Ceilometer is OpenStack's metering project that collects usage data from OpenStack components like Nova, Glance, and Cinder. It allows for single collection of per-user/tenant usage data across all resources. Ceilometer is designed to be scalable, provide a simple REST API, and be extensible via plugins. DreamHost plans to use Ceilometer to measure usage for billing by customizing it to track instance hours, storage, and bandwidth usage.
Ceilometer is a tool that collects usage and performance data, while Heat orchestrates complex deployments on top of OpenStack. Heat aims to autoscale its deployments, scaling up when they're running hot and scaling back when idle.
Ceilometer can access decisive data and trigger the appropriate actions in Heat. The result of these two OpenStack projects meeting is value creation in the form of an alarming API in Ceilometer and its consumption in Heat.
Slides presented at the Fall OpenStack Design Summit in Hong Kong
Google Cloud Platform - Building a scalable mobile applicationLukas Masuch
In this presentation we give an overview on several services of the Google Cloud Platform and showcase an Android application utilizing these technologies. We cover technologies, such as Google App Engine, Cloud Endpoints, Cloud Storage, Cloud Datastore and Google Cloud Messaging (GCM). We will talk about pitfalls, show meaningful code examples (in Java) and provide several tips and dev tools on how to get the most out of Google’s Cloud Platform.
This document discusses Amazon SageMaker, Amazon's fully managed machine learning platform. It provides an overview of SageMaker's capabilities including built-in algorithms, frameworks, notebooks, hyperparameter tuning, and access to public datasets. Examples of using SageMaker for tasks like image classification and deep learning are also mentioned.
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!
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.
Stabilizing the Jenga tower: Scaling out CeilometerPradeep Kilambi
This document discusses the evolution of Ceilometer, an OpenStack component for collecting and managing telemetry data. Ceilometer collects metrics from OpenStack services and stores them for later retrieval and analysis. The architecture has changed over time to improve scalability, with a shift to active-active workload partitioning in Kilo and integration with Gnocchi in Liberty for more efficient storage of time-series metric data. Best practices are provided around data collection, storage, and deployment scenarios to help operators reliably collect and manage telemetry at scale.
Eoghan Glynn, Ceilometer Project PTL, outlines the changes made in the Icehouse release as well as upcoming updates for Juno.
Learn more about Ceilometer here: https://wiki.openstack.org/wiki/Ceilometer
Ceilometer is OpenStack's metering project that collects usage data from OpenStack components like Nova, Glance, and Cinder. It allows for single collection of per-user/tenant usage data across all resources. Ceilometer is designed to be scalable, provide a simple REST API, and be extensible via plugins. DreamHost plans to use Ceilometer to measure usage for billing by customizing it to track instance hours, storage, and bandwidth usage.
Ceilometer is a tool that collects usage and performance data, while Heat orchestrates complex deployments on top of OpenStack. Heat aims to autoscale its deployments, scaling up when they're running hot and scaling back when idle.
Ceilometer can access decisive data and trigger the appropriate actions in Heat. The result of these two OpenStack projects meeting is value creation in the form of an alarming API in Ceilometer and its consumption in Heat.
Slides presented at the Fall OpenStack Design Summit in Hong Kong
Google Cloud Platform - Building a scalable mobile applicationLukas Masuch
In this presentation we give an overview on several services of the Google Cloud Platform and showcase an Android application utilizing these technologies. We cover technologies, such as Google App Engine, Cloud Endpoints, Cloud Storage, Cloud Datastore and Google Cloud Messaging (GCM). We will talk about pitfalls, show meaningful code examples (in Java) and provide several tips and dev tools on how to get the most out of Google’s Cloud Platform.
This document discusses Amazon SageMaker, Amazon's fully managed machine learning platform. It provides an overview of SageMaker's capabilities including built-in algorithms, frameworks, notebooks, hyperparameter tuning, and access to public datasets. Examples of using SageMaker for tasks like image classification and deep learning are also mentioned.
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!
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.
Stabilizing the Jenga tower: Scaling out CeilometerPradeep Kilambi
This document discusses the evolution of Ceilometer, an OpenStack component for collecting and managing telemetry data. Ceilometer collects metrics from OpenStack services and stores them for later retrieval and analysis. The architecture has changed over time to improve scalability, with a shift to active-active workload partitioning in Kilo and integration with Gnocchi in Liberty for more efficient storage of time-series metric data. Best practices are provided around data collection, storage, and deployment scenarios to help operators reliably collect and manage telemetry at scale.
