This document summarizes key components of Microsoft Azure's data platform, including SQL Database, NoSQL options like Azure Tables, Blob Storage, and Azure Files. It provides an overview of each service, how they work, common use cases, and demos of creating resources and accessing data. The document is aimed at helping readers understand Azure's database and data storage options for building cloud applications.
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 how businesses need to build a data strategy and modernize their data platforms to harness the power of data from diverse and growing sources. It provides examples of how organizations like healthcare and energy companies are using technologies like machine learning, real-time analytics, and predictive modeling on data from various sources to improve outcomes, predict trends, and drive business decisions. The Microsoft data platform is positioned as helping businesses manage both traditional and new forms of data, gain insights faster, and transform into data-driven organizations through offerings like SQL Server, Azure, Power BI, and the Internet of Things.
Introduction to Windows Azure Data ServicesRobert Greiner
This document provides an overview of using Azure for data management. It discusses using PartitionKey and RowKey to organize data into partitions in Azure table storage. It also recommends using the Azure Storage Client library for .NET applications and describes retry policies for handling errors. Links are provided for additional documentation on Azure table storage and messaging between Azure services.
Azure SQL Database is a relational database-as-a-service hosted in the Azure cloud that reduces costs by eliminating the need to manage virtual machines, operating systems, or database software. It provides automatic backups, high availability through geo-replication, and the ability to scale performance by changing service tiers. Azure Cosmos DB is a globally distributed, multi-model database that supports automatic indexing, multiple data models via different APIs, and configurable consistency levels with strong performance guarantees. Azure Redis Cache uses the open-source Redis data structure store with managed caching instances in Azure for improved application performance.
Technical session on Databases as Service in Azure
Technical session - Azure SQL DB on Dec 20, 2020
https://youtu.be/Cl4IDpc_0yc
Technical session - 2 on Azure SQL DB - Dec 27, 2020
https://youtu.be/_4lZ54eI3F0
Technical session on Azure Cosmos DB -Dec 27, 2020
https://youtu.be/rtDwX1K_64k
Microsoft Azure Cosmos DB is a multi-model database that supports document, key-value, wide-column and graph data models. It provides high throughput, low latency and global distribution across multiple regions. Cosmos DB supports multiple APIs including SQL, MongoDB, Cassandra and Gremlin to allow developers to use their preferred API based on their application needs and skills. It also provides automatic scaling of throughput and storage across all data partitions.
Migrating on premises workload to azure sql databasePARIKSHIT SAVJANI
This document provides an overview of migrating databases from on-premises SQL Server to Azure SQL Database Managed Instance. It discusses why companies are moving to the cloud, challenges with migration, and the tools and services available to help with assessment and migration including Data Migration Service. Key steps in the migration workflow include assessing the database and application, addressing compatibility issues, and deploying the converted schema to Managed Instance which provides high compatibility with on-premises SQL Server in a fully managed platform as a service model.
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 how businesses need to build a data strategy and modernize their data platforms to harness the power of data from diverse and growing sources. It provides examples of how organizations like healthcare and energy companies are using technologies like machine learning, real-time analytics, and predictive modeling on data from various sources to improve outcomes, predict trends, and drive business decisions. The Microsoft data platform is positioned as helping businesses manage both traditional and new forms of data, gain insights faster, and transform into data-driven organizations through offerings like SQL Server, Azure, Power BI, and the Internet of Things.
Introduction to Windows Azure Data ServicesRobert Greiner
This document provides an overview of using Azure for data management. It discusses using PartitionKey and RowKey to organize data into partitions in Azure table storage. It also recommends using the Azure Storage Client library for .NET applications and describes retry policies for handling errors. Links are provided for additional documentation on Azure table storage and messaging between Azure services.
Azure SQL Database is a relational database-as-a-service hosted in the Azure cloud that reduces costs by eliminating the need to manage virtual machines, operating systems, or database software. It provides automatic backups, high availability through geo-replication, and the ability to scale performance by changing service tiers. Azure Cosmos DB is a globally distributed, multi-model database that supports automatic indexing, multiple data models via different APIs, and configurable consistency levels with strong performance guarantees. Azure Redis Cache uses the open-source Redis data structure store with managed caching instances in Azure for improved application performance.
Technical session on Databases as Service in Azure
Technical session - Azure SQL DB on Dec 20, 2020
https://youtu.be/Cl4IDpc_0yc
Technical session - 2 on Azure SQL DB - Dec 27, 2020
https://youtu.be/_4lZ54eI3F0
Technical session on Azure Cosmos DB -Dec 27, 2020
https://youtu.be/rtDwX1K_64k
Microsoft Azure Cosmos DB is a multi-model database that supports document, key-value, wide-column and graph data models. It provides high throughput, low latency and global distribution across multiple regions. Cosmos DB supports multiple APIs including SQL, MongoDB, Cassandra and Gremlin to allow developers to use their preferred API based on their application needs and skills. It also provides automatic scaling of throughput and storage across all data partitions.
Migrating on premises workload to azure sql databasePARIKSHIT SAVJANI
This document provides an overview of migrating databases from on-premises SQL Server to Azure SQL Database Managed Instance. It discusses why companies are moving to the cloud, challenges with migration, and the tools and services available to help with assessment and migration including Data Migration Service. Key steps in the migration workflow include assessing the database and application, addressing compatibility issues, and deploying the converted schema to Managed Instance which provides high compatibility with on-premises SQL Server in a fully managed platform as a service model.
