Azure provides cloud computing services including computing, analytics, networking, storage, and more. It offers virtual machines, databases, websites, and other services that can be accessed from anywhere and scaled up as needed. Azure aims to provide enterprise-grade services that are economical, scalable, and hybrid-ready to work with existing on-premises systems. It has data centers across the world and over 600,000 servers to provide its services globally at scale.
The document discusses microservices and provides information on:
- The benefits of microservices including faster time to market, lower deployment costs, and more revenue opportunities.
- What defines a microservice such as being independently deployable and scalable.
- Differences between monolithic and microservice architectures.
- Moving applications to the cloud and refactoring monolithic applications into microservices.
- Tools for building microservices including Azure Service Fabric and serverless/Functions.
- Best practices for developing, deploying, and managing microservices.
Researchers used deep learning techniques like ResNet and data augmentation to improve the accuracy of detecting snow leopards from 63.4% to 90%. They used transfer learning on a ResNet model to extract features from images, then trained a logistic regression classifier on those features to detect snow leopards. They also averaged predictions from multiple images and doubled their training data by flipping images horizontally. This helped improve the model's ability to identify snow leopards in photos.
This document discusses cloud-native applications and serverless computing. It begins with an introduction to cloud-native applications and core technologies like containers, orchestrators, and microservices. Examples are then given of how companies like Fujifilm and ASOS have benefited from serverless architectures on Azure. The document concludes with an overview of Azure serverless services like Functions, Event Grid, Cosmos DB, and Logic Apps and a sample serverless application architecture diagram.
Microsoft provides an AI platform and tools for developers to build, train, and deploy intelligent applications and services. Key elements of Microsoft's AI offerings include:
- A unified AI platform spanning infrastructure, tools, and services to make AI accessible and useful for every developer.
- Powerful tools for AI development including deep learning frameworks, coding and management tools, and AI services for tasks like computer vision, natural language processing, and more.
- Capabilities for training models at scale using GPU accelerated compute on Azure and deploying trained models as web APIs, mobile apps, or other applications.
- A focus on trusted, responsible, and inclusive AI that puts users in control and augments rather than replaces human
Azure Machine Learning Services provides an end-to-end, scalable platform for operationalizing machine learning models. It allows users to deploy models everywhere from containers and Kubernetes to SQL Datawarehouse and Cosmos DB. It also offers tools to boost data science productivity, increase experimentation, and automate model retraining. The platform seamlessly integrates with Azure services and is built to deploy models globally at scale with high availability and low latency.
The document discusses how organizations can leverage cloud, data, and AI to gain competitive advantages. It notes that 80% of organizations now adopt cloud-first strategies, AI investment increased 300% in 2017, and data is expected to grow dramatically. The document promotes Microsoft's cloud-based analytics services for harnessing data at scale from various sources and types. It provides examples of how companies have used these services to improve customer experience, reduce costs, speed up insights, and gain operational efficiencies.
Training of Python scikit-learn models on AzureMark Tabladillo
This intermediate-level presentation covers latest Azure technology for deploying Python sci-kit models on Azure. The presentation is a demo using a Microsoft Data Science Virtual Machine (DSVM), Visual Studio Code, Azure Machine Learning Service, Azure Machine Learning Compute, Azure Storage Blobs, and Azure Container Registry to train a model from a Python 3 Anaconda environment.
The presentation will include an architectural diagram and downloadable code from Github.
YouTube recording at https://www.youtube.com/watch?v=HyzbxHBpAbg&feature=youtu.be
The document discusses microservices and provides information on:
- The benefits of microservices including faster time to market, lower deployment costs, and more revenue opportunities.
- What defines a microservice such as being independently deployable and scalable.
- Differences between monolithic and microservice architectures.
- Moving applications to the cloud and refactoring monolithic applications into microservices.
- Tools for building microservices including Azure Service Fabric and serverless/Functions.
- Best practices for developing, deploying, and managing microservices.
Researchers used deep learning techniques like ResNet and data augmentation to improve the accuracy of detecting snow leopards from 63.4% to 90%. They used transfer learning on a ResNet model to extract features from images, then trained a logistic regression classifier on those features to detect snow leopards. They also averaged predictions from multiple images and doubled their training data by flipping images horizontally. This helped improve the model's ability to identify snow leopards in photos.
This document discusses cloud-native applications and serverless computing. It begins with an introduction to cloud-native applications and core technologies like containers, orchestrators, and microservices. Examples are then given of how companies like Fujifilm and ASOS have benefited from serverless architectures on Azure. The document concludes with an overview of Azure serverless services like Functions, Event Grid, Cosmos DB, and Logic Apps and a sample serverless application architecture diagram.
Microsoft provides an AI platform and tools for developers to build, train, and deploy intelligent applications and services. Key elements of Microsoft's AI offerings include:
- A unified AI platform spanning infrastructure, tools, and services to make AI accessible and useful for every developer.
- Powerful tools for AI development including deep learning frameworks, coding and management tools, and AI services for tasks like computer vision, natural language processing, and more.
- Capabilities for training models at scale using GPU accelerated compute on Azure and deploying trained models as web APIs, mobile apps, or other applications.
- A focus on trusted, responsible, and inclusive AI that puts users in control and augments rather than replaces human
Azure Machine Learning Services provides an end-to-end, scalable platform for operationalizing machine learning models. It allows users to deploy models everywhere from containers and Kubernetes to SQL Datawarehouse and Cosmos DB. It also offers tools to boost data science productivity, increase experimentation, and automate model retraining. The platform seamlessly integrates with Azure services and is built to deploy models globally at scale with high availability and low latency.
The document discusses how organizations can leverage cloud, data, and AI to gain competitive advantages. It notes that 80% of organizations now adopt cloud-first strategies, AI investment increased 300% in 2017, and data is expected to grow dramatically. The document promotes Microsoft's cloud-based analytics services for harnessing data at scale from various sources and types. It provides examples of how companies have used these services to improve customer experience, reduce costs, speed up insights, and gain operational efficiencies.
Training of Python scikit-learn models on AzureMark Tabladillo
This intermediate-level presentation covers latest Azure technology for deploying Python sci-kit models on Azure. The presentation is a demo using a Microsoft Data Science Virtual Machine (DSVM), Visual Studio Code, Azure Machine Learning Service, Azure Machine Learning Compute, Azure Storage Blobs, and Azure Container Registry to train a model from a Python 3 Anaconda environment.
The presentation will include an architectural diagram and downloadable code from Github.
YouTube recording at https://www.youtube.com/watch?v=HyzbxHBpAbg&feature=youtu.be
This document provides an overview of Microsoft Azure cloud computing services. It highlights Azure's core infrastructure services including compute, storage, networking and security. It also lists advanced workloads like web/mobile development, IoT, microservices, serverless computing and more. The document shares case studies on how companies have used Azure services like Azure Storage, SQL Data Warehouse, Site Recovery and SAP on Azure to improve performance, reduce costs and gain operational efficiencies. It promotes Azure's tools for DevOps, analytics, cognitive services and high performance computing. Finally, it provides links to learn more about specific Azure services and capabilities.
Spark is an open-source framework for large-scale data processing. Azure Databricks provides Spark as a managed service on Microsoft Azure, allowing users to deploy production Spark jobs and workflows without having to manage infrastructure. It offers an optimized Databricks runtime, collaborative workspace, and integrations with other Azure services to enhance productivity and scale workloads without limits.