Eoghan Glynn, Ceilometer Project PTL, outlines the changes made in the Icehouse release as well as upcoming updates for Juno.
Learn more about Ceilometer here: https://wiki.openstack.org/wiki/Ceilometer
The document discusses linear regression and demonstrates its use through three machine learning demos. It begins with an introduction to linear regression, the Weka software, and a first demo using Weka's GUI. It then describes the microservices architecture of a second demo using Weka's Java API with Spring Boot microservices. Finally, it outlines a third full stack demo built with Angular 10. Source code for the demos is available online.
GCP Gaming 2016 Seoul, Korea Gaming AnalyticsChris Jang
The document discusses creating a gaming analytics platform using Google Cloud Platform. It describes collecting diverse data from sources like user acquisition campaigns, app stores, and custom game events. This data can then be analyzed using standard metrics, key game indicators, and custom questions. BigQuery is recommended for batch processing while Dataflow (Apache Beam) enables real-time streaming analytics. Dataflow provides autoscaling, fully managed processing, and allows batch and streaming in one framework. This speeds up development time compared to typical big data architectures.
The document discusses various techniques for implementing location services in an Android application while being battery efficient. It covers options for determining location like GPS, WiFi and Bluetooth. It also discusses APIs for simple synchronous location updates, asynchronous callback-based updates and scheduling location updates in the background. The document provides recommendations for transparency with users, monitoring battery life, and tools for analyzing battery usage like Battery Historian.
This document discusses eBay's private cloud and journey with OpenStack over the past 6 years. It outlines the challenges of developing OpenStack at scale to support eBay's needs, including network design, security, onboarding, CI/CD, configuration management, high availability, monitoring, logging, and customer support. It discusses lessons learned around the difficulty of turning OpenStack into an enterprise-grade cloud, and future directions including enabling containers/microservices, programmable application security, and software-defined networks and data centers to create an automated, efficient, and secure cloud infrastructure.
Google App Engine (GAE) is a platform that provides on-demand access to a shared pool of configurable computing resources over the internet. It allows developers to build and host web applications and services using Google infrastructure. GAE provides automatic scaling, high availability, and it supports various programming languages including Python, Java, Go and PHP. Developers can use GAE services like Datastore, Memcache, Search and URLFetch to build applications, and GAE integrates with other Google products and services.
Learn about core functions and architecture of Zentral. Zentral is a open source hub to process event streams from osquery and other sources into the ElasticStack. Besides support for distinct osquery features like file carving, Zentral provides numerous integrations for inventory acquisition and alerting.
The document discusses setting up and interacting with Bluetooth Low Energy (BLE) devices from an Android application. It explains that to find BLE devices, you use the startLescan() method. To connect to a device, you use the connectGatt() method, passing in a Context, autoConnect boolean, and BluetoothGattCallback. This establishes a connection to the device's GATT server. Once connected, you can discover services, read and write attributes, and enable notifications. When finished, close the BluetoothGatt client to release resources.
This document describes how to resize images using an AWS Lambda function triggered by S3 events. It involves creating two S3 buckets, one for source images and one for resized images. A Lambda function is configured with an IAM role to access S3 and CloudWatch, and is set as a trigger for objects added to the source bucket. Testing confirms the function resizes images to thumbnails and saves them to the destination bucket on object uploads.
Pythian Analytics-as-a-Service on Google Cloud Platform - Technical OverviewPythian
This document provides an overview of Pythian's Analytics-as-a-Service offering hosted on Google Cloud Platform. The service ingests data from multiple sources using Apache NiFi, transforms the data using Apache Spark for scalability, warehouses the data in Google BigQuery for fast queries, and provides sandbox environments using Google Cloud Datalab for data science work. Users can learn more by visiting Pythian's website.
This document summarizes Google Cloud Platform (GCP). It discusses how GCP provides true economic benefits of cloud through Google's future-oriented architecture and direct access to Google software innovations. It highlights GCP's openness by empowering customers to choose. The document then overviews GCP's infrastructure, data services, application services, and runtime services to enable no-touch operations and breakthrough insights. It concludes by thanking the audience.
Christoph Bussler [Google Cloud] | IoT Event Processing and Analytics with In...InfluxData
The presentation introduces a Google Cloud native architecture for collecting, processing, analyzing and archiving events from IoT devices, vehicles as well as upstream software systems. InfluxDB and its connection to global native Google Cloud services like BigQuery or Cloud Machine Learning Engine as well as Kubernetes is at the center of the architecture. The architecture demonstrates how access to global scaling cloud services address use cases from the Energy Sector.