Microsoft Azure Offerings and New Services Mohamed Tawfik
Microsoft Azure offers a wide range of computing services including networking, compute, storage, databases, developer tools, and analytics services. It provides benefits such as pay-as-you-go pricing, quick setup, scalability, redundancy, and high availability. Microsoft has seen incredible growth in Azure due to its ability to convert its large enterprise customer base into Azure customers and build hybrid cloud solutions. The presentation highlights several new Azure services and features in networking, compute, storage, databases, and security.
Microsoft certified azure developer associateGaurav Singh
The Mastering Microsoft Azure Developer Training makes you proficient in developing, planning, and scaling your web applications on Microsoft Azure. It includes training on Azure App Services, Azure Storage, Azure Virtual Machines, Azure SQL Database , Microservices, Azure AD, Azure Automation and DevOps using real-life case studies. The curriculum has been designed by Microsoft MVPs & Industry expert to earn Microsoft Azure Developer Associate Certification (AZ-204).
This document provides an overview and summary of the author's background and expertise. It states that the author has over 30 years of experience in IT working on many BI and data warehouse projects. It also lists that the author has experience as a developer, DBA, architect, and consultant. It provides certifications held and publications authored as well as noting previous recognition as an SQL Server MVP.
These slides are a copy of a last Azure Cosmos DB + Gremlin API in Action session which I had the pleasure to present on June 2nd, 2018 at PASS SQL Saturday event in Montreal. The original PowerPoint version contained much more elaborate series of animations. We understand that those had to be flatten for upload in this case. Though I guess you'll get the idea of the logic involved.
Cosmos DB is Microsoft's flagship Serverless database service in the Azure cloud. This slide-deck, presented at the Nashville Azure Meetup event on 09/20/2018 covers the why and what of Cosmos DB was is meant to be a good segue into further detailed and advanced topics. The slide-deck presents 3 use-cases for using Cosmos DB in E-Commerce, Healthcare, and IoT. Stay Tuned!
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.
This document provides an overview of Azure SQL Managed Instance and how it compares to other Azure SQL options. It discusses how Managed Instance takes care of database management tasks like backups, high availability, and updates. It also summarizes the service tiers of General Purpose and Business Critical and their key features like storage performance and read replicas. Finally, it outlines approaches for migrating databases to Managed Instance using tools like DMA and restoring backups.
This document provides an overview of Azure SQL DB environments. It discusses the different types of cloud platforms including IaaS, PaaS and DBaaS. It summarizes the key features and benefits of Azure SQL DB including automatic backups, geo-replication for disaster recovery, and elastic pools for reducing costs. The document also covers pricing models, performance monitoring, automatic tuning capabilities, and security features of Azure SQL DB.
Introduction to Azure SQL Database Managed Instance SQLKonferenz 2018. Showing architecture and overview of the features that are available in public preview.
In this presentation, we will do assess the on-premises environment and determining what workloads and databases are ready to make the move and what can you do to improve their Azure readiness while reducing downtime during the migration. Planning and assessment plays a critical role in moving to the cloud. We would see wide range of resources and tools to get an assessment completed with ease while identifying workload dependencies with practical tips and tricks focusing on sizing and costs. And finally, we’ll assess the SQL instances and identify their readiness for Azure as well.
Microsoft Azure platform provides a database as a service offering that allows developers to use SQL in the same way as they would in an on-premises location.
Azure provides several data related services for storing, processing, and analyzing data in the cloud at scale. Key services include Azure SQL Database for relational data, Azure DocumentDB for NoSQL data, Azure Data Warehouse for analytics, Azure Data Lake Store for big data storage, and Azure Storage for binary data. These services provide scalability, high availability, and manageability. Azure SQL Database provides fully managed SQL databases with options for single databases, elastic pools, and geo-replication. Azure Data Warehouse enables petabyte-scale analytics with massively parallel processing.
Azure SQL Database Managed Instance is a new flavor of Azure SQL Database that is a game changer. It offers near-complete SQL Server compatibility and network isolation to easily lift and shift databases to Azure (you can literally backup an on-premise database and restore it into a Azure SQL Database Managed Instance). Think of it as an enhancement to Azure SQL Database that is built on the same PaaS infrastructure and maintains all it's features (i.e. active geo-replication, high availability, automatic backups, database advisor, threat detection, intelligent insights, vulnerability assessment, etc) but adds support for databases up to 35TB, VNET, SQL Agent, cross-database querying, replication, etc. So, you can migrate your databases from on-prem to Azure with very little migration effort which is a big improvement from the current Singleton or Elastic Pool flavors which can require substantial changes.
Customer migration to azure sql database from on-premises SQL, for a SaaS app...George Walters
Why would someone take a working on-premises SaaS infrastructure, and migrate it to Azure? We review the technology decisions behind this conversion, and business choices behind migrating to Azure. The SQL 2012 infrastructure and application was migrated to PaaS Services. Finally, how would we do this architecture in 2019.
This document provides an introduction to Cloudant, which is a fully managed NoSQL database as a service (DBaaS) that provides a scalable and flexible data layer for web and mobile applications. The presentation discusses NoSQL databases and why they are useful, describes Cloudant's features such as document storage, querying, indexing and its global data presence. It also provides examples of how companies like FitnessKeeper and Fidelity Investments use Cloudant to solve data scaling and management challenges. The document concludes by outlining next steps for signing up and exploring Cloudant.
This document discusses two options for hosting SQL databases on Microsoft Azure: Azure SQL Database and SQL Server virtual machines. It provides demos of creating and connecting to databases with each option, covering aspects like security, auditing, performance, and pricing. Links are included for more information on tier performance and pricing for Azure SQL Database, as well as hosting SQL on Amazon AWS.
