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.
The document discusses exploiting identity and access management (IAM) in Google Cloud Platform (GCP). It begins with an introduction of the presenter and agenda. It then covers the key concepts of IAM in GCP, including role types, VPC service controls to control data flows, and access context manager. A deep dive on service accounts explains what they are, how bindings work, and the risk of impersonating accounts. The demo illustrates how a stolen credential could enable access to resources via service account impersonation. Key takeaways recommend restricting elevated service accounts, binding permissions specifically, avoiding default accounts and primitive roles.
Cloud computing is the delivery of computing resources like servers, storage, databases, and software over the Internet. There are different types of cloud including public, private, and hybrid clouds. Google Cloud Platform (GCP) provides various computing, storage, networking, security, and other services to users. GCP offers products and services for compute, storage, networking, security, big data, machine learning, and management tools to build solutions in the cloud. Some advantages of GCP include flexible billing, fast scaling, global datacenter network, and petabyte data processing capabilities.
Presentation for Introduction to Google Cloud Platform. This PPT provides basic understanding for services provided by Google Cloud Platform like Compute, Storage, VPC, IAM.
The eBook is a comprehensive checklist to get started with planning your Enterprise Cloud Strategy. A closer look at the evolution of cloud computing and its future prospects. Understand exactly how cloud can revolutionize your business.
An introduction to the future of cloud in terms of DBaaS, Big Data Analytics & Machine Learning.
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.
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.
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
Google Cloud Platform itself has been on a very rapid rise over the past few years. It has a lot of advantages over AWS or Microsoft Azure. In this slideshow, you can learn more about these top advantages. For more details, you can also read this post https://kinsta.com/blog/google-cloud-hosting/
The document discusses exploiting identity and access management (IAM) in Google Cloud Platform (GCP). It begins with an introduction of the presenter and agenda. It then covers the key concepts of IAM in GCP, including role types, VPC service controls to control data flows, and access context manager. A deep dive on service accounts explains what they are, how bindings work, and the risk of impersonating accounts. The demo illustrates how a stolen credential could enable access to resources via service account impersonation. Key takeaways recommend restricting elevated service accounts, binding permissions specifically, avoiding default accounts and primitive roles.
Cloud computing is the delivery of computing resources like servers, storage, databases, and software over the Internet. There are different types of cloud including public, private, and hybrid clouds. Google Cloud Platform (GCP) provides various computing, storage, networking, security, and other services to users. GCP offers products and services for compute, storage, networking, security, big data, machine learning, and management tools to build solutions in the cloud. Some advantages of GCP include flexible billing, fast scaling, global datacenter network, and petabyte data processing capabilities.
Presentation for Introduction to Google Cloud Platform. This PPT provides basic understanding for services provided by Google Cloud Platform like Compute, Storage, VPC, IAM.
The eBook is a comprehensive checklist to get started with planning your Enterprise Cloud Strategy. A closer look at the evolution of cloud computing and its future prospects. Understand exactly how cloud can revolutionize your business.
An introduction to the future of cloud in terms of DBaaS, Big Data Analytics & Machine Learning.
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.
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.
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
Google Cloud Platform itself has been on a very rapid rise over the past few years. It has a lot of advantages over AWS or Microsoft Azure. In this slideshow, you can learn more about these top advantages. For more details, you can also read this post https://kinsta.com/blog/google-cloud-hosting/
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.
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.
Getting started with GCP ( Google Cloud Platform)bigdata trunk
This document provides an overview and introduction to Google Cloud Platform (GCP). It begins with introductions and an agenda. It then discusses cloud computing concepts like deployment models and service models. It provides details on specific GCP computing, storage, machine learning, and other services. It describes how to set up Qwiklabs to do hands-on labs with GCP. Finally, it discusses next steps like training and certification for expanding GCP knowledge.
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
Google Cloud Platform & rockPlace Big Data Event-Mar.31.2016Chris Jang
This document discusses Google Cloud Platform and its data and analytics capabilities. It begins by explaining the evolution of cloud computing models from virtualized data centers to true on-demand cloud services. It then highlights some of Google Cloud Platform's key differentiators like true cloud economics, future-proof infrastructure, access to innovation, and Google-grade security. The document provides overviews of Google Cloud Platform's storage, database, big data, and machine learning offerings and common use cases for each. It also showcases some of Google's innovations in data analytics and machine learning technologies.
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)
This document provides an overview of cloud computing and Google Cloud Platform (GCP). It defines cloud computing, describes the key facets of cloud including ubiquity, scalability, and intelligence. It introduces several GCP services for computing, databases, data analytics, networking, and security. It discusses the shared responsibility model and recommends learning computer science fundamentals before focusing on specific cloud providers. Training resources for GCP certifications are also listed.
The document discusses Big Data challenges at Dyno including having a multi-terabyte data warehouse with over 100 GB of new raw data daily from 65 online and unlimited offline data sources, facing daily data quality problems, and needing to derive user interests and intentions from user information, behavior, and other data while managing a high performance and cost effective system. It also advertises job openings at Dyno for frontend and backend developers.