Google Tech Talk with Dr. Eric Brewer in Korea Apr.27.2015Chris Jang
This document summarizes a Google Tech Talk given by Dr. Eric Brewer on containers. The talk discussed how Google has been using containers for over 10 years to manage applications, with over 2 billion containers launched per week. Containers were described as providing simplification of management, performance isolation, and efficiency. Docker and Linux containers were discussed as merging the packaging benefits of Docker with the isolation capabilities of Linux containers. Kubernetes, an open source container orchestration system inspired by Google's internal systems, was also summarized.
This document discusses integrating Angular with Meteor. Some key points:
- Angular-Meteor adds a way to augment or replace Meteor's Blaze reactive templating library with Angular.
- It provides services like $meteorCollection for reactive collections, $meteorObject for single objects, $meteorSubscribe for subscriptions, and $meteorCall for methods.
- Collections in Angular-Meteor provide 3-way data binding between the template, controller scope, and database using Meteor cursors for efficient updates.
- Security features like collection permissions still work as usual.
- Angular-Meteor aims to put all data directly into the scope,
developmentSEED Presentation for Earth Observation in the Cloud Demo DayAmazon Web Services
Earth observation data from satellites like Landsat is now more publicly available than ever before, allowing not just scientists but also non-scientists and computers to access and utilize the data. Tools are being built like Landsat-API and Landsat-util to make this satellite imagery more programmatically accessible. Companies like Astro Digital are working on scalable platforms to process satellite images on-demand through cloud-based APIs and services in order to generate actionable data and insights through real-time analysis and machine learning.
Event streaming pipeline with Windows Azure and ArcGIS Geoevent extensionRoberto Messora
Real time monitoring and Internet of Things are key success factors in many business activities.
In this presentation we will show how we solved a common issue in managing a large number of different types of event per second that contain some sort of geographical information.
We built a processing pipeline leveraging the high ingestion capabilities of Windows Azure Event Hub and Stream Analytics, then applying location analytics procedures with ArcGIS GeoEvent Processor.
In this way we can select just the informations we need to be processed by the ArcGIS platform, reducing the number of events and normalizing data content.
Integrating google maps into Salesforce - Starting with description of the Project we have worked upon, there’s an app we created for searching and showing Account’s location on the Map and knowing a route map from one location to another location via some locations(Checkpoints). For the requirement we used Google maps api which is in Javascript format. There are some predefined javascript functions used in the Google map api.
Troposphere Python infrastructure as code for AWS CloudformationPatrick Pierson
Infrastructure as code is managing computing infrastructure through machine-processable definition files instead of physical configuration. Cloudformation helps model and set up AWS resources so less time is spent managing them. Troposphere allows easier creation of Cloudformation JSON by writing Python code to describe AWS resources, and includes basic OpenStack support.
The document discusses cloud services and why developers should build them. It defines cloud services using examples like Amazon S3 for file storage and New Relic for performance monitoring. These services take over infrastructure headaches like scaling by running software as hosted, managed services where the provider handles operations and maintenance in exchange for usage-based fees. The document argues the cloud services market is emerging and offers exciting opportunities to develop new offerings.
This document discusses Google Cloud Platform's Internet of Things (IoT) architecture and services. It describes how IoT data can be captured using protocols and streaming into Google Cloud Pub/Sub. Machine learning algorithms can then detect patterns in real-time streams. Data is also archived in Cloud Storage. Google Cloud Dataflow is highlighted for processing both batch and stream workloads, with features like autoscaling, intuitive programming model, and unified processing of data.
Weather data meets ibm cloud. part 1 ingestion and processing of weather da...Einar Karlsen
This recipe - co-authored with Julia Wiegel and Rene Meyer - shows how to ingest and process weather data using the Weather Company Data Service (API), IBM Cloud Functions (based on Apache OpenWhisk) and IBM Event Streams (based on Apache Kafka). It was originally published on IBM Developer.
The document discusses linear regression and demonstrates its use through three machine learning demos. It begins with an introduction to linear regression, the Weka software, and a first demo using Weka's GUI. It then describes the microservices architecture of a second demo using Weka's Java API with Spring Boot microservices. Finally, it outlines a third full stack demo built with Angular 10. Source code for the demos is available online.