The document discusses various use cases for Azure Cosmos DB including handling peak sales periods with elastic scaling, delivering real-time recommendations, leveraging IoT telemetry to build experiences, delivering high-quality app experiences globally at scale, and modernizing and building new apps with real-time personalization. It provides examples of companies like Walmart Labs, ASOS, and The Walking Dead game using Cosmos DB for these scenarios. The document also discusses migrating NoSQL workloads from databases like MongoDB, Cassandra, and DynamoDB to Azure Cosmos DB and provides an example of Symantec migrating Cassandra workloads.
AWS Partner Presentation - PetaByte Scale Computing on Amazon EC2 with BigDat...Amazon Web Services
The document discusses challenges with processing and storing large amounts of data at petabyte scales. Traditional relational databases do not scale well for this amount of data. The solution proposed uses Hadoop for distributed processing of large datasets and Amazon S3 and NoSQL databases for scalable storage. A software-based storage engine called iMoveS is suggested to intelligently migrate data between different storage options based on policies and access patterns to make management easier and improve performance, availability, and lower costs.
Data saturday Oslo Azure Purview Erwin de KreukErwin de Kreuk
Azure Purview provides unified data governance capabilities including automated data discovery, classification, and lineage visualization. It helps organizations overcome data governance silos, comply with regulations, and increase data agility. The key components of Azure Purview include the Data Map for automated metadata extraction and lineage, the Data Catalog for data discovery and governance, and Insights for monitoring data usage. It supports governance of data across cloud and on-premises environments in a serverless and fully managed platform.
Bay Area Azure Meetup - Ignite update sessionNills Franssens
Slidedeck used for the Bay Area Azure Meetup. Microsoft released a ton of new services and updates at Ignite in September. Let’s take some time together to walk through a highlight of the updates and new services announced. We will start by going over the updates in the infrastructure and applications space – and finish off the evening with the novelties in the data and AI area.
For the last 3 decades, Microsoft has been powered by Machine Learning. Come to this session for a first time ever, under the hood look at how we use ML to improve every product and business at Microsoft. Then, see how that same technology is available to you in Azure.
This document provides an overview of cloud computing and the top 6 cloud service providers:
1. It defines cloud, cloud computing, and cloud services as computing resources, data storage, and services available over the internet.
2. The top 6 cloud service providers are identified as Amazon Web Services, Microsoft Azure, Google Cloud, Alibaba Cloud, IBM Cloud, and Oracle.
3. Each provider is briefly described, highlighting their service categories including compute, storage, databases, analytics, AI/ML, security, and networking.
SRV406 How to Step Off the PC Refresh Treadmill with Amazon WorkSpacesAmazon Web Services
Are you tired of the perpetual PC refresh cycle? Do you wish you could save money by extending the lifespan of your PCs? In this session, we’ll show you how Amazon WorkSpaces can help you defeat the PC refresh treadmill by using cloud desktops that can run on commodity hardware, Chromebooks, tablets, or even smartphones. Amazon WorkSpaces provides a virtual perpetual PC that runs on AWS, with bundles designed for general productivity, power users, and graphics applications. We’ll provide a demonstration showing you how easy it is to get started, and what it’s like to use a desktop that’s running on AWS.
Designing big data analytics solutions on azureMohamed Tawfik
This document discusses designing big data analytics solutions on Azure. It provides an overview of Azure's data landscape and common architectural patterns and scenarios for building analytics solutions using various Azure data and analytics services. These include Azure SQL Data Warehouse, Azure Data Lake Store, Azure Data Factory, Azure Machine Learning, and Power BI for reporting and visualization. The document also discusses using these services to build solutions for scenarios like data warehousing, data lakes, ETL/ELT, machine learning, streaming analytics and more.
David J. Rosenthal gave a presentation about Microsoft's Azure cloud platform. He discussed how Azure can help companies with digital transformation by engaging customers, empowering employees, and optimizing operations. He provided examples of how companies are using Azure services like AI, IoT, analytics and more to modernize applications, gain insights from data, and improve productivity. Rosenthal emphasized that Azure offers a secure, flexible cloud platform that businesses can use to innovate, grow and transform both today and in the future.
What are the Business Benefits of Microsoft AzureChris Roche
This document outlines the business benefits of Microsoft Azure, including its strong security features with data centers like spy movie facilities, cost savings from no longer needing to replace servers, scalability to flexibly adjust needs, ability to use hybrid cloud and on-premise resources, fast speed, disaster recovery by backing up to the cloud, and compliance with security and privacy demands.
Join Joseph Sirosh, Corporate Vice President of the Cloud AI Platform, for a deep dive into the AI platform and exciting AI use cases. Joseph will showcase how every developer can infuse intelligence into their applications and create amazing new experiences with AI. In this exciting overview, you will learn about the application of AI technologies in the cloud. We will help you understand how to add pre-built AI capabilities like object detection, face understanding, translation and speech to applications. We will show how developers can build Cognitive Search applications that understand deep content in images, text and other data. We will also show how the platform can be used to build your own custom AI models for predictive applications and how to use the Azure platform to accelerate machine learning. Joseph will also show how companies assemble end-to-end systems of intelligence using the rich variety of data and application development services on Azure.
This document provides an overview of business intelligence and analytics tools from Microsoft, focusing on Power BI. Power BI allows users to perform discovery, exploration, and ad-hoc analysis of large datasets through custom visualizations and live data access. It also allows organizations to get more from existing Reporting Services investments. The document includes quotes from various companies praising Power BI for providing instrumental business intelligence solutions and transforming decision making through data-driven insights.
Hadoop and DynamoDB provide scalable data storage and analytics capabilities. Hadoop uses Elastic MapReduce to process large datasets stored in S3 and HDFS. It allows querying live data stored in DynamoDB or archived data stored in S3. Results can be exported between the two services. DynamoDB is a NoSQL database that provides unlimited storage, consistent performance, and ability to scale without downtime. It is integrated with Hadoop for analytics use cases.
Azure Days 2019: Grösser und Komplexer ist nicht immer besser (Meinrad Weiss)Trivadis
«Moderne» Data Warehouse/Data Lake Architekturen strotzen oft nur von Layern und Services. Mit solchen Systemen lassen sich Petabytes von Daten verwalten und analysieren. Das Ganze hat aber auch seinen Preis (Komplexität, Latenzzeit, Stabilität) und nicht jedes Projekt wird mit diesem Ansatz glücklich.
Der Vortrag zeigt die Reise von einer technologieverliebten Lösung zu einer auf die Anwender Bedürfnisse abgestimmten Umgebung. Er zeigt die Sonnen- und Schattenseiten von massiv parallelen Systemen und soll die Sinne auf das Aufnehmen der realen Kundenanforderungen sensibilisieren.
The cloud is all the rage. Does it live up to its hype? What are the benefits of the cloud? Join me as I discuss the reasons so many companies are moving to the cloud and demo how to get up and running with a VM (IaaS) and a database (PaaS) in Azure. See why the ability to scale easily, the quickness that you can create a VM, and the built-in redundancy are just some of the reasons that moving to the cloud a “no brainer”. And if you have an on-prem datacenter, learn how to get out of the air-conditioning business!
Running Microsoft SharePoint On AWS - Smartronix and AWS - WebinarAmazon Web Services
Miles Ward, Solution Architect, AWS
Robert Groat, Chief Technology Officer, Smartronix
discuss how you can run microsoft Enterprise Applications like SharePoint on AWS Cloud, Architecture. Recovery.gov
The Carlyle Group Modernizes File Services with CTERA and AWSAmazon Web Services
The Carlyle Group, one of the world’s largest private equity firm and an organization with strict security and private requirements, sought a cloud-enabled solution that would replace legacy remote office storage infrastructure and provide fast local file access for users.
