How to setup a REST API with Google Cloud Functions, Express and Google Cloud Datastore in less than 30 minutes.
Demo Code is available at https://github.com/Pindar/demo-cloud-functions-express-api
https://goo.gl/8KXPoA
The document compares the service reliability of major cloud computing providers in 2014 by measuring their downtime hours, number of outages, and annual availability percentage. Microsoft Azure had the most total downtime hours at 43.1 while Amazon S3 had the fewest outages at 3. Amazon S3 and Azure Object Storage had the highest availability at over 99.99%. The document concludes by stating that RapidScale offers a 100% uptime guarantee for more reliable business continuity than the other providers.
This document discusses options for deploying microservices on DigitalOcean using container orchestration tools. It describes Dokku, Docker Swarm, and Kubernetes. Dokku is suited for single server use and extensibility with plugins. Docker Swarm provides native clustering with simple setup but less maturity than other tools. Kubernetes has a strong community, supports multiple container types, and uses etcd for cluster state storage, but has a more complex setup. The document also provides next steps like centralized logging, monitoring, and provisioning automation once a cluster is established. It emphasizes doing the simplest thing to get started and considering your specific context when choosing tools.
This document discusses continuous integration and continuous deployment (CI/CD) with Docker and Kubernetes. It begins with an introduction to the presenter and an overview of previous parts of an AKS learning series. The document then covers CI/CD topics like building pipelines in Azure DevOps, deploying containers to an AKS cluster using kubectl and Helm, and references additional resources. Code demonstrations are provided for CI with Build Pipelines, continuous deployment to AKS with kubectl and Helm, and a release pipeline.
Distributed Programming with GridGain and ScalaCodemotion
This document provides an overview of GridGain and Scala for cloud computing. It includes an agenda that is 10% talking and 90% live coding. Key facts about GridGain note over 1,000,000 starts worldwide each month. GridGain provides a compute grid (MapReduce) and data grid (distributed cache) with zero deployment and auto scaling for Java and Scala. The live coding demo will show a Scala-based cloud application deployed in 2 minutes without any pre-built code. Q&A follows the presentation.
Debug and Monitor Multi-container Apps on AKSNilesh Gule
The slides are related to Azure learning series Hands on series. This is the fifth part of the series where we cover the debugging and monitoring containers deployed to a managed Kubernetes cluster. The Kubernetes cluster is provisioned using Azure Kubernetes Service (AKS). Azure container monitoring is used as one of the options. For the open source solution, we liked at Prometheus and Grafana.
Azure kubernetes service (aks) part 4 - Deploy multi-container app to AKS c...Nilesh Gule
Slidedeck of the presentation done as part of Learning AKS Hands on series. The session covered provisioning of AKS cluster using Azure CLI and Azure portal. The multi container tech talks applications was deployed to the ASK cluster. The persistent state management was handled using Kubernetes Persistence Volumes and Persistent Volume Claims backed by Azure disks.
The document compares the service reliability of major cloud computing providers in 2014 by measuring their downtime hours, number of outages, and annual availability percentage. Microsoft Azure had the most total downtime hours at 43.1 while Amazon S3 had the fewest outages at 3. Amazon S3 and Azure Object Storage had the highest availability at over 99.99%. The document concludes by stating that RapidScale offers a 100% uptime guarantee for more reliable business continuity than the other providers.
This document discusses options for deploying microservices on DigitalOcean using container orchestration tools. It describes Dokku, Docker Swarm, and Kubernetes. Dokku is suited for single server use and extensibility with plugins. Docker Swarm provides native clustering with simple setup but less maturity than other tools. Kubernetes has a strong community, supports multiple container types, and uses etcd for cluster state storage, but has a more complex setup. The document also provides next steps like centralized logging, monitoring, and provisioning automation once a cluster is established. It emphasizes doing the simplest thing to get started and considering your specific context when choosing tools.
This document discusses continuous integration and continuous deployment (CI/CD) with Docker and Kubernetes. It begins with an introduction to the presenter and an overview of previous parts of an AKS learning series. The document then covers CI/CD topics like building pipelines in Azure DevOps, deploying containers to an AKS cluster using kubectl and Helm, and references additional resources. Code demonstrations are provided for CI with Build Pipelines, continuous deployment to AKS with kubectl and Helm, and a release pipeline.
Distributed Programming with GridGain and ScalaCodemotion
This document provides an overview of GridGain and Scala for cloud computing. It includes an agenda that is 10% talking and 90% live coding. Key facts about GridGain note over 1,000,000 starts worldwide each month. GridGain provides a compute grid (MapReduce) and data grid (distributed cache) with zero deployment and auto scaling for Java and Scala. The live coding demo will show a Scala-based cloud application deployed in 2 minutes without any pre-built code. Q&A follows the presentation.