GCP Gaming 2016 Seoul, Korea Gaming AnalyticsChris Jang
The document discusses creating a gaming analytics platform using Google Cloud Platform. It describes collecting diverse data from sources like user acquisition campaigns, app stores, and custom game events. This data can then be analyzed using standard metrics, key game indicators, and custom questions. BigQuery is recommended for batch processing while Dataflow (Apache Beam) enables real-time streaming analytics. Dataflow provides autoscaling, fully managed processing, and allows batch and streaming in one framework. This speeds up development time compared to typical big data architectures.
The document discusses various techniques for implementing location services in an Android application while being battery efficient. It covers options for determining location like GPS, WiFi and Bluetooth. It also discusses APIs for simple synchronous location updates, asynchronous callback-based updates and scheduling location updates in the background. The document provides recommendations for transparency with users, monitoring battery life, and tools for analyzing battery usage like Battery Historian.
This document discusses eBay's private cloud and journey with OpenStack over the past 6 years. It outlines the challenges of developing OpenStack at scale to support eBay's needs, including network design, security, onboarding, CI/CD, configuration management, high availability, monitoring, logging, and customer support. It discusses lessons learned around the difficulty of turning OpenStack into an enterprise-grade cloud, and future directions including enabling containers/microservices, programmable application security, and software-defined networks and data centers to create an automated, efficient, and secure cloud infrastructure.
Google App Engine (GAE) is a platform that provides on-demand access to a shared pool of configurable computing resources over the internet. It allows developers to build and host web applications and services using Google infrastructure. GAE provides automatic scaling, high availability, and it supports various programming languages including Python, Java, Go and PHP. Developers can use GAE services like Datastore, Memcache, Search and URLFetch to build applications, and GAE integrates with other Google products and services.
Learn about core functions and architecture of Zentral. Zentral is a open source hub to process event streams from osquery and other sources into the ElasticStack. Besides support for distinct osquery features like file carving, Zentral provides numerous integrations for inventory acquisition and alerting.
The document discusses setting up and interacting with Bluetooth Low Energy (BLE) devices from an Android application. It explains that to find BLE devices, you use the startLescan() method. To connect to a device, you use the connectGatt() method, passing in a Context, autoConnect boolean, and BluetoothGattCallback. This establishes a connection to the device's GATT server. Once connected, you can discover services, read and write attributes, and enable notifications. When finished, close the BluetoothGatt client to release resources.
This document describes how to resize images using an AWS Lambda function triggered by S3 events. It involves creating two S3 buckets, one for source images and one for resized images. A Lambda function is configured with an IAM role to access S3 and CloudWatch, and is set as a trigger for objects added to the source bucket. Testing confirms the function resizes images to thumbnails and saves them to the destination bucket on object uploads.
Pythian Analytics-as-a-Service on Google Cloud Platform - Technical OverviewPythian
This document provides an overview of Pythian's Analytics-as-a-Service offering hosted on Google Cloud Platform. The service ingests data from multiple sources using Apache NiFi, transforms the data using Apache Spark for scalability, warehouses the data in Google BigQuery for fast queries, and provides sandbox environments using Google Cloud Datalab for data science work. Users can learn more by visiting Pythian's website.
This document summarizes Google Cloud Platform (GCP). It discusses how GCP provides true economic benefits of cloud through Google's future-oriented architecture and direct access to Google software innovations. It highlights GCP's openness by empowering customers to choose. The document then overviews GCP's infrastructure, data services, application services, and runtime services to enable no-touch operations and breakthrough insights. It concludes by thanking the audience.
Christoph Bussler [Google Cloud] | IoT Event Processing and Analytics with In...InfluxData
The presentation introduces a Google Cloud native architecture for collecting, processing, analyzing and archiving events from IoT devices, vehicles as well as upstream software systems. InfluxDB and its connection to global native Google Cloud services like BigQuery or Cloud Machine Learning Engine as well as Kubernetes is at the center of the architecture. The architecture demonstrates how access to global scaling cloud services address use cases from the Energy Sector.
Google Tech Talk with Dr. Eric Brewer in Korea Apr.27.2015Chris Jang
This document summarizes a Google Tech Talk given by Dr. Eric Brewer on containers. The talk discussed how Google has been using containers for over 10 years to manage applications, with over 2 billion containers launched per week. Containers were described as providing simplification of management, performance isolation, and efficiency. Docker and Linux containers were discussed as merging the packaging benefits of Docker with the isolation capabilities of Linux containers. Kubernetes, an open source container orchestration system inspired by Google's internal systems, was also summarized.
This document discusses integrating Angular with Meteor. Some key points:
- Angular-Meteor adds a way to augment or replace Meteor's Blaze reactive templating library with Angular.