Cloud Computing: Making the right choiceIndicThreads
Session Presented @IndicThreads Cloud Computing Conference, Pune, India ( http://u10.indicthreads.com )
------------
The concept of cloud computing is quickly scaling the chasm between hype and reality. Cloud Computing is rapidly becoming popular amongst enterprises that realize the benefits of shared infrastructure, lowered costs and minimal management overheads. But not all organizations and applications may benefit from a cloud computing platform. A legacy application ported in a native fashion to a cloud computing platform may not utilize any of the platform’s USPs at all. More importantly, wrong choice of platform can be disastrous. Deciding the optimal cloud vendor or platform for your requirements is a complex task.
Consider the plethora of choices available in the world of cloud computing:
* Public Cloud or Private Cloud or Hybrid Cloud
* Infrastructure-as-a-Service (IaaS): Amazon AWS, Rackspace Cloud, GoGrid, Terremark,
* Platform-as-a-Service (PaaS): Google AppEngine, Microsoft Azure, Heroku
* Software-as-a-Service (SaaS): Salesforce, Netsuite, Google Apps, saas.com
* Should you use IaaS, PaaS or SaaS for your application?
* Which cloud database fits your application? SimpleDB, SQL, RDS, Hadoop?
We will discuss the various business and technology factors to consider, while choosing a cloud vendor. We will explore the pros and cons of various cloud vendors and their offerings. Lastly, we will also discuss some real-life use-cases of applications and servers being migrated to cloud computing and what factors led to selection of a particular cloud vendor.
Takeaways from the session
This talk would serve as an introduction to a wide variety of cloud computing platforms. The audience would be able to answer questions like: “What options are available for cloud computing?”, “What are their pros and cons?”, “Should I consider migrating my application or server to the cloud?”, “Should I use IaaS, PaaS or SaaS?”, “Which is the best cloud vendor for my use-case?”
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.
Introduction to Google Cloud Platform (GCP) | Google Cloud Tutorial for Begin...Edureka!
(Google Cloud Certification Training - Cloud Architect: edureka.co/google-cloud-architect-certification-training)
This Edureka tutorial will provide you with a detailed introduction to Google Cloud Platform and it's various Cloud Services Services. Learn why GCP is preferred over other cloud Providers and also learn about the different Zones and Regions where the servers are hosted, with a great demo.
Google Cloud Platform for the EnterpriseVMware Tanzu
SpringOne Platform 2016
Speakers: Jay Marshall; Principal Strategic Advisor, Google. Vic Iglesias; Solutions Architect, Google.
Whether you are running Spring Apps on Tomcat or Spring Boot on Cloud Foundry, Google Cloud Platform allows you to deploy all of your applications on the same global infrastructure that allows Google to return billions of search results in milliseconds, serve six billion hours of YouTube video per month, and provide storage for almost a billion Gmail users. Join the Google team as they illustrate how Google's cloud was built for the enterprise.
Google Cloud Platform Tutorial | GCP Fundamentals | EdurekaEdureka!
( Google Cloud Certification Training - Cloud Architect: https://www.edureka.co/google-cloud-a... ) This Tutorial on Google Cloud Platform will provide you a detailed introduction to GCP and it's Cloud Services Services. Learn why GCP is preferred over other cloud Providers and also learn about the various Zones and Regions where the servers are hosted.
Google Cloud Dataflow is a unified streaming and batch data processing service that allows users to set up pipelines to process data in various patterns. It features both horizontal and vertical autoscaling, real-time monitoring, and integration with other frameworks. Getting started involves choosing a programming model like Java, Python, or SQL and running sample pipelines locally or on the Cloud Dataflow service. Use cases include stream analytics, real-time AI, log and sensor data processing. The documentation provides more in-depth information on features and usage.
Google Cloud Platform provides cloud computing services such as compute power, database storage, applications, and other IT services via remote servers accessed over the internet. It launched services starting in 2008 and has grown to include compute engine, storage, networking, databases, machine learning, and more. Pricing is based on usage with free tiers and discounts for heavy usage to reduce costs compared to maintaining own hardware.
This document discusses Google Cloud Platform tools for big data and machine learning. It provides an overview of BigQuery for cloud data warehousing and big data analytics. It also covers managed Hadoop and data processing tools like Cloud Composer, Dataproc, and Dataflow. Finally, it discusses Google's machine learning tools ranging from high-level APIs to Cloud ML Engine for building custom models and AutoML for automating the machine learning process.
The document discusses Google Cloud Platform and its capabilities for big data and analytics. It notes that Google Cloud Platform is built on Google's infrastructure which powers its own services and has 17 years of experience building cloud infrastructure. It then summarizes several key services including Compute Engine, App Engine, BigQuery, Cloud Dataflow, and Cloud Dataproc that can be used for infrastructure, platforms, software, as well as big data, analytics, and machine learning.
Google Cloud Platform: Prototype ->Production-> Planet scaleIdan Tohami
As one of Big Data’s Founding Fathers, Google explored the technological changes we faced over the past 10 years and present their solutions to the new data challenges within the Google Cloud ecosystem
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.
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.
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.
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.
Getting started with GCP ( Google Cloud Platform)bigdata trunk
This document provides an overview and introduction to Google Cloud Platform (GCP). It begins with introductions and an agenda. It then discusses cloud computing concepts like deployment models and service models. It provides details on specific GCP computing, storage, machine learning, and other services. It describes how to set up Qwiklabs to do hands-on labs with GCP. Finally, it discusses next steps like training and certification for expanding GCP knowledge.
