Presented by, Dr Christian Geuer-Pollmann, Senior Technology Evangelist at Microsoft.
The presentation gives a solid overview to the Microsoft Azure platform, with a special emphasis on scenarios for IoT workloads. First, Christian provides an introduction to Microsoft Azure’s IaaS compute and networking infrastructure (i.e. virtual machines, virtual networks, load balancers and HA concepts). The second part of the presentation focuses on higher-order services in Azure, such as relational data bases, machine learning, search, and NoSQL offerings. Last, Christian explains how the Azure Service Bus and the Intelligent Systems Services fit into the overall IoT landscape.
Using Azure Managed Identities for your App Services by Jan de Vries from 4Do...DevClub_lv
Jan de Vries from 4DotNet will share experience on “Using Azure Managed Identities for your App Services“.
He will show you what needs to be set up in your application and AAD to get you started. When everything is set up correctly you can manage the access to all of your API’s via Azure Active Directory and even restrict access to specific endpoints if you want.
You’ll leave this session knowing how to set up your services by using the built-in capabilities of Azure and make your complete environment more secure and easy to manage.
Jan is a Cloud Solution Architect at 4DotNet (Netherlands). His main focus is on developing highly performant and scalable solutions using the awesome services provided by the Microsoft Azure platform. Because of his expertise, he has been able to help out multiple customers to bring their on-premise solution to the cloud and guide them towards a better software development ecosystem.
This document provides an overview of implementing Microsoft Azure infrastructure solutions. It covers cloud computing concepts and the history of cloud computing. It also provides an in-depth look at Microsoft Azure, including the Azure management portals, using PowerShell to manage Azure, and hands-on labs for getting started with Azure.
Global Azure is the biggest Microsoft Azure community event with over 10,000 people from 192 locations across 57 countries. The agenda includes an introduction to IoT, prototyping connected objects, Azure building blocks, a demo, and some code. When building IoT solutions, choices must be made around how devices are powered and connected to cloud services, and what protocols are used to encode and transmit data. Event Hubs and Stream Analytics can be used to process IoT data at scale from various sources in the cloud. The NAO robot is proposed as an interface for an ambient intelligence weather station prototype that collects data from sensors via AMQP and displays information through HTTP requests.
This document discusses Microsoft Azure Mobile Services, which provides a backend platform for building and managing mobile apps. It includes features for storage, authentication, push notifications, scheduling jobs, and more. The document demonstrates how to get started with Mobile Services, customize backend logic, add authentication, and scale the services. It also provides an overview of the Azure Mobile Services architecture and pricing tiers.
The document discusses several demos of hardware accelerated machine learning inference:
- A heavy edge demo showing hardware accelerated inferencing on the edge using a Minnow Board.
- A drone app creation demo.
- A vision AI developer kit demo.
An Azure virtual network (VNet) provides connectivity and security for virtual machines and allows access to the public internet and other VMs. Network security groups contain rules that allow or deny network traffic, and Azure load balancers distribute incoming internet traffic across VMs. Availability sets distribute VMs across update and fault domains for redundancy and high availability. Virtual network gateways connect Azure VNets and on-premises networks, while Traffic Manager controls traffic distribution across endpoints in different datacenters.
CCI2018 - Azure Network - Security Best Practiceswalk2talk srl
Francesco Molfese presented on Azure network security best practices. He discussed how to use Azure networking services like virtual networks, network security groups, application security groups, service endpoints, Azure Firewall, and DDoS protection to implement a zero trust network model. A hub-spoke topology with services in the hub and workloads in the spokes provides segmentation and security. Monitoring, logging, and alerts from services like Network Watcher and Azure Monitor help provide visibility and protection. The presentation provided demos and recommendations on configuring these services to securely network Azure resources.
Part 01: Azure Virtual Networks – An OverviewNeeraj Kumar
A virtual network in Azure is similar to the network that we have in our on-premises environment, helping us connect different resources. The azure network helps us connect virtual machines (VMs), create a connected system as a part of a FARMs so that they can communicate with each other, and talk to the on-premises systems as well in special connected scenarios.
This is the Part 1 of the Azure Virtual Networking Servies and is the part of the AZ-100 certification examination, and it provides an overview of the vNet, and the components of the virtual network that an Azure Administrator has to deal with on a daily basis.
In this demo heavy session you will learn what’s available for modern IoT developers. Azure IoT Hub, Device Provisioning Service, Time Series Insight, Azure Location Based Services, Visual Studio Code will all be put to contribution and you won’t believe all that can be achieved in only 60 minutes.
SGD is a product that enables secure browser-initiated access to server-hosted applications from various client devices. It supports access to Windows, Linux, Unix, and mainframe applications as well as web applications. SGD provides a single access point and supports various usage scenarios and experiences. It is optimized for performance over different network conditions and adheres to high security standards.
The document describes Microsoft's global network and connectivity options for connecting on-premises networks to Azure. It includes a diagram of the Microsoft global network with over 70 locations worldwide. It also describes ExpressRoute for private connectivity, including premium SKUs that allow cross-region connectivity. Virtual WAN is introduced as a managed connectivity service that can incorporate ExpressRoute and internet connections across on-premises and Azure networks.
Jihoon Son presents Apache Tajo, an open source data warehouse system that supports SQL queries. Tajo can run on OpenStack Swift object storage without any code modifications, addressing the need for SQL queries on Swift data. Son demonstrates how Tajo integrates with Swift, discusses configurations, and addresses the data locality problem. Advanced integration techniques like a location-aware computing model are presented to improve performance when Tajo and Swift clusters are co-located. The roadmap includes specialized storage layers for Swift and support for additional storage like Cinder and Ceph block storage.
The document discusses several Azure network architectures including:
1) An Azure landing zone with firewall/WAF that includes hub-spoke VNets with web, business, and data tiers separated across spokes connected to an on-premises network.
2) An Azure network architecture deployed to a primary region including production and non-production subscriptions, VNets, and resource groups separated by function and connected to an on-premises network via VPN.
3) A hub-spoke network topology with shared services and subnets in a central hub VNet and workloads separated across spoke VNets connected to the hub.
Cybersecurity is important in any software solution. It’s even more important in the Internet of Things. This session takes you through building and prototyping secure, Internet to Things solutions using Azure Sphere; the Linux-based, secured, connected, crossover microcontroller unit (MCU) from Microsoft. We’ll look at securing Azure Sphere devices, writing and deploying code, and communicating with Azure IoT Hub. You’ll leave this session better prepared to build more highly secured IoT solutions using Microsoft Azure.
