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Leveraging ApsaraDB to Deploy Business Data on the Cloud
- 1. Presenter: David Wang Alibaba Cloud Product Specialist Leveraging ApsaraDB to Deploy Business Data on the Cloud
- 2. Outline ApsaraDB Introduction Countering Challenges Functional Solutions Typical Customers Introduction to ApsaraDB
- 3. Business Applications Redis Memcache MySQL SQL Server PostgreSQL MongoDB PPAS (Oracle) POLARDB Hbase HybridDB for MySQL(PetaData) HybridDB for PG(GreenPlum) Product Relationships Cache Fast Storage Long-term Analysis Big Covers over 70% of key online database engines
- 4. Product Relationships ApsaraDB RDS MySQL SQL Server PostgreSQL PPAS(Oracle) NoSQL Redis MongoDB Memcahce Data Warehousing HBase HTAP ADS Tools DTS DMS HybridDB for MySQL(PetaData) HybridDB for PostgreSQL(GreenPlum)
- 5. Product Features High Availability SSDs used as storage, verifiable backup restorability at any time The first RCPIS Grade III cloud database in China Master-Slave backup nodes & disaster tolerance solutions to ensure business continuity Automated management & monitoring Top database expert team to provide customer support Raft algorithm guaranteed consistency Free migration of full or incremental data without downtime
- 6. ApsaraDB Introduction Countering Challenges Functional Solutions Typical Customers
- 7. ApsaraDB Usage Poor Database Performance Weak O&M Platform Sensitive Data Difficulties Recruiting DBAs Current Issues
- 8. Poor Database Performance Performance & Capacity - 60 CPUs + 470 GB memory (exclusive physical machines) - 2TB SSD＋50000 IOPS - 100,000–150,000 QPS - No-downtime configuration changes Source Code Improvements - MySQLPostgreSQLRedisMongoDB - Locks, transaction optimization, and optimized master/slave syncing to improve performance 3–5 times over
- 9. Sensitive Data Security Features VPC: Isolated network environments IP Whitelist: Controlled client sources SSL: Encrypted network traffic TDE: Transparent data encryption SQL audit tracking: Detailed access records
- 10. Weak O&M Platform Automated O&M • Fault self-recovery • Backup self-verification • High-frequency monitoring • Webpage operations • Comprehensive analysis for resources, SQL databases, and engines - CPU resources - Memory resources - Storage resources - Connection count IOPS - Statement consumption summary and ranking - Execution plan analysis - Table structure analysis - Database lock analysis - Transaction optimization analysis - Deadlock rollback
- 11. Difficulties Recruiting DBAs Expert Services • Implementation of data migration to the cloud • Database emergency support • Database health diagnostics • Business escort service for high-traffic events • Customized open-source database source code ] Invoice Invoice_ID Price Tax Date Due Date Total ] ] ] ] ] Product Product_ID Material_ID Type Availability Stock Subcontractor_ID Subcontractor Subcontractor_ID Name Address Postal Code EmailMaterial Material_ID Material_Type Availability Stock Subcontractor Order Order_ID Order_Type Product_Type Product_Location Product_ID Event Event_ID Location Date Address_ID
- 12. ApsaraDB Introduction Countering Challenges Functional Solutions Typical Customers
- 13. Functions List Function ApsaraDB ECS User-created Database Service availability Master/Backup architecture ✔️ Hot standby ✖️ Local disaster tolerance ✔️ Multiple zones ✖️ Remote disaster tolerance ✔️ DR instances ✖️ Fault drills ✔️ Master/Backup switchover ✖️ Data reliability Online storage redundancy ✔️ Local RAID ✔️ Ultra/SSD cloud disks Offline long-term backup ✔️ Up to 730 days ✖️ Time point recovery ✔️ Instance clone ✖️ Data replication ✔️ Asynchronous/Semisynchronous ✖️ Data security Network isolation ✔️ White list groups ✔️ ECS security groups Audit logs ✔️ SQL audit/keyword filtering ✖️ Network encryption ✔️ SSL ✖️ Encrypted storage ✔️ TDE ✖️ Monitoring and alarms Resource monitoring ✔️ CPU/MEM/DISK/IOPS ✔️ Engine monitoring ✔️ QPS/TPS/etc ✖️ Seconds-level monitoring ✔️ 300s/60s ✔️ 300s Cloud Monitor alarms ✔️ Resource alarms/Availability alarms ✖️ Parameter management Parameter templates ✔️ Almost 100 optional parameters ✖️ Change history ✔️ Change record tracing ✖️ Performance optimization Overhead cost analysis ✔️ SQL consumption statistics ✖️ Optimization recommendations ✔️ Missing index analysis ✖️ All-in-one service Data management ✔️ DMS visual user interface ✖️ Data synchronization ✔️ DTS online data migration/subscription ✖️