In choosing CTERA and AWS, Carlyle now leverages a single platform for NAS home directory and network file share access at regional offices; file-based collaboration for mobile users around the world. CTERA and AWS represented a solution to solve Carlyle’s business challenges, meet its IT requirements, and conform to its IT security mandate.
Join us to learn how CTERA and AWS helped the Carlyle Group leverage a single platform for NAS home directory and network file share access at regional offices as well as cloud-based file collaboration for roaming users around the world.
Big Data Expo 2015 - Microsoft Transform you data into intelligent actionBigDataExpo
Er zijn veel beloftes rondom Big Data. Iedereen praat erover maar hoe begin je zonder meteen een grote business case op te moeten stellen. Cortana Analytics Suite is laagdrempelig en een makkelijk toegankelijk Advanced Analytics platform om je ideeën op haalbaarheid te testen maar daarna ook door te groeien naar (grote) productie implementaties. In deze sessie krijg je een overzicht van de scenario’s die Cortana Analytics biedt. Denk daar bij aan IOT, Machine Learning maar ook Churn Analysis, Forecasting en Predictive Maintenance.
Microsoft Azure Explained - Hitesh D KeshariaHARMAN Services
Microsoft Azure is a cloud computing platform that allows users to build, deploy, and manage applications and services through a global network of Microsoft-managed data centers. It provides infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS). Azure offers various computing, web & mobile, data & storage, analytics, networking, and other services to help developers build and manage applications in the cloud. It aims to offer reliability, scalability, and easy management to users while ensuring a high availability rate of 99.95%.
This document provides an overview of Microsoft Azure cloud computing services. It highlights Azure's core infrastructure services including compute, storage, networking and security. It also lists advanced workloads like web/mobile development, IoT, microservices, serverless computing and more. The document shares case studies on how companies have used Azure services like Azure Storage, SQL Data Warehouse, Site Recovery and SAP on Azure to improve performance, reduce costs and gain operational efficiencies. It promotes Azure's tools for DevOps, analytics, cognitive services and high performance computing. Finally, it provides links to learn more about specific Azure services and capabilities.
Spark is an open-source framework for large-scale data processing. Azure Databricks provides Spark as a managed service on Microsoft Azure, allowing users to deploy production Spark jobs and workflows without having to manage infrastructure. It offers an optimized Databricks runtime, collaborative workspace, and integrations with other Azure services to enhance productivity and scale workloads without limits.
The document discusses various use cases for Azure Cosmos DB including handling peak sales periods with elastic scaling, delivering real-time recommendations, leveraging IoT telemetry to build experiences, delivering high-quality app experiences globally at scale, and modernizing and building new apps with real-time personalization. It provides examples of companies like Walmart Labs, ASOS, and The Walking Dead game using Cosmos DB for these scenarios. The document also discusses migrating NoSQL workloads from databases like MongoDB, Cassandra, and DynamoDB to Azure Cosmos DB and provides an example of Symantec migrating Cassandra workloads.
AWS Partner Presentation - PetaByte Scale Computing on Amazon EC2 with BigDat...Amazon Web Services
The document discusses challenges with processing and storing large amounts of data at petabyte scales. Traditional relational databases do not scale well for this amount of data. The solution proposed uses Hadoop for distributed processing of large datasets and Amazon S3 and NoSQL databases for scalable storage. A software-based storage engine called iMoveS is suggested to intelligently migrate data between different storage options based on policies and access patterns to make management easier and improve performance, availability, and lower costs.
Data saturday Oslo Azure Purview Erwin de KreukErwin de Kreuk
Azure Purview provides unified data governance capabilities including automated data discovery, classification, and lineage visualization. It helps organizations overcome data governance silos, comply with regulations, and increase data agility. The key components of Azure Purview include the Data Map for automated metadata extraction and lineage, the Data Catalog for data discovery and governance, and Insights for monitoring data usage. It supports governance of data across cloud and on-premises environments in a serverless and fully managed platform.
Bay Area Azure Meetup - Ignite update sessionNills Franssens
Slidedeck used for the Bay Area Azure Meetup. Microsoft released a ton of new services and updates at Ignite in September. Let’s take some time together to walk through a highlight of the updates and new services announced. We will start by going over the updates in the infrastructure and applications space – and finish off the evening with the novelties in the data and AI area.
For the last 3 decades, Microsoft has been powered by Machine Learning. Come to this session for a first time ever, under the hood look at how we use ML to improve every product and business at Microsoft. Then, see how that same technology is available to you in Azure.
This document provides an overview of cloud computing and the top 6 cloud service providers:
1. It defines cloud, cloud computing, and cloud services as computing resources, data storage, and services available over the internet.
2. The top 6 cloud service providers are identified as Amazon Web Services, Microsoft Azure, Google Cloud, Alibaba Cloud, IBM Cloud, and Oracle.
3. Each provider is briefly described, highlighting their service categories including compute, storage, databases, analytics, AI/ML, security, and networking.
SRV406 How to Step Off the PC Refresh Treadmill with Amazon WorkSpacesAmazon Web Services
Are you tired of the perpetual PC refresh cycle? Do you wish you could save money by extending the lifespan of your PCs? In this session, we’ll show you how Amazon WorkSpaces can help you defeat the PC refresh treadmill by using cloud desktops that can run on commodity hardware, Chromebooks, tablets, or even smartphones. Amazon WorkSpaces provides a virtual perpetual PC that runs on AWS, with bundles designed for general productivity, power users, and graphics applications. We’ll provide a demonstration showing you how easy it is to get started, and what it’s like to use a desktop that’s running on AWS.
Designing big data analytics solutions on azureMohamed Tawfik
This document discusses designing big data analytics solutions on Azure. It provides an overview of Azure's data landscape and common architectural patterns and scenarios for building analytics solutions using various Azure data and analytics services. These include Azure SQL Data Warehouse, Azure Data Lake Store, Azure Data Factory, Azure Machine Learning, and Power BI for reporting and visualization. The document also discusses using these services to build solutions for scenarios like data warehousing, data lakes, ETL/ELT, machine learning, streaming analytics and more.
David J. Rosenthal gave a presentation about Microsoft's Azure cloud platform. He discussed how Azure can help companies with digital transformation by engaging customers, empowering employees, and optimizing operations. He provided examples of how companies are using Azure services like AI, IoT, analytics and more to modernize applications, gain insights from data, and improve productivity. Rosenthal emphasized that Azure offers a secure, flexible cloud platform that businesses can use to innovate, grow and transform both today and in the future.
What are the Business Benefits of Microsoft AzureChris Roche
This document outlines the business benefits of Microsoft Azure, including its strong security features with data centers like spy movie facilities, cost savings from no longer needing to replace servers, scalability to flexibly adjust needs, ability to use hybrid cloud and on-premise resources, fast speed, disaster recovery by backing up to the cloud, and compliance with security and privacy demands.
Join Joseph Sirosh, Corporate Vice President of the Cloud AI Platform, for a deep dive into the AI platform and exciting AI use cases. Joseph will showcase how every developer can infuse intelligence into their applications and create amazing new experiences with AI. In this exciting overview, you will learn about the application of AI technologies in the cloud. We will help you understand how to add pre-built AI capabilities like object detection, face understanding, translation and speech to applications. We will show how developers can build Cognitive Search applications that understand deep content in images, text and other data. We will also show how the platform can be used to build your own custom AI models for predictive applications and how to use the Azure platform to accelerate machine learning. Joseph will also show how companies assemble end-to-end systems of intelligence using the rich variety of data and application development services on Azure.
