Key Azure Services List

Key Azure Services List

CPU and Memory

• Virtual Machines
• VMs: Drives, SSD, Speed, Cores
• Lynux VM
• Windows VMs
• VM Images: Templated Images
• Scale Lets : Grow VM instaces based on load
• Availability Sets:
• Managed Disk: Virtual Disks
• App Services
• Run Web App of your choice
• Flexible Deployment: GIT, Azure Dev Ops, FTP
• Scaling
• Application Healing: If App Service goes down, Azure deploys the code in another App Service Instace
• Deployment Slot: Move from Stage to Production
• Containers
• AKS
• Azure Container Instances:
• Azure Container Registry
• ServerLess: No VM, No Web App
• Azure Functions : C#, JS, Powershell ; Trigger; Http Request; Message
• Logic Apps: Workflow;
• Event Grid: Pub/Sub ; App Events and Infrastructure events
• Compute At Scale: Massive Scale
• Batch Scale : To spin up several VMs to run intensive process;
• HDInsight: Processing capabilities in BigData;

Data Storage

• Characteristics: Scalable, Available, Global (Region, Country)
• Self Managed: VM or Container; Possible Predefined Images; You mange compute and disks; Patch responsibility
• Service Based: Provision an Instance; Choose scale characteristics; Manage by Azure; No patching
• Relational:
• Azure SQL: Managed Instance; Elastic pool
• My SQL
• Maria DB
• PostgreSQL
• Non-Relational
• Table Storage: Key Value storage;
• Blog Storage: Files; PDF;
• Queues: Short term data storge
• Redis Cache: Performance
• Cosmos DB
• Self Hosted: MongoDB, Cassandra, Neo4j
• Azure CosmosDB: Multi-model DB; MongoDB, Cassandra are Neo4j encapsulated in Azure CosmosDB.
• Graph/Gremlin
• Table
• Cassandra
• Globally Distributed
• Multi-Latency
• Low Latency
• Five Consistency Levels
• Azure DataLake (v2)
• Large Scale data storage build for Analytics
• Multi-model access - File/Blob ; Analytics can use either File Based or Blob based to access data
• Built on Azure Blob Storage

 

Data Processing

•     Ingestion Event Hubs: Vast quantity of data.
• Data Factory: Moving ETL; Like SSIS ; Different systems; Different Clouds

 

 

Data analytics

• SQL Data warehouse:
• Analysis Service: Visual Studio Tools; For end users reporting
• Stream Analytics
• Real Time data Analysis
• High volume message Processing
• Ingest, analyze and output
• Azure HD Insight
• Open source analytic Tools: Spark, Hadoop, Hive, Storm, Kafka, HBase
• On BigData
• Azure Data Bricks
• Clould Optimized Spark Service
• Deep Azure integration: Azure AD, Security
• Cognitive Service
• Prepackaged machine learning
• Decision; Speech; Language; Vision; Search
• PowerBi
• Render Reports
• Charts etc
• Azure Synapse
• A workspace to manage below
• SQL Data warehouse + Data Bricks
• All your storage
• Data Movement (ETL)
• Machine Learning

 

Integration

• Connecting systems and applications
• Within a cloud
• Cloud to data center
• Between clouds
• Cloud to SaaS
• Messaging and Events
• Service Bus - Brokered or relayed messages
• Event Grid: Pub/Sub;
• API Management: Publish; Secure; Manage API;
• Logic Apps Workflow
• Orchestrating messaging interactions
• Control Flow
• Integration Accounts
• Enterprise file formats
• XML/JSON transformation
• Partners managements: Certificates; End Points etc

 

Network

• Virtual Network: Define network
• Public IP Addresses
• Network Security Groups
• Service Endpoint Policies
• Connecting environments
• Express Route:
• On-premise data gateway
• CDN
• Traffic Manager: Rules for traffic;
• Load Balancer
• DNS Zones
• Edge Services:
• Application gateway
• Front Door

 

Management: Monitor

• Deploy, Restrict access
• Manage
• Portal: Web based to to manage
• CLI
• Cloud Shell: Commandline interface inside browser
• Mobile App
• Backup and site recovery
• Automation and Scheduling : On demand or schedule;
• RBAC: Role based access control.
• Deploying Azure resources
• Azure Resource Manager
• Define resources in a Templated
• Resource groups, locations and services
• Create relationships between resources
• Deploy template with parameters
• Azure Deployment Manager:
• Coordinate deployment of ARM
• Define Service Topology
• Define Rollout steps
• Monitoring and Alerts
• Monitor
• Network watcher
• Alerts : Can be configured and be notified.

 

Development Tools

• REST / Web API
• Cross-platform access
• Client SDKs wrap API
• Developing for Azure
• SDKs:
• Developer Tools:
• Container Development
• Build and Deploy : ARM template;
• Azure SDKs:
• PHP, Python, Node.JS, Java, .NET, Ruby
• Many are cross-platform
• Azure service coverage varies based on subscriptions.
• Developer Tools
• Visual Studio: Logic Apps, Service Fabric, ; Extension; Integrated with azure
• Eclipse: Plugin
• Visual Studio Code:JS, Node.JS;
• IntelliJ: Azure extensions;
• Container Development
• Docker (Local development)
• Cloud Deployment
• Azure Dev Spces:
• On top of AKS
• Rapid interactive development on Kubernetes
• Team-focused
• Build and Deploy
• GIT
• ARM Template: With parameter files
• Azure DevOps
• Azure Boards: Work Items, Bugs
• Azure Repos: GIT, team foundation
• Azure Pipelines: Build and Release; Tasks
• Azure Test Plans

   

Identity: 

• Management level, Application Level. Secrets
• Azure Active Directory:
• Core directory services
• Multi-factor authentication
• Directory Synchronization
• Identity and Directory Services
• Azure Active Directory
• Azure AD Domain Services
• Azure AD B2C: Expose end points to customer
• Application and Identity   
• Managed Identities: Application Pool Identity; Service Account;
• Application Registrations:
• Enterprise Application: Third party software;
• Data Protection Tools
• Information Protection
• Key Vault: Store secrets;
• Hardware Security Module:
• Azure Security Center
• Monitor VMs and apps:
• Include VMs from your data center
• Visualization through Azure Monitor
• Advise and alerts
• Addition Security Services
• Azure Sentinel
• Azure Defender
• Role Based Access Control:

 

Other Azure Services

• Media Services: Stream;
• Mobile Apps: Notification Hubs;
• IoT: Messaging; Telemetry;
• Mixed Reality
• Blockchain
• Bot Service:
• Search: Cognitive ; Bing