This document provides an overview and introduction to Google Cloud Platform products and services including Cloud Datastore, Cloud Storage, Cloud SQL, BigQuery, App Engine, Compute Engine, and more. Key features and benefits are highlighted for each service such as scalability, availability, developer tools and SDKs, pricing models, and comparisons to other cloud offerings. Code samples and steps to get started with the services are also provided.
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 - 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!
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.
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.
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.
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)
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.
Built on the same infrastructure that allows Google to return billions of search results in milliseconds, serve 6 billion hours of YouTube video per month and provide storage for 680 million Gmail users, Google Cloud Platform enables developers to build, test and deploy applications on Google’s highly-scalable and reliable infrastructure. Wether you use Google Deployment Manager, Ansible, Chef, Puppet, or Salt, you can now virtually automate everything!
What is Google Cloud Platform - GDG DevFest 18 DepokImre Nagi
This document provides an overview of Google Cloud Platform (GCP) services presented by Imre Nagi. It discusses:
1. What cloud computing is and how GCP provides infrastructure like virtual machines, networking, and storage in Google's data centers while handling scaling, migrations, and maintenance.
2. The main GCP services including Compute Engine, Kubernetes Engine, App Engine, and Cloud Functions for deploying applications, as well as storage, database, analytics, and machine learning services.
3. Options for deploying applications to GCP including using Compute Engine virtual machines, containers on Kubernetes Engine, or serverless functions on Cloud Functions. It notes advantages of managed services like App Engine over unmanaged infrastructure.
Cloud-Native Roadshow Google Cloud Platform - Los AngelesVMware Tanzu
The document discusses Google Cloud Platform services which include computing, storage, networking and machine learning APIs, and highlights how these services bring battle-tested technologies from Google products to provide highly scalable, reliable and secure cloud infrastructure. It also provides overviews of various machine learning and data APIs available on Google Cloud Platform and how they can be used to power applications.
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.
Google Cloud Connect @ Korea
- Google Cloud Vision
- G Suite Product Roadmap
- Google Cloud Security
- Google Cloud Machine Learning
- G suite Customer Stories
Powering your Apps via Google Cloud PlatformRomin Irani
Presentation at Google DevFest Ahmedabad, December 2014. This talk gives an overview of Google Cloud Platform and then goes into Cloud Endpoints and building out a simple IoT Project
App Engine is Google's fully managed platform as a service that allows developers to build and run applications on Google's infrastructure. It provides several services including Cloud Datastore for scalable storage, Cloud SQL for relational databases, Cloud Storage for file storage, and Task Queues for background processing. Developers can build and deploy applications using App Engine's SDKs and APIs, and App Engine automatically scales applications up and down as traffic levels change.
Google Cloud Platform provides infrastructure and platform services including Compute Engine (IaaS), App Engine (PaaS), and storage and database services. The document provides an overview of these services, how they compare to traditional infrastructure approaches, and how to get started with Google Cloud Platform. Key services highlighted include Compute Engine for virtual machines, App Engine for scalable hosting of applications, BigQuery for big data analytics, and Cloud Storage for file storage.
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.
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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
Spark on Dataproc - Israel Spark Meetup at taboolatsliwowicz
This document summarizes a presentation about Google Cloud Dataproc, a fully managed Spark and Hadoop service. It provides an overview of Dataproc's features like fast cluster provisioning, minute-based billing, and integration with other Google Cloud services. The presentation demonstrates Dataproc's pricing and performance advantages over AWS EMR, and outlines Google's roadmap to add more frameworks, tools, and data stores to Dataproc.
This document provides an introduction to Google Cloud Platform services including Google Cloud Storage, Cloud SQL, BigQuery, and Compute Engine. It includes steps to get started with each service through tutorials and labs. The document demonstrates how to create buckets and load data to Cloud Storage, set up databases in Cloud SQL, load CSV data to BigQuery, and create virtual machines on Compute Engine along with networking configurations. Quick start links are also provided for each service.
The document provides an overview of Google Cloud Platform products and services including Google App Engine, Cloud Storage, Cloud Datastore, BigQuery, Cloud SQL, and Compute Engine. It describes the key features of each service such as scalability, availability, data consistency, and pay-as-you-go pricing. Developer tools and interfaces are also highlighted for accessing and managing the various cloud services.