- It provides services like $meteorCollection for reactive collections, $meteorObject for single objects, $meteorSubscribe for subscriptions, and $meteorCall for methods.
- Collections in Angular-Meteor provide 3-way data binding between the template, controller scope, and database using Meteor cursors for efficient updates.
- Security features like collection permissions still work as usual.
- Angular-Meteor aims to put all data directly into the scope,
developmentSEED Presentation for Earth Observation in the Cloud Demo DayAmazon Web Services
Earth observation data from satellites like Landsat is now more publicly available than ever before, allowing not just scientists but also non-scientists and computers to access and utilize the data. Tools are being built like Landsat-API and Landsat-util to make this satellite imagery more programmatically accessible. Companies like Astro Digital are working on scalable platforms to process satellite images on-demand through cloud-based APIs and services in order to generate actionable data and insights through real-time analysis and machine learning.
Event streaming pipeline with Windows Azure and ArcGIS Geoevent extensionRoberto Messora
Real time monitoring and Internet of Things are key success factors in many business activities.
In this presentation we will show how we solved a common issue in managing a large number of different types of event per second that contain some sort of geographical information.
We built a processing pipeline leveraging the high ingestion capabilities of Windows Azure Event Hub and Stream Analytics, then applying location analytics procedures with ArcGIS GeoEvent Processor.
In this way we can select just the informations we need to be processed by the ArcGIS platform, reducing the number of events and normalizing data content.
Integrating google maps into Salesforce - Starting with description of the Project we have worked upon, there’s an app we created for searching and showing Account’s location on the Map and knowing a route map from one location to another location via some locations(Checkpoints). For the requirement we used Google maps api which is in Javascript format. There are some predefined javascript functions used in the Google map api.
Troposphere Python infrastructure as code for AWS CloudformationPatrick Pierson
Infrastructure as code is managing computing infrastructure through machine-processable definition files instead of physical configuration. Cloudformation helps model and set up AWS resources so less time is spent managing them. Troposphere allows easier creation of Cloudformation JSON by writing Python code to describe AWS resources, and includes basic OpenStack support.
The document discusses cloud services and why developers should build them. It defines cloud services using examples like Amazon S3 for file storage and New Relic for performance monitoring. These services take over infrastructure headaches like scaling by running software as hosted, managed services where the provider handles operations and maintenance in exchange for usage-based fees. The document argues the cloud services market is emerging and offers exciting opportunities to develop new offerings.
This document discusses Google Cloud Platform's Internet of Things (IoT) architecture and services. It describes how IoT data can be captured using protocols and streaming into Google Cloud Pub/Sub. Machine learning algorithms can then detect patterns in real-time streams. Data is also archived in Cloud Storage. Google Cloud Dataflow is highlighted for processing both batch and stream workloads, with features like autoscaling, intuitive programming model, and unified processing of data.
Weather data meets ibm cloud. part 1 ingestion and processing of weather da...Einar Karlsen
This recipe - co-authored with Julia Wiegel and Rene Meyer - shows how to ingest and process weather data using the Weather Company Data Service (API), IBM Cloud Functions (based on Apache OpenWhisk) and IBM Event Streams (based on Apache Kafka). It was originally published on IBM Developer.
Cloud to hybrid edge cloud evolution Jun112020.pptxMichel Burger
Michel Burger discusses extending cloud computing to the edge by deploying microservices and other cloud-native technologies closer to endpoints and data sources. He outlines how software and computing models have evolved over time from mainframes to client-server architectures to modern cloud-native approaches. Burger also discusses principles for building cloud applications including designing for failure, scaling, and managing state.
Web services allow communication between devices over a network by following set rules and standards. They take in data, process it, and return information. Common examples include Google Maps and cloud computing services. Web services are widely used, such as for email, weather, and document storage. They work by running on top of existing protocols and being hosted on remote servers that clients can access over the internet. The main benefits are centralized data processing and storage, sharing of information between clients, and improved security. The future of web services involves greater use of cloud computing and combining data from different services into single applications.
Weather data meets ibm cloud. part 3 transformation and aggregation of weat...Einar Karlsen
This IBM Developer article shows how to extract, transform and load weather data stored by IBM Cloud Object Storage using IBM SQL Query, pandas, Apache Spark, IBM Watson Studio and Jupyter notebooks for Python.
The document summarizes Samidip Basu's presentation to the Central Ohio Windows Phone User Group about developing for Windows Phone 7 and Mango. Some key points from the presentation include:
- An overview of push notifications, live tiles, and the different types of notifications in Windows Phone.