This document provides an overview of business intelligence and analytics tools from Microsoft, focusing on Power BI. Power BI allows users to perform discovery, exploration, and ad-hoc analysis of large datasets through custom visualizations and live data access. It also allows organizations to get more from existing Reporting Services investments. The document includes quotes from various companies praising Power BI for providing instrumental business intelligence solutions and transforming decision making through data-driven insights.
Hadoop and DynamoDB provide scalable data storage and analytics capabilities. Hadoop uses Elastic MapReduce to process large datasets stored in S3 and HDFS. It allows querying live data stored in DynamoDB or archived data stored in S3. Results can be exported between the two services. DynamoDB is a NoSQL database that provides unlimited storage, consistent performance, and ability to scale without downtime. It is integrated with Hadoop for analytics use cases.
Azure Days 2019: Grösser und Komplexer ist nicht immer besser (Meinrad Weiss)Trivadis
«Moderne» Data Warehouse/Data Lake Architekturen strotzen oft nur von Layern und Services. Mit solchen Systemen lassen sich Petabytes von Daten verwalten und analysieren. Das Ganze hat aber auch seinen Preis (Komplexität, Latenzzeit, Stabilität) und nicht jedes Projekt wird mit diesem Ansatz glücklich.
Der Vortrag zeigt die Reise von einer technologieverliebten Lösung zu einer auf die Anwender Bedürfnisse abgestimmten Umgebung. Er zeigt die Sonnen- und Schattenseiten von massiv parallelen Systemen und soll die Sinne auf das Aufnehmen der realen Kundenanforderungen sensibilisieren.
The cloud is all the rage. Does it live up to its hype? What are the benefits of the cloud? Join me as I discuss the reasons so many companies are moving to the cloud and demo how to get up and running with a VM (IaaS) and a database (PaaS) in Azure. See why the ability to scale easily, the quickness that you can create a VM, and the built-in redundancy are just some of the reasons that moving to the cloud a “no brainer”. And if you have an on-prem datacenter, learn how to get out of the air-conditioning business!
Running Microsoft SharePoint On AWS - Smartronix and AWS - WebinarAmazon Web Services
Miles Ward, Solution Architect, AWS
Robert Groat, Chief Technology Officer, Smartronix
discuss how you can run microsoft Enterprise Applications like SharePoint on AWS Cloud, Architecture. Recovery.gov
The Carlyle Group Modernizes File Services with CTERA and AWSAmazon Web Services
The Carlyle Group, one of the world’s largest private equity firm and an organization with strict security and private requirements, sought a cloud-enabled solution that would replace legacy remote office storage infrastructure and provide fast local file access for users.
In choosing CTERA and AWS, Carlyle now leverages a single platform for NAS home directory and network file share access at regional offices; file-based collaboration for mobile users around the world. CTERA and AWS represented a solution to solve Carlyle’s business challenges, meet its IT requirements, and conform to its IT security mandate.
Join us to learn how CTERA and AWS helped the Carlyle Group leverage a single platform for NAS home directory and network file share access at regional offices as well as cloud-based file collaboration for roaming users around the world.
Big Data Expo 2015 - Microsoft Transform you data into intelligent actionBigDataExpo
Er zijn veel beloftes rondom Big Data. Iedereen praat erover maar hoe begin je zonder meteen een grote business case op te moeten stellen. Cortana Analytics Suite is laagdrempelig en een makkelijk toegankelijk Advanced Analytics platform om je ideeën op haalbaarheid te testen maar daarna ook door te groeien naar (grote) productie implementaties. In deze sessie krijg je een overzicht van de scenario’s die Cortana Analytics biedt. Denk daar bij aan IOT, Machine Learning maar ook Churn Analysis, Forecasting en Predictive Maintenance.
Microsoft Azure Explained - Hitesh D KeshariaHARMAN Services
Microsoft Azure is a cloud computing platform that allows users to build, deploy, and manage applications and services through a global network of Microsoft-managed data centers. It provides infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS). Azure offers various computing, web & mobile, data & storage, analytics, networking, and other services to help developers build and manage applications in the cloud. It aims to offer reliability, scalability, and easy management to users while ensuring a high availability rate of 99.95%.
The document introduces Microsoft Azure and provides some key details. It discusses how Azure provides faster application development and quick scaling. It also notes Azure offers lower costs compared to traditional infrastructure. As an example, it highlights Windows Azure Storage and how it provides huge global infrastructure scale with over 100 datacenters in 19 regions worldwide.
The Basics of Getting Started With Microsoft AzureMicrosoft Azure
The document describes various capabilities provided by Microsoft Azure including hosting virtual machines and web applications, mobile backend services, cloud services, storage options, SQL databases, media services, integration services, identity and access management, virtual networking, and infrastructure as a service. It provides details on virtual machine sizes, disks, networking, security, backups, and cross-premise connectivity in Azure.
Billions of Messages in Real Time: Why Paypal & LinkedIn Trust an Engagement ...confluent
(Bruno Simic, Solutions Engineer, Couchbase)
Breakout during Confluent’s streaming event in Munich. This three-day hands-on course focused on how to build, manage, and monitor clusters using industry best-practices developed by the world’s foremost Apache Kafka™ experts. The sessions focused on how Kafka and the Confluent Platform work, how their main subsystems interact, and how to set up, manage, monitor, and tune your cluster.
Caserta Concepts, Datameer and Microsoft shared their combined knowledge and a use case on big data, the cloud and deep analytics. Attendes learned how a global leader in the test, measurement and control systems market reduced their big data implementations from 18 months to just a few.
Speakers shared how to provide a business user-friendly, self-service environment for data discovery and analytics, and focus on how to extend and optimize Hadoop based analytics, highlighting the advantages and practical applications of deploying on the cloud for enhanced performance, scalability and lower TCO.
Agenda included:
- Pizza and Networking
- Joe Caserta, President, Caserta Concepts - Why are we here?
- Nikhil Kumar, Sr. Solutions Engineer, Datameer - Solution use cases and technical demonstration
- Stefan Groschupf, CEO & Chairman, Datameer - The evolving Hadoop-based analytics trends and the role of cloud computing
- James Serra, Data Platform Solution Architect, Microsoft, Benefits of the Azure Cloud Service
- Q&A, Networking
For more information on Caserta Concepts, visit our website: http://casertaconcepts.com/
.NET Usergroup Oldenburg 26. März 2015 - von Winfried Klinker und Andre Hühn
Microsoft Azure gehört zu den Cloud-Diensten, die Microsoft anbietet. Es umfasst neben dem Hosting von virtuellen Maschinen insbesondere eine große Sammlung an Diensten (wie SQL Azure, Mobile Services, Machine Learning).
Wir geben einen ersten Überblick über die Features von Azure insbesondere für Entwickler. Dabei werden wir sowohl auf die Platform as a Service (PaaS) Angebote wie auch auf die Infrastructe as a Service (IaaS) eingehen. Außerdem geben wir einen Einblick in moderne Cloud Architektur und zeigen Best Practices bei der Cloud Entwicklung auf. Dabei werden Beispiele aus der Praxis zeigen, wie man eine Fehlertolerante und robuste Cloud Lösung erstellen kann.
Über die Sprecher:
Winfried Klinker ist als Software Architekt bei der Firma Sitrion in Oldenburg tätig. Er beschäftigt sich größtenteils mit Cloud Architekturen mit Microsoft Azure vor allem in Bezug auf Backends für mobile Anwendungen.
Andre Hühn ist Team Lead für Entwicklung mobiler Apps bei der Firma Sitrion in Oldenburg und beeinflusst damit die Richtung der Architektur für das Sitrion ONE Produkt.
