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4.1 KiB
title, type, source-type, category, tags, date-added, video-source, audio-source, status
| title | type | source-type | category | tags | date-added | video-source | audio-source | status | |||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| CTP Topic 66 Exposing the differences between PostgreSQL RDS and Aurora | cloud-learning | video | DevOps & SRE/01_AWS-Landing-Zone |
|
2026-04-14 | nas:///volume2/work/Public Cloud Learning Sessions/CTP _ Topic 66_ Exposing the differences between PostgreSQL RDS and Aurora.mp4 | summarized (Gemini 摘要) |
CTP Topic 66 Exposing the differences between PostgreSQL RDS and Aurora
Source: NAS /volume2/work/Public Cloud Learning Sessions/CTP _ Topic 66_ Exposing the differences between PostgreSQL RDS and Aurora.mp4
Type: VIDEO | Category: 01_AWS-Landing-Zone
Status: 🟡 Awaiting Whisper transcription → Summary
摘要
RDS vs. Aurora: Key Differences
Greg Klau presented a detailed comparison of PostgreSQL on Amazon RDS and Aurora, focusing on performance, cost, and use cases. The session covered choosing between the two, running blue-green and cross-region operations, monitoring, and network performance tweaks for high availability.
Key Differences and Considerations
- Minimum Size and Cost: RDS offers smaller, cheaper instances suitable for small databases, while Aurora has a higher minimum size and cost due to its architecture.
- Maximum Size and Performance: Aurora scales to larger databases and offers better IO performance, making it suitable for databases exceeding 10-20 terabytes.
- Auto Scaling: Aurora offers auto-scaling (Serverless v2) but with limitations on instance shapes, versions, and regions.
- Recovery Time Objective (RTO): Aurora boasts a 30-second RTO, compared to RDS's two minutes in the event of an AZ failure.
- Storage Flexibility: RDS provides more storage options (GP2, GP3, provisioned IOPS, magnetic), while Aurora charges per IO.
- With RDS, you get to choose multiple different storage mechanisms.
- Aurora IO is generally unbounded because they're motivated to give you as much IO as you can consume because they're charging you per IO.
Architectural Comparison
- RDS: Uses compute with attached storage (EBS). Multi-AZ setup involves another compute and storage node for failover. Replication across regions is asynchronous.
- Aurora: Employs six EBS volumes across three availability zones, managed by Amazon. Adding compute uses the same cluster volume, avoiding data replication for read replicas. Aurora Global allows multi-region setups with asynchronous replication.
- With Aurora, you get six EBS volumes. They're spread across three availability zones.
- Endpoints: RDS has one endpoint per cluster, while Aurora has separate writer and reader endpoints.
Database Switchover and Failover
- RDS: Requires blocking access, forcing a new primary, destroying the old cluster, and rebuilding it as a standby.
- Aurora: Allows clean, managed switchovers using Aurora Global, without re-replication. Failover involves promoting a secondary region and re-adding the failed region as a new global cluster after it recovers.
Blue-Green Deployments (Aurora MySQL Only)
- Aurora MySQL supports blue-green deployments for major version upgrades, creating a duplicate environment for testing before switching over. This involves logical replication to a green environment, with guardrails to prevent data loss.
Monitoring
- Both RDS and Aurora offer monitoring options via CloudWatch, Grafana, and Performance Insights. Performance Insights provides a view of database load, query performance, and wait times.
- Aurora utilizes free local storage (ephemeral SSD) for temporary work, which is fixed per instance type. RDS uses EBS for temporary storage.
High Availability Performance Tweaks
- Lower DNS time to live (TTL) to one second for faster failover.
- Adjust TCP Keep-Alive settings to detect database failures quickly.
- Use JDBC connection string overloading with reader and writer endpoints for resilience.
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最后更新: 2026-04-14