- A demonstration of building shopping list, social, and music apps that utilize Mango features like multitasking and background agents.
- A discussion of developing mobile applications using services on Windows Azure, including storage, SQL databases, and integrating with OData services.
- A preview of new features coming in the Mango update like multi-tasking, sockets, and enhanced push notifications.
Google Cloud Platform - Building a scalable Mobile ApplicationBenjamin Raethlein
by Lukas Masuch, Henning Muszynski and Benjamin Raethlein
Originally held on 'Karlsruhe Entwicklertag 2015'
In this presentation we give an overview on several services of the Google Cloud Platform and showcase an Android application utilizing these technologies. We cover technologies, such as Google App Engine, Cloud Endpoints, Cloud Storage, Cloud Datastore and Google Cloud Messaging (GCM). We will talk about pitfalls, show meaningful code examples (in Java) and provide several tips and dev tools on how to get the most out of Google’s Cloud Platform.
Google Cloud infrastructure in Conrad Connect by Google & waylayVeselin Pizurica
Conrad Connect lets users interconnect smart devices from different ecosystems with online services. It provides customized dashboards to visualise data from different vendors. It also allows users to build advanced automation rules or to control devices and services using voice and smart bots.
Conrad Connect application is built on top of the waylay platform and it is managed and deployed in the Google cloud.
With close to 100K connected devices, 20 million API calls a day and few billion metrics per week stored, many challenges need to be addressed: How to constantly scale up the platform with exponential growth of the users? How to manage deployments, new releases and upgrades?
In this talk you will learn more how waylay leverages some of the latest Google technologies to address these challenges
End To End Machine Learning With Google Cloud Tu Pham
This document discusses end-to-end machine learning with Google Cloud. It outlines an 8-step process for collecting raw data, converting it to Apache Parquet files, uploading it to Cloud Storage, exploring it in Datalab, developing models in TensorFlow/Scikit-learn, training models at scale on Cloud ML Engine, deploying models via APIs on Compute Engine, and exposing APIs with Load Balancing. Key principles discussed are keeping it simple, avoiding repetition, and focusing on scalability, performance, and cost optimization. The presenter encourages planning systems with single responsibilities, separating real-time and batch flows, and saving on networking, instance, and storage costs through monitoring.
Cloud computing infrastructure provides on-demand computing resources and platforms through utility computing models. The document defines public and private clouds and compares two major cloud platforms, Amazon EC2 and Google AppEngine. Both platforms provide scalable, reliable computing resources on demand but differ in their abstraction levels and programming models. While cloud computing offers benefits like reduced costs and maintenance, adoption challenges include availability, data security, and software licensing issues.
The document discusses upcoming features in Windows Phone 7 Mango, the cloud, Azure, and related technologies. It provides demonstrations of using push notifications from the cloud, browsing Netflix movies with OData, and building applications with MVC3, EF 4.1, SQL Azure and OData on Windows Phone 7. It also discusses features rumored to be in Mango like tethering, turn-by-turn directions in Bing, and front-facing cameras.
Google Cloud Next '22 Recap: Serverless & Data editionDaniel Zivkovic
See what's new in #Serverless and #Data at GCP. Our guest, Guillaume Blaquiere - Stack Overflow contributor & #GCP #Developer Expert from France, covered the best #GoogleCloudNext announcements, practically demoed how to benefit from #BigQuery Remote Functions and answered many questions.
The meetup recording with TOC for easy navigation is at https://youtu.be/AuZZTwHIcdY
P.S. For more interactive lectures like this, go to http://youtube.serverlesstoronto.org/ or sign up for our upcoming live events at https://www.meetup.com/Serverless-Toronto/events/
ALT-F1.BE : The Accelerator (Google Cloud Platform)Abdelkrim Boujraf
The Accelerator is an IT infrastructure able to collect and analyze a massive amount of public data on the WWW.
The Accelerator leverages the untapped potential of web data with the first solution designed for diverse sectors,
completely scalable, available on-premise, and cloud-provider agnostic.