This document provides an overview of Microsoft Azure cloud services and platforms for modern business. It discusses how Azure allows businesses to rapidly setup environments, scale infrastructure to meet demands, and increase efficiency at a reduced cost compared to on-premises solutions. The document highlights key Azure services including compute, storage, databases, analytics, networking, identity management, and applications. It also provides examples of Fortune 500 companies and partners using Azure and demos of the Azure portal.
This is the complete deck presented at the Westin Calgary Hotel, on August 16th, 2016.
It covers the current state of the AWS Big Data Solution set. Contains several use cases of Big Data, Machine Learning, and a tutorial on how to implement and use Big Data on the AWS Cloud Platform.
This document provides an overview and introduction to Windows Azure SQL Database. It discusses key topics such as:
- SQL Database service tiers including Basic, Standard, and Premium, which are differentiated by performance levels measured in Database Transaction Units (DTUs) and other features.
- Database size limits and performance metrics for each tier.
- Database replication and high availability capabilities to ensure reliability.
- Support for common SQL Server features while noting some limitations compared to on-premises SQL Server.
- Considerations for database naming, users/logins, migrations, and automation in the SQL Database platform.
- Indexing requirements and compatibility differences to be aware of.
Cortana Analytics Workshop: The "Big Data" of the Cortana Analytics Suite, Pa...MSAdvAnalytics
Lance Olson. Cortana Analytics is a fully managed big data and advanced analytics suite that helps you transform your data into intelligent action. Come to this two-part session to learn how you can do "big data" processing and storage in Cortana Analytics. In the first part, we will provide an overview of the processing and storage services. We will then talk about the patterns and use cases which make up most big data solutions. In the second part, we will go hands-on, showing you how to get started today with writing batch/interactive queries, real-time stream processing, or NoSQL transactions all over the same repository of data. Crunch petabytes of data by scaling out your computation power to any sized cluster. Store any amount of unstructured data in its native format with no limits to file or account size. All of this can be done with no hardware to acquire or maintain and minimal time to setup giving you the value of "big data" within minutes. Go to https://channel9.msdn.com/ to find the recording of this session.
AWS Cloud Kata 2013 | Singapore - Getting to Scale on AWSAmazon Web Services
This session will focus on how to get from 'Minimum Viable Product' (MVP) to scale. It will also explain how to deal with unpredictable demand and how to build a scalable business. Attend this session to learn how to:
Scale web servers and app services with Elastic Load Balancing and Auto Scaling on Amazon EC2
Scale your storage on Amazon S3 and S3 Reduced Redundancy Storage
Scale your database with Amazon DynamoDB, Amazon RDS, and Amazon ElastiCache
Scale your customer base by reaching customers globally in minutes with Amazon CloudFront
Jelastic PaaS for Hosting companies, Telcos & MSPs. Jelatic allows hosting companies to enter to the DevOps market and monetize trendy Docker technology
Microsoft is a leading global provider of cloud computing services for businesses of all sizes.
Cloud computing is the delivery of computing services — including servers, storage, databases, networking, software, analytics, and intelligence — over the Internet to offer faster innovation, flexible resources, and economies of scale.
Windows Azure is Microsoft's application platform for the public cloud. You can use this platform in many different ways. For instance, you can use Windows Azure to build a web application that runs and stores its data in Microsoft datacenters. You can use Windows Azure just to store data, with the applications that use this data running on-premises (that is, outside the public cloud). You can use Windows Azure to create virtual machines for development and test or to run SharePoint and other applications.
So you got a handle on what Big Data is and how you can use it to find business value in your data. Now you need an understanding of the Microsoft products that can be used to create a Big Data solution. Microsoft has many pieces of the puzzle and in this presentation I will show how they fit together. How does Microsoft enhance and add value to Big Data? From collecting data, transforming it, storing it, to visualizing it, I will show you Microsoft’s solutions for every step of the way
Leapfrog into Serverless - a Deloitte-Amtrak Case Study | Serverless Confere...Gary Arora
This talk was delivered at the Serverless Conference in New York City in 2017. Deloitte and Amtrak built a Serverless Cloud-Native solution on AWS for real-time operational datastore and near real-time reporting data mart that modernized Amtrak's legacy systems & applications. With Serverless solutions, we are able leapfrog over several rungs of computing evolution.
Gary Arora is a Cloud Solutions Architect at Deloitte Consulting, specializing on Azure & AWS.
The document discusses the infrastructure and APIs available for Windows Phone development. It outlines the core plumbing, common type system, and standard programming model that make up the infrastructure. It then lists many of the Windows Phone Platform APIs that are available for developers to use, including APIs for tasks, controls, media, and more. It also includes code examples and references to Microsoft documentation and resources for Windows Phone development.
HMD shipments are forecast to grow rapidly over the next few years, reaching around 76 million units by 2020. Immersive computing technologies like virtual reality, augmented reality and mixed reality are poised for growth as they blend physical and digital worlds and allow for natural language and gesture-based interactions. Developers can create immersive applications for these platforms across entertainment, training, manufacturing and other areas using tools like Unity, Windows Mixed Reality and Azure cognitive services.
This document contains configuration information for endpoints and runtime execution for a process. It specifies starting the process with the startup.cmd file and setting it as ready on process start. It lists several endpoints for HTTP, TCP, and other protocols on various ports for input. It also contains SQL connection strings and registry settings for TCP/IP parameters including keep alive times and data retransmissions.
Combining Private and Public Clouds into Meaningful HybridsDavid Chou
The document discusses hybrid cloud scenarios that combine public and private clouds. It defines private and public clouds and their differences. Private clouds provide more control while public clouds provide scale. Hybrid clouds blend both models. The document outlines several hybrid cloud deployment patterns and application patterns, including using public clouds for variable capacity and private clouds for predictable workloads. It emphasizes the need for cloud-optimized application design and integration across cloud services when building hybrid applications.
CloudConnect 2011 - Building Highly Scalable Java Applications on Windows AzureDavid Chou
This document discusses building highly scalable Java applications on Windows Azure. It provides an overview of Windows Azure, including its infrastructure and services. It then covers how to deploy and run Java applications on Azure, including using various Java application servers like Tomcat, Jetty, and GlassFish. It also discusses some considerations for architecting applications to scale on Azure.
The document discusses building highly scalable Java applications on Windows Azure. It provides an overview of Windows Azure, including its compute and storage services. It then covers how to deploy and run Java applications on Azure, including using Tomcat, Jetty, GlassFish, and accessing SQL Azure and storage. It discusses current limitations and how the Eclipse tools will support Java development for Azure. Finally, it covers architectural approaches for scaling applications, comparing vertical to horizontal scaling.
Windows Azure AppFabric is a platform that provides middleware services for developing and managing cloud applications at scale. It includes services for messaging, caching, identity management, and integrating applications. It also allows building and managing composite applications composed of distributed application components hosted on Windows Azure. The AppFabric platform aims to simplify cloud development by providing these services and capabilities through a consistent programming model.
Scale as a competitive advantage allows companies to leverage large amounts of data. As data volumes grow exponentially, companies are utilizing cloud computing and distributed architectures to process petabytes of information daily across thousands of servers. This enables new applications, insights, and business models driven by "big data."
This document provides an overview of architecting cloud applications for scale. It discusses key concepts like horizontal scaling, distributed computing, and common cloud architecture patterns. Specific examples are given of how large companies like Facebook, Twitter, and Flickr architect their systems using horizontal scaling, partitioning, caching, and other techniques to handle massive loads in a scalable way.
This document provides an overview of the Windows Phone 7 platform, including:
- The application frameworks that power Windows Phone apps, such as Silverlight and XNA.
- The app model and hosting environment, including sandboxing and isolation of apps.