Serverless computing allows running applications without managing infrastructure. Google Cloud Platform offers serverless options like Cloud Functions, Cloud Run, and App Engine. Common serverless patterns include publish-subscribe using PubSub, triggering functions from events, and data pipelines with Dataflow. Serverless applications are built using containers, functions, and fully managed services to focus on code and reduce operational overhead.
Get Ready to Become Google Associate Cloud EngineerAmaaira Johns
Start Here---> https://bit.ly/3fPkOXd <---Get complete detail on Google exam guide to crack Cloud Engineer. You can collect all information on Google tutorial, practice test, books, study material, exam questions, and syllabus. Firm your knowledge on Cloud Engineer and get ready to crack Google certification. Explore all information on Google exam with the number of questions, passing percentage, and time duration to complete the test.
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.
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.
Exploring Google (Cloud) APIs with Python & JavaScriptwesley chun
This is a 1-hr 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)
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!!
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.
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.
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.
The 'macro view' on Big Query:
We started with an overview, some typical uses and moved to project hierarchy, access control and security.
In the end we touch about tools and demos.
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 document outlines a presentation on Heroku, a cloud platform that allows developers to deploy, run, and manage modern apps. It discusses what Heroku is, how it uses buildpacks and dynos, common add-ons for services like databases and monitoring, and how to get started using Heroku with tools like the CLI and deploying apps from GitHub. The presentation also covers Heroku features, demos some example apps deployed on Heroku, and discusses best practices like the Twelve-Factor App methodology.
The document outlines a presentation about Heroku, a cloud platform that allows developers to deploy, run, and manage modern apps. It discusses what Heroku is, how it uses buildpacks and dynos, common add-ons for services like databases and monitoring, and how to get started using Heroku with tools like the CLI and deploying apps from GitHub. The presentation also covers Heroku features, demos some example apps deployed on Heroku, and discusses best practices like the Twelve-Factor App methodology.
Supercharge your data analytics with BigQueryMárton Kodok
Powering interactive data analysis require massive architecture, and Know-How to build a fast real-time computing system. BigQuery solves this problem by enabling super-fast, SQL-like queries against petabytes of data using the processing power of Google’s infrastructure. We will cover its core features, creating tables, columns, views, working with partitions, clustering for cost optimizations, streaming inserts, User Defined Functions, and several use cases for everydaay developer: funnel analytics, behavioral analytics, exploring unstructured data.
The other part will be about BigQuery ML, which enables users to create and execute machine learning models in BigQuery using standard SQL queries. BigQuery ML democratizes machine learning by enabling SQL practitioners to build models using existing SQL tools and skills. BigQuery ML increases development speed by eliminating the need to move data.
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.
Google Compute Engine allows users to launch and manage virtual machine instances on Google's infrastructure. Key features include quotas on resources, creation of instances specifying zone, machine type, and boot options. The Google Cloud SDK and gcutil command can be used to automate tasks like creating instances. Startup scripts enable running custom commands when an instance boots. Backups can be done using disk snapshots, images, or by bundling a disk. VPN services can also be set up on Google Compute Engine using OpenVPN.
Kubernetes Basics provides an overview of Kubernetes concepts and components. It discusses pods vs deployments, scaling deployments, rolling updates, stateful vs stateless applications, daemon sets, secrets, configmaps, services, ingress, storage classes, network policies, and Kubernetes CLI commands. Hands-on examples are given for running commands, exposing services, deleting resources, executing commands in pods, viewing logs, and getting resource information. YAML files are shown for defining deployments, services, and ingress. Skills discussed include using configmaps as environment variables, sidecar deployments, init containers, labels and node selectors, private registries, taints and tolerations, resource management, and readiness and liveness probes.
Simon Su presented on using Google Cloud Platform for IoT applications. The document discussed key concepts in IoT like connectivity, devices, sensors and cloud infrastructure. It provided examples of using various Google Cloud services for IoT like Cloud PubSub for messaging, BigQuery for data storage, Cloud Functions for serverless computing, Cloud Vision API for image recognition and Cloud IoT Core for connecting devices. Code samples were given to illustrate how to use these services for common IoT tasks.
This document provides an overview of various Google Cloud Platform services including Compute Engine, Networking, Load Balancing, Cloud Launcher, Cloud Storage, Cloud SQL, Cloud Monitoring, Cloud DNS, and Deployment Manager. It includes descriptions of the basic concepts and functionality for each service. It also outlines several hands-on labs demonstrating how to use specific GCP services like backing up instances to Cloud Storage snapshots, exporting Cloud SQL databases to Cloud Storage, enabling Cloud Logging, and deploying a VM instance using Deployment Manager.