Azure Networking: Innovative Features and Multi-VNet TopologiesMarius Zaharia
Are you looking to deploy a more complex structure of resources in Azure, all secured and segregated by precise boundaries while closely communicating with each other? Following the arrival of the advanced IaaS networking features in Azure (network security groups, routing, multi-NIC, …) and their maturation in the last months, here is the moment for you to find a modern architectural vision of networking in Azure, with focus on multi-VNET / VPN topologies, and based on ARM deployment model.
Azure supports both Linux and Windows containers that allow for efficient isolation and resource sharing. It provides container services and tools including Docker images, Kubernetes, Mesos and Docker support to deploy and manage containers at cloud scale. Azure's container infrastructure can be used to build applications with microservices architecture and provide agility and cost control.
Private clouds are cloud infrastructure that resides within a company's own datacenter and is managed internally. They allow a company to have cloud-like capabilities while maintaining control and security over their own data. Private clouds work by using virtualization and a controller to provision and track physical resources like servers, storage, and networks as more capacity is needed. The document discusses the private cloud platforms Eucalyptus, OpenStack, and CloudStack, comparing their architectures, development histories, and strengths for different use cases.
Presentation from the following session ; http://expertslive.nl/sessions/end-to-end-automation-what-happens-when-we-throw-arm-dsc-posh-into-a-blender-en/
"Wat voor een magisch efffect komt naar boven wanneer we Azure Resource Manager, Desired State Configuration & Powershell in een blender duwen? We zetten de stand op “DevOps” en nemen gelijk een kijkje naar wat dit marketing verhaaltje nu in praktijk zal betekenen voor een ITpro!"
22/11/2016
ITProceed 2015 - Securing Sensitive Data with Azure Key VaultTom Kerkhove
Security has become more and more important as we move to the cloud and countries & companies are being hacked – remember the Sony hack? But how do we securely store sensitive data such as connection strings to our databases? Where do we store our encryption keys? Can I share them with my customers? How do I prevent abuse of my secrets and block them from doing so?
That’s what this session is all about – I will introduce you to the concepts of Microsoft Azure Key Vault where you can use this as it allows you to securely store keys, credentials and other secrets in the cloud. We will also have a look at how it enables us to store encryption keys for SQL Server TDE and how it can help you safeguard your cloud solutions even more.
This document discusses Internet of Things (IoT) solutions using Microsoft Azure cloud services. It provides an overview of IoT, why the cloud is useful for IoT, and Azure IoT services. It also demonstrates connecting devices to Azure using protocols like MQTT and streaming data to analytics tools. Finally, it discusses IoT platforms and devices like Arduino that can be used to build IoT solutions.
Scaling MongoDB in the cloud with Microsoft AzureIvan Fioravanti
Scaling MongoDB in the cloud with Microsoft Azure.
From my MongoDB Evening Talk of 1st April in Milan.
What we do, why, and how with MongoDB, with a lot of tips & tricks from our real life experience.
The three aaS's of MongoDB in Windows AzureMongoDB
The document discusses the three deployment options - IaaS, PaaS, and SaaS - for running MongoDB on Microsoft's Windows Azure cloud platform. It provides an overview of Windows Azure, then demonstrates deploying MongoDB replica sets on Windows Azure virtual machines (IaaS), worker roles (PaaS), and using the hosted MongoDB service from MongoLab (SaaS). The document concludes by discussing hybrid approaches and factors to consider for each deployment option.
Link Labs provides wireless connectivity and data management software for Internet of Things products and solutions. Their Symphony Link technology offers long range and low power wireless connectivity that can connect thousands of devices to gateways over large areas with battery life lasting over 10 years. It provides an alternative to cellular and short-range wireless technologies and makes it possible for battery-powered sensors to connect over wide areas. Link Labs focuses on working with large industrial companies in sectors like agriculture, security, smart cities, and utilities.
OIES Consulting provides IoT strategic consulting and business development services to help companies translate IoT potential into profitable value. Their services include IoT strategy, market entry plans, solution design, and business planning. They target IoT vendors, service providers, system integrators, and enterprises in industries like manufacturing, retail, and insurance.
The document provides an introduction to the Internet of Things (IoT) and discusses Ayla Networks' agile IoT platform. Some key points include:
1) The IoT will dwarf all other stages of the internet and is estimated to have a potential economic impact of $3.9-11 trillion annually by 2025.
2) Connected devices and implementing cloud connectivity presents many challenges due to the complex system requirements.
3) Ayla Networks' single layer of software fabric streamlines connectivity between devices, applications, and the cloud, accelerating time to market over traditional models.
4) The platform provides production-ready networking, global presence, scalability, security, and actionable
This document discusses OIES Consulting's services for selecting an Internet of Things (IoT) platform. It outlines a multi-step process they use, including developing a shortlist of 5-6 platforms by matching client business needs to their taxonomy of platform capabilities. They then perform hands-on testing, questionnaire analysis, and technical, functional, development, and business assessments of shortlisted platforms. OIES assists clients with requests for information and proposals, evaluation criteria, and makes an unbiased recommendation on the optimal platform. Their goal is to apply experience to make a fact-based purchasing decision that meets current and future requirements.
In this talk we will review the factors that drive the capacity requirements: volume of queries, access patterns, indexing, working set size, among others. View the slides with video recording: www.mongodb.com/presentations/hardware-provisioning-mongodb
1) Two case studies are presented of companies provisioning MongoDB clusters correctly and incorrectly. A Spanish bank stored 6 months of logs (18TB total) in MongoDB and sized their cluster to handle a 4TB working set. An online retailer moved their product catalog to MongoDB and deployed a single replica set large enough to hold all 240GB of data to meet their performance needs.
2) A software company deployed a replica set incorrectly by overspending on physical servers and underprovisioning EC2 instances, causing the EC2 instances to be a bottleneck. Another company did not provision enough RAM for their workload.
3) Key lessons are to understand performance needs up front, get help from MongoDB, conduct proof of concepts to
IoT across devices with Windows 10 and Azure IoT Suite by Admir TuzovićBosnia Agile
More and more, we’re seeing the Internet of Things (IoT) become part of the fabric of business, helping converge an organization’s assets, data and processes with people and business systems. Today, this intersection is allowing enterprises to uncover new opportunities, create new business models and transform their operations – from elevators, to particle accelerators and washing machines – to become truly digital businesses.
Microsoft’s vision is to help companies thrive in this era of IoT, delivering open, scalable platforms and services that any company, whether startup or the most established global enterprises, can use to create new value, right now. We have made huge investments in the Windows 10 IoT operating system for devices, and equally with the Azure IoT Suite, we’re bringing together a variety of Azure services to help our customers accelerate their transformation to digital businesses.
