If the single node fails, the entire business system becomes unavailable. This is the most significant and critical risk of a single-node architecture, which lacks resilience features such as service redundancy and automatic failover.

The application's capacity is limited by the performance of a single node, creating a bottleneck. Scaling up can be expensive, time-consuming, and disruptive to service.

Performing maintenance or upgrades on the single node can lead to service downtime. Each standalone machine has its own Internet-facing entry point, making it difficult to manage security policies consistently.

Critical components must have more than one copy. Any single component can become a point of failure.

The system must continuously monitor the status of each component to detect failures promptly.

Upon detecting a failure, the system must fail over automatically. Relying on manual intervention significantly extends downtime.

Combine multi-instance redundancy, ALB for load balancing, and a multi-AZ deployment to achieve automatic fault isolation and traffic shifting at the application layer. For details, see the deployment guide in this document.

Decouple all variable states from application servers and store them in an external, independent storage service that all instances can share.

Auto scaling allows the system to maintain service quality during peak times while saving costs during off-peak periods, combining high availability with cost optimization.

Store structured data, such as user information and order records, in ApsaraDB RDS. Use a primary/standby architecture for high availability. If the primary node experiences an unrecoverable failure, the system automatically triggers a failover to the standby node. This process is transparent to the application and requires no manual intervention.

As part of making applications stateless, migrate unstructured data like images, videos, and documents to OSS. OSS uses a multi-replica mechanism to ensure data durability. Choose zone-redundant storage for availability zone-level high availability.

Migrate user sessions to the high-performance distributed cache service, Tair. This allows any ECS instance handling a request to access or update user state by interacting with the same Tair instance.

Deploy a production environment in the primary region and a standby environment in a disaster recovery region. Under normal conditions, the standby environment only receives data synchronization—DTS for structured data and OSS cross-region replication for unstructured data—and does not handle business requests. In a disaster, you can activate the standby system and manually update DNS records or use GTM to trigger an automatic switchover, restoring business services within minutes to hours.

This is an enhanced architecture commonly used in industries like finance that have extremely high stability requirements. It essentially layers intra-city high availability with active-standby disaster recovery. In the production region, the business system is deployed across two different availability zones, forming an intra-city HA cluster (the two centers) that can automatically withstand a single data center failure. In the disaster recovery region, a disaster recovery center (the third center) is deployed and kept in sync with the production environment.

Deploy complete, independent production environments in multiple regions. All regions actively handle real user traffic, with no primary/standby distinction. GTM routes user requests to the optimal region based on geographic location and network latency. If a region fails, GTM automatically removes it from the address pool, and user traffic naturally flows to other healthy regions. This process is seamless to users, achieving automatic failover for region-level outages.

For end-to-end monitoring, collect key metrics and set alerts for the application layer (ALB request success rate, response time; ECS CPU/memory), data layer (ApsaraDB RDS connections, slow queries, primary/standby sync delay; Tair memory usage, hit rate), and business layer (order volume, payment success rate).

When a request traverses multiple components such as ALB → ECS → Tair → ApsaraDB RDS, ARMS can visualize the entire call chain. This allows you to precisely locate which component is causing delays or errors, reducing troubleshooting time from hours to minutes.

Collect application and access logs from all instances into Log Service (SLS). This prevents log loss if an instance fails and enables cross-instance log searching and analysis, providing a complete record for incident review and security audits.