Debug and Monitor Multi-container Apps on AKSNilesh Gule
The slides are related to Azure learning series Hands on series. This is the fifth part of the series where we cover the debugging and monitoring containers deployed to a managed Kubernetes cluster. The Kubernetes cluster is provisioned using Azure Kubernetes Service (AKS). Azure container monitoring is used as one of the options. For the open source solution, we liked at Prometheus and Grafana.
Azure kubernetes service (aks) part 4 - Deploy multi-container app to AKS c...Nilesh Gule
Slidedeck of the presentation done as part of Learning AKS Hands on series. The session covered provisioning of AKS cluster using Azure CLI and Azure portal. The multi container tech talks applications was deployed to the ASK cluster. The persistent state management was handled using Kubernetes Persistence Volumes and Persistent Volume Claims backed by Azure disks.
Alexandr Marchenko "Kubernetes - easy peasy"Fwdays
So here we have our brand new app, but how about its deployment, autoscale, high availability and so on?
We're gonna take a journey from source code posted to GitHub to deployment in Google Cloud Platform which will be capable to take bazillion of requests.
Will make our own docker image and see how it is looks like in practice.
Will start our first kubernetes cluster and deploy our app.
Will have a sneak peak into autoscaler and high availability
Meteor platform presentation made at Javascript Meetup in Chisinau, Moldova. This presentation makes a short introduction to the platform and its features.
This document summarizes an introduction to the Meteor.js framework. It outlines what will be covered, including how the presenter got started, a hello world example, architectural insights, and resources. The presentation discusses key aspects of Meteor.js like using the same code for all platforms, and how it allows full-stack JavaScript development with real-time data synchronization.
CloudStack / Saltstack lightning talk at DevOps AmsterdamSebastien Goasguen
CloudStack is an open source cloud computing platform that allows management of virtual servers and storage. SaltStack allows configuration management of those servers. Libcloud provides a Python API to interface with multiple cloud providers including CloudStack. The Salt Cloud module uses libcloud to provision nodes on CloudStack and configure them using SaltStack. This allows defining profiles for nodes to deploy on CloudStack and provisioning them using Salt Cloud commands.
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.
Meteor is a full stack JavaScript framework that allows building reactive web and mobile applications quickly. It uses MongoDB, Node.js and packages to build apps. Apps can be created with a single command and include templates, collections, publications and subscriptions to manage data reactivity. Meteor apps can also be deployed easily to meteor.com or other servers using mup.
Core AWS services in the presentation with AWS logos.
- Diagram of a Basic AWS VPC Infrastracutre
- Diagram of Highly Available & Fault Tolerant Systems
- Example of the Application Load Balancer and how it routes traffic.
- A project based on AWS Lambda, API Gateway and DynamoDB.
Getting started with Azure Machine Learning StudioGeorge Spyrou
This document discusses using Azure Machine Learning Studio to build a machine learning model. It describes defining a problem, preparing earthquake data, training a classification model, publishing a web service, and testing the service. The architecture connects a seismological station to Azure services like queues, functions, and storage to analyze earthquake data and notify personnel via speech API. Azure Machine Learning Studio is highlighted as a fully-managed cloud service to easily build, deploy, and share predictive analytics solutions.
[GCP Summit 2018] Kubernetes with Nginx and Elasticsearch on GCP용호 최
The document describes setting up a Kubernetes cluster on Google Cloud Platform with Nginx, Elasticsearch, and a Node.js web service. It defines user scenarios for full-text search, autocomplete, and aggregated search results. Diagrams show the search flow and simple Kubernetes architecture. The process documented the deployment of Elasticsearch on Kubernetes using clusters, services for discovery and load balancing, and configurations for the web service and Elasticsearch deployments and services.
Cheat sheet compare AWS and azure computingGanesh Pol
AWS and Azure both provide virtual machines and serverless compute options. Some key differences are:
AWS offers EC2 instances and Elastic Beanstalk while Azure has Virtual Machines and Application Service. Lambda supports more languages than Azure Functions but throttles after 300 seconds while Azure Functions has no time restriction. Both platforms offer container registry and orchestration services like ECS, AKS, and ACS but Azure also has Event Grid and Service Fabric.
Kubernetes is an open-source tool for automating deployment, scaling, and load balancing of containerized applications. It groups containers into logical units and manages deploying applications across clusters of nodes. Kubernetes allows scaling containers up and down as needed. It provides a dashboard and commands to configure a master node and join additional nodes to the cluster. Microservices break large applications into autonomous services, each focused on a single business capability. They allow independent development, deployment, and fault isolation of services using different technologies.