This document discusses developing Azure solutions for different audiences including web developers, corporate developers, and ISV developers. It covers key aspects of developing Azure solutions such as cloud service anatomy, the differences in developing for Azure, worker and web role call order, migrating data and services to Azure, diagnostics, and best practices. The conclusion emphasizes that Azure provides flexibility in development with specific APIs, casual development scenarios, best practices, and supporting technologies.
Spark is fast becoming a critical part of Customer Solutions on Azure. Databricks on Microsoft Azure provides a first-class experience for building and running Spark applications. The Microsoft Azure CAT team engaged with many early adopter customers helping them build their solutions on Azure Databricks.
In this session, we begin by reviewing typical workload patterns, integration with other Azure services like Azure Storage, Azure Data Lake, IoT / Event Hubs, SQL DW, PowerBI etc. Most importantly, we will share real-world tips and learnings that you can take and apply in your Data Engineering / Data Science workloads
Azure templates can be used to deploy and manage Azure resources in a declarative and repeatable way. They define the resources to deploy, including virtual machines, databases, and networking components, as well as the relationships between resources. Azure templates allow for idempotent deployments, simplified orchestration of rollbacks and upgrades, and cross-resource configuration and updates. They are stored as JSON or ARM template files in source control and can be deployed via the Azure CLI, PowerShell, or REST APIs. A wide range of community-created quickstart templates are available on GitHub for common workload deployments.
Microsoft Azure Offerings and New Services Mohamed Tawfik
Microsoft Azure offers a wide range of computing services including networking, compute, storage, databases, developer tools, and analytics services. It provides benefits such as pay-as-you-go pricing, quick setup, scalability, redundancy, and high availability. Microsoft has seen incredible growth in Azure due to its ability to convert its large enterprise customer base into Azure customers and build hybrid cloud solutions. The presentation highlights several new Azure services and features in networking, compute, storage, databases, and security.
Microsoft certified azure developer associateGaurav Singh
The Mastering Microsoft Azure Developer Training makes you proficient in developing, planning, and scaling your web applications on Microsoft Azure. It includes training on Azure App Services, Azure Storage, Azure Virtual Machines, Azure SQL Database , Microservices, Azure AD, Azure Automation and DevOps using real-life case studies. The curriculum has been designed by Microsoft MVPs & Industry expert to earn Microsoft Azure Developer Associate Certification (AZ-204).
This document provides an overview and summary of the author's background and expertise. It states that the author has over 30 years of experience in IT working on many BI and data warehouse projects. It also lists that the author has experience as a developer, DBA, architect, and consultant. It provides certifications held and publications authored as well as noting previous recognition as an SQL Server MVP.
These slides are a copy of a last Azure Cosmos DB + Gremlin API in Action session which I had the pleasure to present on June 2nd, 2018 at PASS SQL Saturday event in Montreal. The original PowerPoint version contained much more elaborate series of animations. We understand that those had to be flatten for upload in this case. Though I guess you'll get the idea of the logic involved.
Cosmos DB is Microsoft's flagship Serverless database service in the Azure cloud. This slide-deck, presented at the Nashville Azure Meetup event on 09/20/2018 covers the why and what of Cosmos DB was is meant to be a good segue into further detailed and advanced topics. The slide-deck presents 3 use-cases for using Cosmos DB in E-Commerce, Healthcare, and IoT. Stay Tuned!
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.
This document provides an overview of Azure SQL Managed Instance and how it compares to other Azure SQL options. It discusses how Managed Instance takes care of database management tasks like backups, high availability, and updates. It also summarizes the service tiers of General Purpose and Business Critical and their key features like storage performance and read replicas. Finally, it outlines approaches for migrating databases to Managed Instance using tools like DMA and restoring backups.
This document provides an overview of Azure SQL DB environments. It discusses the different types of cloud platforms including IaaS, PaaS and DBaaS. It summarizes the key features and benefits of Azure SQL DB including automatic backups, geo-replication for disaster recovery, and elastic pools for reducing costs. The document also covers pricing models, performance monitoring, automatic tuning capabilities, and security features of Azure SQL DB.
Introduction to Azure SQL Database Managed Instance SQLKonferenz 2018. Showing architecture and overview of the features that are available in public preview.
In this presentation, we will do assess the on-premises environment and determining what workloads and databases are ready to make the move and what can you do to improve their Azure readiness while reducing downtime during the migration. Planning and assessment plays a critical role in moving to the cloud. We would see wide range of resources and tools to get an assessment completed with ease while identifying workload dependencies with practical tips and tricks focusing on sizing and costs. And finally, we’ll assess the SQL instances and identify their readiness for Azure as well.
Microsoft Azure platform provides a database as a service offering that allows developers to use SQL in the same way as they would in an on-premises location.
Azure provides several data related services for storing, processing, and analyzing data in the cloud at scale. Key services include Azure SQL Database for relational data, Azure DocumentDB for NoSQL data, Azure Data Warehouse for analytics, Azure Data Lake Store for big data storage, and Azure Storage for binary data. These services provide scalability, high availability, and manageability. Azure SQL Database provides fully managed SQL databases with options for single databases, elastic pools, and geo-replication. Azure Data Warehouse enables petabyte-scale analytics with massively parallel processing.