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
Google Cloud Platform & rockPlace Big Data Event-Mar.31.2016Chris Jang
This document discusses Google Cloud Platform and its data and analytics capabilities. It begins by explaining the evolution of cloud computing models from virtualized data centers to true on-demand cloud services. It then highlights some of Google Cloud Platform's key differentiators like true cloud economics, future-proof infrastructure, access to innovation, and Google-grade security. The document provides overviews of Google Cloud Platform's storage, database, big data, and machine learning offerings and common use cases for each. It also showcases some of Google's innovations in data analytics and machine learning technologies.
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)
This document provides an overview of cloud computing and Google Cloud Platform (GCP). It defines cloud computing, describes the key facets of cloud including ubiquity, scalability, and intelligence. It introduces several GCP services for computing, databases, data analytics, networking, and security. It discusses the shared responsibility model and recommends learning computer science fundamentals before focusing on specific cloud providers. Training resources for GCP certifications are also listed.
The document discusses Big Data challenges at Dyno including having a multi-terabyte data warehouse with over 100 GB of new raw data daily from 65 online and unlimited offline data sources, facing daily data quality problems, and needing to derive user interests and intentions from user information, behavior, and other data while managing a high performance and cost effective system. It also advertises job openings at Dyno for frontend and backend developers.
Cloud Computing: Making the right choiceIndicThreads
Session Presented @IndicThreads Cloud Computing Conference, Pune, India ( http://u10.indicthreads.com )
------------
The concept of cloud computing is quickly scaling the chasm between hype and reality. Cloud Computing is rapidly becoming popular amongst enterprises that realize the benefits of shared infrastructure, lowered costs and minimal management overheads. But not all organizations and applications may benefit from a cloud computing platform. A legacy application ported in a native fashion to a cloud computing platform may not utilize any of the platform’s USPs at all. More importantly, wrong choice of platform can be disastrous. Deciding the optimal cloud vendor or platform for your requirements is a complex task.
Consider the plethora of choices available in the world of cloud computing:
* Public Cloud or Private Cloud or Hybrid Cloud
* Infrastructure-as-a-Service (IaaS): Amazon AWS, Rackspace Cloud, GoGrid, Terremark,
* Platform-as-a-Service (PaaS): Google AppEngine, Microsoft Azure, Heroku
* Software-as-a-Service (SaaS): Salesforce, Netsuite, Google Apps, saas.com
* Should you use IaaS, PaaS or SaaS for your application?
* Which cloud database fits your application? SimpleDB, SQL, RDS, Hadoop?
We will discuss the various business and technology factors to consider, while choosing a cloud vendor. We will explore the pros and cons of various cloud vendors and their offerings. Lastly, we will also discuss some real-life use-cases of applications and servers being migrated to cloud computing and what factors led to selection of a particular cloud vendor.
Takeaways from the session
This talk would serve as an introduction to a wide variety of cloud computing platforms. The audience would be able to answer questions like: “What options are available for cloud computing?”, “What are their pros and cons?”, “Should I consider migrating my application or server to the cloud?”, “Should I use IaaS, PaaS or SaaS?”, “Which is the best cloud vendor for my use-case?”
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.
Introduction to Google Cloud Platform (GCP) | Google Cloud Tutorial for Begin...Edureka!
(Google Cloud Certification Training - Cloud Architect: edureka.co/google-cloud-architect-certification-training)
This Edureka tutorial will provide you with a detailed introduction to Google Cloud Platform and it's various Cloud Services Services. Learn why GCP is preferred over other cloud Providers and also learn about the different Zones and Regions where the servers are hosted, with a great demo.
Google Cloud Platform for the EnterpriseVMware Tanzu
SpringOne Platform 2016
Speakers: Jay Marshall; Principal Strategic Advisor, Google. Vic Iglesias; Solutions Architect, Google.
Whether you are running Spring Apps on Tomcat or Spring Boot on Cloud Foundry, Google Cloud Platform allows you to deploy all of your applications on the same global infrastructure that allows Google to return billions of search results in milliseconds, serve six billion hours of YouTube video per month, and provide storage for almost a billion Gmail users. Join the Google team as they illustrate how Google's cloud was built for the enterprise.
Google Cloud Platform Tutorial | GCP Fundamentals | EdurekaEdureka!
( Google Cloud Certification Training - Cloud Architect: https://www.edureka.co/google-cloud-a... ) This Tutorial on Google Cloud Platform will provide you a detailed introduction to GCP and it's Cloud Services Services. Learn why GCP is preferred over other cloud Providers and also learn about the various Zones and Regions where the servers are hosted.
Google Cloud Dataflow is a unified streaming and batch data processing service that allows users to set up pipelines to process data in various patterns. It features both horizontal and vertical autoscaling, real-time monitoring, and integration with other frameworks. Getting started involves choosing a programming model like Java, Python, or SQL and running sample pipelines locally or on the Cloud Dataflow service. Use cases include stream analytics, real-time AI, log and sensor data processing. The documentation provides more in-depth information on features and usage.
Google Cloud Platform provides cloud computing services such as compute power, database storage, applications, and other IT services via remote servers accessed over the internet. It launched services starting in 2008 and has grown to include compute engine, storage, networking, databases, machine learning, and more. Pricing is based on usage with free tiers and discounts for heavy usage to reduce costs compared to maintaining own hardware.