Experimenting and Learning Kubernetes and TensorflowBen Hall
This document discusses experimenting with Kubernetes and Tensorflow. It begins with an introduction of the author and overview of learning via interactive browser-based labs on Katacoda.com. Then it demonstrates setting up Minikube and Kubeadm to create Kubernetes clusters, deploying Tensorflow models and services on Kubernetes using Deployments and Jobs, and considerations for scaling Kubernetes and Tensorflow workloads. It concludes with a call to action for others to share their experiences by writing scenarios on Katacoda.
This document discusses Elasticsearch and compares it to Keboola. It mentions that Keboola Connection provides storage, API, console, extractors, and event handling for MySQL and Elasticsearch. It also discusses Keboola's provisioning of AWS resources using Cloudformation templates and Chef for installing software and configuring instances.
We are using Elasticsearch to power the search feature of our public frontend, serving 10k queries per hour across 8 markets in SEA.
Here we are sharing our experiences of running Elasticsearch on Kubernetes, presenting our general setup, configuration tweaks and possible pitfalls.
Meteor is a JavaScript platform for building mobile and web applications. It allows developers to use JavaScript on both the client and server, write code that is shared between client and server, and automatically syncs data between clients in real-time. The seven principles of Meteor are data on the wire, one language, database everywhere, latency compensation, full stack reactivity, embrace the ecosystem, and simplicity equals productivity. To get started with Meteor, install Node.js and Meteor, create an example app, and run it. File structure separates code by server, client, and common functionality.
Master your Kubernetes Stack and your Cloud Services with Open Service BrokerSandra Ahlgrimm
Kubernetes is allowing seamless integration with the vast array of service brokers available in the microservice-based software ecosystem via the Service Catalog. The Open Service Broker API is an industry standard that allows service operators to integrate with multiple platforms using a single API specification. This session showcases the usage of the Open Service Broker and the Service Catalog.
Speaker: Sandra Kriemann, @skriemhild
Cloud Developer Advocate, focusing on Open Source Technologies especially Containers.
Building a chrome extension with meteorJonathan Perl
This document discusses building Chrome extensions using Meteor. It covers why build extensions, the main parts of extensions like HTML/CSS, JavaScript and Chrome APIs, and UI elements like browser actions and popups. It then explains how Meteor can be used to build extensions, including using Meteor-DDP to communicate between the extension and Meteor app server, and how to handle more complex use cases like the Code Bounty extension. Resources for learning more are provided at the end.
This document discusses deploying Mattermost, an open source Slack-alternative, on Azure Kubernetes Service (AKS). It outlines configuring AKS, deploying Kubernetes resources like Mattermost, Prometheus and Grafana using tools like Terraform and Helm. Future prospects discussed include adding logging with Fluentd, continuous delivery with Spinnaker/Tekton, and a service mesh like Istio. The GitHub source provided does not include a database, which must be provisioned separately beforehand using Azure Database for PostgreSQL.
Idea to Production - with Gitlab and KubernetesSimon Dittlmann
Setting up a continuous delivery pipeline form scratch with gitlab.com and Kubernetes (Google Container Service GKE) on Google Cloud Platform.
The entire source code is available at https://github.com/Pindar/gcloud-k8s-express-app
Blog post https://www.itnotes.de/gitlab/kubernetes/k8s/gke/gcloud/2017/03/05/idea-to-production-with-gitlab-and-kubernetes/
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.
Alexandr Marchenko "Kubernetes - easy peasy"Fwdays
So here we have our brand new app, but how about its deployment, autoscale, high availability and so on?
We're gonna take a journey from source code posted to GitHub to deployment in Google Cloud Platform which will be capable to take bazillion of requests.
Will make our own docker image and see how it is looks like in practice.
Will start our first kubernetes cluster and deploy our app.
Will have a sneak peak into autoscaler and high availability
Meteor platform presentation made at Javascript Meetup in Chisinau, Moldova. This presentation makes a short introduction to the platform and its features.
This document summarizes an introduction to the Meteor.js framework. It outlines what will be covered, including how the presenter got started, a hello world example, architectural insights, and resources. The presentation discusses key aspects of Meteor.js like using the same code for all platforms, and how it allows full-stack JavaScript development with real-time data synchronization.
CloudStack / Saltstack lightning talk at DevOps AmsterdamSebastien Goasguen
CloudStack is an open source cloud computing platform that allows management of virtual servers and storage. SaltStack allows configuration management of those servers. Libcloud provides a Python API to interface with multiple cloud providers including CloudStack. The Salt Cloud module uses libcloud to provision nodes on CloudStack and configure them using SaltStack. This allows defining profiles for nodes to deploy on CloudStack and provisioning them using Salt Cloud commands.