Azure SQL Database Managed Instance is a new flavor of Azure SQL Database that is a game changer. It offers near-complete SQL Server compatibility and network isolation to easily lift and shift databases to Azure (you can literally backup an on-premise database and restore it into a Azure SQL Database Managed Instance). Think of it as an enhancement to Azure SQL Database that is built on the same PaaS infrastructure and maintains all it's features (i.e. active geo-replication, high availability, automatic backups, database advisor, threat detection, intelligent insights, vulnerability assessment, etc) but adds support for databases up to 35TB, VNET, SQL Agent, cross-database querying, replication, etc. So, you can migrate your databases from on-prem to Azure with very little migration effort which is a big improvement from the current Singleton or Elastic Pool flavors which can require substantial changes.
Customer migration to azure sql database from on-premises SQL, for a SaaS app...George Walters
Why would someone take a working on-premises SaaS infrastructure, and migrate it to Azure? We review the technology decisions behind this conversion, and business choices behind migrating to Azure. The SQL 2012 infrastructure and application was migrated to PaaS Services. Finally, how would we do this architecture in 2019.
This document provides an introduction to Cloudant, which is a fully managed NoSQL database as a service (DBaaS) that provides a scalable and flexible data layer for web and mobile applications. The presentation discusses NoSQL databases and why they are useful, describes Cloudant's features such as document storage, querying, indexing and its global data presence. It also provides examples of how companies like FitnessKeeper and Fidelity Investments use Cloudant to solve data scaling and management challenges. The document concludes by outlining next steps for signing up and exploring Cloudant.
This document discusses two options for hosting SQL databases on Microsoft Azure: Azure SQL Database and SQL Server virtual machines. It provides demos of creating and connecting to databases with each option, covering aspects like security, auditing, performance, and pricing. Links are included for more information on tier performance and pricing for Azure SQL Database, as well as hosting SQL on Amazon AWS.
This document discusses developing Azure solutions for different audiences including web developers, corporate developers, and ISV developers. It covers key aspects of developing Azure solutions such as cloud service anatomy, the differences in developing for Azure, worker and web role call order, migrating data and services to Azure, diagnostics, and best practices. The conclusion emphasizes that Azure provides flexibility in development with specific APIs, casual development scenarios, best practices, and supporting technologies.
Spark is fast becoming a critical part of Customer Solutions on Azure. Databricks on Microsoft Azure provides a first-class experience for building and running Spark applications. The Microsoft Azure CAT team engaged with many early adopter customers helping them build their solutions on Azure Databricks.
In this session, we begin by reviewing typical workload patterns, integration with other Azure services like Azure Storage, Azure Data Lake, IoT / Event Hubs, SQL DW, PowerBI etc. Most importantly, we will share real-world tips and learnings that you can take and apply in your Data Engineering / Data Science workloads
Azure templates can be used to deploy and manage Azure resources in a declarative and repeatable way. They define the resources to deploy, including virtual machines, databases, and networking components, as well as the relationships between resources. Azure templates allow for idempotent deployments, simplified orchestration of rollbacks and upgrades, and cross-resource configuration and updates. They are stored as JSON or ARM template files in source control and can be deployed via the Azure CLI, PowerShell, or REST APIs. A wide range of community-created quickstart templates are available on GitHub for common workload deployments.
Azure SQL Database is a cloud-based relational database service built on the Microsoft SQL Server engine. It provides predictable performance and scalability with minimal downtime and administration. Key features include elastic pools for cost-effective scaling, built-in backups and disaster recovery, security features like encryption and auditing, and tools for management and monitoring performance. The document provides an overview of Azure SQL Database capabilities and service tiers for databases and elastic pools.
This document provides a summary of Antonios Chatzipavlis's background and experience working with SQL Server. It details his career starting with SQL Server 6.0 in 1996 and earning his first Microsoft certification. It lists the various Microsoft certifications and roles he has held, including becoming an MVP for SQL Server. It also introduces his creation of SQL School Greece in 2012 to share his knowledge.
Microsoft released SQL Azure more than two years ago - that's enough time for testing (I hope!). So, are you ready to move your data to the Cloud? If you’re considering a business (i.e. a production environment) in the Cloud, you need to think about methods for backing up your data, a backup plan for your data and, eventually, restoring with Red Gate Cloud Services (and not only). In this session, you’ll see the differences, functionality, restrictions, and opportunities in SQL Azure and On-Premise SQL Server 2008/2008 R2/2012. We’ll consider topics such as how to be prepared for backup and restore, and which parts of a cloud environment are most important: keys, triggers, indexes, prices, security, service level agreements, etc.
The document provides an overview of Microsoft Cloud services including Azure Services Platform, Online Services, and Live Services. It describes key Azure components like compute, storage, SQL services, .NET services, and developer tools. It recommends that readers download the Visual Studio tools and SDK to start developing applications, deploy to the cloud after getting an account, and provide feedback to help shape Microsoft cloud offerings.
This document provides an overview and summary of SQL Azure and cloud services from Red Gate. The document begins with an introduction to SQL Azure, including compatibility with different SQL Server versions, limitations, and security requirements. It then covers topics like database sizing, naming conventions, migration support, and using indexes. The document next discusses cloud services from Red Gate for backup, restore, and scheduling of SQL Azure databases. It concludes with some example links and a short demo. The overall summary discusses key capabilities and services for managing SQL Azure databases and backups in the cloud.
The document discusses the Windows Azure platform and its core services including compute, storage, database, service bus, and access control. It then summarizes Microsoft SQL Azure, which provides familiar SQL Server capabilities in the cloud. Key points about SQL Azure include its scalable architecture with automatic replication and failover, flexible tenancy and deployment models, and support for both relational and non-relational data through existing SQL Server tools and APIs. The document also outlines some differences and limitations compared to on-premises SQL Server deployments.