This document discusses Google Cloud Platform tools for big data and machine learning. It provides an overview of BigQuery for cloud data warehousing and big data analytics. It also covers managed Hadoop and data processing tools like Cloud Composer, Dataproc, and Dataflow. Finally, it discusses Google's machine learning tools ranging from high-level APIs to Cloud ML Engine for building custom models and AutoML for automating the machine learning process.
The document discusses Google Cloud Platform and its capabilities for big data and analytics. It notes that Google Cloud Platform is built on Google's infrastructure which powers its own services and has 17 years of experience building cloud infrastructure. It then summarizes several key services including Compute Engine, App Engine, BigQuery, Cloud Dataflow, and Cloud Dataproc that can be used for infrastructure, platforms, software, as well as big data, analytics, and machine learning.
Google Cloud Platform: Prototype ->Production-> Planet scaleIdan Tohami
As one of Big Data’s Founding Fathers, Google explored the technological changes we faced over the past 10 years and present their solutions to the new data challenges within the Google Cloud ecosystem
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.
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.
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
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. .
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.
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!
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.
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.
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.
- 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.
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!!
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.
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 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.
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.
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.
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 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.
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.
Similar a Cloud computing overview & Technical intro to Google Cloud (20)
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)
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.
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.
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.
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.
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!
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.
Skybuffer AI: Advanced Conversational and Generative AI Solution on SAP Busin...Tatiana Kojar
Skybuffer AI, built on the robust SAP Business Technology Platform (SAP BTP), is the latest and most advanced version of our AI development, reaffirming our commitment to delivering top-tier AI solutions. Skybuffer AI harnesses all the innovative capabilities of the SAP BTP in the AI domain, from Conversational AI to cutting-edge Generative AI and Retrieval-Augmented Generation (RAG). It also helps SAP customers safeguard their investments into SAP Conversational AI and ensure a seamless, one-click transition to SAP Business AI.
With Skybuffer AI, various AI models can be integrated into a single communication channel such as Microsoft Teams. This integration empowers business users with insights drawn from SAP backend systems, enterprise documents, and the expansive knowledge of Generative AI. And the best part of it is that it is all managed through our intuitive no-code Action Server interface, requiring no extensive coding knowledge and making the advanced AI accessible to more users.
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
Skybuffer SAM4U tool for SAP license adoptionTatiana Kojar
Manage and optimize your license adoption and consumption with SAM4U, an SAP free customer software asset management tool.
SAM4U, an SAP complimentary software asset management tool for customers, delivers a detailed and well-structured overview of license inventory and usage with a user-friendly interface. We offer a hosted, cost-effective, and performance-optimized SAM4U setup in the Skybuffer Cloud environment. You retain ownership of the system and data, while we manage the ABAP 7.58 infrastructure, ensuring fixed Total Cost of Ownership (TCO) and exceptional services through the SAP Fiori interface.
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
Taking AI to the Next Level in Manufacturing.pdfssuserfac0301
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
Generating privacy-protected synthetic data using Secludy and MilvusZilliz
During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
Trusted Execution Environment for Decentralized Process MiningLucaBarbaro3
Presentation of the paper "Trusted Execution Environment for Decentralized Process Mining" given during the CAiSE 2024 Conference in Cyprus on June 7, 2024.
Dive into the realm of operating systems (OS) with Pravash Chandra Das, a seasoned Digital Forensic Analyst, as your guide. 🚀 This comprehensive presentation illuminates the core concepts, types, and evolution of OS, essential for understanding modern computing landscapes.
Beginning with the foundational definition, Das clarifies the pivotal role of OS as system software orchestrating hardware resources, software applications, and user interactions. Through succinct descriptions, he delineates the diverse types of OS, from single-user, single-task environments like early MS-DOS iterations, to multi-user, multi-tasking systems exemplified by modern Linux distributions.
Crucial components like the kernel and shell are dissected, highlighting their indispensable functions in resource management and user interface interaction. Das elucidates how the kernel acts as the central nervous system, orchestrating process scheduling, memory allocation, and device management. Meanwhile, the shell serves as the gateway for user commands, bridging the gap between human input and machine execution. 💻
The narrative then shifts to a captivating exploration of prominent desktop OSs, Windows, macOS, and Linux. Windows, with its globally ubiquitous presence and user-friendly interface, emerges as a cornerstone in personal computing history. macOS, lauded for its sleek design and seamless integration with Apple's ecosystem, stands as a beacon of stability and creativity. Linux, an open-source marvel, offers unparalleled flexibility and security, revolutionizing the computing landscape. 🖥️
Moving to the realm of mobile devices, Das unravels the dominance of Android and iOS. Android's open-source ethos fosters a vibrant ecosystem of customization and innovation, while iOS boasts a seamless user experience and robust security infrastructure. Meanwhile, discontinued platforms like Symbian and Palm OS evoke nostalgia for their pioneering roles in the smartphone revolution.
The journey concludes with a reflection on the ever-evolving landscape of OS, underscored by the emergence of real-time operating systems (RTOS) and the persistent quest for innovation and efficiency. As technology continues to shape our world, understanding the foundations and evolution of operating systems remains paramount. Join Pravash Chandra Das on this illuminating journey through the heart of computing. 🌟
Introduction of Cybersecurity with OSS at Code Europe 2024Hiroshi SHIBATA
I develop the Ruby programming language, RubyGems, and Bundler, which are package managers for Ruby. Today, I will introduce how to enhance the security of your application using open-source software (OSS) examples from Ruby and RubyGems.