The Azure IoT Suite is an integrated offering that takes advantage of all the relevant Azure capabilities to connect devices and other assets (i.e. “things”), capture the diverse and voluminous data they generate, integrate and orchestrate the flow of that data, and manage, analyze and present it as usable information to the people who need it to make better decisions as well as intelligently automate operations. The offering, while customizable to fit the unique needs of organizations, will also provide finished applications to speed deployment of common scenarios we see across many industries, such as remote monitoring, asset management and predictive maintenance, while providing the ability to grow and scale solutions to millions of “things.”
The document discusses Internet of Things (IoT) platforms and architectures. It provides three key points:
1) An IoT platform uses a standardized architecture to streamline onboarding new applications and manage information in a unified, secure, and flexible end-to-end system.
2) The architecture includes components for network interoperability, device and service management, data acquisition and verification, data analytics, data services, and backend systems.
3) Implementing an IoT platform can provide benefits to smart cities through use cases like smart street lighting, waste management, and parking that reduce energy and maintenance costs.
The document discusses HP's Internet of Things (IoT) platform and solutions for communications service providers (CSPs) to capitalize on opportunities in the IoT market. It describes HP's IoT platform architecture which includes capabilities for device and service management, data acquisition and verification, data analytics, and network interworking. It also discusses how the platform allows CSPs to launch new revenue streams, enhance customer experiences, and optimize investments. The document provides examples of HP's energy management solution which uses the IoT platform to securely provide home automation and energy control services.
IoT and the Oil & Gas industry at M2M Oil & Gas 2014 in LondonEurotech
How the Internet of Things is catching up with the Oil & Gas industry.
How Eurotech's IoT architecture had its roots in the oil & gas industry, and why it is still relevant today.
The document discusses IBM's Watson IoT Platform. It describes how the platform connects devices through sensors and analytics to generate insights that can improve operations, customer experiences, and create new business models. Specifically, it allows collecting data from hundreds of thousands of devices in real-time, analyzing the data to monitor performance and predict maintenance needs, and using cognitive technologies like Watson to gain new intelligence from physical systems and processes. The platform provides security, scalability, analytics and applications to help companies transform their business using IoT.
Watson IoT Platform Sizing & Pricing - Sept 2016Jason Lu
The document provides information about IBM's Watson IoT Platform, including its pricing and financing options. The platform allows connecting devices and sensors to collect and analyze IoT data. It offers a free tier for basic use as well as paid dedicated and local options that provide more connections and storage. Pricing is based on the amount of data processed and stored each month. Financing options are also available to spread payments for the Watson IoT solutions over time.
IOT Factory - Open IOT Platform & Startup StudioLionel Anciaux
IOT Factory is a Software Platform and a Project Studio providing Fast and Reliable IOT projects & Startups development capabilities.
At the core of IOT Factory is an Open Platform designed to easily build, deploy and operate Internet of Things projects & products. It is Devices and Telecommunication networks agnostic, provides easy dashboarding, reporting, alerting and back-end integrations capabilities, based on a Big Data repository and strong web services APIs.
As a Project Studio, IOT Factory aims at providing financing and business support to project owners willing to develop innovative companies.
IOT Factory is located in Brussels, Paris and Moscow. Through our Clients, Partners and Startups eco-system, we already offer solutions in Smart Metering, Pets Tracking, Industry 4.0, Smart Agriculture, etc.
Let’s talk about your challenges, and analyze together how IOT could solve it !
This document discusses centralized and decentralized capabilities that could be provided by an Internet of Things (IOT) Platform as a Service (PaaS). Centralized capabilities discussed include device management, protocol hub, device discovery, event aggregation, telemetry data storage, event simulation, event notifications, and real-time data visualization. Decentralized capabilities discussed include peer-to-peer secure messaging, contract enforcement/messaging trust, and file sharing. The document also discusses how some of these capabilities could be implemented and compares Cloudfoundry and blockchain as foundational models for centralized and decentralized IOT PaaS respectively.
The document discusses Microsoft Azure and its Internet of Things (IoT) capabilities. It describes Azure's global infrastructure and wide range of platform services. It then focuses on the key components of Azure IoT Suite, including preconfigured solutions, agent libraries to connect heterogeneous devices, Azure IoT Hub for connectivity, Stream Analytics for real-time event processing, Machine Learning for predictive analytics, Power BI for data visualization, and Logic Apps for workflow integration. The Azure IoT Suite provides a comprehensive solution to connect millions of devices, analyze data, and integrate with business systems.
The breath and depth of Azure products that fall under the AI and ML umbrella can be difficult to follow. In this presentation I’ll first define exactly what AI, ML, and deep learning is, and then go over the various Microsoft AI and ML products and their use cases.
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.
Azure Infrastructure Services provides compute, network, and storage services on Microsoft's Azure cloud platform. The presentation discusses how IT infrastructure supports business objectives, outlines various Azure services including virtual machines, networking, storage and identity/access management, and demonstrates how to migrate applications to Azure through strategies like lift and shift or refactoring for the cloud. It also compares Azure services to analogous offerings on AWS.
The document summarizes a presentation given by the Wisconsin .NET Users Group in September 2009. It discusses challenges facing enterprises and how cloud computing addresses issues like high infrastructure costs, limited data center capacity, and lack of a common platform. It introduces the Windows Azure platform and how it provides automated management, scalability, and a familiar development experience. Key aspects of Windows Azure including its architecture, SQL Azure, and pricing models are summarized.
1 Introduction to Microsoft data platform analytics for releaseJen Stirrup
Part 1 of a conference workshop. This forms the morning session, which looks at moving from Business Intelligence to Analytics.
Topics Covered: Azure Data Explorer, Azure Data Factory, Azure Synapse Analytics, Event Hubs, HDInsight, Big Data
This document provides an introduction to Microsoft Azure and its services. It outlines 7 modules that cover: 1) an introduction to Azure, 2) virtual machines, 3) networking, 4) Active Directory, 5) cloud services and web sites, 6) SQL Server and SharePoint, and 7) management and monitoring. The instructor is then introduced as Michael Washam, the original developer of the Azure PowerShell cmdlets and a globally recognized speaker on Azure.
This document discusses migrating to the cloud with Microsoft Azure and Office 365. It provides an overview of migration scenarios for email and files with Office 365, and discusses how to migrate applications and use development tools in Azure. Options for storage, web apps, and hybrid cloud solutions are presented. Security and privacy features of Office 365 are outlined. Finally, available migration tools for email and files are listed.
This document provides an overview of Microsoft's Azure IoT platform and services. It describes Azure services for ingesting and analyzing IoT device data like IoT Hub, Stream Analytics, Machine Learning, and Time Series Insights. It also outlines edge computing capabilities with IoT Edge and device management solutions. Finally, it showcases several IoT solutions and provides links to learn more about building IoT applications on Azure.
The document provides an overview of the Windows Azure Platform, including its core services and capabilities. It discusses Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS) models. It also summarizes key services like Windows Azure, SQL Azure, AppFabric, and the consumption pricing models.
