G Suite GCP
BigQuery
Apps Script
Slides Sheets
Application
request
Big data
analytics
App summary
● Leverage GCP from the G Suite world
● Google BigQuery for data analysis
● Build the final mile with G Suite
● Driven by Google Apps Script
● Google Sheets for visualization
● Google Slides for presentable results
● "Glued" together w/G Suite serverless
● Build this app (codelab)
● g.co/codelabs/bigquery-sheets-slides
● Application source code
● github.com/googlecodelabs/bigquery-sheets-slides
● Presented at Google Cloud NEXT (Jul 2018)
● cloud.withgoogle.com/next18/sf/sessions/session/156878
51. Online resources & summary
What's available for students & educators?5
Session Summary
● Why go cloud?
○ Cloud computing has taken the world by storm
○ You're behind if you're not already using it… it's not too late!
● Google Cloud and why serverless?
○ Many features: compute, storage, AI/ML, NW, data processing, etc.
○ Serverless lets users focus on just their logic (apps or functions)
○ Interesting possibilities using both platforms (GCP + G Suite)
52. References
● G Suite and Google Apps Script documentation
○ developers.google.com/gsuite
○ developers.google.com/apps-script
● GCP docs source code (i.e., App Engine & Cloud Functions quickstarts)
○ github.com/GoogleCloudPlatform/python-docs-samples
○ github.com/GoogleCloudPlatform/nodejs-docs-samples
● Inspirational demo apps' resources
○ cloud.withgoogle.com/next18/sf/sessions/session/156878
○ cloud.google.com/blog/products/application-development/
adding-custom-intelligence-to-gmail-with-serverless-on-gcp
○ bit.ly/2OcptaG
Learning resources
● Codelabs: self-paced hands-on tutorials
○ Google codelabs: need a Gmail account, always free
■ g.co/codelabs/cloud
○ Qwiklabs codelabs: don't need a Gmail acct; typically not free
■ google.qwiklabs.com
■ Individuals can request 200 more credits; 5000 credits for use in courses
● Official GCP docs: cloud.google.com
○ Recommended: Getting Started, Cloud Console, Cloud Shell, Cloud SDK, GCP
Free Tier (need a credit card), Community
● YouTube video series: youtube.com/GoogleCloud
○ Recommended: Cloud Minute shorts & Cloud NEXT videos
○ G Suite Dev Show: goo.gl/JpBQ40
53. Resources for Universities
● Education grant program
○ Teaching grants
■ $50USD for students
■ $100USD for faculty & TAs for courses
■ You'll barely use any of it… key: no need to give Google a credit card
○ Research grants
■ Larger amounts, granted for longer period of time
○ Turnaround time: 5-7 business days
● Teacher center
○ teachercenter.withgoogle.com/gcp
○ Apply here for education grants
○ Apply here for Qwiklabs credits
Thank you! Questions?
Wesley Chun
wescpy@gmail.com
@wescpy