The first topic is CVE (Common Vulnerabilities and Exposures). I have published CVEs many times. But what exactly is a CVE? I'll provide a basic understanding of CVEs and explain how to detect and handle vulnerabilities in OSS.
Next, let's discuss package managers. Package managers play a critical role in the OSS ecosystem. I'll explain how to manage library dependencies in your application.
I'll share insights into how the Ruby and RubyGems core team works to keep our ecosystem safe. By the end of this talk, you'll have a better understanding of how to safeguard your code.
Main news related to the CCS TSI 2023 (2023/1695)Jakub Marek
An English 🇬🇧 translation of a presentation to the speech I gave about the main changes brought by CCS TSI 2023 at the biggest Czech conference on Communications and signalling systems on Railways, which was held in Clarion Hotel Olomouc from 7th to 9th November 2023 (konferenceszt.cz). Attended by around 500 participants and 200 on-line followers.
The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
The videorecording (in Czech) from the presentation is available here: https://youtu.be/WzjJWm4IyPk?si=SImb06tuXGb30BEH .
Best 20 SEO Techniques To Improve Website Visibility In SERPPixlogix Infotech
Boost your website's visibility with proven SEO techniques! Our latest blog dives into essential strategies to enhance your online presence, increase traffic, and rank higher on search engines. From keyword optimization to quality content creation, learn how to make your site stand out in the crowded digital landscape. Discover actionable tips and expert insights to elevate your SEO game.
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
Programming Foundation Models with DSPy - Meetup SlidesZilliz
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
5th LF Energy Power Grid Model Meet-up SlidesDanBrown980551
5th Power Grid Model Meet-up
It is with great pleasure that we extend to you an invitation to the 5th Power Grid Model Meet-up, scheduled for 6th June 2024. This event will adopt a hybrid format, allowing participants to join us either through an online Mircosoft Teams session or in person at TU/e located at Den Dolech 2, Eindhoven, Netherlands. The meet-up will be hosted by Eindhoven University of Technology (TU/e), a research university specializing in engineering science & technology.
Power Grid Model
The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services.
Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.
Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization.
What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
-Insightful presentations covering two practical applications of the Power Grid Model.
-An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024.
-An interactive brainstorming session to discuss and propose new feature requests.
-An opportunity to connect with fellow Power Grid Model enthusiasts and users.
Cloud computing overview & Technical intro to Google Cloud
1. Cloud computing overview &
Google Cloud technical intro
Wesley Chun
Developer Advocate, Google
G Suite Dev Show
goo.gl/JpBQ40
About the speaker
Developer Advocate, Google Cloud
● Mission: enable current and future
developers everywhere to be
successful using Google Cloud and
other Google developer tools & APIs
● Videos: host of the G Suite Dev Show
on YouTube
● Blogs: developers.googleblog.com &
gsuite-developers.googleblog.com
● Twitters: @wescpy, @GoogleDevs,
@GSuiteDevs
Previous experience / background
● Software engineer & architect for 20+ years
● One of the original Yahoo!Mail engineers
● Author of bestselling "Core Python" books
(corepython.com)
● Technical trainer, teacher, instructor since
1983 (Computer Science, C, Linux, Python)
● Fellow of the Python Software Foundation
● AB (Math/CS) & CMP (Music/Piano), UC
Berkeley and MSCS, UC Santa Barbara
● Adjunct Computer Science Faculty, Foothill
College (Silicon Valley)
2. Why and Agenda
● Cloud has taken industry by storm (all?)
● Not enough developer awareness of cloud computing
● Need to prep next-generation cloud-ready workforce
● Challenging to keep up with latest industry trends
1
Cloud computing
overview
2
Google Cloud
(GCP + G Suite)
3
Serverless
platforms
4
Inspirational
Ideas
5
Summary &
wrap-up
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, Docker
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, Docker
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, Docker
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, Docker
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, Docker
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, Docker
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
8. G Suite APIs
Top-level documentation and comprehensive developers
overview video at developers.google.com/gsuite
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, Docker
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
firebase
Running Code: Cloud Run
Google Cloud Run
cloud
12. Storage
(where to put your data)
Storing Data: Cloud Storage & Cloud Filestore
cloud
cloud
15. Machine Learning
(analyze your data)
Machine Learning… where are you?
● Aware: read up on ML its ability to help derive
insights based on a massive amount of data
● User: awareness, but putting ML to use by
using existing tools or calling APIs; requires
ZERO prior knowledge of ML
● Scientist: know enough about ML, have the
technical skills to build, train, and deploy
predictive models & make new predictions
16. Full Spectrum of AI & ML Offerings
App Developer Data Scientist ML Scientist/Researcher
Use pre-built models Use/extend OSS SDK
ML EngineAuto ML
Build custom models
ML APIs
Storing and Analyzing Data: BigQuery
Google BigQuery
cloud
17. Machine Learning: Cloud Natural Language
Google Cloud Natural Language API
cloud
Machine Learning: Cloud Vision & Video Intelligence
Google Cloud Vision & Video
Intelligence APIs
cloud
cloud
19. Machine Learning: Cloud ML Engine
Google Cloud Machine Learning Engine
cloud
Data transformation/ETL
● Open sourced as Apache
Beam (supports Apache
Spark and Flink)
20. G Suite
(collaborate & communicate)
G Suite: Gmail
Gmail API
read &
send messages labels
search manage settings
developers
21. G Suite: Google Calendar
Calendar API
access modify create
events
developers
G Suite: Google Docs & Slides
Docs & Slides APIs
developers
developers
22. G Suite: Google Sheets
Sheets API
developers
G Suite: Google Drive
Drive API read
write permissions/sharing
import/export
developers
23. REST API examples
Short Python code snippets using GCP & G Suite APIs
API key (public data) vs. OAuth2 access (private data)
25. The first word on Security
Authentication ("authn") vs authorization ("authz")
● authn: you are who you say you are
○ login & passwd
○ handprint authentication
○ retina scan
● authz: okay, you are who you say you are, but can you haz data?