Azure Synapse Analytics is Azure SQL Data Warehouse evolved: a limitless analytics service, that brings together enterprise data warehousing and Big Data analytics into a single service. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources, at scale. Azure Synapse brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate business intelligence and machine learning needs. This is a huge deck with lots of screenshots so you can see exactly how it works.
Microsoft Azure zmienia się. Jego częśc poświęcona bazie danych (Windows Azure SQL Database) zmienia się jeszcze szybciej. Podczas tej sesji chciałbym pokazac tym, którzy nie widzieli, oraz przypomniec tym, którzy już coś wiedzą - o co chodzi z WASD, jakie zmiany nastapiły i czego możemy po tej bazie oczekiwać. Dla odważnych będzie okazja podłączenia się do konta w chmurze i przetestowania ych rozwiązań samemu.
These are the slides for my talk "An intro to Azure Data Lake" at Azure Lowlands 2019. The session was held on Friday January 25th from 14:20 - 15:05 in room Santander.
The new Microsoft Azure SQL Data Warehouse (SQL DW) is an elastic data warehouse-as-a-service and is a Massively Parallel Processing (MPP) solution for "big data" with true enterprise class features. The SQL DW service is built for data warehouse workloads from a few hundred gigabytes to petabytes of data with truly unique features like disaggregated compute and storage allowing for customers to be able to utilize the service to match their needs. In this presentation, we take an in-depth look at implementing a SQL DW, elastic scale (grow, shrink, and pause), and hybrid data clouds with Hadoop integration via Polybase allowing for a true SQL experience across structured and unstructured data.
Azure SQL Database is a cloud-based relational database service built on Microsoft SQL Server that provides predictable performance, scalability, high availability with no downtime, and near-zero administration. It offers instant scalability, database replication across regions for backup, and has Microsoft handle common management operations. Developers can access data using ADO.NET, Java, PHP, Node.js, Python, Ruby and JSON. It provides features like stored procedures, triggers, views, encryption, temporal tables, performance monitoring, row-level security, and dynamic data masking.
A Real World Guide to Building Highly Available Fault Tolerant SharePoint FarmsEric Shupps
Building SharePoint farms for development and testing is easy. But building highly available farms to meet enterprise service level agreements that are fault tolerant, scalable and connected to the cloud? Not quite so easy. In this workshop you will learn how to plan, design and implement a highly availability farm architecture based upon proven techniques and practical guidance. You will also discover how to connect on-premise deployments to the cloud, manage security and identity synchronization, correctly configure workflow farms, and prepare your environment for app integration.
Microsoft SQL Azure - Building Applications Using SQL Azure PresentationMicrosoft Private Cloud
Building Applications Using SQL Azure provides an overview of using Microsoft's SQL Azure platform as a service. It covers setting up a SQL Azure account, connecting applications, managing security, creating database objects, migrating schemas and data, performance considerations, and building a simple application connected to SQL Azure. The presentation aims to help database developers and architects understand how to build applications using the SQL Azure relational database service.
This document discusses SQL Azure, Microsoft's relational database service. It describes the logical and physical structure, including that databases are organized at the subscription and server level, and SQL Azure uses sharding across SQL Server instances. Key points are that each database is limited to 150GB in size, there is a built-in firewall, and data is committed using a quorum-based scheme across replicas. Migration options like SSIS and the Generate Script Wizard are also outlined.
Microsoft Azure is a cloud computing platform that provides computing and data services. It includes Windows Azure for running applications, SQL Azure for cloud-based data services based on SQL Server, and App Fabric for distributed infrastructure services. Windows Azure provides a Windows environment for applications and storage in Microsoft data centers. SQL Azure offers data services based on SQL Server in the cloud. App Fabric provides distributed services to both cloud and local applications.
What is in a modern BI architecture? In this presentation, we explore PaaS, Azure Active Directory and Storage options including SQL Database and SQL Datawarehouse.
QA or the Highway - Component Testing: Bridging the gap between frontend appl...zjhamm304
These are the slides for the presentation, "Component Testing: Bridging the gap between frontend applications" that was presented at QA or the Highway 2024 in Columbus, OH by Zachary Hamm.
"Choosing proper type of scaling", Olena SyrotaFwdays
Imagine an IoT processing system that is already quite mature and production-ready and for which client coverage is growing and scaling and performance aspects are life and death questions. The system has Redis, MongoDB, and stream processing based on ksqldb. In this talk, firstly, we will analyze scaling approaches and then select the proper ones for our system.
zkStudyClub - LatticeFold: A Lattice-based Folding Scheme and its Application...Alex Pruden
Folding is a recent technique for building efficient recursive SNARKs. Several elegant folding protocols have been proposed, such as Nova, Supernova, Hypernova, Protostar, and others. However, all of them rely on an additively homomorphic commitment scheme based on discrete log, and are therefore not post-quantum secure. In this work we present LatticeFold, the first lattice-based folding protocol based on the Module SIS problem. This folding protocol naturally leads to an efficient recursive lattice-based SNARK and an efficient PCD scheme. LatticeFold supports folding low-degree relations, such as R1CS, as well as high-degree relations, such as CCS. The key challenge is to construct a secure folding protocol that works with the Ajtai commitment scheme. The difficulty, is ensuring that extracted witnesses are low norm through many rounds of folding. We present a novel technique using the sumcheck protocol to ensure that extracted witnesses are always low norm no matter how many rounds of folding are used. Our evaluation of the final proof system suggests that it is as performant as Hypernova, while providing post-quantum security.
Paper Link: https://eprint.iacr.org/2024/257
Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectorsDianaGray10
Join us to learn how UiPath Apps can directly and easily interact with prebuilt connectors via Integration Service--including Salesforce, ServiceNow, Open GenAI, and more.