- The common hardware capabilities across Windows Phones, including touchscreens, cameras, and sensors.
- The tools and services available to developers, such as the emulator, cloud services, and Xbox Live integration.
- The process for deploying and distributing apps through the Windows Phone Marketplace.
Silverlight is a development platform for creating engaging web and mobile applications using .NET. It allows visually rich experiences through technologies like HD video, 3D graphics, and animation. Silverlight supports a wide range of platforms and browsers and provides tools for building business and consumer applications. Some key capabilities include media playback, rich graphics, data binding, and cross-platform deployment. Major companies like Netflix, the NFL, and NBC have used Silverlight to deliver interactive video experiences with features like HD streaming, DVR controls, and multiple simultaneous camera views.
Microsoft Cloud Computing - Windows Azure PlatformDavid Chou
The document provides an overview of Microsoft's cloud computing platform. It discusses Microsoft's strategy of providing a hybrid cloud that allows customers to run applications both on-premise and in the public cloud. It highlights key services offered, such as compute infrastructure (web and worker roles), SQL Azure database, storage, and AppFabric. Case studies are presented showing how various companies have used the Microsoft cloud platform.
This document discusses data options in the cloud, including database choices like SQL Server, SQL Azure Database, and hosted SQL Server. It covers features of SQL Azure like scalability, high availability, and self-provisioning. Storage options like Windows Azure Storage blobs, tables, and queues are described. SQL Server 2008 R2 improvements in performance, manageability, business intelligence, and master data management are highlighted. Pricing models for SQL Azure and Windows Azure Storage are provided at the end.
This document discusses various data access technologies in .NET including DataSet/DataReader, nHibernate, LINQ to SQL, Entity Framework, ADO.NET Data Services, and their roles in layered architectures. It provides overviews of each technology, how they fit into LINQ, and recommendations for when to use each one based on scenarios like database support needs, object-relational mapping requirements, and access through services.
This document summarizes key metrics and timelines for the growth of various cloud services. It highlights that over 15 years, one service has grown to have over 450 million active users, while another processes over 5 billion conference minutes per year after 7 years. The document also outlines details on a new $500 million data center facility that can house servers in shipping containers to deliver high density and energy efficiency.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/building-and-scaling-ai-applications-with-the-nx-ai-manager-a-presentation-from-network-optix/
Robin van Emden, Senior Director of Data Science at Network Optix, presents the “Building and Scaling AI Applications with the Nx AI Manager,” tutorial at the May 2024 Embedded Vision Summit.
In this presentation, van Emden covers the basics of scaling edge AI solutions using the Nx tool kit. He emphasizes the process of developing AI models and deploying them globally. He also showcases the conversion of AI models and the creation of effective edge AI pipelines, with a focus on pre-processing, model conversion, selecting the appropriate inference engine for the target hardware and post-processing.
van Emden shows how Nx can simplify the developer’s life and facilitate a rapid transition from concept to production-ready applications.He provides valuable insights into developing scalable and efficient edge AI solutions, with a strong focus on practical implementation.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
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.
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.
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.
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.
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.
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
3. Azure
footprint
(19 regions online,
>600K servers each)
CentralUS
DesMoines,IA
WestUS
California
NorthEurope
Dublin
EastUS
Boydton,VA
EastUS2
Boydton,VA
USGov
Boydton,VA
NorthCentralUS
Chicago,IL
USGov
DesMoines,IA
SouthCentral
US
SanAntonio,
TX
BrazilSouth
SaoPaulo
WestEurope
Amsterdam
ChinaNorth*
Beijing
ChinaSouth*
Shanghai
JapanEast
Saitama
JapanWest
Osaka
IndiaWest
TBD
IndiaEast
TBD
EastAsia
HongKong
SEAsia
Singapore
Australia West
Melbourne
Australia East
Sydney
4. >30Trillion
Storage objects
in Azure
1,200,000
SQL databases
in Azure
>50%
Fortune 500 using
Azure
>10,000
New Azure customers
a week
350Million
Azure Active Directory users
>18Billion
Azure Active Directory
authentications/week
40%
Azure revenue comes
from startups and ISVs
5. Compute
• Virtual Machines
• Cloud Services
• Batch
• Scheduler
• RemoteApp
Web & Mobile
• Websites
• Mobile Services
• API Management
• Notification Hubs
• WebJobs
Data
• SQL Database
• DocumentDB
• Redis Cache
• Queue Storage
• Table Storage
• Search
Analytics
• HDInsight
• Machine Learning
• Stream Analytics
• Data Factory
• Event Hubs
Hybrid Integration
• BizTalk Services
• Service Bus
• Site Recovery
Storage
• Blob Storage
• Files
• Backup
Networking
• Virtual Network
• ExpressRoute
• Traffic Manager
Media & CDN
• Media Services
• Content
Distribution
Network
Identity
• Active Directory
• Multi-Factor
Authentication
Management
• Scheduler
• Automation
• Operational Insights
Azure Services
6. Deploy and scale modern websites and web apps in
seconds
• .NET, Java, PHP, Node.js, Python
• Built-in auto-scale and load-balancing
• High availability with auto-patching
• Continuous deployment with Git, TFS, GitHub
• SQL Databases, MySQL, DocumentDB, Search,
MongoDB
• WordPress, Umbraco, Joomla, Drupal
Web Sites
A fully managed Platform-as-a-Service (PaaS) that enables you to build, deploy and scale enterprise-
grade web Apps in seconds. Focus on your application code, and let Azure take care of the infrastructure
to scale and securely run it for you.
7. Add a cloud backend to your app in minutes
• Host a .NET or Node.js web API with 24x7
monitoring and management
• Use single sign-on with Active Directory,
Facebook, Twitter, and Google
• Push notifications to individual users and dynamic
audience segments
• Store data in SQL, Table Storage, and MongoDB
• Use cloud-based sync to build apps that work
offline
• Auto-Scale to millions of devices
Mobile Services
Rapidly build engaging cross-platform and native apps for iOS, Android, Windows or Mac, store app
data in the cloud or on-premises, authenticate users, send push notifications, as well as add your custom
backend logic in C# or Node.js.
8. Engage users on iOS, Android, Windows and Kindle Fire
devices. Notification Hubs supports:
• Broadcasting to millions of users in minutes
• Segmented push notifications based on interest
• Secure push notifications (push-to-pull)
• Push-to-sync scenarios
• Enhanced second-screen experience for media apps
• More…
Notification Hubs
A high-volume, low-latency mobile push notification engine that works with any existing app backend,
whether hosted on-premises or in the cloud.
9. Cloud-scale telemetry ingestion from websites, apps,
and devices
• Log millions of events per second in near real time
• Connect devices with flexible authorization and
throttling
• Time-based event buffering
• Managed service with elastic scale
• Broad platform reach with native client libraries
• Pluggable adapters for other cloud services
Event Hubs
A highly scalable publish-subscribe ingestor that can intake millions of events per second to process and
analyze the massive amounts of data produced by connected devices and applications.
10. A fully-managed search solution that allows developers to enable search experiences in applications.
Embed a sophisticated search experience into web and mobile applications without having to worry about the
complexities of full-text search and without having to deploy, maintain or manage any infrastructure.
Perfect for enterprise cloud developers, cloud software vendors, cloud architects who need a fully-managed search
solution.