○ OAuth2 - mostly authz, but some authn
○ Mostly about 3rd-party access to data
○ Users must give YOUR code access to THEIR data
○ Most of the time when you see "auth", it refers to authz
● Some refer to this as "consent" vs. "credentials…" which is which?
Cloud/GCP console
console.cloud.google.com
● Hub of all developer activity
● Applications == projects
○ New project for new apps
○ Projects have a billing acct
● Manage billing accounts
○ Financial instrument required
○ Personal or corporate credit cards,
Free Trial, and education grants
● Access GCP product settings
● Manage users & security
● Manage APIs in devconsole
26. ● View application statistics
● En-/disable Google APIs
● Obtain application credentials
Using Google APIs
goo.gl/RbyTFD
API manager aka Developers Console (devconsole)
console.developers.google.com
OAuth2 or
API key
HTTP-based REST APIs 1
HTTP
2
Google APIs request-response workflow
● Application makes request
● Request received by service
● Process data, return response
● Results sent to application
(typical client-server model)
27. Google APIs client
libraries for many
languages; demos in
developers.google.com/
api-client-library
SIMPLE
AUTHORIZED
Which do you choose?
28. List (first 100) files/folders in Google Drive
from __future__ import print_function
from googleapiclient import discovery
from httplib2 import Http
from oauth2client import file, client, tools
SCOPES = 'https://www.googleapis.com/auth/drive.metadata.readonly'
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
Try our Node.js customized reporting tool codelab:
g.co/codelabs/sheets
Why use the Sheets API?
data visualization
customized reports
Sheets as a data source
29. 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
Try our Node.js BigQuery GitHub license analyzer codelab:
g.co/codelabs/slides
Why use the Slides API?
data visualization
presentable reports
30. Try our Node.js Markdown-to-Google-Slides generator:
github.com/gsuitedevs/md2googleslides
Why use the Slides API?
customized presentations
Replace text & images from template deck
requests = [
# (global) search-and-replace text
{'replaceAllText': {
'findText': '{{TITLE}}',
'replaceText': 'Hello World!',
}},
# replace text-based image placeholders (global)
{'replaceAllShapesWithImage': {
'imageUrl': IMG_URL, # link to product logo
'replaceMethod': 'CENTER_INSIDE',
'containsText': {'text': '{{LOGO}}'},
}},
]
SLIDES.presentations().batchUpdate(body={'requests': requests},
presentationId=DECK_ID, fields='').execute()
Replacing text
and images
goo.gl/o6EFwk
31. +
Mail merge
=
Mail merge (template search & replace)
requests = [
# (global) search-and-replace text
{'replaceAllText': {
'containsText': {'text': '{{TITLE}}'},
'replaceText': 'Hello World!',
}},
]
DOCS.documents().batchUpdate(body={'requests': requests},
documentId=DOC_ID, fields='').execute()
Mail merge
goo.gle/2KrPNeG
32. 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()
Top 10 most common Shakespeare words
$ python 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
33. 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.'''
print('TEXT:', TEXT)
data = {'type': 'PLAIN_TEXT', 'content': TEXT}
NL = discovery.build('language', 'v1', developerKey=API_KEY)
# sentiment analysis
sent = NL.documents().analyzeSentiment(
body={'document': data}).execute().get('documentSentiment')
print('nSENTIMENT: score (%s), magnitude (%s)' % (sent['score'], sent['magnitude']))
# content classification
print('nCATEGORIES:')
cats = NL.documents().classifyText(body={'document': data}).execute().get('categories')
for cat in cats:
print('* %s (%s)' % (cat['name'][1:], cat['confidence']))
Simple sentiment & classification analysis
$ python nl_sent_simple.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)
34. Text-to-Speech: synthsizing audio text
# request body (with text body using 16-bit linear PCM audio encoding)
body = {
'input': {'text': text},
'voice': {
'languageCode': 'en-US',
'ssmlGender': 'FEMALE',
},
'audioConfig': {'audioEncoding': 'LINEAR16'},
}
# call Text-to-Speech API to synthesize text (write to text.wav file)
T2S = discovery.build('texttospeech', 'v1', developerKey=API_KEY)
audio = T2S.text().synthesize(body=body).execute().get('audioContent')
with open('text.wav', 'wb') as f:
f.write(base64.b64decode(audio))
Speech-to-Text: transcribing audio text
# request body (16-bit linear PCM audio content, i.e., from text.wav)
body = {
'audio': {'content': audio},
'config': {
'languageCode': 'en-US',
'encoding': 'LINEAR16',
},
}
# call Speech-to-Text API to recognize text
S2T = discovery.build('speech', 'v1', developerKey=API_KEY)
rsp = S2T.speech().recognize(
body=body).execute().get('results')[0]['alternatives'][0]
print('** %.2f%% confident of this transcript:n%r' % (
rsp['confidence']*100., rsp['transcript']))
35. Speech-to-Text: transcribing audio text
$ python s2t_demo.py
** 92.03% confident of this transcript:
'Google headquarters 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'
Video intelligence: make videos searchable
# request body (single payload, base64 binary video)
body = {
"inputContent": video,
"features": ['LABEL_DETECTION', 'SPEECH_TRANSCRIPTION'],
"videoContext": {"speechTranscriptionConfig": {"languageCode": 'en-US'}},
}
# perform video shot analysis followed by speech analysis
VINTEL = discovery.build('videointelligence', 'v1', developerKey=API_KEY)
resource = VINTEL.videos().annotate(body=body).execute().get('name')
while True:
results = VINTEL.operations().get(name=resource).execute()
if results.get('done'):
break
time.sleep(random.randrange(8)) # expo-backoff probably better
36. Video intelligence: make videos searchable
# display shot labels followed by speech transcription
for labels in results['response']['annotationResults']:
if 'shotLabelAnnotations' in labels:
print('n** Video shot analysis labeling')
for shot in labels['shotLabelAnnotations']:
seg = shot['segments'][0]
print(' - %s (%.2f%%)' % (
shot['entity']['description'], seg['confidence']*100.))