The document discusses the intelligent edge and hybrid cloud computing. It defines the intelligent edge as where data is created and processed outside traditional centralized data centers. It predicts that by 2025, 75% of enterprise data will be created and processed at the edge. It then provides an overview of different Azure products and solutions for intelligent edge computing, including Azure Sphere, IoT Edge, Stack Edge, and Stack Hub. It discusses how these products bring cloud services and capabilities to the edge through appliances, gateways, and on-premises servers to enable hybrid cloud solutions.
.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.
The document provides an overview of the main services available on the Azure cloud computing platform. It describes compute, networking, storage, mobile, database, web, Internet of Things (IoT), big data, artificial intelligence (AI), and DevOps services available and provides examples of specific services within each category. The services aim to provide scalable, secure, globally accessible options for hosting applications and data in the cloud.
Evangelos Kapsalakis, Partner Specialist at Microsoft, provides valuable insights on Microsoft Azure and its flexibility when it comes to migration deployment. From Cloud Migration Through Automation: Next Level Flexibility virtual event, hosted on September 30, 2020
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.
This document discusses Microsoft Azure, a cloud computing platform. It provides an overview of Azure's capabilities including infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS). It highlights key Azure services such as virtual machines, SQL database, web apps, machine learning, and more. The document also discusses how Azure enables businesses to rapidly setup environments, scale infrastructure, and increase efficiency at a lower cost compared to on-premises solutions.
The document discusses challenges facing today's enterprises including cutting costs, driving value with tight budgets, maintaining security while increasing access, and finding the right transformative capabilities. It then discusses challenges in building applications such as scaling, availability, and costs. The document introduces the Windows Azure platform as a solution, highlighting its fundamentals of scale, automation, high availability, and multi-tenancy. It provides considerations for using cloud computing on or off premises and discusses ownership models.
Similar to MongoDB IoT City Tour STUTTGART: The Microsoft Azure Platform for IoT (20)
MongoDB SoCal 2020: Migrate Anything* to MongoDB AtlasMongoDB
This presentation discusses migrating data from other data stores to MongoDB Atlas. It begins by explaining why MongoDB and Atlas are good choices for data management. Several preparation steps are covered, including sizing the target Atlas cluster, increasing the source oplog, and testing connectivity. Live migration, mongomirror, and dump/restore options are presented for migrating between replicasets or sharded clusters. Post-migration steps like monitoring and backups are also discussed. Finally, migrating from other data stores like AWS DocumentDB, Azure CosmosDB, DynamoDB, and relational databases are briefly covered.
MongoDB SoCal 2020: Go on a Data Safari with MongoDB Charts!MongoDB
These days, everyone is expected to be a data analyst. But with so much data available, how can you make sense of it and be sure you're making the best decisions? One great approach is to use data visualizations. In this session, we take a complex dataset and show how the breadth of capabilities in MongoDB Charts can help you turn bits and bytes into insights.
MongoDB SoCal 2020: Using MongoDB Services in Kubernetes: Any Platform, Devel...MongoDB
MongoDB Kubernetes operator and MongoDB Open Service Broker are ready for production operations. Learn about how MongoDB can be used with the most popular container orchestration platform, Kubernetes, and bring self-service, persistent storage to your containerized applications. A demo will show you how easy it is to enable MongoDB clusters as an External Service using the Open Service Broker API for MongoDB
MongoDB SoCal 2020: A Complete Methodology of Data Modeling for MongoDBMongoDB
Are you new to schema design for MongoDB, or are you looking for a more complete or agile process than what you are following currently? In this talk, we will guide you through the phases of a flexible methodology that you can apply to projects ranging from small to large with very demanding requirements.
MongoDB SoCal 2020: From Pharmacist to Analyst: Leveraging MongoDB for Real-T...MongoDB
Humana, like many companies, is tackling the challenge of creating real-time insights from data that is diverse and rapidly changing. This is our journey of how we used MongoDB to combined traditional batch approaches with streaming technologies to provide continues alerting capabilities from real-time data streams.
MongoDB SoCal 2020: Best Practices for Working with IoT and Time-series DataMongoDB
Time series data is increasingly at the heart of modern applications - think IoT, stock trading, clickstreams, social media, and more. With the move from batch to real time systems, the efficient capture and analysis of time series data can enable organizations to better detect and respond to events ahead of their competitors or to improve operational efficiency to reduce cost and risk. Working with time series data is often different from regular application data, and there are best practices you should observe.
This talk covers:
Common components of an IoT solution
The challenges involved with managing time-series data in IoT applications
Different schema designs, and how these affect memory and disk utilization – two critical factors in application performance.
How to query, analyze and present IoT time-series data using MongoDB Compass and MongoDB Charts
At the end of the session, you will have a better understanding of key best practices in managing IoT time-series data with MongoDB.
Join this talk and test session with a MongoDB Developer Advocate where you'll go over the setup, configuration, and deployment of an Atlas environment. Create a service that you can take back in a production-ready state and prepare to unleash your inner genius.
MongoDB .local San Francisco 2020: Powering the new age data demands [Infosys]MongoDB
Our clients have unique use cases and data patterns that mandate the choice of a particular strategy. To implement these strategies, it is mandatory that we unlearn a lot of relational concepts while designing and rapidly developing efficient applications on NoSQL. In this session, we will talk about some of our client use cases, the strategies we have adopted, and the features of MongoDB that assisted in implementing these strategies.
MongoDB .local San Francisco 2020: Using Client Side Encryption in MongoDB 4.2MongoDB
Encryption is not a new concept to MongoDB. Encryption may occur in-transit (with TLS) and at-rest (with the encrypted storage engine). But MongoDB 4.2 introduces support for Client Side Encryption, ensuring the most sensitive data is encrypted before ever leaving the client application. Even full access to your MongoDB servers is not enough to decrypt this data. And better yet, Client Side Encryption can be enabled at the "flick of a switch".
This session covers using Client Side Encryption in your applications. This includes the necessary setup, how to encrypt data without sacrificing queryability, and what trade-offs to expect.
MongoDB .local San Francisco 2020: Using MongoDB Services in Kubernetes: any ...MongoDB
MongoDB Kubernetes operator is ready for prime-time. Learn about how MongoDB can be used with most popular orchestration platform, Kubernetes, and bring self-service, persistent storage to your containerized applications.
MongoDB .local San Francisco 2020: Go on a Data Safari with MongoDB Charts!MongoDB
These days, everyone is expected to be a data analyst. But with so much data available, how can you make sense of it and be sure you're making the best decisions? One great approach is to use data visualizations. In this session, we take a complex dataset and show how the breadth of capabilities in MongoDB Charts can help you turn bits and bytes into insights.