Building IoT Apps in the Cloud WebinarDreamFactory
Ben Busse of DreamFactory and Nat Frampton of FramTack talk about architecting IoT apps in the cloud, including:
- How FramTack is architecting IoT apps for the cloud
- The importance of open standards for IoT
- How DreamFactory helps FramTack develop and deploy IoT apps in the cloud
- Demo of FramTack's Solution Family product for IoT
You can also view the webinar recording here https://www.youtube.com/watch?v=SYd6wcMt_aQ
The Busy Bee Platform allows users to write business logic once using simple XML and JavaScript and automatically generates apps for multiple platforms. It handles all the complexities of application development across devices and interfaces, including security, scalability, database management, and analytics. Case studies demonstrate how modules can be added and synced across devices for applications like a connected fork, quadcopter, mobile sales app, and smart car. The platform offers flexible pricing plans tailored for individuals, small/medium enterprises, and large enterprises.
This document describes setting up an Internet of Things (IoT) system using Amazon Web Services (AWS) to simulate jet engine and environmental sensor data. It involves:
1. Registering devices ("things") in the AWS IoT registry and attaching security policies to allow communication.
2. Creating rules to publish device data to a DynamoDB database and send email alerts using Simple Notification Service (SNS).
3. Simulating device data from a laptop and Raspberry Pi, including jet engine readings and rainfall data downloaded from a government site. The Raspberry Pi also self-monitors temperature and triggers alerts.
The document describes building an Azure IoT controlled device using a WeMos D1 Mini and relay shield to create a flood detection device. It discusses connecting the device to Azure IoT Hub using the C SDK and setting up logic in Azure functions and Logic Apps to send alert emails and SMS messages when flooding is detected. It also provides an overview of Azure IoT Hub capabilities including device twins, direct methods, and protocols.
Ankit Saini presented on cloud computing, beginning with an introduction that cloud computing uses remote servers and the internet to maintain data and applications. The presentation defined cloud computing, discussed deployment models including public, private and hybrid clouds, and service models including infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS). Key cloud computing providers and their services were also outlined, such as Amazon Web Services which provides elastic compute cloud (EC2), simple storage service (S3), simple queue service (SQS), and simple database service (SDB).
This document contains the slides and script for a presentation on Windows Azure by John Weston from Microsoft. The presentation introduces cloud computing and defines it as running applications using shared computing resources that can scale on demand. It outlines the components of the Windows Azure platform including compute, storage, databases and services. It discusses how to get started with Windows Azure and pricing models. It also previews upcoming features like pre-configured virtual machines and enhanced storage capabilities. The goal is to answer questions about cloud computing, Microsoft's commitment to it, what Windows Azure is, cost savings potential, and its future direction.
Similar to Prototyping your Next Big Idea - An introduction to Google Cloud Platform (20)
Introducing Milvus Lite: Easy-to-Install, Easy-to-Use vector database for you...Zilliz
Join us to introduce Milvus Lite, a vector database that can run on notebooks and laptops, share the same API with Milvus, and integrate with every popular GenAI framework. This webinar is perfect for developers seeking easy-to-use, well-integrated vector databases for their GenAI apps.
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
20 Comprehensive Checklist of Designing and Developing a WebsitePixlogix Infotech
Dive into the world of Website Designing and Developing with Pixlogix! Looking to create a stunning online presence? Look no further! Our comprehensive checklist covers everything you need to know to craft a website that stands out. From user-friendly design to seamless functionality, we've got you covered. Don't miss out on this invaluable resource! Check out our checklist now at Pixlogix and start your journey towards a captivating online presence today.
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfMalak Abu Hammad
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!SOFTTECHHUB
As the digital landscape continually evolves, operating systems play a critical role in shaping user experiences and productivity. The launch of Nitrux Linux 3.5.0 marks a significant milestone, offering a robust alternative to traditional systems such as Windows 11. This article delves into the essence of Nitrux Linux 3.5.0, exploring its unique features, advantages, and how it stands as a compelling choice for both casual users and tech enthusiasts.
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024Neo4j
Neha Bajwa, Vice President of Product Marketing, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
Building RAG with self-deployed Milvus vector database and Snowpark Container...Zilliz
This talk will give hands-on advice on building RAG applications with an open-source Milvus database deployed as a docker container. We will also introduce the integration of Milvus with Snowpark Container Services.
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Full-RAG: A modern architecture for hyper-personalizationZilliz
Mike Del Balso, CEO & Co-Founder at Tecton, presents "Full RAG," a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Speck&Tech
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
6. Break into three steps
Weather
API data
Data
Processing
IOT
devices
Sent for
Send
configuration
changes to
Website that allows users to
choose a weather,
then send weather data
1 2 3
13. {“weather”: “sunny”} ? {“fan”:”on”,
“umbrella” : “open”
“menu” :
“menu_for_sunny_days”}
What goes in here?