if 'speechTranscriptions' in labels:
print('** Speech transcription')
speech = labels['speechTranscriptions'][0]['alternatives'][0]
print(' - %r (%.2f%%)' % (
speech['transcript'], speech['confidence']*100.))
Video intelligence: make videos searchable
$ python3 vid_demo.py you-need-a-hug.mp4
** Video shot analysis labeling
- vacation (30.62%)
- fun (61.53%)
- interaction (38.93%)
- summer (57.10%)
** Speech transcription
- 'you need a hug come here' (79.27%)
37. Higher-level GCP SDK & API client libraries
1. Bad news: Just showed you the "harder
way" of using Google Cloud Platform APIs
2. Good news: it's even easier with the GCP
SDK and higher-level client libraries
3. Why (not)? Not all Google APIs have high-
level client libraries. Lower-level serves as
"LCD" for accessing more Google APIs
cloud.google.com/sdk
cloud.google.com/apis/docs
3
Run your code on Google
Cloud serverless
GCP: Google App Engine , Google Cloud Functions
G Suite: Google Apps Script , Google App Maker
38. Serverless: what & why
● What is serverless?
○ Misnomer
○ "No worries"
○ Developers focus on writing code & solving business problems*
● Why serverless?
○ Fastest growing segment of cloud... per analyst research*:
■ $1.9B (2016) and $4.25B (2018) ⇒ $7.7B (2021) and $14.93B (2023)
○ What if you go viral? Autoscaling: your new best friend
○ What if you don't? Code not running? You're not paying.
* in USD; source:Forbes (May 2018), 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, Docker
Serverless: PaaS-y compute/processing
Google Apps Script, App Maker
Salesforce1/force.com
39. Google App Engine
App-hosting in the cloud
Why does App Engine exist?
● Focus on app not DevOps
○ Web app
○ Mobile backend
○ Cloud service
● Enhance productivity
● Deploy globally
● Fully-managed
● Auto-scaling
● Pay-per-use
● Familiar languages
40. Hello World (3 files: Python "MVP")
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
Deploy:
$ gcloud app deploy
Access globally:
https://PROJECT_ID.appspot.com
Open source repo at
github.com/GoogleCloudPlatform/python-docs-samples/
tree/master/appengine/standard_python37/hello_world
Google Cloud Functions
Function-hosting in the cloud
41. Why does Cloud Functions exist?
● Don't have entire app?
○ No framework "overhead" (LAMP, MEAN...)
○ Deploy microservices
● Event-driven
○ Triggered via HTTP or background events
○ Auto-scaling & highly-available
○ Pay per use
● Familiar development environment
○ Cmd-line or developer console
● Cloud Functions for Firebase
○ Mobile app use-cases
● Available runtimes
○ JS/Node.js 6, 8, 10
○ Python 3.7
○ Go 1.11, 1.12
○ Java 8
main.py
def hello_world(request):
return 'Hello World!'
Deploy:
$ gcloud functions deploy hello --runtime python37 --trigger-http
Access globally (curl):
curl -X POST https://GCP_REGION-PROJECT_ID.cloudfunctions.net/hello
-H "Content-Type:application/json"
Access globally (browser):
GCP_REGION-PROJECT_ID.cloudfunctions.net/hello
Hello World (Python "MVP")
42. Google Apps Script
Customized JS runtime for automation, extension, and integration
with G Suite and other Google or external services
What can you do with this?
43. 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);
GmailApp.sendEmail('friend@example.com', 'Map',
'See below.', {attachments:[map]});
}
JS
Google Cloud Run
Container-hosting in the cloud
44. The rise of containers ● Any language
● Any library
● Any binary
● Ecosystem of base images
● Industry standard
“We can’t be locked in.”
“How can we use
existing binaries?”
“Why do I have to choose between
containers and serverless?”
“Can you support language _______ ?”
Serverless not accessible to everyone...
45. Code, build, deploy
.js .rb .go
.sh.py ...