The best part is you can achieve this without building a custom workflow! Say goodbye to the hassle of using separate automations to call APIs. By seamlessly integrating within App Studio, you can now easily streamline your workflow, while gaining direct access to our Connector Catalog of popular applications.
We’ll discuss and demo the benefits of UiPath Apps and connectors including:
Creating a compelling user experience for any software, without the limitations of APIs.
Accelerating the app creation process, saving time and effort
Enjoying high-performance CRUD (create, read, update, delete) operations, for
seamless data management.
Speakers:
Russell Alfeche, Technology Leader, RPA at qBotic and UiPath MVP
Charlie Greenberg, host
Freshworks Rethinks NoSQL for Rapid Scaling & Cost-EfficiencyScyllaDB
Freshworks creates AI-boosted business software that helps employees work more efficiently and effectively. Managing data across multiple RDBMS and NoSQL databases was already a challenge at their current scale. To prepare for 10X growth, they knew it was time to rethink their database strategy. Learn how they architected a solution that would simplify scaling while keeping costs under control.
From Natural Language to Structured Solr Queries using LLMsSease
This talk draws on experimentation to enable AI applications with Solr. One important use case is to use AI for better accessibility and discoverability of the data: while User eXperience techniques, lexical search improvements, and data harmonization can take organizations to a good level of accessibility, a structural (or “cognitive” gap) remains between the data user needs and the data producer constraints.
That is where AI – and most importantly, Natural Language Processing and Large Language Model techniques – could make a difference. This natural language, conversational engine could facilitate access and usage of the data leveraging the semantics of any data source.
The objective of the presentation is to propose a technical approach and a way forward to achieve this goal.
The key concept is to enable users to express their search queries in natural language, which the LLM then enriches, interprets, and translates into structured queries based on the Solr index’s metadata.
This approach leverages the LLM’s ability to understand the nuances of natural language and the structure of documents within Apache Solr.
The LLM acts as an intermediary agent, offering a transparent experience to users automatically and potentially uncovering relevant documents that conventional search methods might overlook. The presentation will include the results of this experimental work, lessons learned, best practices, and the scope of future work that should improve the approach and make it production-ready.
Northern Engraving | Modern Metal Trim, Nameplates and Appliance PanelsNorthern Engraving
What began over 115 years ago as a supplier of precision gauges to the automotive industry has evolved into being an industry leader in the manufacture of product branding, automotive cockpit trim and decorative appliance trim. Value-added services include in-house Design, Engineering, Program Management, Test Lab and Tool Shops.
ScyllaDB is making a major architecture shift. We’re moving from vNode replication to tablets – fragments of tables that are distributed independently, enabling dynamic data distribution and extreme elasticity. In this keynote, ScyllaDB co-founder and CTO Avi Kivity explains the reason for this shift, provides a look at the implementation and roadmap, and shares how this shift benefits ScyllaDB users.
In our second session, we shall learn all about the main features and fundamentals of UiPath Studio that enable us to use the building blocks for any automation project.
📕 Detailed agenda:
Variables and Datatypes
Workflow Layouts
Arguments
Control Flows and Loops
Conditional Statements
💻 Extra training through UiPath Academy:
Variables, Constants, and Arguments in Studio
Control Flow in Studio
AppSec PNW: Android and iOS Application Security with MobSFAjin Abraham
Mobile Security Framework - MobSF is a free and open source automated mobile application security testing environment designed to help security engineers, researchers, developers, and penetration testers to identify security vulnerabilities, malicious behaviours and privacy concerns in mobile applications using static and dynamic analysis. It supports all the popular mobile application binaries and source code formats built for Android and iOS devices. In addition to automated security assessment, it also offers an interactive testing environment to build and execute scenario based test/fuzz cases against the application.
This talk covers:
Using MobSF for static analysis of mobile applications.
Interactive dynamic security assessment of Android and iOS applications.
Solving Mobile app CTF challenges.
Reverse engineering and runtime analysis of Mobile malware.
How to shift left and integrate MobSF/mobsfscan SAST and DAST in your build pipeline.
"Scaling RAG Applications to serve millions of users", Kevin GoedeckeFwdays
How we managed to grow and scale a RAG application from zero to thousands of users in 7 months. Lessons from technical challenges around managing high load for LLMs, RAGs and Vector databases.
This talk will cover ScyllaDB Architecture from the cluster-level view and zoom in on data distribution and internal node architecture. In the process, we will learn the secret sauce used to get ScyllaDB's high availability and superior performance. We will also touch on the upcoming changes to ScyllaDB architecture, moving to strongly consistent metadata and tablets.
What is an RPA CoE? Session 1 – CoE VisionDianaGray10
In the first session, we will review the organization's vision and how this has an impact on the COE Structure.
Topics covered:
• The role of a steering committee
• How do the organization’s priorities determine CoE Structure?
Speaker:
Chris Bolin, Senior Intelligent Automation Architect Anika Systems
What is an RPA CoE? Session 2 – CoE RolesDianaGray10
In this session, we will review the players involved in the CoE and how each role impacts opportunities.
Topics covered:
• What roles are essential?
• What place in the automation journey does each role play?
Speaker:
Chris Bolin, Senior Intelligent Automation Architect Anika Systems
Introduction of Cybersecurity with OSS at Code Europe 2024Hiroshi SHIBATA
I develop the Ruby programming language, RubyGems, and Bundler, which are package managers for Ruby. Today, I will introduce how to enhance the security of your application using open-source software (OSS) examples from Ruby and RubyGems.
