Let's meet and talk about Microsoft Azure PaaS offerings. The PaaS layer provides many scalable and globally deployed services completely manged by Microsoft that allow developer to focus on specific business requirements and to leave the infrastructure bits to the cloud provider. We will underline the differences between Virtual Machines, Cloud Services and Azure Web Apps on the compute layer. Later we will compare SQL Server and Azure SQL. Then we will focus on Data Storage and Data Analytics services that gives incredible power to developers and data professionals. Most of the examples we cover are platform agnostic so people from any programming background are welcome to join and share their unique experience. Microsoft Azure is getting more open and open source friendly with every new day! Come and join us to learn more about Microsoft Azure and enjoy your journey with the public cloud!

1. Azure PaaS Overview
Kanio Dimitrov,
Tokyo Azure Meetup

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Tokyo Azure Meetup
• Practical Knowledge
• Microsoft Azure Focus
• Create Global Azure community
• Learn | Share | Enjoy cool demos!

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About Me
Azure Architect
Azure Advisor
Twitter
@azurekanio
Website
http://azurekan.wordpress.com

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Standing On The Shoulders of Giants
If I have seen further,
it is by standing on the
shoulders of giants.
Isaac Newton

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• Hyper Scale
• Cost Effective
• Global Spread
Public Cloud

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PaaS - Platform as a Service
Platform for:
• Developing
• Running
• Managing
Infrastructure fully
managed by Cloud
Provider
Applications
PROS
CONS
Less Control
Possible Lock-in

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Azure PaaS Services
Data Lake App Service
API
Management
Event Hubs Azure Active
Directory
Azure SQL
Batch Automation Stream
Analytics
Storage Cloud Service CDN
Document DB Service Fabric HDInsight Key Vault Redis Cache Machine Learning
IoT Suite Service Bus Azure Search App Insights Media Services Data Factory

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Focus
Data Lake App Service
API
Management Event Hubs
Azure Active
Directory
Azure SQL
Stream
Analytics
Storage
BlobLogic AppWeb App
Store Analytics

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Use Case
Check Status
If update required
Check Status
If update required
Kill switch functionality,
activated in case of emergency
on client or server side.
Mobile Client Mobile ClientWeb API

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Requirements
• Latency – up to 500 ms
• Monitoring – Tracking every request and response
• SLA –
• Global Use

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Web Portal – Azure Web App
Auto Scale
Deployment < 1 min
• Git / GitHub
Supports:
• Java
• PHP
• Node.js
• Python
Azure
Web AppUser

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Authentication - Azure Active Directory
Azure
Web App
Azure Active
Directory
Identity and access
management
• Best Security Practices
• Multi Factor Authentication
• On-Premise Integration

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Data Storage – Azure SQL
• Database as a service
• Provision for minutes
• Self-managed for near-
zero maintenance
Azure SQLAzure
Web App
Database

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API – Azure Web App
Issues to address:
• Manage Access to API
• Interactive Documentation
• Distribute Globally
Azure SQLAzure
Web App
Database
API

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API Proxy – API Management
• Single API Endpoint
• Throttling, rate limits, quota
• Modify API requests /
responses
Mobile
Client
API
Management
Azure
Web App
APIAPI Proxy

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API Management

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API Management Advantages

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API Management Tracking – Event Hubs
• Giant Queue
• Million of events / second
• Similar to Apache Kafka
API
Management Event Hub
API Proxy Message
Broker

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API Management Policies
// Create context variable
<set-variable name="responseDateTime" value="@(DateTime.UtcNow)" />
….
<log-to-eventhub logger-id="{logger-name}">
@{
// Create JSON Object
var response = new JObject();
// Add body as a property
response.Add(new JProperty("body", context.Response.Body.As<JObject>(true)));
// Add response time as a property
response.Add(new JProperty("responseTime",
DateTime.UtcNow.Subtract((DateTime)context.Variables["responseDateTime"]).Milliseconds))
// return result as a string
return response.ToString()
}
</log-to-eventhub>

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Real Time Processing – Stream Analytics
• Million of events / second
• SQL based language
• Similar to Apache Storm
Event
Hub
Stream
Analytics
Message
Broker
Real Time
Analytics

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Real Time Processing – Rich Output
Stream
Analytics
Power BI
Visual Reports
Logic App
Workflow App in the cloud
Storage
Blob
File in the cloud
Real Time
Analytics

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Big Data Processing – Data Lake
Input
Storage
Blob
Data Lake Store
& Analytics Jobs
Output Storage
Blob
File in the cloud “Infinite” Storage
and Big Data
Processing done in
SQL and C#
File in the cloud

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Azure Data Lake (ADL) Architecture

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ADL Store

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ADL Analytics Jobs
• Cost Effective
• Dynamic scaling
• U-SQL – T-SQL & C#
• Very rich tooling in Visual Studio

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T-SQL U-SQL C#
Extendable with
custom algorithms
New features added to
standard T-SQL
Most of T-SQL
declarative features

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Lambda Architecture
Mobile Client
Power BI
Graph Reports
Logic App
Workflow
Web App
Portal
Azure SQL
Database
Web App
API API Proxy
API Management Event Hub
Message
Broker
Stream
Analytics
Real Time
Processing
Storage Blob
File in the cloud
Data Lake Store &
Analytics Jobs
Big Data
Storage Blob
File in the cloud
Real Time
Processing
Batch Processing
(Data at Rest)

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Demo

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Questions

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