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.
Meteor is a full stack JavaScript framework that allows building reactive web and mobile applications quickly. It uses MongoDB, Node.js and packages to build apps. Apps can be created with a single command and include templates, collections, publications and subscriptions to manage data reactivity. Meteor apps can also be deployed easily to meteor.com or other servers using mup.
Core AWS services in the presentation with AWS logos.
- Diagram of a Basic AWS VPC Infrastracutre
- Diagram of Highly Available & Fault Tolerant Systems
- Example of the Application Load Balancer and how it routes traffic.
- A project based on AWS Lambda, API Gateway and DynamoDB.
Getting started with Azure Machine Learning StudioGeorge Spyrou
This document discusses using Azure Machine Learning Studio to build a machine learning model. It describes defining a problem, preparing earthquake data, training a classification model, publishing a web service, and testing the service. The architecture connects a seismological station to Azure services like queues, functions, and storage to analyze earthquake data and notify personnel via speech API. Azure Machine Learning Studio is highlighted as a fully-managed cloud service to easily build, deploy, and share predictive analytics solutions.
[GCP Summit 2018] Kubernetes with Nginx and Elasticsearch on GCP용호 최
The document describes setting up a Kubernetes cluster on Google Cloud Platform with Nginx, Elasticsearch, and a Node.js web service. It defines user scenarios for full-text search, autocomplete, and aggregated search results. Diagrams show the search flow and simple Kubernetes architecture. The process documented the deployment of Elasticsearch on Kubernetes using clusters, services for discovery and load balancing, and configurations for the web service and Elasticsearch deployments and services.
Cheat sheet compare AWS and azure computingGanesh Pol
AWS and Azure both provide virtual machines and serverless compute options. Some key differences are:
AWS offers EC2 instances and Elastic Beanstalk while Azure has Virtual Machines and Application Service. Lambda supports more languages than Azure Functions but throttles after 300 seconds while Azure Functions has no time restriction. Both platforms offer container registry and orchestration services like ECS, AKS, and ACS but Azure also has Event Grid and Service Fabric.
Kubernetes is an open-source tool for automating deployment, scaling, and load balancing of containerized applications. It groups containers into logical units and manages deploying applications across clusters of nodes. Kubernetes allows scaling containers up and down as needed. It provides a dashboard and commands to configure a master node and join additional nodes to the cluster. Microservices break large applications into autonomous services, each focused on a single business capability. They allow independent development, deployment, and fault isolation of services using different technologies.
Experimenting and Learning Kubernetes and TensorflowBen Hall
This document discusses experimenting with Kubernetes and Tensorflow. It begins with an introduction of the author and overview of learning via interactive browser-based labs on Katacoda.com. Then it demonstrates setting up Minikube and Kubeadm to create Kubernetes clusters, deploying Tensorflow models and services on Kubernetes using Deployments and Jobs, and considerations for scaling Kubernetes and Tensorflow workloads. It concludes with a call to action for others to share their experiences by writing scenarios on Katacoda.
This document discusses Elasticsearch and compares it to Keboola. It mentions that Keboola Connection provides storage, API, console, extractors, and event handling for MySQL and Elasticsearch. It also discusses Keboola's provisioning of AWS resources using Cloudformation templates and Chef for installing software and configuring instances.
We are using Elasticsearch to power the search feature of our public frontend, serving 10k queries per hour across 8 markets in SEA.
Here we are sharing our experiences of running Elasticsearch on Kubernetes, presenting our general setup, configuration tweaks and possible pitfalls.
Meteor is a JavaScript platform for building mobile and web applications. It allows developers to use JavaScript on both the client and server, write code that is shared between client and server, and automatically syncs data between clients in real-time. The seven principles of Meteor are data on the wire, one language, database everywhere, latency compensation, full stack reactivity, embrace the ecosystem, and simplicity equals productivity. To get started with Meteor, install Node.js and Meteor, create an example app, and run it. File structure separates code by server, client, and common functionality.
Master your Kubernetes Stack and your Cloud Services with Open Service BrokerSandra Ahlgrimm
Kubernetes is allowing seamless integration with the vast array of service brokers available in the microservice-based software ecosystem via the Service Catalog. The Open Service Broker API is an industry standard that allows service operators to integrate with multiple platforms using a single API specification. This session showcases the usage of the Open Service Broker and the Service Catalog.
Speaker: Sandra Kriemann, @skriemhild
Cloud Developer Advocate, focusing on Open Source Technologies especially Containers.