This document provides instructions for enabling and using the serial console on a Windows machine. It outlines connecting to the VM from port 3, using "?" to check available commands, running "cmd" to start a new command session, and "ch -sn [session name]" to switch sessions. Finally, it notes you can reset the password using "Create or reset Windows password" and login to access the Windows command prompt for troubleshooting.
Cloud Spanner is a fully managed relational database that provides global scale, SQL support, and strong consistency across multiple regions. It is horizontally scalable, provides automatic replication and maintenance, and supports transactions with ACID semantics. Spanner offers high availability, enterprise-grade security with encryption and IAM controls, and supports multiple programming languages through client libraries. Performance scales based on the number of nodes provisioned, with a minimum of 3 nodes recommended for production workloads.
Google Cloud Computing compares GCE, GAE and GKESimon Su
Google Cloud Computing compares GCE, GKE and GAE. GCE provides raw compute, storage and networking resources and requires more management overhead. GAE focuses on application logic and requires less management. GKE offers managed Kubernetes infrastructure and services. Each option has different strengths for workloads like microservices, containerized services, or large-scale applications requiring quick scaling. Monitoring and management features like Stackdriver are also compared.
The document provides information about Simon Su and his expertise in Google Dataflow. It includes Simon's contact information and links to his online profiles. It then discusses Simon's areas of specialization including data scientist, data engineer, and frontend engineer. The document proceeds to provide information about preparing for a Google Dataflow workshop, including documents and labs to review. It also discusses Google Cloud services for data processing and analysis like Dataflow, BigQuery, Pub/Sub, and Dataproc. Finally, it outlines the agenda for the workshop, which will include hands-on labs to deploy users' first Dataflow project and create a streaming Dataflow model.
This document outlines labs for Google Cloud Dataflow workshops. Lab 1 covers setting up the Dataflow environment and building a first project. Lab 2 focuses on deploying the first project to Google Cloud Platform. Lab 3 builds streaming Dataflow by creating PubSub topics/subscriptions and deploying streaming samples that read from PubSub and write to BigQuery.
GCPUG meetup 201610 - Dataflow IntroductionSimon Su
This document provides information about Simon Su and Sunny Hu, who will be presenting on Google's BigData solution. It includes their contact information and backgrounds. Simon's areas of focus include Node.js and blogging. Sunny's skills include project management, system analysis, and Java. The document also advertises a Facebook and Google+ group for the Google Cloud Platform User Group Taiwan, where people can share experiences using GCP. It poses trivia questions about Google's infrastructure and provides timelines of Google's BigData innovations.
使用 Raspberry pi + fluentd + gcp cloud logging, big query 做iot 資料搜集與分析Simon Su
This is a short training for introduce Pi to use fluentd to collect data and use Google Cloud Logging and BigQuery as backend and then use Apps Script and Google Sheet as presentation layer.
This document provides an overview of Docker concepts and commands for building, running, and managing Docker containers. It demonstrates how to run a simple Node.js application as a Docker container using commands like docker run, docker build, docker ps, and docker-compose. It also shows how to link containers, mount folders, push images to Docker Hub, and remove containers.
Google Cloud Platform Introduction - 2016Q3Simon Su
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.
Navigating Post-Quantum Blockchain: Resilient Cryptography in Quantum Threatsanupriti
In the rapidly evolving landscape of blockchain technology, the advent of quantum computing poses unprecedented challenges to traditional cryptographic methods. As quantum computing capabilities advance, the vulnerabilities of current cryptographic standards become increasingly apparent.
This presentation, "Navigating Post-Quantum Blockchain: Resilient Cryptography in Quantum Threats," explores the intersection of blockchain technology and quantum computing. It delves into the urgent need for resilient cryptographic solutions that can withstand the computational power of quantum adversaries.
Key topics covered include:
An overview of quantum computing and its implications for blockchain security.
Current cryptographic standards and their vulnerabilities in the face of quantum threats.
Emerging post-quantum cryptographic algorithms and their applicability to blockchain systems.
Case studies and real-world implications of quantum-resistant blockchain implementations.
Strategies for integrating post-quantum cryptography into existing blockchain frameworks.
Join us as we navigate the complexities of securing blockchain networks in a quantum-enabled future. Gain insights into the latest advancements and best practices for safeguarding data integrity and privacy in the era of quantum threats.
