Cloud-Quake , Global Azure Bootcamp 2016
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Adobe AEM Managed Services started deploying Production AEM workloads on Azure in Nov 2017. In this session, we will share our learnings and offer advice to those thinking about deploying their AEM workloads on Azure.Anton Boyko "The future of serverless computing"
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In my session I will talk about the current state and the future of serverless computing. I will show several demos that show how to start using serverless computing, what are the application scenarios for it, how it can scale, what it will cost, etc.
This session will be useful for developers and architects who are seeking a way to create an app utilizing all your previous skills, but make it scalable, reliable, fast and cost efficient.
Mod05lec24(resource mgmt i)
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Automation for cloud
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Anton Boyko, "The evolution of microservices platform or marketing gibberish"
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TechTalk_Cloud Performance Testing_0.6
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Performance Evaluation and Tuning of Virtual Infrastructure Managers for (Micro) Virtual Network Functions
Virtualized Network Functions (VNFs) are emerging as the keystone of 5G network architectures: flexibility, agility, fast instantiation times, consolidation, Commercial Off The Shelf (COTS) hardware support and significant cost savings are fundamental for meeting the requirements of the new generation of mobile networks. In this paper we deal with the management of the virtual computing resources for the execution of Micro VNFs. This functionality is performed by the Virtual Infrastructure Manager (VIM) in the NFV MANagement and Orchestration (MANO) reference architecture. We discuss the VIM instantiation process and propose a generic reference model, starting from the analysis of two Open Source VIMs, namely OpenStack Nova and Nomad. We implemented a tuned version of the VIMs with the specific goal of reducing the duration of the instantiation process. We realized a performance comparison of the two VIMs, both considering the plain and the tuned versions. The tuned VIMs and the performance evaluation tools that we have employed are provided openly and can be downloaded from our repository.
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cloud_futures_2.0_Papazachos
This document proposes using cloud computing to rapidly generate earthquake shake maps through stochastic simulations. It describes implementing a map-reduce model on the Microsoft Azure cloud to parallelize simulations for many receivers after an earthquake. Results like peak ground acceleration maps could be produced within minutes to aid scientists and emergency responders. The method was tested in Greece and provides a cost-effective way to process simulations as needed without dedicated computing resources.
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George Spyrou presented on developing a speech to text component using Azure Logic Apps and Cognitive Services. The architecture uses Azure Active Directory, App Service, Azure SQL Database, Logic Apps, Functions and Cognitive Services. It also uses Azure Blob Storage and Azure Queue Storage. The presentation included a demo and references to Logic Apps, Speech to Text, FFmpeg, Xabe.FFmpeg, Azure Data Movement Library, and the CdT transcription service.
Global Azure 2020 - Developing a Speech to Text component
This document discusses developing a speech to text component using Azure services like Logic Apps, Cognitive Services, and Azure storage. It describes an architecture that uses Azure Active Directory, App Service, SQL Database, Logic Apps, Functions, and Blob Storage. It also provides a demo and references for Logic Apps, Speech to Text, FFmpeg, and Xabe.FFmpeg. The document is authored by George Spyrou from Intrasoft International SA.
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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.
Azure Global Bootcamp 2017 - Microsoft Cognitive Services
Microsoft Cognitive Services are a set of APIs, SDKs, and services that allow developers to make applications more intelligent, engaging, and discoverable by incorporating capabilities like speech recognition, language processing, and facial recognition. The presentation introduced Cognitive Services APIs and their development setup, and demonstrated the Speech API through a text-to-speech demo using Speech Synthesis Markup Language.
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This document discusses cross-platform mobile development using Xamarin. It notes that while native mobile apps require separate codebases for each platform, Xamarin allows sharing of C# code across iOS, Android, and Windows apps while providing full native API access and high performance. Xamarin.Forms takes this further by allowing shared UI code and a common backend across platforms. Resources for downloading Xamarin, sample apps, and learning materials are also provided.
AirNow app presentation at EUAPPCUP competition
The AirNow app provides air quality and pollution level data for major cities from the European Environmental Agency and U.S. Environmental Protection Agency. It has been downloaded over 10,000 times since December 2013 and is featured in app stores in several countries. Future plans for the app include adding support for more Chinese cities and a paid version with push notifications.
Appcampus Alumni activities
George Spyrou organized the first year activities for Appcampus alumni which included establishing a LinkedIn group with 103 members, a Twitter account with 71 followers, and a Facebook group for community engagement. Beta testing opportunities were provided through a website for teams to find additional testers. Alumni also used mailing lists for skills sharing, help requests, and announcing app launches. VisionMobile and Gengo services were contacted but only Gengo offered discounts through API access.
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Cloud-Quake , Global Azure Bootcamp 2016
- 1. Cloud-Quake Collection and public Dissemination of near-real time earthquake shaking information using Azure George Spyrou , Software Engineer
- 2. Cloud-Quake
- 3. The problem: Minimize the execution time for shake maps calculations in near real time
- 4. SMSIM , Fortran programs for simulating ground motions from earthquakes • Console application • Written in Fortran • Text files as input & output • Execution time ~ 2 minutes / station • Independent calculation for each station
- 5. Architecture Worker roles Table storage Blob storage Queue storage Management API
- 6. Geophysics lab (Linux) Azure cloud Earthquake queue Start cloud service Stations Results Shake map Partition Reducer Simulation
- 7. Demo
- 9. Benefits • Execution time was minimized to < 10 minutes • Reduced cost because the Cloud-Quake is executed only a few times per month • No need for maintaining infrastructure
- 10. Thank you :) George Spyrou george@plusapps.eu @gspyrou http://www.linkedin.com/in/gspyrou