Building a chrome extension with meteorJonathan Perl
This document discusses building Chrome extensions using Meteor. It covers why build extensions, the main parts of extensions like HTML/CSS, JavaScript and Chrome APIs, and UI elements like browser actions and popups. It then explains how Meteor can be used to build extensions, including using Meteor-DDP to communicate between the extension and Meteor app server, and how to handle more complex use cases like the Code Bounty extension. Resources for learning more are provided at the end.
This document discusses deploying Mattermost, an open source Slack-alternative, on Azure Kubernetes Service (AKS). It outlines configuring AKS, deploying Kubernetes resources like Mattermost, Prometheus and Grafana using tools like Terraform and Helm. Future prospects discussed include adding logging with Fluentd, continuous delivery with Spinnaker/Tekton, and a service mesh like Istio. The GitHub source provided does not include a database, which must be provisioned separately beforehand using Azure Database for PostgreSQL.
Idea to Production - with Gitlab and KubernetesSimon Dittlmann
Setting up a continuous delivery pipeline form scratch with gitlab.com and Kubernetes (Google Container Service GKE) on Google Cloud Platform.
The entire source code is available at https://github.com/Pindar/gcloud-k8s-express-app
Blog post https://www.itnotes.de/gitlab/kubernetes/k8s/gke/gcloud/2017/03/05/idea-to-production-with-gitlab-and-kubernetes/
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.
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.
This session will cover the development & deployment of containerized ASP.NET Core 6 apps using Docker and Azure and architectural design & implementation approaches using .NET and Docker containers. The different services to deploy on Azure like Azure Container Registry, Azure Container instance, Azure Container Apps, and Azure Kubernetes Services as an orchestrator will be reviewed. We will also create the different resources and explore the different tools and properties if attendees prefer not to use Docker-Compose.yml. Then we will deploy our application that's based on Docker images using Azure App Service. And finally, we will configure continuous deployment for our web app with a webhook that monitors changes to the Docker image.
https://conferences.techwell.com/archives/agiledevopswest-2023/program/concurrent-sessions/build-containerized-applications-using-docker-and-azure-agile-devops-west-2023.html
This document discusses connecting a Raspberry Pi to Google Cloud services like Cloud IoT Core and Cloud Pub/Sub. It provides steps to install the Google Cloud SDK on the Raspberry Pi, register a device in Cloud IoT Core, and use an MQTT client on the Raspberry Pi to publish sensor data to Cloud Pub/Sub. The document also introduces Google Cloud Messaging architecture and services in the Google Cloud IoT platform.
Cloud Run - the rise of serverless and containerizationMárton Kodok
Cloud Run allows developers to deploy containerized applications in a serverless fashion without having to manage infrastructure. It brings the benefits of serverless computing like autoscaling and pay-per-use billing to containers. The presentation covers how to build, deploy and optimize applications on Cloud Run including mitigating cold starts through techniques like minimum instances, CPU boosting, and using leaner base images. It also demonstrates how to integrate DockerSlim for container size optimization and security hardening. In conclusion, Cloud Run provides a simple developer experience for building and managing containerized applications at scale in a serverless way.
Skill Petals - Google Associate Cloud Engineer GCP-ACE Syllabus.pdfthinkcomtech
Skill Petals is providing a GCP - Associate Cloud Engineer Certificate after successful completion of Google Cloud Platform- Associate Cloud Engineer Course. Find the complete syllabus of this cloud computing global certification training program. Add this global certification to your cv along with all your relevant skills.
code lab live Google Cloud Endpoints [DevFest 2015 Bari]Nicola Policoro
Google Cloud Platform provides scalable infrastructure and services like Compute Engine, App Engine, Cloud Storage, and Cloud Endpoints. Cloud Endpoints allows for building server-side logic on App Engine and auto-generates client libraries for Android, iOS, and web apps. It exposes REST APIs with built-in authorization. The demo shows creating an App Engine backend with Cloud Endpoints and generating Java client libraries for use in an Android app.
The document provides an overview of Google Cloud Storage including key concepts like buckets, objects, storage classes, encryption, versioning, access controls, and retention policies. It also describes how to configure and use object lifecycle management and signed URLs with Cloud Storage. Hands-on examples are provided to demonstrate common Cloud Storage tasks.
Here's an intro to the 30 Days of Google Cloud program to kickstart your career in the cloud as well as earn exciting prizes & digital badges. To start with, your facilitator, Mohini Gupta, will be taking you on board this journey, explaining you these :
1.) Introduction to the program
2.) About GCP Crash Course
3.) A Tour of Qwiklabs and the Google Cloud Platform Lab
4.) Hands-on lab experience
Deploy With Codefresh to Kubernetes in 3 stepsJenny Passi
This document provides a 3-step process for deploying an application to Kubernetes using Codefresh and Google Kubernetes Engine (GKE).