● Any language, library, binary
○ HTTP port, stateless
● Bundle into container
○ Build w/Docker OR
○ Google Cloud Build
○ Image ⇒ Container Registry
● Deploy to Cloud Run (native or GKE)
StateHTTP
https://yourservice.run.app
Cloud Run
Fully serverless
No cluster to manage
Pay for what you use
Cloud Run on GKE
Serverless experience
Access custom nodes, GPUs, VPC
Simplicity of Cloud Run
With flexibility of GKE
Fully-managed Kubernetes cluster
Serverless containers, where you want them
Deploy to your
self-managed
Kubernetes cluster
Cloud Run compatible
With Knative open API
Runs on-prem or in other cloud on
Self-managed Kubernetes cluster
46. 4 All of Cloud (inspiration)
Build with both GCP tools and G Suite
Custom intelligence in Gmail
Analyze G Suite data with GCP
47. Gmail message processing with GCP
Gmail
Cloud
Pub/Sub
Cloud
Functions
Cloud
Vision
G Suite GCP
Star
message
Message
notification
Trigger
function
Extract
images
Categorize
images
48. Inbox augmented with Cloud Function
● Gmail API: sets up notification forwarding to Cloud Pub/Sub
● developers.google.com/gmail/api/guides/push
● Pub/Sub: triggers logic hosted by Cloud Functions
● cloud.google.com/functions/docs/calling/pubsub
● Cloud Functions: "orchestrator" accessing GCP APIs
● Combine all of the above to add custom intelligence to Gmail
● Deep dive code blog post
● cloud.google.com/blog/products/application-development/
adding-custom-intelligence-to-gmail-with-serverless-on-gcp
● Application source code
● github.com/GoogleCloudPlatform/cloud-functions-gmail-nodejs
App summary
49. Big data analysis to slide presentation
Access GCP tools from G Suite
52. Supercharge G Suite with GCP
G Suite GCP
BigQuery
Apps Script
Slides Sheets
Application
request
Big data
analytics
53. App summary
● Leverage GCP and build the "final mile" with G Suite
● Driven by Google Apps Script
● Google BigQuery for data analysis
● 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
● Video and blog post
● bit.ly/2OcptaG
● Application source code
● github.com/googlecodelabs/bigquery-sheets-slides
● Presented at Google Cloud NEXT (Jul 2018 [DEV229] & Apr 2019 [DEV212])
● cloud.withgoogle.com/next18/sf/sessions/session/156878
● cloud.withgoogle.com/next/sf/sessions?session=DEV212
Online resources & summary
What's available for students & educators?5
54. 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!
○ Help train the next generation cloud-ready workforce!
● 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)
References
● G Suite & GCP home pages & documentation
○ developers.google.com/gsuite
○ developers.google.com/apps-script
○ github.com/gsuitedevs
● Google Cloud Platform (GCP) documentation & open source repos
○ cloud.google.com/gcp
○ cloud.google.com/docs
○ github.com/GoogleCloudPlatform/{python,nodejs}-docs-samples
○ Know AWS? Compare w/GCP at: cloud.google.com/docs/compare/aws
● Google APIs Client Libraries (G Suite & GCP) & Google Cloud SDK (GCP-only)
○ developers.google.com/api-client-library
○ cloud.google.com/sdk
55. More references
● Relevant videos
○ goo.gl/RbyTFD (new Google APIs project setup)
○ goo.gl/KMfbeK (common Python OAuth2 boilerplate code review)
○ goo.gl/ZIgf8k (APIs intro codelab [Drive API])
● Relevant codelabs
○ g.co/codelabs/gsuite-apis-intro (Drive API)
○ g.co/codelabs/apps-script-intro
○ codelabs.developers.google.com/codelabs/cloud-app-engine-python
○ codelabs.developers.google.com/codelabs/cloud-starting-cloudfunctions
● Inspirational apps
○ bit.ly/2OcptaG
○ cloud.google.com/blog/products/application-development/
adding-custom-intelligence-to-gmail-with-serverless-on-gcp
○ cloud.withgoogle.com/next/sf/sessions?session=DEV212
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
■ Puchase credits a la carte, or discounted in-bulk / via subscription
● Official GCP documentation
○ cloud.google.com/gcp/getting-started
○ Recommended: Getting Started, Cloud Console, Cloud Shell, Cloud SDK, Community
● YouTube video series:
○ youtube.com/GoogleCloud
○ Recommended: Cloud Minute shorts & Cloud NEXT videos
○ G Suite Dev Show: goo.gl/JpBQ40
56. Security in Google Cloud
● Google Cloud Security home page: cloud.google.com/security
● Google Cloud Security whitepaper: bit.ly/2Qb3wXX
● Compliance: stds, regulations, certifications: cloud.google.com/security/compliance
● Transparency report (incl. service disruptions): transparencyreport.google.com
● G Suite Security and Trust (PDF "eBook;" links disabled): bit.ly/2WQ1fnI
● G Suite Encryption whitepaper (PDF): bit.ly/2JrmdGy
● GCP Encryption-at-rest whitepaper (PDF):
cloud.google.com/security/encryption-at-rest/default-encryption
● Google Cloud Encryption-in-transit whitepaper (PDF):
cloud.google.com/security/encryption-in-transit
● Google data centers: google.com/about/datacenters
Thank you! Questions?
Wesley Chun
@wescpy
Progress bars: goo.gl/69EJVw