Surface Your Data
Search
11. 100% Apache Hadoop-based service in the cloud
• Scale to petabytes on demand
• Process unstructured and semi-structured data
• Develop in Java, .NET, and more
• No hardware to buy or maintain
• Pay only for what you use
• Spin up a Hadoop cluster in minutes
• Visualize your Hadoop data in Excel
• Easily integrate on-premises Hadoop clusters
HDInsight
A Hadoop distribution powered by the cloud that can handle any amount of data, scaling from terabytes
to petabytes on demand. Spin up any number of nodes at anytime. Charged only for the compute and
storage used.
?
12. Powerful cloud-based predictive analytics
• Fully managed: no hardware or software to buy
• Integrated: drag, drop and connect
• Best in class algorithms: proven solutions from Xbox
& Bing
• R built-in: use over 350 R packages or bring your
own R code
• Deploy in minutes: operationalize with a click
• Visualization: Graphs, distribution and comparison
tools allow for novel feature and model optimization
Machine Learning
A fully-managed cloud service for predictive analytics. It combines new analytics tools, powerful
algorithms, and years of Microsoft machine learning research into one simple, easy-to-use cloud service.
It gives data novices and startups inexpensive access to tools previously available only to the most
sophisticated businesses. Larger enterprises can unleash value from data more quickly and efficiently.
13. Keep apps and devices connected across private and
public clouds
• Build reliable and elastic cloud apps with messaging
• Protect your application from temporary peaks
• Distribute messages to multiple independent
backend systems
• Reach millions of devices with sub-second response
times
• Decouple your applications from each other
• Build solutions that work with existing networks
Service Bus
A generic, cloud-based messaging system for connecting just about anything—applications, services,
and devices—wherever they are. Connect apps running on Azure, on-premises—or both. Connect
appliances, sensors, and other devices like tablets or phones to a central application or to each other.
14. Backend
web services
Hosted
anywhere-
Public cloud or
On-premise
Publish APIs to users securely and at scale
• Scale to millions of API calls
• Throttle, rate limit and quota your APIs
• Bring modern formats like JSON and REST to
existing APIs
• Mobile enable enterprise APIs
• Maximize developer success with interactive
console
• Get deep insights with rich analytics
API Management
API Management helps protect your mission critical systems with authentication, rate limiting, quotas
and caching to ease load under pressure. Target new clients with CORS and JSONP support and
optimize performance with caching, all via simple configuration. API Management supplies the tools,
analytics, and reporting for end-to-end management right out of the box.
Developers/
API consumers
Apps
ADMIN/ API
Providers
15. • Scalable to thousands of databases
• Predictable performance you can dial up or down
• Availability-backed by replicas & uptime SLA
• Data protection via auditing, restore & geo-
replication
• Programmatic DBA-like functionality for efficient
DevOps
• Self-managed for near-zero maintenance
• Elastic Scale (in preview) enables the data-tier of an
application to scale out and in via industry-standard
sharding practices
SQL Database
a relational database-as-a-service that makes enterprise-grade capabilities easily accessible for cloud
architects and developers by delivering predictable performance, scalability, business continuity, data
protection and security, and near-zero administration.
SQL
Database
16. A NoSQL document database-as-a-service, fully managed by Microsoft Azure.
For cloud-designed apps when query over schema-free data; reliable and predictable performance; and rapid
development are key. First of its kind database service to offer native support for JavaScript, SQL query and
transactions over schema-free JSON documents.
Perfect for cloud architects and developers who need an enterprise-ready NoSQL document database.
DocumentDB
17. • Basic – Single node. Multiple sizes.
• Standard – Two-node Master/Slave. Includes SLA and
replication support. Multiple Sizes
• Available in sizes up to 53 GB
• Managed cache replication, helping increase
availability of cache data across cache failures
• Provisioned from management portal, and monitor
health and performance
Redis Cache
A secure, dedicated Redis cache, hosted in Azure and managed by Microsoft. The low latency, high-
throughput capabilities of the Redis engine helps scale the data tier independently for more efficient use
of compute resources in an application layer.
18. Fast, parallel writes,
secure and
protected both in
transit and while at
rest in the cloud.
Secure HTTP and
fast UDP upload.
Elastically cloud
scalable to handle
100s or even 1000s
of parallel tasks,
multiple video and
audio formats.
AES 128-bit Clear
Key or PlayReady
DRM with options
to host license keys
in the cloud.
Dynamic Packaging
optimizes storage
by encoding once
and delivering all
formats on the fly.
Static Packaging for
Smooth Streaming
and HLS.
Caching via Azure
CDN or 3rd-party,
pulling securely
from origins
including token-
based
authentication and
geo-blocking.
Deliver to all of the
most popular client
devices including
Windows PCs, Mac,
iOS, Android, game
consoles, smart TVs,
and more.
Media Services
Create end-to-end media workflows with flexible and highly scalable encoding, packaging, and
distribution services. Securely upload, store, encode and package video or audio content for both on-
demand and live streaming delivery to a wide array of TV, PC and mobile device endpoints.
19. Identity and access management for the cloud
• Single sign-on to any cloud app
• Works with multiple platforms and devices
• Integrates with on-premises Active Directory
• Enterprise scale and SLA
• Enforce multi-factor authentication
• Pre-integrated with thousands of SaaS solutions
Active Directory
A comprehensive identity and access management cloud solution. It combines core directory services,
advanced identity governance, security, and application access management. Azure AD also offers an
identity management platform to deliver access control to their applications, based on centralized policy
and rules.
20. Launch Windows Server and Linux in minutes
• Scale from 1 to 1000s of VM instances
• Built-in virtual networking, load-balancing
• Leverage hybrid consistency with on-premises
• Per-minute billing
• Oracle, MySQL, Redis, MongoDB
• Ubuntu, SUSE, Chef, Puppet, Docker
• Auto-scale based upon a schedule or CPU usage
• D-series VMs – SSDs and 60% faster processors
• G-series VMs – 32 cores, 450GB RAM, 6.5TB SSD
Virtual Machines
Use Virtual Machines to provision on-demand, scalable compute infrastructure when you need flexible
resources. Create VMs that run Windows, Linux, and enterprise applications. Or, capture your own
images to create custom VMs.
21. Reliable, economical cloud storage for data big and small
• Manage petabytes of storage
• Automatically replicated to 3 copies per region
• Geo-redundant storage across hundreds of miles for
higher availability across data centers
• Industry standard SMB file sharing across VMs
• Pay for what you use with competitive pricing
• REST, .NET, Java, C++, node.js, PowerShell, etc.
• Premium storage – 32TB, >50K IOPS per VM
Storage
Provides the flexibility to store and retrieve large amounts of unstructured data, such as documents and
media files with Azure Blobs; structured noSQL based data with Azure Tables; reliable messages with
Azure Queues, and use SMB based Azure Files for migrating on-premises applications to the cloud.
22.
23.
24. Sochi 2014 Olympics
Broadcasters 5
Countries 22 (population of 900M)
Channels 204
Program Hours 10,000
Channel Hours 88,000
Azure Data Centers 6
Azure Cores ~10,000
Largest Authenticated Event 2.1M viewers
Storage >100 TB
Storage Transactions ~500B
Hours Viewed ~19.3M
Unique Daily Viewers >100M
Bytes Served 35 Petabytes
NBC Sports Line Up on Microsoft Azure
English Premier
League
310 Events 930 hrs.
Sunday Night Football 22 events 66 hrs.
Pro Football Talk 96 days 2.5 hrs/day
Notre Dame Football 8 games 24 hrs.
Motocross 8 events 20 hrs.
F1 30 events 57 hrs.
MLS 15 games 45 hrs.
NHL 50 games 150 hrs.
PGA Golf 57 Matches 195.5 hrs.
Olympics 2014 50 channels ~3500 hrs.
Editor's Notes
What is Azure?