Are you interested in dipping your toes in the cloud native observability waters, but as an engineer you are not sure where to get started with tracing problems through your microservices and application landscapes on Kubernetes? Then this is the session for you, where we take you on your first steps in an active open-source project that offers a buffet of languages, challenges, and opportunities for getting started with telemetry data.
The project is called openTelemetry, but before diving into the specifics, we’ll start with de-mystifying key concepts and terms such as observability, telemetry, instrumentation, cardinality, percentile to lay a foundation. After understanding the nuts and bolts of observability and distributed traces, we’ll explore the openTelemetry community; its Special Interest Groups (SIGs), repositories, and how to become not only an end-user, but possibly a contributor.We will wrap up with an overview of the components in this project, such as the Collector, the OpenTelemetry protocol (OTLP), its APIs, and its SDKs.
Attendees will leave with an understanding of key observability concepts, become grounded in distributed tracing terminology, be aware of the components of openTelemetry, and know how to take their first steps to an open-source contribution!
Key Takeaways: Open source, vendor neutral instrumentation is an exciting new reality as the industry standardizes on openTelemetry for observability. OpenTelemetry is on a mission to enable effective observability by making high-quality, portable telemetry ubiquitous. The world of observability and monitoring today has a steep learning curve and in order to achieve ubiquity, the project would benefit from growing our contributor community.
The Rise of Supernetwork Data Intensive ComputingLarry Smarr
Invited Remote Lecture to SC21
The International Conference for High Performance Computing, Networking, Storage, and Analysis
St. Louis, Missouri
November 18, 2021
Performance Budgets for the Real World by Tammy EvertsScyllaDB
Performance budgets have been around for more than ten years. Over those years, we’ve learned a lot about what works, what doesn’t, and what we need to improve. In this session, Tammy revisits old assumptions about performance budgets and offers some new best practices. Topics include:
• Understanding performance budgets vs. performance goals
• Aligning budgets with user experience
• Pros and cons of Core Web Vitals
• How to stay on top of your budgets to fight regressions
How to Avoid Learning the Linux-Kernel Memory ModelScyllaDB
The Linux-kernel memory model (LKMM) is a powerful tool for developing highly concurrent Linux-kernel code, but it also has a steep learning curve. Wouldn't it be great to get most of LKMM's benefits without the learning curve?
This talk will describe how to do exactly that by using the standard Linux-kernel APIs (locking, reference counting, RCU) along with a simple rules of thumb, thus gaining most of LKMM's power with less learning. And the full LKMM is always there when you need it!
An invited talk given by Mark Billinghurst on Research Directions for Cross Reality Interfaces. This was given on July 2nd 2024 as part of the 2024 Summer School on Cross Reality in Hagenberg, Austria (July 1st - 7th)
In this follow-up session on knowledge and prompt engineering, we will explore structured prompting, chain of thought prompting, iterative prompting, prompt optimization, emotional language prompts, and the inclusion of user signals and industry-specific data to enhance LLM performance.
Join EIS Founder & CEO Seth Earley and special guest Nick Usborne, Copywriter, Trainer, and Speaker, as they delve into these methodologies to improve AI-driven knowledge processes for employees and customers alike.
Fluttercon 2024: Showing that you care about security - OpenSSF Scorecards fo...Chris Swan
Have you noticed the OpenSSF Scorecard badges on the official Dart and Flutter repos? It's Google's way of showing that they care about security. Practices such as pinning dependencies, branch protection, required reviews, continuous integration tests etc. are measured to provide a score and accompanying badge.
You can do the same for your projects, and this presentation will show you how, with an emphasis on the unique challenges that come up when working with Dart and Flutter.
The session will provide a walkthrough of the steps involved in securing a first repository, and then what it takes to repeat that process across an organization with multiple repos. It will also look at the ongoing maintenance involved once scorecards have been implemented, and how aspects of that maintenance can be better automated to minimize toil.
Quantum Communications Q&A with Gemini LLM. These are based on Shannon's Noisy channel Theorem and offers how the classical theory applies to the quantum world.
Transcript: Details of description part II: Describing images in practice - T...BookNet Canada
This presentation explores the practical application of image description techniques. Familiar guidelines will be demonstrated in practice, and descriptions will be developed “live”! If you have learned a lot about the theory of image description techniques but want to feel more confident putting them into practice, this is the presentation for you. There will be useful, actionable information for everyone, whether you are working with authors, colleagues, alone, or leveraging AI as a collaborator.
