SlideShare a Scribd company logo
Building data solutions in Cloud
Dinusha Kumarasiri
About Me
 Senior Solution Architect at LB Finance PLC
 Former Microsoft MVP
 Microsoft Certified Trainer (MCT)
 Cloud Enthusiast
 Love to share what I know
Workshop Agenda
 Introduction to cloud computing
 Cloud service models
 Data solutions
 Azure App Service
 Azure Cognitive Services
 Building Cloud Native applications with Azure
Agenda for Today
 Building data solutions
 Working with unstructured data
 Working with structured data
 Working with semi-structured data

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Building data solutions in Cloud
Storage accounts
 To contain all Azure data objects
Points to consider
 Redundancy levels
 LRS, ZRS, GRS, GZRS, RA-GRS, RA-GZRS
 Performance tiers / Lifecycle management
 Hot, Cold, Archive
 Security
 Access keys, Shared access signature, RBAC
 Manage
 Portal, CLI, PowerShell, REST API, Azure Storage Explorer
Unstructured data – Blob Storage
 Scalable and secure object storage in cloud
 Block Blob
 Page Blob
 Append Blob
 REST API
https://contosouor.blob.core.windows.net/vehi
cles?comp=list

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This document provides an overview of Viknaraj's background and expertise in modern IT technologies. Viknaraj has over 17 years of experience in IT and worked in network engineering for over 11 years. He specializes in Microsoft products including servers, cloud infrastructure, Office 365, and virtualization. The document then provides brief 1-2 sentence definitions of key technologies including cloud computing, virtualization, artificial intelligence, internet of things, blockchain, machine learning, big data, image processing, and video processing. It concludes by inviting questions and discussion and providing Viknaraj's contact information.

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The document discusses the experience and qualifications of M Viknaraj related to cloud infrastructure and Microsoft technologies. It includes over 17 years of experience in IT and networking, specializing in Microsoft server infrastructure, cloud infrastructure, Office 365, and virtualization. It also provides information on cloud computing concepts like infrastructure as a service, platform as a service, software as a service, virtual machines, and data centers.

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Unstructured data - Files
 Managed file shares in the cloud
 Supports common protocols (NFS, SMB)
 Synchronize with on-premises file shares (Azure File Sync)
Unstructured data - Queues
 Durable queues for large-volume cloud services
 To decouple application components with asynchronous message queueing
 Improve resiliency of the total solution
 Highly scalable to improve the elasticity of solution
Structured data – Azure SQL
 Relational database service build for Cloud
 Fully managed PaaS offering
 Highly scalable with auto scale
Semi-structured data - Table
 NoSQL key/value store with a schemaless design
 Fully managed PaaS offering
 Suitable for applications that require a flexible schema
 Performs OData-based queries
 Highly scalable

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Building Data Solutions with Azure

  • 1. Building data solutions in Cloud Dinusha Kumarasiri
  • 2. About Me  Senior Solution Architect at LB Finance PLC  Former Microsoft MVP  Microsoft Certified Trainer (MCT)  Cloud Enthusiast  Love to share what I know
  • 3. Workshop Agenda  Introduction to cloud computing  Cloud service models  Data solutions  Azure App Service  Azure Cognitive Services  Building Cloud Native applications with Azure
  • 4. Agenda for Today  Building data solutions  Working with unstructured data  Working with structured data  Working with semi-structured data
  • 7. Storage accounts  To contain all Azure data objects Points to consider  Redundancy levels  LRS, ZRS, GRS, GZRS, RA-GRS, RA-GZRS  Performance tiers / Lifecycle management  Hot, Cold, Archive  Security  Access keys, Shared access signature, RBAC  Manage  Portal, CLI, PowerShell, REST API, Azure Storage Explorer
  • 8. Unstructured data – Blob Storage  Scalable and secure object storage in cloud  Block Blob  Page Blob  Append Blob  REST API https://contosouor.blob.core.windows.net/vehi cles?comp=list
  • 9. Unstructured data - Files  Managed file shares in the cloud  Supports common protocols (NFS, SMB)  Synchronize with on-premises file shares (Azure File Sync)
  • 10. Unstructured data - Queues  Durable queues for large-volume cloud services  To decouple application components with asynchronous message queueing  Improve resiliency of the total solution  Highly scalable to improve the elasticity of solution
  • 11. Structured data – Azure SQL  Relational database service build for Cloud  Fully managed PaaS offering  Highly scalable with auto scale
  • 12. Semi-structured data - Table  NoSQL key/value store with a schemaless design  Fully managed PaaS offering  Suitable for applications that require a flexible schema  Performs OData-based queries  Highly scalable
  • 13. Semi-structured data – Cosmos DB  NoSQL database service with open-source API support and varying consistency models  Open-source API support  SQL/ Mongo DB (Document storage)  Cassandra (Column storage)  Table (Key/Value storage)  Gremlin (Graph storage)  Allows multi-region writes  Varying consistency models  Strong consistency  Session consistency  Eventual consistency

Editor's Notes

  1. Research Projects : Mobile responsive, Approval through phone, AI for Leasing
  2. Research Projects : Mobile responsive, Approval through phone, AI for Leasing
  3. Research Projects : Mobile responsive, Approval through phone, AI for Leasing
  4. Research Projects : Mobile responsive, Approval through phone, AI for Leasing
  5. Research Projects : Mobile responsive, Approval through phone, AI for Leasing
  6. Research Projects : Mobile responsive, Approval through phone, AI for Leasing
  7. Research Projects : Mobile responsive, Approval through phone, AI for Leasing
  8. Research Projects : Mobile responsive, Approval through phone, AI for Leasing
  9. Research Projects : Mobile responsive, Approval through phone, AI for Leasing
  10. Research Projects : Mobile responsive, Approval through phone, AI for Leasing
  11. Research Projects : Mobile responsive, Approval through phone, AI for Leasing
  12. Research Projects : Mobile responsive, Approval through phone, AI for Leasing