MongoDB .local San Francisco 2020: From SQL to NoSQL -- Changing Your MindsetMongoDB
When you need to model data, is your first instinct to start breaking it down into rows and columns? Mine used to be too. When you want to develop apps in a modern, agile way, NoSQL databases can be the best option. Come to this talk to learn how to take advantage of all that NoSQL databases have to offer and discover the benefits of changing your mindset from the legacy, tabular way of modeling data. We’ll compare and contrast the terms and concepts in SQL databases and MongoDB, explain the benefits of using MongoDB compared to SQL databases, and walk through data modeling basics so you feel confident as you begin using MongoDB.
MongoDB .local San Francisco 2020: MongoDB Atlas JumpstartMongoDB
Join this talk and test session with a MongoDB Developer Advocate where you'll go over the setup, configuration, and deployment of an Atlas environment. Create a service that you can take back in a production-ready state and prepare to unleash your inner genius.
MongoDB .local San Francisco 2020: Tips and Tricks++ for Querying and Indexin...MongoDB
The document discusses guidelines for ordering fields in compound indexes to optimize query performance. It recommends the E-S-R approach: placing equality fields first, followed by sort fields, and range fields last. This allows indexes to leverage equality matches, provide non-blocking sorts, and minimize scanning. Examples show how indexes ordered by these guidelines can support queries more efficiently by narrowing the search bounds.
MongoDB .local San Francisco 2020: Aggregation Pipeline Power++MongoDB
Aggregation pipeline has been able to power your analysis of data since version 2.2. In 4.2 we added more power and now you can use it for more powerful queries, updates, and outputting your data to existing collections. Come hear how you can do everything with the pipeline, including single-view, ETL, data roll-ups and materialized views.
MongoDB .local San Francisco 2020: A Complete Methodology of Data Modeling fo...MongoDB
The document describes a methodology for data modeling with MongoDB. It begins by recognizing the differences between document and tabular databases, then outlines a three step methodology: 1) describe the workload by listing queries, 2) identify and model relationships between entities, and 3) apply relevant patterns when modeling for MongoDB. The document uses examples around modeling a coffee shop franchise to illustrate modeling approaches and techniques.
MongoDB .local San Francisco 2020: MongoDB Atlas Data Lake Technical Deep DiveMongoDB
MongoDB Atlas Data Lake is a new service offered by MongoDB Atlas. Many organizations store long term, archival data in cost-effective storage like S3, GCP, and Azure Blobs. However, many of them do not have robust systems or tools to effectively utilize large amounts of data to inform decision making. MongoDB Atlas Data Lake is a service allowing organizations to analyze their long-term data to discover a wealth of information about their business.
This session will take a deep dive into the features that are currently available in MongoDB Atlas Data Lake and how they are implemented. In addition, we'll discuss future plans and opportunities and offer ample Q&A time with the engineers on the project.
MongoDB .local San Francisco 2020: Developing Alexa Skills with MongoDB & GolangMongoDB
Virtual assistants are becoming the new norm when it comes to daily life, with Amazon’s Alexa being the leader in the space. As a developer, not only do you need to make web and mobile compliant applications, but you need to be able to support virtual assistants like Alexa. However, the process isn’t quite the same between the platforms.
How do you handle requests? Where do you store your data and work with it to create meaningful responses with little delay? How much of your code needs to change between platforms?
In this session we’ll see how to design and develop applications known as Skills for Amazon Alexa powered devices using the Go programming language and MongoDB.
MongoDB .local Paris 2020: Realm : l'ingrédient secret pour de meilleures app...MongoDB
aux Core Data, appréciée par des centaines de milliers de développeurs. Apprenez ce qui rend Realm spécial et comment il peut être utilisé pour créer de meilleures applications plus rapidement.
MongoDB .local Paris 2020: Upply @MongoDB : Upply : Quand le Machine Learning...MongoDB
Il n’a jamais été aussi facile de commander en ligne et de se faire livrer en moins de 48h très souvent gratuitement. Cette simplicité d’usage cache un marché complexe de plus de 8000 milliards de $.
La data est bien connu du monde de la Supply Chain (itinéraires, informations sur les marchandises, douanes,…), mais la valeur de ces données opérationnelles reste peu exploitée. En alliant expertise métier et Data Science, Upply redéfinit les fondamentaux de la Supply Chain en proposant à chacun des acteurs de surmonter la volatilité et l’inefficacité du marché.
UiPath Community Day Kraków: Devs4Devs ConferenceUiPathCommunity
We are honored to launch and host this event for our UiPath Polish Community, with the help of our partners - Proservartner!
We certainly hope we have managed to spike your interest in the subjects to be presented and the incredible networking opportunities at hand, too!
Check out our proposed agenda below 👇👇
08:30 ☕ Welcome coffee (30')
09:00 Opening note/ Intro to UiPath Community (10')
Cristina Vidu, Global Manager, Marketing Community @UiPath
Dawid Kot, Digital Transformation Lead @Proservartner
09:10 Cloud migration - Proservartner & DOVISTA case study (30')
Marcin Drozdowski, Automation CoE Manager @DOVISTA
Pawel Kamiński, RPA developer @DOVISTA
Mikolaj Zielinski, UiPath MVP, Senior Solutions Engineer @Proservartner
09:40 From bottlenecks to breakthroughs: Citizen Development in action (25')
Pawel Poplawski, Director, Improvement and Automation @McCormick & Company
Michał Cieślak, Senior Manager, Automation Programs @McCormick & Company
10:05 Next-level bots: API integration in UiPath Studio (30')
Mikolaj Zielinski, UiPath MVP, Senior Solutions Engineer @Proservartner
10:35 ☕ Coffee Break (15')
10:50 Document Understanding with my RPA Companion (45')
Ewa Gruszka, Enterprise Sales Specialist, AI & ML @UiPath
11:35 Power up your Robots: GenAI and GPT in REFramework (45')
Krzysztof Karaszewski, Global RPA Product Manager
12:20 🍕 Lunch Break (1hr)
13:20 From Concept to Quality: UiPath Test Suite for AI-powered Knowledge Bots (30')
Kamil Miśko, UiPath MVP, Senior RPA Developer @Zurich Insurance
13:50 Communications Mining - focus on AI capabilities (30')
Thomasz Wierzbicki, Business Analyst @Office Samurai
14:20 Polish MVP panel: Insights on MVP award achievements and career profiling
Navigating Post-Quantum Blockchain: Resilient Cryptography in Quantum Threatsanupriti
In the rapidly evolving landscape of blockchain technology, the advent of quantum computing poses unprecedented challenges to traditional cryptographic methods. As quantum computing capabilities advance, the vulnerabilities of current cryptographic standards become increasingly apparent.