The first topic is CVE (Common Vulnerabilities and Exposures). I have published CVEs many times. But what exactly is a CVE? I'll provide a basic understanding of CVEs and explain how to detect and handle vulnerabilities in OSS.
Next, let's discuss package managers. Package managers play a critical role in the OSS ecosystem. I'll explain how to manage library dependencies in your application.
I'll share insights into how the Ruby and RubyGems core team works to keep our ecosystem safe. By the end of this talk, you'll have a better understanding of how to safeguard your code.
2. Data Platform Components
A NoSQL document store that
offers fast time to market,
differentiated querying and
tuning capabilities with
schema-less web scale
Relational Non-Relational
SQL DB (PAAS) Table Storage File/ Blob StorageDocument DBSQL VM (IAAS)
5. The Basics
SQL Server database technology as a service
Fully Managed
Enterprise-ready with automatic support for HA
Designed to scale out elastically with demand
Ideal for simple and complex applications
7. How It Works
Client Layer - Used by application to communicate
directly with SQL Database.
Services Layer – Gateway between Client layer and
Platform layer.
Platform Layer – Includes physical servicers and
services that support the Services layer.
Infrastructure Layer – IT administration of the
physical HW and OS.
PHP
WCF Data
Services
SQL Server
Applications
and Tools
ODBC ADO.NET
Tabular Data Stream (TDS)
8. Server Provisioning
Service head that contains databases
Connect via automatically generated FQDN
(xxx.database.windows.net)
Initially contains only a master database
Log on to Microsoft Azure Management Portal
Create a SQL Database server
Specify admin login credentials
Add firewall rules and enable service access
Use Microsoft Azure Platform PowerShell cmdlets
(or use REST API directly)
wappowershell.codeplex.com
9. Selecting the right Edition
Service
Tier
Performance
Level
Common App
Pattern
Performance Business Continuity
Max DB
Size
Trans. Perf.
Objective
DTUs PITR DR / GEO-Rep
Basic Basic Small DB, SQL opp 2 GB Reliability / Hr. 5 Past 7
Days
DB Copy +
Manual Export
Standard S1 / S2 Wrkgp/cloud app,
multiple concurrent
operations
250 GB Reliability / Min. 15/ 50 Past 14
Days
DB Copy +
Manual Export
Premium P1 / P2 / P3 Mission Critical, High
volume, Many
concurrent Users
500 GB Reliability / sec. 100/
200/
800
Past 35
Days
Active Geo-
replication
12. Create Database…
Transact-SQL
Languages
.NET Framework (C#, Visual Basic, F#) via ADO.NET
C / C++ via ODBC
Java via Microsoft JDBC provider
PHP via Microsoft PHP provider
Frameworks
OData, Entity Framework, WCF Data Services, NHibernate
Tools
SQL Server Management Studio (2008 R2 and later)
SQL Server command-line utilities (SQLCMD, BCP)
CA Erwin® Data Modeler
Embarcadero Technologies DBArtisan®
Focus on logical vs. physical administration
Database and log files automatically placed
Three high-availability replicas maintained for every database
Tables require a clustered index
Maximum database size is 500 GB
Use command, distributed transactions, distributed views
Service Broker
Common Language Runtime (CLR)
SQL Agent
SQL Profiler
Native Encryption
13. Enhanced Tooling
Web designers for tables, views, stored procs
Interactive query editing and execution
Visual Studio IDE for database development
Includes modern designers and projects with declarative,
model-driven development
Develop and test in both connected and disconnected states
Platform targeting for both SQL Server (2005 and above)
and SQL Database
Get it free with Web PI, with SQL Server 2012 and with Visual
Studio 11
14. Database Deployment
Alternative to traditional script based approach
Dramatically simplifies deployment, migration and versioning of
databases
Provides a single unit of deployment for schema (dacpac) or for
schema + data (bacpac)
Supports automatic versioning of database schemas
Supports platform targeting for both SQL Server (2005 and above)
and SQL Database
Build from scratch or extract from existing db
With SQL Server Data Tools
With SQL Server 2012/2014 Management Studio
With SQL Database Import/Export Service
Via sqldacexamples.codeplex.com
17. Server Benefits
SQL authentication supported (No Integrated authentication)
The Admin login is similar to sa
Connect to master to administer logins
loginmanager: Server-Level security role for creating logins
dbmanager: Server-Level security role for creating databases
18. Database Benefits
Logins require an associated user account
The Admin login is automatically associated with dbo
The dbo has full rights in the database
Manage users with CREATE / ALTER / DROP USER commands
Add users to roles via sp_add_rolemember to grant privileges
Utilize schemas where appropriate
19. SQL Database Firewall
• IP Address-based access control for SQL Database
• Rules can be defined at the server and database
• No IP authorized by default
• Configurable using the SQL Database Portal and
REST API
• Option to disable/enable access from applications
hosted in Microsoft Azure
20. Application Connectivity
1. TDS (Tabular Data Stream) protocol over TCP/IP supported
2. SSL required
3. Use firewall rules to connect from outside Microsoft data center
ASP.NET EXAMPLE:
1. login: [login]@[server]
2. Idle connections
3. Long running transactions
4. DoS guard
5. Failover events
6. Throttling
7. Connection pooling and Retry logic
8. Latency introduced for updates
9. No cross-database dependencies
<connectionStrings>
<addname="AdventureWorks"connectionString=
"Data
Source=[server].database.windows.net;
Integrated Security=False;
Initial Catalog=ProductsDb;
User Id=[login];
Password=[password];
Trusted_Connection=False;
Encrypt=true;"
providerName="System.Data.SqlClient"/>
</connectionStrings>
21. Elastic SQL Database – Scaling out!
• .NET Client Libraries
• Management of Shards
• Data Access
23. Run SQL on VM
• Run any SQL product on cloud VM
• Support for SQL Server, Oracle, MySql
• Ready to go VM images available in Gallery
• Persistent storage using attached disk in blob storage
23Microsoft Azure
25. Azure Storage Architecture
“Microsoft Azure Storage: A Highly Available Cloud Storage Service with Strong Consistency”, ACM
Symposium on Operating System Principals (SOSP), Oct. 2011
27. “I wish I could go to storage and provision a cloud drive, giving
it a namespace, and that drive would then be UNC-addressable
by the OSes.”