Step 1 is to add the Kubernetes cluster to Codefresh.
Step 2 is to deploy containers, demonstrated using a demo chat application with both public and private services deployed to the cluster.
Step 3 is to automate deployments by adding a deployment step to the Codefresh pipeline.
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.
Continuous Delivery of Cloud Applications with Docker Containers and IBM BluemixFlorian Georg
This document discusses continuous delivery of cloud applications using Docker containers on IBM Bluemix. It provides an overview of benefits of continuous delivery such as increased stability. It then discusses why containers and cloud PaaS platforms are useful for application development. It also demonstrates how to use the IBM Container Service to build, deploy and manage containerized applications on Bluemix through features like private registries, container groups, public IP binding, storage and integration with Cloud Foundry services. The document includes code samples and discusses using a delivery pipeline with Bluemix DevOps services to enable continuous deployment through staging and production environments.
This document outlines the agenda for a meetup on cloud computing hosted by StartupDecode. The meetup includes sessions on what cloud computing is, cloud computing on AWS, hands-on tutorials for Heroku and AWS, and a networking apéro. The hands-on portions will guide attendees on deploying a sample Rails app to Heroku with AWS S3 integration for file storage.
Cloud Computing:
Cloud computing is the delivery of different services through the Internet. These resources include tools and applications like data storage, servers, databases, networking, and software.
This document discusses IBM Bluemix and Docker. It provides an overview of Bluemix as an open standards cloud platform for building, running, and managing applications. It then discusses how Docker containers work and their benefits compared to virtual machines. Several demos are presented showing different scenarios for running a Node.js and CouchDB application locally and on Bluemix both traditionally and using Docker containers. References and documentation links are also provided.
February EPD Webinar: How do I...use PiCloud for cloud computing?Enthought, Inc.
In this Enthought Python Distribution Webinar, Ken Elkabany, co-founder of PiCloud, shows us how to run scientific and numeric Python code remotely on Amazon EC2. Through a partnership with Enthought, PiCloud now hosts EPD on it's cloud servers, allowing all EPD users to run their code remotely with ease. Several demonstrations are provided. For example code, visit http://enthought.com/training/webinars.php.
What is Augmented Reality Image Trackingpavan998932
Augmented Reality (AR) Image Tracking is a technology that enables AR applications to recognize and track images in the real world, overlaying digital content onto them. This enhances the user's interaction with their environment by providing additional information and interactive elements directly tied to physical images.
GraphSummit Paris - The art of the possible with Graph TechnologyNeo4j
Sudhir Hasbe, Chief Product Officer, 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.
Revolutionizing Visual Effects Mastering AI Face Swaps.pdfUndress Baby
The quest for the best AI face swap solution is marked by an amalgamation of technological prowess and artistic finesse, where cutting-edge algorithms seamlessly replace faces in images or videos with striking realism. Leveraging advanced deep learning techniques, the best AI face swap tools meticulously analyze facial features, lighting conditions, and expressions to execute flawless transformations, ensuring natural-looking results that blur the line between reality and illusion, captivating users with their ingenuity and sophistication.
Web:- https://undressbaby.com/
A Study of Variable-Role-based Feature Enrichment in Neural Models of CodeAftab Hussain
Understanding variable roles in code has been found to be helpful by students
in learning programming -- could variable roles help deep neural models in
performing coding tasks? We do an exploratory study.
- These are slides of the talk given at InteNSE'23: The 1st International Workshop on Interpretability and Robustness in Neural Software Engineering, co-located with the 45th International Conference on Software Engineering, ICSE 2023, Melbourne Australia
Measures in SQL (SIGMOD 2024, Santiago, Chile)Julian Hyde
SQL has attained widespread adoption, but Business Intelligence tools still use their own higher level languages based upon a multidimensional paradigm. Composable calculations are what is missing from SQL, and we propose a new kind of column, called a measure, that attaches a calculation to a table. Like regular tables, tables with measures are composable and closed when used in queries.
SQL-with-measures has the power, conciseness and reusability of multidimensional languages but retains SQL semantics. Measure invocations can be expanded in place to simple, clear SQL.
To define the evaluation semantics for measures, we introduce context-sensitive expressions (a way to evaluate multidimensional expressions that is consistent with existing SQL semantics), a concept called evaluation context, and several operations for setting and modifying the evaluation context.
