High Level Overview of Windows Azure- EPC Group
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High Level Overview of Windows Azure- EPC Group
- 3. • 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.
- 4. Topics to Review • Windows Azure SQL Database • Architecture • Application Connectivity • Scalability • Windows Azure Table Storage • Architecture • Querying • Best Practices and Considerations • Cost • Transactions
- 5. Application Connectivity Considerations And Best Practices • login: [login]@[server] • Idle connections • Long running transactions • DoS guard • Failover events • Throttling • Connection pooling and Retry logic • Latency introduced for updates • No cross-database dependencies
- 6. A Seamless Offering from the Private Cloud to the Public Cloud
- 7. Scalability Model For The Cloud Cloud Applications • Require Scale Beyond Scale-Up • Demand the Best Economics • Best Price/Performance • Elasticity + Pay-as-you-go
- 8. Obstacles • Defining the Tenant • Establishing Tenant’s surrogate key • Elastic Scalability (Splits/Merges/Tenant Moving) • Application Lifecycle Management (Dev; Test; Deploy; Upgrades) • Overcoming limitations of existing tools & available features • Transient nature of connectivity
- 13. No Fixed Schema
- 14. Querying
- 15. 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 – 20,000 tps/partition, several thousand tps/account • Windows 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
- 16. PARTITIONKEY (CATEGORY) ROWKEY (TITLE) TIMESTAMP MODELYEAR Bikes Super Duper Cycle … 2009 Bikes Quick Cycle 200 Deluxe … 2007 … … … … Canoes Whitewater … 2009 Canoes Flatwater … 2006 PARTITIONKEY (CATEGORY) ROWKEY (TITLE) TIMESTAMP MODELYEAR Rafts 14ft Super Tourer … 1999 … … … … Skis Fabrikam Back Trackers … 2009 … … … … Tents Super Palace … 2008 PARTITIONKEY (CATEGORY) ROWKEY (TITLE) TIMESTAMP MODELYEAR Bikes Super Duper Cycle … 2009 Bikes Quick Cycle 200 Deluxe … 2007 … … … … Canoes Whitewater … 2009 Canoes Flatwater … 2006 Rafts 14ft Super Tourer … 1999 … … … … Skis Fabrikam Back Trackers … 2009 … … … … Tents Super Palace … 2008 Partitions and Partition Ranges
Notes de l'éditeur
- Here we can see that the Front-End layer takes incoming requests, and a given front-end server can talk to all of the partition servers it needs to in order to process the incoming requests. The partition layer consists of all of the partition servers, with a master system to perform the automatic load balancing (described below) and assignments of partitions. As shown in the figure, each partition server is assigned a set of object partitions (Blobs, Entities, Queues). The Partition Master constantly monitors the overall load on each partition sever as well the individual partitions, and uses this for load balancing. Then the lowest layer of the storage architecture is the Distributed File System layer, which stores and replicates the data, and all partition servers can access any of the DFS severs.It is important to understand that partitions are not tied to specific partition servers, since the data is stored in the DFS layer. The partition layer can therefore easily load balance and assign partitions to different partition servers, since any partition server can potentially provide access to any partition.The partition layer assigns partitions to partition severs based on each partition’s load. A given partition server may serve many partitions, and the Partition Master continuously monitors the load on all partition servers. If it sees that a partition server has too much load, the partition layer will automatically load balance some of the partitions from that partition server to a partition server with low load.