This presentation, "Navigating Post-Quantum Blockchain: Resilient Cryptography in Quantum Threats," explores the intersection of blockchain technology and quantum computing. It delves into the urgent need for resilient cryptographic solutions that can withstand the computational power of quantum adversaries.
Key topics covered include:
An overview of quantum computing and its implications for blockchain security.
Current cryptographic standards and their vulnerabilities in the face of quantum threats.
Emerging post-quantum cryptographic algorithms and their applicability to blockchain systems.
Case studies and real-world implications of quantum-resistant blockchain implementations.
Strategies for integrating post-quantum cryptography into existing blockchain frameworks.
Join us as we navigate the complexities of securing blockchain networks in a quantum-enabled future. Gain insights into the latest advancements and best practices for safeguarding data integrity and privacy in the era of quantum threats.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/07/intels-approach-to-operationalizing-ai-in-the-manufacturing-sector-a-presentation-from-intel/
Tara Thimmanaik, AI Systems and Solutions Architect at Intel, presents the “Intel’s Approach to Operationalizing AI in the Manufacturing Sector,” tutorial at the May 2024 Embedded Vision Summit.
AI at the edge is powering a revolution in industrial IoT, from real-time processing and analytics that drive greater efficiency and learning to predictive maintenance. Intel is focused on developing tools and assets to help domain experts operationalize AI-based solutions in their fields of expertise.
In this talk, Thimmanaik explains how Intel’s software platforms simplify labor-intensive data upload, labeling, training, model optimization and retraining tasks. She shows how domain experts can quickly build vision models for a wide range of processes—detecting defective parts on a production line, reducing downtime on the factory floor, automating inventory management and other digitization and automation projects. And she introduces Intel-provided edge computing assets that empower faster localized insights and decisions, improving labor productivity through easy-to-use AI tools that democratize AI.
Quantum Communications Q&A with Gemini LLM. These are based on Shannon's Noisy channel Theorem and offers how the classical theory applies to the quantum world.
Data Protection in a Connected World: Sovereignty and Cyber Securityanupriti
Delve into the critical intersection of data sovereignty and cyber security in this presentation. Explore unconventional cyber threat vectors and strategies to safeguard data integrity and sovereignty in an increasingly interconnected world. Gain insights into emerging threats and proactive defense measures essential for modern digital ecosystems.
The Rise of Supernetwork Data Intensive ComputingLarry Smarr
Invited Remote Lecture to SC21
The International Conference for High Performance Computing, Networking, Storage, and Analysis
St. Louis, Missouri
November 18, 2021
Performance Budgets for the Real World by Tammy EvertsScyllaDB
Performance budgets have been around for more than ten years. Over those years, we’ve learned a lot about what works, what doesn’t, and what we need to improve. In this session, Tammy revisits old assumptions about performance budgets and offers some new best practices. Topics include:
• Understanding performance budgets vs. performance goals
• Aligning budgets with user experience
• Pros and cons of Core Web Vitals
• How to stay on top of your budgets to fight regressions
Video traffic on the Internet is constantly growing; networked multimedia applications consume a predominant share of the available Internet bandwidth. A major technical breakthrough and enabler in multimedia systems research and of industrial networked multimedia services certainly was the HTTP Adaptive Streaming (HAS) technique. This resulted in the standardization of MPEG Dynamic Adaptive Streaming over HTTP (MPEG-DASH) which, together with HTTP Live Streaming (HLS), is widely used for multimedia delivery in today’s networks. Existing challenges in multimedia systems research deal with the trade-off between (i) the ever-increasing content complexity, (ii) various requirements with respect to time (most importantly, latency), and (iii) quality of experience (QoE). Optimizing towards one aspect usually negatively impacts at least one of the other two aspects if not both. This situation sets the stage for our research work in the ATHENA Christian Doppler (CD) Laboratory (Adaptive Streaming over HTTP and Emerging Networked Multimedia Services; https://athena.itec.aau.at/), jointly funded by public sources and industry. In this talk, we will present selected novel approaches and research results of the first year of the ATHENA CD Lab’s operation. We will highlight HAS-related research on (i) multimedia content provisioning (machine learning for video encoding); (ii) multimedia content delivery (support of edge processing and virtualized network functions for video networking); (iii) multimedia content consumption and end-to-end aspects (player-triggered segment retransmissions to improve video playout quality); and (iv) novel QoE investigations (adaptive point cloud streaming). We will also put the work into the context of international multimedia systems research.
An invited talk given by Mark Billinghurst on Research Directions for Cross Reality Interfaces. This was given on July 2nd 2024 as part of the 2024 Summer School on Cross Reality in Hagenberg, Austria (July 1st - 7th)
Hire a private investigator to get cell phone recordsHackersList
Learn what private investigators can legally do to obtain cell phone records and track phones, plus ethical considerations and alternatives for addressing privacy concerns.
this resume for sadika shaikh bca studentSadikaShaikh7
I am a dedicated BCA student with a strong foundation in web technologies, including PHP and MySQL. I have hands-on experience in Java and Python, and a solid understanding of data structures. My technical skills are complemented by my ability to learn quickly and adapt to new challenges in the ever-evolving field of computer science.
Scaling Connections in PostgreSQL Postgres Bangalore(PGBLR) Meetup-2 - MydbopsMydbops
This presentation, delivered at the Postgres Bangalore (PGBLR) Meetup-2 on June 29th, 2024, dives deep into connection pooling for PostgreSQL databases. Aakash M, a PostgreSQL Tech Lead at Mydbops, explores the challenges of managing numerous connections and explains how connection pooling optimizes performance and resource utilization.
Key Takeaways:
* Understand why connection pooling is essential for high-traffic applications
* Explore various connection poolers available for PostgreSQL, including pgbouncer
* Learn the configuration options and functionalities of pgbouncer
* Discover best practices for monitoring and troubleshooting connection pooling setups
* Gain insights into real-world use cases and considerations for production environments
This presentation is ideal for:
* Database administrators (DBAs)
* Developers working with PostgreSQL
* DevOps engineers
* Anyone interested in optimizing PostgreSQL performance
Contact info@mydbops.com for PostgreSQL Managed, Consulting and Remote DBA Services
MYIR Product Brochure - A Global Provider of Embedded SOMs & SolutionsLinda Zhang
This brochure gives introduction of MYIR Electronics company and MYIR's products and services.
MYIR Electronics Limited (MYIR for short), established in 2011, is a global provider of embedded System-On-Modules (SOMs) and
comprehensive solutions based on various architectures such as ARM, FPGA, RISC-V, and AI. We cater to customers' needs for large-scale production, offering customized design, industry-specific application solutions, and one-stop OEM services.
MYIR, recognized as a national high-tech enterprise, is also listed among the "Specialized
and Special new" Enterprises in Shenzhen, China. Our core belief is that "Our success stems from our customers' success" and embraces the philosophy
of "Make Your Idea Real, then My Idea Realizing!"