Link to presentation recording and slides: https://bnctechforum.ca/sessions/details-of-description-part-ii-describing-images-in-practice/
Presented by BookNet Canada on June 25, 2024, with support from the Department of Canadian Heritage.
Implementations of Fused Deposition Modeling in real worldEmerging Tech
The presentation showcases the diverse real-world applications of Fused Deposition Modeling (FDM) across multiple industries:
1. **Manufacturing**: FDM is utilized in manufacturing for rapid prototyping, creating custom tools and fixtures, and producing functional end-use parts. Companies leverage its cost-effectiveness and flexibility to streamline production processes.
2. **Medical**: In the medical field, FDM is used to create patient-specific anatomical models, surgical guides, and prosthetics. Its ability to produce precise and biocompatible parts supports advancements in personalized healthcare solutions.
3. **Education**: FDM plays a crucial role in education by enabling students to learn about design and engineering through hands-on 3D printing projects. It promotes innovation and practical skill development in STEM disciplines.
4. **Science**: Researchers use FDM to prototype equipment for scientific experiments, build custom laboratory tools, and create models for visualization and testing purposes. It facilitates rapid iteration and customization in scientific endeavors.
5. **Automotive**: Automotive manufacturers employ FDM for prototyping vehicle components, tooling for assembly lines, and customized parts. It speeds up the design validation process and enhances efficiency in automotive engineering.
6. **Consumer Electronics**: FDM is utilized in consumer electronics for designing and prototyping product enclosures, casings, and internal components. It enables rapid iteration and customization to meet evolving consumer demands.
7. **Robotics**: Robotics engineers leverage FDM to prototype robot parts, create lightweight and durable components, and customize robot designs for specific applications. It supports innovation and optimization in robotic systems.
8. **Aerospace**: In aerospace, FDM is used to manufacture lightweight parts, complex geometries, and prototypes of aircraft components. It contributes to cost reduction, faster production cycles, and weight savings in aerospace engineering.
9. **Architecture**: Architects utilize FDM for creating detailed architectural models, prototypes of building components, and intricate designs. It aids in visualizing concepts, testing structural integrity, and communicating design ideas effectively.
Each industry example demonstrates how FDM enhances innovation, accelerates product development, and addresses specific challenges through advanced manufacturing capabilities.
Scaling Connections in PostgreSQL Postgres Bangalore(PGBLR) Meetup-2 - MydbopsMydbops
This presentation, delivered at the Postgres Bangalore (PGBLR) Meetup-2 on June 29th, 2024, dives deep into connection pooling for PostgreSQL databases. Aakash M, a PostgreSQL Tech Lead at Mydbops, explores the challenges of managing numerous connections and explains how connection pooling optimizes performance and resource utilization.
Key Takeaways:
* Understand why connection pooling is essential for high-traffic applications
* Explore various connection poolers available for PostgreSQL, including pgbouncer
* Learn the configuration options and functionalities of pgbouncer
* Discover best practices for monitoring and troubleshooting connection pooling setups
* Gain insights into real-world use cases and considerations for production environments
This presentation is ideal for:
* Database administrators (DBAs)
* Developers working with PostgreSQL
* DevOps engineers
* Anyone interested in optimizing PostgreSQL performance
Contact info@mydbops.com for PostgreSQL Managed, Consulting and Remote DBA Services
9. Features
● NoSQL database service
● Support ACID transactions
● High availability, Strong / Eventual
consistency
● Google infrastructure & management
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○
○
○
No planned downtime.
Replicated across multiple datacenters.
Automatically scales to handle traffic increase.
Monitored by Google engineers.
10. Developer Support
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●
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GAE integrate (Python, Java, Go, Php)
Local development server
Auto / Customize index
JSON API over REST
GQL query language
CLI tool - GCD
Web tool - Google Cloud Console
Usage statistic
16. Google Cloud Storage
watch videos, screen casts,
and presentations that walk
through how to use Google
Cloud Storage.
VIDEOS
download sample
applications, read howto
guides, and learn how to use
Google Cloud Storage with
other Google products.
SAMPLES
Google Cloud Storage Object storage service, without limit and global deployed
ask questions, discuss
solutions, and join our
vibrant community of
developers.