A talk at SIGMOD, June 9–15, 2024, Santiago, Chile
Authors: Julian Hyde (Google) and John Fremlin (Google)
https://doi.org/10.1145/3626246.3653374
E-commerce Application Development Company.pdfHornet Dynamics
Your business can reach new heights with our assistance as we design solutions that are specifically appropriate for your goals and vision. Our eCommerce application solutions can digitally coordinate all retail operations processes to meet the demands of the marketplace while maintaining business continuity.
E-Invoicing Implementation: A Step-by-Step Guide for Saudi Arabian CompaniesQuickdice ERP
Explore the seamless transition to e-invoicing with this comprehensive guide tailored for Saudi Arabian businesses. Navigate the process effortlessly with step-by-step instructions designed to streamline implementation and enhance efficiency.
What is Master Data Management by PiLog Groupaymanquadri279
PiLog Group's Master Data Record Manager (MDRM) is a sophisticated enterprise solution designed to ensure data accuracy, consistency, and governance across various business functions. MDRM integrates advanced data management technologies to cleanse, classify, and standardize master data, thereby enhancing data quality and operational efficiency.
Zoom is a comprehensive platform designed to connect individuals and teams efficiently. With its user-friendly interface and powerful features, Zoom has become a go-to solution for virtual communication and collaboration. It offers a range of tools, including virtual meetings, team chat, VoIP phone systems, online whiteboards, and AI companions, to streamline workflows and enhance productivity.
Neo4j - Product Vision and Knowledge Graphs - GraphSummit ParisNeo4j
Dr. Jesús Barrasa, Head of Solutions Architecture for EMEA, Neo4j
Découvrez les dernières innovations de Neo4j, et notamment les dernières intégrations cloud et les améliorations produits qui font de Neo4j un choix essentiel pour les développeurs qui créent des applications avec des données interconnectées et de l’IA générative.
SOCRadar's Aviation Industry Q1 Incident Report is out now!
The aviation industry has always been a prime target for cybercriminals due to its critical infrastructure and high stakes. In the first quarter of 2024, the sector faced an alarming surge in cybersecurity threats, revealing its vulnerabilities and the relentless sophistication of cyber attackers.
SOCRadar’s Aviation Industry, Quarterly Incident Report, provides an in-depth analysis of these threats, detected and examined through our extensive monitoring of hacker forums, Telegram channels, and dark web platforms.
UI5con 2024 - Boost Your Development Experience with UI5 Tooling ExtensionsPeter Muessig
The UI5 tooling is the development and build tooling of UI5. It is built in a modular and extensible way so that it can be easily extended by your needs. This session will showcase various tooling extensions which can boost your development experience by far so that you can really work offline, transpile your code in your project to use even newer versions of EcmaScript (than 2022 which is supported right now by the UI5 tooling), consume any npm package of your choice in your project, using different kind of proxies, and even stitching UI5 projects during development together to mimic your target environment.
Need for Speed: Removing speed bumps from your Symfony projects ⚡️Łukasz Chruściel
No one wants their application to drag like a car stuck in the slow lane! Yet it’s all too common to encounter bumpy, pothole-filled solutions that slow the speed of any application. Symfony apps are not an exception.
In this talk, I will take you for a spin around the performance racetrack. We’ll explore common pitfalls - those hidden potholes on your application that can cause unexpected slowdowns. Learn how to spot these performance bumps early, and more importantly, how to navigate around them to keep your application running at top speed.
We will focus in particular on tuning your engine at the application level, making the right adjustments to ensure that your system responds like a well-oiled, high-performance race car.
Do you want Software for your Business? Visit Deuglo
Deuglo has top Software Developers in India. They are experts in software development and help design and create custom Software solutions.
Deuglo follows seven steps methods for delivering their services to their customers. They called it the Software development life cycle process (SDLC).
Requirement — Collecting the Requirements is the first Phase in the SSLC process.
Feasibility Study — after completing the requirement process they move to the design phase.
Design — in this phase, they start designing the software.
Coding — when designing is completed, the developers start coding for the software.
Testing — in this phase when the coding of the software is done the testing team will start testing.
Installation — after completion of testing, the application opens to the live server and launches!
Maintenance — after completing the software development, customers start using the software.
AI Fusion Buddy Review: Brand New, Groundbreaking Gemini-Powered AI AppGoogle
AI Fusion Buddy Review: Brand New, Groundbreaking Gemini-Powered AI App
👉👉 Click Here To Get More Info 👇👇
https://sumonreview.com/ai-fusion-buddy-review
AI Fusion Buddy Review: Key Features
✅Create Stunning AI App Suite Fully Powered By Google's Latest AI technology, Gemini
✅Use Gemini to Build high-converting Converting Sales Video Scripts, ad copies, Trending Articles, blogs, etc.100% unique!