AC Atlassian Coimbatore Session Slides( 22/06/2024)apoorva2579
This is the combined Sessions of ACE Atlassian Coimbatore event happened on 22nd June 2024
The session order is as follows:
1.AI and future of help desk by Rajesh Shanmugam
2. Harnessing the power of GenAI for your business by Siddharth
3. Fallacies of GenAI by Raju Kandaswamy
Interaction Latency: Square's User-Centric Mobile Performance MetricScyllaDB
Mobile performance metrics often take inspiration from the backend world and measure resource usage (CPU usage, memory usage, etc) and workload durations (how long a piece of code takes to run).
However, mobile apps are used by humans and the app performance directly impacts their experience, so we should primarily track user-centric mobile performance metrics. Following the lead of tech giants, the mobile industry at large is now adopting the tracking of app launch time and smoothness (jank during motion).
At Square, our customers spend most of their time in the app long after it's launched, and they don't scroll much, so app launch time and smoothness aren't critical metrics. What should we track instead?
This talk will introduce you to Interaction Latency, a user-centric mobile performance metric inspired from the Web Vital metric Interaction to Next Paint"" (web.dev/inp). We'll go over why apps need to track this, how to properly implement its tracking (it's tricky!), how to aggregate this metric and what thresholds you should target.
16. some selected platform services …
SQL
Azure
RDBMS as a Service
HDInsight Hadoop Cluster as a Service
API
Management
API Proxy for Security, etc.
Azure
Cache
Redis Cache as a Service
Machine
Learning
Machine Learning as a Svc
Traffic
Manager
DNS Loadbalancer
Document
DB
{} Managed NoSQL Doc DB
Azure
Search
Managed Search Service
27. ML API API service service and the Developer
Developer
• Tested models available as an url that can be called from any end point
Portal
Azure Ops Team
Studio
Data Scientist
HDInsight
Azure Storage
Desktop Data
&
ML API service
ML Studio
• Access and prepare data
• Create, test and train models
• Collaborate
• One click to stage for
production via the API service
Azure Portal & ML API service
• Create ML Studio workspace
• Assign storage account(s)
• Monitor ML consumption
• See alerts when model is ready
• Deploy models to web service
29. The IoT ecosystem has been fragmented
Secure?
Connect Configure Harness Administer Extend
Limited flexibility
Inaccessible data
Slow implementation Unsecure data and assets
Incompatible
with infrastructure Unreliable service
30. Connect Configure Harness Administer Extend
Flexible and extensible solution
Accessible data
Intelligent Systems Service
An integrated solution
Finished service provided by
Partner built
Protect
Faster implementation Protect data and assets
Compatible with existing infrastructure
Reliable service
31. Accelerate implementation and time-to-value
Connect across a range of endpoints
OSS Agent (C-library) for arbitrary
systems
Enable broad connectivity options
Connect directly to ISS
or though a local gateway (for
constrained devices)
Connect quickly
Intelligent Systems Service SDK
for Windows
Integrate existing devices and infrastructure
Existing apps through OData
Connect
Agent
Agent
Agent
Agent
Agent
Gateway
32. Optimize performance and reliability
Configure
Deploy out-of-the-box cloud services Automate alarms and response options
preferences
adding or decommissioning devices
changing alarm actions and severity levels
adding new rules
changing connectivity and storage options
Reduce costs with a finished SaaS solution
that does not require development time
and building infrastructure
Use built-in metadata that works with
multiple data schema to drive
intelligent actions and insights such as
command and control
Configure alarms and response options; ISS
provides a number of alarms that can be
configured and customized to support a
number of response options
Drive intelligent actions Adjust as needs change
33. Produce data-driven business insights
Harness
Capture a variety of data Use familiar analytics tools
Apply configurable and customizable
business rules to enable alarming and
eventing based on ingressed data and
through a complex event processing
engine
Capture machine-generated, user-generated and
transaction data using a variety of protocols:
MQTT, AMQP, HTTPS and plug-in protocols
Enable data ingress to Azure Tables, SQL
Azure and on-premises SQL, and access
Intelligent Systems Service BLOB data
seamlessly with your HDInsight account
Use common tools such as Excel and
HDInsight for deep analytics, and enable
data egress through OData interfaces to
other analytics tools both cloud-based and
on-premises
10101110101010101010
10010101010101010110
10101010101110101001
01001101010101010101
10101010101001010101
10101010101001101010
1110101010101
Simplify analysis with rationalized data Apply business rules
34. Achieve new levels of control
Operate from a central dashboard Manage remotely
Support configuration of connected
devices so specific actions are taken on
device groups rather than on an
individual basis, reducing manual
intervention
Use the Intelligent Systems Service Operator
Portal to remotely manage devices, including
monitoring, maintenance, data transfer and
deployment of software
Securely log in from remote devices
and products to retrieve data, control
devices, and diagnose and resolve
issues
Group endpoints for simplified management
Administer
Distribute packages and commands
Leverage the command and control dashboard to
support multiple management activities such as
distributing packages, sending commands and
setting timed transmissions
35. Innovate and grow on a flexible platform
Extend
Integrate existing systems Scale as needed
Work with familiar SI, ISV and OEM partners
that have deep industry expertise to create
rich, customized experiences and vertical
solutions
Connect your on-premises
environment with solution services
running in the Azure public cloud
Incorporate new devices, apps, data and
infrastructure into your existing setup with
the Intelligent Systems Service SDK or the
public SDK
Address variable demands with scalable and
efficient data collection and storage in the Azure
cloud through support of Azure Tables and
Azure BLOB
+
Capitalize on cloud capabilities Innovate with third-party solutions
36. Feel confident your data is protected
Protect
Unify protection system-wide Configure granular permissions
Secure your data with automatic geo-replication
of data across datacenters that
are geographically separate
Simplify security relationships by using secure
protocols like HTTPS and AMQP
Enable data ingress and egress to and
from the cloud via secure protocols with
the Azure Service Bus
Federate granular permissions to ensure
the right people get the right access, and
manage permissions with a consistent
approach across datacenters and the cloud
Transport data through secure channels Access full data recovery features
0101
1100
37. Thank you / chgeuer@microsoft.com
Build with PaaS Use as SaaS
The presentation gives a solid overview to the Microsoft Azure platform, with a special emphasis on scenarios for IoT workloads. First, Christian provides an introduction to Microsoft Azure’s IaaS compute and networking infrastructure (i.e. virtual machines, virtual networks, load balancers and HA concepts). The second part of the presentation focuses on higher-order services in Azure, such as relational data bases, machine learning, search, and NoSQL offerings. Last, Christian explains how the Azure Service Bus and the Intelligent Systems Services fit into the overall IoT landscape.