COMMUNITY
17. What is Cloud Storage?
SDK, API Support
Web Console
GAE Integrate
Oauth2 Integrate
Unlimited
Global Deploy
18. GCS - Features
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High Capacity and Scalability
Strong Data Consistency
Google Cloud Console Projects
Bucket Locations
REST APIS
OAuth 2.0 Authentication
Authenticated Browser Downloads
Google Account Support for Sharing
19. Compare
Google CloudStorage
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Location
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US, UK
Replicate strategy
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Global
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Specify zone
Access auth
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Oauth2
Others
○
Publish as a web
site
○
SDK, API
S3@AWS
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Location
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US, EU, Asia
Replicate strategy
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Specify zone
Access auth
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API Key
Others
○
Publish as a web
site
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SDK, API
25. Connect tools
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Using the command line prompt
API console SQL prompt
Admin tools and reporting tools
External applications
From App Engine: Java, Python
From Google Apps Script scripts
26. Compare
Google CloudSQL
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DB type
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MySQL
Location
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US, UK
Availability strategy
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Backup
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Replicate
Security
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SSL
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Access Firewall
Global strategy
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Specify zone
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With AppEngine
Service integrate
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Dump to Cloud
Storage
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BigQuery Integrate
RDS@AWS
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DB type
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MySQL, Oracle,
Microsoft SQL
Server, PostgreSQL
Location
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US, EU, Asia
Availability strategy
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Backup
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Snapshot
Security
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Access Firewall
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VPC/VPN
SQLServer@Azure
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DB type
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Microsoft SQL
Location
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US, EU, Asia
Availability strategy
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Data sync
Security
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Access Firewall
31. BigQuery Features
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TB level data analysis
Fast mining response
SQL like query language
Multi-dataset interactive
support
● Cheap and pay by use
● Offline job support
34. Compare
Google BigQuery
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Service strategy
○
Base on Google
search
Store Location
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Global
Query strategy
○
SQL like language
Security
○
Oauth2
Source
○
JSON, CSV
Developer support
○
Java, Python SDK
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Apps Script SDK
○
RESTful API
○
3rd Party tools
EMR@AWS
●
●
●
●
●
●
Service strategy
○
Base on Google
released
Map/Reduce spec
Store Location
○
Base on EMR
machines
Query strategy
○
Map/Reduce java
sdk
Security
○
N/A
Source
○
Text, CSV
Developer support
○
Java SDK
42. Compare
Google AppEngine
●
●
●
●
Java, PHP, Python, Go
support
Services:
○
Memcache
○
Task Queue
○
Cron
○
Datastore
○
CloudSQL
○
CloudStorage
○
Eage Cache
○
Google APIs
Others:
○
IDE full support
○
Auto scale in/out
○
Global already
New:
○
Publish with git
Heroku
●
●
●
Ruby, Java, Node.js,
Python support
Service:
○
Vendor provided
apps
Others:
○
CLI only
○
Manual scale in/out
○
Publish with git
Azure
●
●
●
IIS, Node.js, Python, PHP
support
Service:
○
SQL Service
○
Table Service
○
Blob Service
○
Media Services
○
Service Bus
○
Notification Hubs
○
Scheduler
○
BizTalk Services
○
Active Directory
○
Multi-Factor
Authentication
Others:
○
IDE full support
○
Publish with git
47. Google Style Management
●
●
●
●
●
●
Fancy management console
Share permissions with Google Account
Tag for machine, ACL, routing
Software Defined Networking
Start Script
Mass technical documents share
48. Compare
Google Compute Engine
●
●
●
●
Location
○
US, UK
Machine strategy
○
CentOS, Debian,
Ubuntu, SuSE,
Redhat...
○
Bring self-kernel
Network strategy (SDN)
○
L4 load balancer
○
Routing configure
○
Firewall ACL
Other
○
TAG, Start Script,
Image, Snapshot
○
Availability policy
■
auto-restart
■
on host
maintenance
EC2@AWS
●
●
●
●
Location
○
US, EU, Asia
Machine strategy
○
Amazon Linux,
Ubuntu, Redhat,
SuSE, Windows
Network strategy
○
ELB
○
CloudFront
○
Global IDC
○
Firewall ACL
Other
○
TAG, User Data
Script, AMI,
Snapshot
○
IAM
○
CloudWatch
VM@Azure
●
●
●
●
Location
○
US, EU, Asia
Machine strategy
○
Windows, Ubuntu,
SuSE, OpenLogic,
Oracle Linux
Network strategy
○
VPC
○
Traffic Manager
Other
○
Resizable