✅Create Ultra-HD graphics with a single keyword or phrase that commands 10x eyeballs!
✅Fully automated AI articles bulk generation!
✅Auto-post or schedule stunning AI content across all your accounts at once—WordPress, Facebook, LinkedIn, Blogger, and more.
✅With one keyword or URL, generate complete websites, landing pages, and more…
✅Automatically create & sell AI content, graphics, websites, landing pages, & all that gets you paid non-stop 24*7.
✅Pre-built High-Converting 100+ website Templates and 2000+ graphic templates logos, banners, and thumbnail images in Trending Niches.
✅Say goodbye to wasting time logging into multiple Chat GPT & AI Apps once & for all!
✅Save over $5000 per year and kick out dependency on third parties completely!
✅Brand New App: Not available anywhere else!
✅ Beginner-friendly!
✅ZERO upfront cost or any extra expenses
✅Risk-Free: 30-Day Money-Back Guarantee!
✅Commercial License included!
See My Other Reviews Article:
(1) AI Genie Review: https://sumonreview.com/ai-genie-review
(2) SocioWave Review: https://sumonreview.com/sociowave-review
(3) AI Partner & Profit Review: https://sumonreview.com/ai-partner-profit-review
(4) AI Ebook Suite Review: https://sumonreview.com/ai-ebook-suite-review
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Graspan: A Big Data System for Big Code AnalysisAftab Hussain
We built a disk-based parallel graph system, Graspan, that uses a novel edge-pair centric computation model to compute dynamic transitive closures on very large program graphs.
We implement context-sensitive pointer/alias and dataflow analyses on Graspan. An evaluation of these analyses on large codebases such as Linux shows that their Graspan implementations scale to millions of lines of code and are much simpler than their original implementations.
These analyses were used to augment the existing checkers; these augmented checkers found 132 new NULL pointer bugs and 1308 unnecessary NULL tests in Linux 4.4.0-rc5, PostgreSQL 8.3.9, and Apache httpd 2.2.18.
- Accepted in ASPLOS ‘17, Xi’an, China.
- Featured in the tutorial, Systemized Program Analyses: A Big Data Perspective on Static Analysis Scalability, ASPLOS ‘17.
- Invited for presentation at SoCal PLS ‘16.
- Invited for poster presentation at PLDI SRC ‘16.
DDS Security Version 1.2 was adopted in 2024. This revision strengthens support for long runnings systems adding new cryptographic algorithms, certificate revocation, and hardness against DoS attacks.
DDS-Security 1.2 - What's New? Stronger security for long-running systems
Google Cloud Functions + Express
1. Cloud Functions + Express
…or how to implement a small REST API in less than 30 minutes
2. Who am I?
Simon Dittlmann
Saving the world from
toil since 1998
Developer/Ops,
technology nerd
@SinnerSchrader
#IoT, #docker, #js, #frontend,
#infrastructure, #kubernetes
Contact
SimonDittlmann
github.com/Pindar
dittlmann.com
3. What we’d like to achieve
1. Using Express Framework on Google Cloud Functions
2. Providing a very simple REST API to save blog posts
3. Saving data in Google’s Datastore
And everything in less than 30 Minutes.
4. 1 Setup Cloud
A. Create Google Cloud Project
B. Enable Google Cloud Functions
C. Enable Google Cloud Source
Repositories
D. Create Google Cloud Datastore
5. 2 Setup dev
environment
A. Create Source Repository
“comments-service”
B. Start Cloud Shell, clone
repository
C. Install dependencies:
- express
- gstore-api
- gstore-node
- @google-cloud/datastore
D. Write app.js, index.js and
blog-post.model.js
7. 3 Deploy
A. Run Cloud Function Deployment
B. Use your brand new API
CLI: gcloud beta functions deploy blogapi --source-url
https://source.developers.google.com/p/[PROJECT]/r/comments
-service --source-path / --trigger-http
9. Pro Tip
Setup Continuous Delivery Pipeline
1. Create Build Trigger
2. Create cloudbuild.yaml
3. Adjust Cloudbuild Service
Account IAM Roles according to
Cloud Functions Deployment
needs
10. ● An Object Document Mapping framework makes your life easy and makes
sure that everyone in the project knows the valid “schema”.
● Abstracting the REST-API into a framework like gstore-api shortens your
code-base dramatically and improves developer speed.
● Current implementation with gstore-api lacks on an API Documentation
like swagger.
But it should be possible to extend gstore-api to generate the Swagger API
documentation?!
Learnings
11. Q/A
…Kudos to Sébastien Loix for providing the awesome libraries!
PS: SinnerSchrader is hiring entire teams.