It’s IaaS + PaaS
Azure is the only major cloud platform ranked by Gartner as an industry leader for both infrastructure-as-a-service (IaaS) and platform-as-a-service (PaaS). This powerful combination of managed and unmanaged services lets you build, deploy, and manage applications any way you like for unmatched productivity.
It’s hybrid ready
Some cloud providers make you choose between your datacenter and the public cloud. Not Azure. Its enterprise-proven hybrid cloud solutions give you the best of both worlds, expanding your IT options without added complexity. With Azure, data storage, backup, and recovery become more efficient and economical. It’s also easier to build applications that span both on-premises and the cloud.
It’s open and flexible
Azure supports any operating system, language, tool, and framework— from Windows to Linux, SQL Server to Oracle, C# to Java. It puts the best of Windows and Linux ecosystems at your fingertips, so you can build great applications and services that work with every device.
It’s always up, always on (enterprise grade)
You’ll share the same enterprise-tested platform that powers Skype, Office 365, Bing, and Xbox. Azure offers a 99.95% availability SLA, 24x7 tech support, and round-the-clock service health monitoring. That’s why more than 57% of Fortune 500 companies rely on Azure today. From live streaming Olympic events to online multiplayer online games, our customers are doing some amazing things.
It’s economical and scalable
Azure can quickly scale up or down to match demand, so you only pay for what you use. Per-minute billing and a commitment to match competitor prices for popular infrastructure services like compute, storage and bandwidth means you’re always getting unbeatable price for performance.
It’s everywhere (has hyper-scale)
Azure runs on a growing global network of Microsoft-managed datacenters across 19 regions, giving you a wide range of options for running applications and ensuring your customers always get great performance. Azure is the first multinational cloud provider in mainland China and is continuing to expand to new regions around the globe.
So, what is Azure Search?
Azure Search is a fully-managed search solution that allows developers to enable search in web and mobile applications by embedding a sophisticated search experience into these applications without having to worry about the complexities of full-text search and without having to deploy, maintain or manage any infrastructure.
There are three main points to Azure Search.
First, Azure Search enables developers to Surface their application’s data – We provide all the features you would expect from sophisticated search solutions and provide reliable guaranteed performance on top of that. The tunable ranking models built into Search allow developers to tie search results to their business objectives by promoting results that they want to show up. For example, if you have an ecommerce site, you would want high margin items to come up higher in the search results than low margin items.
Second, Azure Search reduces complexity. It’s a fully managed service so we’re removing the need to worry about corrupt indexes, managing and upgrading hardware, and scaling out. You can easily scale out Azure Search to handle additional storage or throughput when that’s called for by business conditions such as during peak shopping season or if your app is featured in the news and traffic increases dramatically.
Third, Azure Search allows developers to move quickly with confidence. As the name implies, Azure Search runs on Azure. It’s available in the new Preview Portal which is all about being able to get up and running quickly and having lots of complementary services nearby. Also, you control Search using an API which makes it easy and familiar to manage.
These benefits all support the claim that Azure Search is perfect for enterprise cloud developers, cloud software vendors, and cloud architects who need a fully-managed search solution.
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Here’s a simplified snapshot of the whole solution, from storing and managing data, to business users accessing results and making decisions. If you already have a Microsoft Azure subscription or data in the cloud – especially in HDInsight – you are more than halfway there to realizing the benefit of this solution.
Let’s start in the bottom left with the Azure Portal.
The Azure ops team, maybe already accustomed to managing storage accounts or provisioning Azure virtual machines, can get a machine learning environment set up right from the Azure Portal. They can:
Create an ML Studio workspace and dedicated storage account to get their data scientists up and running
Monitor ML consumption to keep track of expenses
See alerts when a model is ready to be published
And deploy models as web services with the ML API Service
Now, moving right, to the ML Studio experience. This where the data scientist will spend her time:
She can execute every step in the data science workflow in one place – ML Studio
She can access and prepare data
Create, test and train models, as well as import her company’s proprietary models securely into her private workspace
Work with R and over 300 of the most popular R packages along with Microsoft’s business class algorithms
Collaborate with colleagues within the office or across the globe as easy as clicking “share my workspace”
Deploy models within minutes rather than weeks or months
And the data scientist has her choice of what data she wants to pull into her models. She can access data already in Azure, query across Big Data in HDInsight, or pull datasets in right from her desktop.
Once the data scientist is ready to publish, that’s when tested models become available to developers via the API service. The business users can access results, from anywhere, on any device. And any model updates simply refresh the model in production with no new development work needed.
Of course Azure SQL DB is somewhere under the covers, SQLServer. This picture illustrates where SQLServer actually lives. Of course there are a number of services build around this that really add value to the picture and deliver those cloud principles (Scale, Elasticity, Self-Service, Resilience etc.). You don’t need to explain all the layers – the point is they are there and actually that in “traditional” IT world, many/most of these functions in the picture are done by people, by IT Pro’s and DBA’s, worrying about how to get dtaabases proivisioned, keep the running, change them, fix them when broken etc.
Click: The other interesting thing about this picture is that when you provision a DB for your app (which you can do in about 6 seconds), the app actually get’s three “virtual” databases and one logical database that it interacts with (click). Each of the three database is located within Windows Azure in Fault Domains – a unit of computers all with redundant hardware, racks, switches etc. There is a “Primary” and two secondaries. Windows Azure is responsible for all the consistency and integrity of the three databases and completely automated will recover from failures and ensure balance of primaries and secondaries across physical nodes.
All you need to do is provision a database, say how big you want it, upload your schema and data, then start using it. EVERYTHING else is taken care of for you. AND you only pay for the actual data you are storing in the database (calculated on a daily basis).
Contrast this picture against doing your own thing in Azure Virtual Machines with SQLServer (or any other database for that matter) AND of course having to provide the same level of resilience.
So what is DocumentDB?
DocumentDB is a NoSQL document database-as-a-service, fully managed by Microsoft Azure.
It is for cloud-designed apps when query over schema-free data; reliable and predictable performance; and rapid development are key. It’s the first of its kind database service to offer native support for JavaScript, SQL query and transactions over schema-free JSON documents.
The key benefits of DocDB can be broken down into three pillars. We'll go into a bit more detail into how DocDB is differentiated in the market based on these pillars.
Rich query and transaction over schema-free data – which includes the concepts of query, automatic indexing, transactions, sql-like query language
Reliable and Predictable Peformance – built for the cloud, tunable consistency, elastic
Rapid Development – benefits of being part of Azure, build with familiar tools (so you can bring your JSON data and take it away)
Together, you have a service that is perfect for cloud architects and developers who need an enterprise-ready NoSQL document database.
With the addition of DocumentDB, here is how the chart looks. You can see how DocumentDB bridges the left and right sides of the chart. Its a database that is fully managed, has elastic scale, is queryable, supports transactions, and easily accessible – all over a schema-free JSON data model and with native JavaScript support.
Instead of storing data in tables, DocDB stores data in JSON documents. Because of the deep commitment and integration of JavaScript and the close knit relationship between JSON and JacaScript, JavaScript is to DocDB as T-SQL is to SQL Server.
You could include Hbase in HDInsight, which is a NoSQL column store, and some of the NoSQL options available in the Azure store on this chart, but today we’re focused on DocumentDB so the goal here is to provide the context for DocDB within what’s already well established on Azure. There are a good number of NoSQL database and more specifically document databases available in the market today such as Mongo, Cassandra, Raven, Couch, Dynamo, Datastore, and others. There’s a battlecard that compares DocDB to some of the more common competitors you’re likely to come up against that will be published on Infopedia. But, we’re not going to specifically go deep on compete today.
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