Azure Files – Customer Quotes
28. • Setup an IaaS VM to host a File Share backed by an IaaS Disk
• Write code to find the IaaS File Share from the rest of the VMs in
your service.
• Write some code to provide high availability
• Handle host upgrades, node failures
• You can only access the File Share from other VMs
Sharing Files – The old way
38. Blob Containers
• Special $root container
• A container holds a set of blobs
• Set access policies at the container level
• Associate Metadata with Container
• List the blobs in a container
• Including Blob Metadata and MD5
• NO search/query. i.e. no WHERE MetadataValue = ?
• Effectively in Partition of 1
• Target of 60MB/s per Blob
42. Uploading a Block Blob
Uploading a large blob
Benefit
Efficient continuation and retry
Parallel and out of order upload of blocks
Microsoft Azure
Storage
44. Shared Access Signatures
• Use short time periods and re-issue
• Use container level policy that can be deleted
• Ad-hoc
• Policy based
45. Ad Hoc Signatures
• Signedresource Blob or Container
• AccessPolicy Start, Expiry and Permissions
• Signature HMAC-SHA256 of above fields
• Single use URLs
• E.g. Provide URL to mobile client to upload to container
46. Policy Based Signatures
• Specify StartTime, ExpiryTime, Permissions
• Signedresource Blob or Container
• Signedidentifier Optional pointer to container policy
• Signature HMAC-SHA256 of above fields
• Providing revocable permissions to certain users/groups
• To revoke: Delete or update container policy
48. Generally scales more easily
• The storage engines of NoSQL stores are designed to minimize
contentions enabling higher throughput and therefore more
scalable
• Lower transaction capability in NoSQL results in less contention
and therefore more scalable
• Less complex query processor means that a single query can’t
degrade service
• Built-in replication capability means that store can scale out which
better aligns to other application tiers (e.g. websites)
• No fixed schema or lower schema requirements
49Microsoft Azure
49. NoSQL on Azure
• Azure Tables service is NoSQL row store
• DocumentDB born in the cloud document database (JSON) and JS
(PAAS).
• HBase is a Big Data (Hadoop) NoSQL store available in HDInsight
• MongoDB is a document (JSON) store
• Cassandra is a columnar store with excellent replication
50Microsoft Azure
53. Entity Properties
Entity can have up to 255 properties
Up to 1MB per entity
Mandatory Properties for every entity
PartitionKey & RowKey (only indexed properties)
Uniquely identifies an entity
Defines the sort order
Timestamp
Optimistic Concurrency
Exposed as an HTTP Etag
No fixed schema for other properties
Each property is stored as a <name, typed value> pair
No schema stored for a table
Properties can be the standard .NET types
String, binary, bool, DateTime, GUID, int, int64, and
double
56. Purpose of the PartitionKey
Entity Locality
Entities in the same partition will be stored together
Efficient querying and cache locality
Endeavour to include partition key in all queries
Entity Group Transactions
Atomic multiple Insert/Update/Delete in same partition in a single transaction
Table Scalability
Target throughput – 500 tps/partition, several thousand tps/account
Microsoft Azure monitors the usage patterns of partitions
Automatically load balance partitions
Each partition can be served by a different storage node
Scale to meet the traffic needs of your table
61. Interaction Model
RESTful interaction over HTTP
Standard HTTP verbs & semantics
Interact using your favorite HTTP client
Built-in Support for TCP
Novel, efficient and powerful
document centric query model
Javascript based sprocs/triggers
/evals
POST
Item
resource TenantFeed URI
PUT
Item
resource Item URI
DELETE Item URI
GET TenantFeed Or
Item URI
Create a new resource
/Execute a script
Replace an existing resource
Delete an existing resource
Read/Query an existing
resource
Update an existing resource
PATCH Item URI
Item
resource
62. location headquarters exports
Belgium 0 1
city
Moscow
city
Athens
0
country city
Germany Berlin
1
country city
France Paris
0
headquarters exports
country city
Italy 0 1
Germany Bonn
city dealers
Berlin 0
city
Amsterdam
name
Hans
location
68. Fortune 500 using Azure
>57% >250k
Active websites
Greater than
1,000,000
SQL Databases in Azure
>20TRILLION
storage
objects >300MILLION
AD users
>13BILLION
authentication/wk
>2
MILLION
requests/sec >1MILLION
Developers
registered with
Visual Studio
Online
71. SQL Database Billing Rates (As of February
2012)
Database Size Price Per Database Per Month
0 to 100 MB Flat $4.995
> 100 to 1 GB Flat $9.99
> 1GB to 10 GB $9.99 for first GB, $3.99 per additional GB
> 10 GB to 50 GB $45.954 for first 10 GB, $1.998 for each additional GB
> 50 GB to 150 GB $145.874 for first 50 GB, $0.999 for each additional GB