14. Cloud Functions
Serverless, scalable functions
Used to connect services together
Can be triggered via HTTP
Just pass it a function and it will take care of provisioning an instance to run the
function on
15. Use Cloud Functions to convert Weather data to
Device Configuration data
Fan Umbrella Menu Recommendation
Sunny On Open Sunny
Cloudy Off Close Cloudy
Rainy On Open Rainy
{“weather” : “sunny”} is converted to {“fan” : “on”,
“umbrella” : open”,
“menu” : “sunny”}
Devices
Weather
16. So far..
Getting weather data
Website (normally a
weather API)
Updates
current
weather
Database
Sends
weather
data
Updates
database
Data Processing
?
Cloud
Functions
Sends New
Device
Configuration
17. Step 3: Build the hardware, connect
them to the cloud
18. Things I used:
1. Motors and servos
2. Raspberry Pi: a miniature computer
a. Its GPIO pins allow it to control devices eg. Motors
3. Cloud IoT Core - a service to connect devices into Google Cloud Platform
Cloud
IoT Core
Sends
configuration
changes to controls Servos and
motors
19. Cloud IoT Core
Use it to manage fleets of IoT devices and handle
authentication
Authentication: Private/public key pairs and JSON
Web tokens
Connects to IoT devices through MQTT or HTTP
protocol
20. Cloud IoT Core: Sending and Receiving Data
It does two main things:
1. Send data (telemetry, state data)
2. Receive data (configuration changes, one off commands)
In the case of telemetry data, data sent to Cloud Pubsub
For configuration changes, data is sent to devices via MQTT
connection
21. Cloud IoT Core
Client on Raspberry Pi listens for configuration changes over MQTT connection
On change in configuration, the Raspberry Pi will configure the devices
accordingly
Devices Sunny Cloudy Rainy
Fan On On, at lower speed Off
Umbrella Open Close Open
Menu Sunny Cloudy Rainy
22. Cloud IoT
Core
Sends
configuration
changes to
controls
Servos and
motors
Configuring Iot Devices
Getting weather data
Website (normally a
weather API)
Updates current weather
Database
Sends weather data
Updates
database
Data Processing
Sends New
Device
Configuration
Cloud
Functions
The full project
24. Ways to get started!
Documentation
Codelabs
Cloud.google.com/blog
QWIKLABS (follow their twitter for info on free credits)
Free $300 USD Credits
Google Cloud Platform podcast
For startups: apply for $3000 in credits
There’s an easy solution to the two is to start small. Build a working prototype first as a small project. Then scale up. Today I will be telling you how you could get started, by introducing the basics of Google Cloud Platform
Different services covering all you need to build working products. Your everyday apps are built on the same backend system GCP has, YouTube, Gmail, drive 150 services, can be very overwhelming to get started. So, i’ll use the project I made for today’s showcase as an example, introduce you to the services I used. First, we come up with an idea
Okay okay, hear me out: Before you start pitching then
I will show you an example of a prototype of a project.
Getting the weather data:
For the purpose of the event, we will have a webpage
Backend figures out what devices do what when it’s sunny. Maps weather patterns to devices
Normally you would call an api to get the current weather and use that to configure your device, but weather variation do not change interestingly within the span of minutes. For the purposes of this demo , we have a web app to choose
(
It is currently ___ (current weather) ___
Google has many options for website hosting. App engine, container engine
What do we do with the weather data?
When you receive data from the API/web app need to convert it to instructions for devices. What does this?
Give it a function at it will run forever, spinning up instances only when needed
You can trigger it in one of three ways:
What do we do with the weather data?
Motors and servos the actual devices moving the umbrella, turn on fan etc
The raspberry pi is
Connecting traditionally unintelligent devices to the cloud.
MQTT is a lightweight messaging protocol optimized for unreliable networks
It is designed for connections with remote locations where a "small code footprint" is required or the network bandwidth is limited
A message broker and two types of clients. Receives all messages from clients.
Message broker and a number of cients
Devices are listening for configuration changes over the MQTT connection
Selling to restaurants everywhere a smart iot system
Cloud iot configurations
Cloud functions can do how many invocations.
Cloud firestore can store data
Fire base hosting: auto scaling
You are building on the shoulders on giants. Leverage the infrastructure they can give you to push forward your big plans
Okay, you’re interested, now how to get started?
QWIKLABS
Nothing beats actually doing its free credits
If you’re a startup, DevFest you can apply up to 3000 credits
Blog contains case studies of what other companies have done