Day1
Overview
1. Cloud - Internet scaling / Internet connects / Resource pool
2. Why the cloud? Rapidly setup environments / Scale to meet peak demands / increase daily activities. (Speed / Scale / Economics)
3. cloud computing patterns: on and off/ growing fast / unpredictable bursting / predictable bursting
4. cloud computing : IaaS(Host) / PaaS(Build) / SaaS(Consume)
Infrastructure as a Service
Platform as a service
Software as a service
5. How are Microsoft Azure Charges Incurred?
Pay only for what you use*
VMs usage is by the minute
VMs that are stopped in Microsoft Azure do not incur charges
Microsoft Azure Enterprise Agreement(EA) billing process differs
6. Microsoft Azure Compute : App service / MS Azure Cloud service / VMs - IaaS
7. How we differentiate with Azure
Hyper-scale / Enterprise Grade / Hybrid
8. Azure Site Recovery
9. MS Azure Active Directory
10. MS Azure Multi-Factor Authentication (多因素认证)
11. SQL Database (Day 2 afternoon)
12. HDInsight (Hadoop/Hive/Pig etc.)
13. Apache Storm for Azure HDInsight : Real-time event processing solution for large, fast steams of data.
14. Apache Spark for Azure HDInsight
15. Azure Machine Learning: 图像识别/小冰、小娜等/分析票务信息 --算法 / CRM
Powerbi.com
16. Azure Stream Analytics : 智能楼宇/交通流量/物联网/监控/计算机日志 (根据时间窗口进行数据分析)
17. Azure Data Factory: 数据清洗
18. Azure App service: Web apps/ Mobile apps / logic apps(系统整合) /API apps
Azure App service Web Apps: 系统负荷扩展
Azure App Service Mobile Apps: 信息推送
Azure App Service Logic Apps:
https://tryappservice.azure.com
Azure Media Services: 视频培训(不需要客户端播放器配置)
Internet of things (IOT)
Compute Scaling
1.Scale UP :纵向扩展
2.Scale Out :水平扩展
Azure Virtual Machine
Azure Network
Day2
微软公有云和高级企业技术服务介绍
微软存储很便宜 0.98元/TB
Severity : A B C D
A: < 1 Hour
B: < 2 Hour or 4 Hour ( C or D)
三种计算模式：Vm/cloud service / app service
PaaS Cloud Service
Cloud Service Basic: Web role / Worker Role (A container of related service roles)
What can it run? Language: C# / Java / VB / C++ / PHP /Python/ Node.js etc.
Framework: .NET / ExpressJS/ Rails/ Zend, etc.
General Rule: If it runs in MS windows, it runs in MS Azure.
Roles & Instances : 可修改池里实例个数
Fault domain（故障域） / upgrade domain（更新域）
Role Lifecycle : Fabric Calls -- Role Lifetime -- Request Routed
Worker Role Patterns
Queue polling worker:
性能考虑（硬件增加一倍，性能不一定增加一倍）/ 安全性考虑（压力测试，获取系统负荷）/
Paas Database Service
Paas Storage
Local Storage and Diagnostics
Role Instance:
Role --> Diagnostic monitors <--> Local Directory Storage --> Cloud
Diagnostics Data Locations
Event logs / Performance counters/ MS Azure logs/ IIS logs/ IIS failed request logs/ crash dumps/ custom file based logs
Caching
Fast
Cheaper
In-role Caching: Dedicated cache
Azure Redis Cache: http://redis.io