Build PolarDB cluster configurations with node specs, read replicas, proxy, serverless scaling, and backup policies.
Last verified: May 2026
Build PolarDB cluster configurations with node specs, read replicas, proxy, serverless scaling, storage, and backup policies.
Required Fields
clusterNameenginenodesOutput will appear here...The builder collects cluster name, engine, version, region, primary node specs, read replica count, proxy configuration, serverless settings, and backup policy. It validates the configuration against current PolarDB capabilities and emits `alicloud_polardb_cluster`, `alicloud_polardb_database`, `alicloud_polardb_account`, and `alicloud_polardb_backup_policy` Terraform resources.
Alibaba Cloud PolarDB is the cloud-native database family — separated compute and storage, with read replicas that scale independently of the primary. The PolarDB Config Builder generates cluster configurations including engine (MySQL-, PostgreSQL-, or Oracle-compatible), node specs, read replicas, proxy configuration, serverless scaling, and backup policies. Output is Terraform-ready and matches `alicloud_polardb_cluster`.
Your application has grown to need five read replicas, and the RDS cost has become hard to justify because each replica duplicates the 4 TB of storage. You migrate to PolarDB where read replicas share storage with the primary. The five replicas now cost only compute, not storage — a meaningful monthly saving. Migration takes a weekend and is transparent to the application.
Use PolarDB proxy for connection pooling and read-write splitting. The proxy handles routing reads to replicas automatically, removing the need for application-level read/write split logic.
Right-size based on workload type. PolarDB's architecture rewards storage-heavy workloads (storage is cheap, replicas cheap) and penalizes write-heavy workloads (writes must replicate). Match cluster topology to workload shape.
PolarDB's compute/storage separation gives you cheaper read replicas (replicas share storage with the primary, so they only cost compute, not duplicated storage) and faster scaling. For workloads with multiple read replicas, large data volumes, or high I/O, PolarDB is often more cost-effective. For small workloads, RDS is simpler.
Serverless mode automatically scales compute capacity based on load, billing only for resources actually used. Suitable for workloads with unpredictable load patterns — bursty applications, development environments, multi-tenant systems where load per tenant varies wildly. For predictable steady-state workloads, provisioned mode is cheaper.
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