- 14. Disaster Tolerance Solution East China Zone A Intranet • Disaster tolerance within a data center: Two nodes in different racks • Dual-data center local disaster tolerance: Log latency no longer than 3ms. Select "Multi-zone" during instance activation. • Coming soon: Dual-data center, tri-copy local disaster tolerance • Remote disaster tolerance: Log transmission delay of shorter than 1 second between two data centers located 300 km to 1000 km apart Master South China Zone A Leased Line M S Master Zone B Provides 3 levels of high-availability (disaster tolerance) architectures for selection
- 15. Read/Write Splitting Provides single-point "read scaling" capabilities • 10 read-only nodes • Independent connection address • Adjustable configurations Data Sync in MillisecondsRead-only Requests Loading Read/Write Service
- 16. Heterogeneous Data Storage • Provides “hotspot data” capabilities • Distributed memory cluster • Up to 512 GB for a single instance • Simple protocols (MemCache/Redis) Hotspot Data Persistent Data Access Common Transactions
- 17. Data Storage Scaling (For Relational Databases) Distributed, low cost, PB-level storage • Designed for IoT data storage and log data storage scenarios • Provides 3–5 years' capacity planning capabilities to enterprises • 7–10x compression capabilities (100 GB –> 15 GB) • Improves Insert performance by 10x • Over 70% compatible with MySQL Application Adaptation Costs HighNone • 60 Core, 470 GB mem • 2TB, 20000 IOPS • Configuration change as desired • 10 read-only nodes • Independent connection address • Adjustable configurations • PetaData • Simultaneous read/write scaling • Data volumes from 8 TB to 1 PB PolarDB, 100% compatible with MySQL, 100 TB
- 18. Data Storage Scaling • Built-in distributed clusters • Application integration with 0 code modification • 512 GB max storage for a single Redis instance Memcache Redis MongoDB • MongoDB Sharding, unlimited memory and storage (For NoSQL Databases)
- 19. Big Data Computing Access to the Data Technology (DT) age: renewed focus on how to make good use of d ata BI & Analytics IoT & Real-time Analytics In- house Cloud Backup Leased Line Access
- 20. ApsaraDB Introduction Countering Challenges Functional Solutions Typical Customers
- 21. Typical Customers After Alipay launched its Yu'E Bao business, Tianhong's accounting computation needs surged. Using RDS cluster instances for parallel computing, the company's revenue accounting time fell from 24 hours to 4 hours. Alipay Tianhong Securities Yu’er Bao
- 22. Typical Customers Chai Jing's documentary "Under the Dome" released a pollution map app The surge in users and traffic caused the app's offline database to crash. Using Alibaba Cloud’s Expert Service, the database was migrated to a read-only RDS instance. There, it was able to withstand dozens of times more access pressure. Community Organization: Pollution Map
- 23. Learn More About ApsaraDB for RDS www.alibabacloud.com/tc (Chinese) www.alibabacloud.com (English)
Editor's Notes
- #13: X86 based&Heterogeneous Network 10 GE -> 25 GE CPU from boardwell -> skylark Deep dive on the different instance families will come soon, on performance, and target business scenarios X-Dragon
- #21: X86 based&Heterogeneous Network 10 GE -> 25 GE CPU from boardwell -> skylark Deep dive on the different instance families will come soon, on performance, and target business scenarios X-Dragon