Slide Objectives:
Explain differences between Push and Pull
Transition:
This is a continuation of Relay vs. Broker discussion
Slide Objectives:
This slide and the next slide list some of integration patterns enabled by queues – load leveling, offline/batch, load balancing (competing consumers)
Slide Objectives:
This slide introduces some integration patterns enabled by topics and subscriptions
<Alternate slide with no animation>
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.
Companies may be creating solutions today, but not in a standardized way. The result has been:
Slow implementation. It might take 18th months to get a solution up and running and even more time to see return on your investment.
Incompatibility with infrastructure. It’s hard to deal with the complexity of multiple protocols, form factors and connectivity methods. It’s hard to leverage your existing technology investments for the long term.
Unsecure data and assets. With complex security models, it’s hard to secure your endpoints or your data.
Unreliable service. It’s hard to guarantee the reliability of your business-critical devices. You don’t want to run the risk of deploying immature technology.
Limited flexibility. Solutions cannot offer scalable data storage at a sustainable price or they are built in an entirely custom, unrepeatable manner.
Inaccessible data. And in the end, you are often left unable to use the data you’re generating for analysis and insight.
Or you’ve looked into IoT before, but it’s been beyond your scope, budget or interest. It’s just been too hard.
T: Microsoft Azure Intelligent Systems Service makes it easier to securely connect, manage, and capture and transform data from industry endpoints.
Silos of data storage, formats, authentication, access and experiences
Centralized command a control is difficult (think app for everything)
Devices are heterogeneous in every way (apis, apps, control…)
The ROI dream of what is possible is why we want to manage devices…
<jonathan>
<jonathan>
Microsoft can help create an intelligent system simply by building on existing investments and providing a foundation for you to achieve your IoT vision.
The solution was built with three guiding principles:
Accelerate Time-to-value. Deploy an out-of-the-box solution that is easy to extend and positioned to scale to quickly realize ROI.
Build on a Trusted Platform. Benefit from the credibility, functionality and innovation of Microsoft Assets and future investments.
Increase Flexibility. Gain greater business insights and control with a single solution for heterogeneous environments.
And it enables the core capabilities required by any customer in any industry:
Connect. Connect endpoints regardless of form-factor, operating system or intelligence to other devices, cloud-based services and infrastructure.
Configure. Apply configurable and customizable business rules that define actions on devices to automate and improve business processes.
Harness. Efficiently capture, store, join, visualize, analyze and share data to drive meaningful business insights.
Administer. Remotely manage data transfer, maintenance, configuration, and software deployment on convenient asset dashboards.
Extend. Address variable demands with scalable and efficient data collection and storage in the cloud. Innovate on top of the solution to create rich, customized experiences.
&
Protect. Underlying all of these capabilities is a unified, enterprise-grade approach to security developed and supported by Microsoft.
T: First, let’s take a look at how Microsoft Azure Intelligent Systems Service easily connects all the endpoints in your environment.
Connect quickly. Connect with Intelligent Systems Service agents for Windows devices delivered through the Intelligent Systems Service SDK.
Connect across a range of endpoints. Easily develop open-source agents supporting other operating systems.
Integrate existing devices and infrastructure. Connect existing devices, data and infrastructure such as LoB applications, Active Directory and others through OData interfaces.
Enable broad connectivity options. Provide connections for unintelligent sensors and actuators through a secure gateway with an Intelligent Systems Service agent.
T: Once your devices are connected and integrated, configure your setup to optimize performance and predict needs.
Deploy out-of-the-box cloud services. Reduce IT burden and costs with a finished SaaS solution that does not require development time and resources to figure out the foundational infrastructure for an IoT solution.
Automate alarms and response options. Configure alarms and response options; Intelligent Systems Service provides a number of alarms that can be configured and customized to support a number of response options.
Drive intelligent actions. Use built-in meta data that works with multiple data schema to drive intelligent actions and insights such as command and control.
Adjust as needs change. Easily manipulate and add preferences as needs change, such as adding or decommissioning devices, changing alarm actions and severity levels, adding new rules and changing connectivity and storage options.
T: The next step is to capture meaningful data.
Capture a variety of data. Capture machine-generated, user-generated and transaction data using a variety of protocols: MQTT, AMQP, HTTPS and plug-in protocols.
Use familiar analytics tools. Use common tools such as Excel and HDInsight for deep analytics, and enable data egress through OData interfaces to other analytics tools both cloud-based and on-premises.
Simplify analysis with rationalized data. Enable data ingress to Azure Tables, SQL Azure and on-premises SQL, and access Intelligent Systems Service BLOB data seamlessly with your HDInsight account.
Apply business rules. Apply configurable and customizable business rules to enable alarming and eventing based on ingressed data and through a complex event processing engine.
T: Intelligent Systems Service then offers simplified management to make the most of endpoint connections and data capturing.
Operate from a central dashboard. Use the Intelligent Systems Service Operator Portal to remotely manage devices, including monitoring, maintenance, data transfer and deployment of software.
Manage remotely. Securely log in from remote devices and products to retrieve data, control devices, and diagnose and resolve issues.
Distribute packages and commands. Leverage the command and control dashboard to support multiple management activities such as distributing packages, sending commands and setting timed transmissions.
Group endpoints for simplified management. Support configuration of connected devices so specific action are taken on device groups rather than on an individual basis, reducing manual intervention.
T: As your needs change, you can easily scale your solution. And to meet additional needs in your industry, work with a trusted partner.
Integrate existing systems. Connect your on-premises environment with solution services running in the Azure public cloud.
Scale as needed. Address variable demands with scalable and efficient data collection and storage in the Azure cloud through support of Azure Tables and Azure BLOB.
Capitalize on cloud capabilities. Incorporate new devices, apps, data and infrastructure into your existing setup with the Intelligent Systems Service SDK or the public SDK.
Innovate with third-party solutions. Work with familiar SI, ISV and OEM partners that have deep industry expertise to create rich, customized experiences and vertical solutions. Microsoft and its partners are industry leaders in innovation.
T: And, lastly, you won’t need to worry about security issues.
Unify protection system-wide. Simplify security relationships by using secure protocols like HTTPS and AMQP.
Configure granular permissions. Federate granular permissions to ensure the right people get the right access, and manage permissions with a consistent approach across datacenters and the cloud.
Transport data through secure channels. Enable data ingress and egress to and from the cloud via secure protocols with the Azure Service Bus.
Access full data recovery features. Secure your data with automatic georeplication of data across datacenters that are geographically separate.
Datenschutz in Azure und die Europäische Article 29 Working Party: http://blogs.technet.com/b/microsoft_blog/archive/2014/04/10/privacy-authorities-across-europe-approve-microsoft-s-cloud-commitments.aspx