Read Only Routing Configuration for High-Availability Architectures

Read Only Routing Configuration for High-Availability ArchitecturesHigh-availability (HA) architectures require careful design to ensure services remain responsive, consistent, and resilient under load or failure. One common scalability and resilience pattern is to separate read and write workloads—sending writes to primary nodes and distributing reads to replicas. Read Only Routing (ROR) is the mechanism that automatically directs read-only client requests to replica (secondary) servers while ensuring write requests go to the primary. Proper ROR configuration increases throughput, reduces latency for read-heavy workloads, and improves fault isolation. This article covers the principles, design considerations, implementation patterns, monitoring, and operational best practices for configuring Read Only Routing in HA architectures.

Why use Read Only Routing?

• Improved scalability: Offloading reads to replicas increases the system’s capacity to handle parallel read requests without impacting write latency on the primary.
• Reduced contention: Read-only queries do not compete with writes for locks and resources on the primary, improving overall throughput.
• Fault isolation: Heavy read traffic targeted at replicas limits the scope of performance issues to non-primary nodes.
• Geographic locality: Read replicas placed in different regions can serve local clients with lower latency.
• Graceful degradation: If replicas fail or lag, the system can continue to serve writes and prioritize critical reads via the primary.

Core concepts

• Primary (or master): node that accepts writes and coordinates replication.
• Replica (secondary): node(s) that receive and apply replication stream; serve read-only queries.
• Read-only session/connection: a client connection or query flagged as read-only, safe for execution on replicas.
• Staleness and replication lag: delay between write commit on primary and its visibility on a replica.
• Consistency models: strong vs eventual consistency; affects whether certain reads are safe on replicas.

Architecture patterns

1. Client-driven routing

   • Clients decide whether to connect to a primary or a replica based on the operation type.
   • Pros: simple; minimal infrastructure.
   • Cons: requires client logic, risk of incorrect routing.

2. Proxy-based routing

   • A proxy (software or load balancer) inspects queries or connection flags and routes read-only traffic to replicas.
   • Examples: PgBouncer/pgPool for PostgreSQL, HAProxy, MySQL Router.
   • Pros: centralizes routing logic, simpler clients.
   • Cons: adds a component that must be highly available and performant.

3. DNS/Service-discovery routing

   • Separate service endpoints for reads and writes (e.g., write.myapp.example => primary; read.myapp.example => replica pool).
   • Pros: simple and widely supported by cloud providers.
   • Cons: less granular control, DNS propagation can complicate failover.

4. Database-native routing

   • Database systems provide built-in mechanisms (e.g., SQL Server Read-Only Routing, Oracle Data Guard, some managed DB offerings) to direct read-only sessions automatically.
   • Pros: tight integration, often handles role transitions.
   • Cons: vendor-specific, may require configuration and version constraints.

Configuration considerations

• Read-only detection

  • Use explicit session/connection flags where possible (e.g., SQL SET TRANSACTION READ ONLY; connection attributes like application_name or read_only flag).
  • If inspecting SQL to determine read-only status, be careful: complex queries, functions, or user-defined procedures may perform writes even though they look read-only.

• Handling transactions

  • Long-running read transactions on replicas can block replica cleanup and replication apply processes. Encourage short-lived reads or snapshot-based reads.
  • Use appropriate transaction isolation levels. Snapshot or repeatable reads can be useful depending on consistency needs.

• Replication lag management

  • Monitor lag and implement policies: if a replica’s lag exceeds a threshold, remove it from read pool or route certain clients to primary.
  • Consider semi-synchronous replication for critical reads to limit data freshness windows.

• Consistency and correctness

  • Some applications require strong consistency for reads immediately following a write (read-your-writes). Provide mechanisms to route such reads to primary or use sticky sessions that ensure the client sees their own writes.
  • For eventual-consistency tolerant reads, prefer replicas for latency and throughput.

• Failover and role transitions

  • Automate promotion of replicas to primary and update ROR configuration accordingly.
  • Use health checks, fencing, and leader election (e.g., Patroni for PostgreSQL, etcd/consul-based coordination) to avoid split-brain scenarios.

• Load balancing and connection pooling

  • Maintain pools of connections per replica and balance queries to avoid hotspots.
  • Use proxy pooling to reduce connection overhead on DB servers.

Example configurations (patterns)

Note: shorter examples below illustrate common techniques without tying to a single database vendor.

1. Proxy-based routing with explicit read-only connections

• Clients open connections with an attribute or run “SET TRANSACTION READ ONLY” at start.
• Proxy recognizes attribute or command and routes to replica pool.

1. DNS endpoints per role

• write.db.example -> primary’s VIP or load balancer
• read.db.example -> load balancer in front of the replica pool
• On failover, update DNS or service registry quickly (use low TTLs or immediate service discovery updates).

1. DB-native Read Only Routing (e.g., SQL Server)

• Configure read-intent connection string parameter in application.
• Configure the cluster’s read-only routing list with replica preferences.

Operational best practices

• Capacity planning: size replicas for expected read workloads and overhead of replication apply.
• Test failovers and routing changes in staging before production.
• Observe replication lag, query latency, and error rates per replica; alert on thresholds.
• Version and schema management: ensure replicas are compatible during rolling upgrades and migrations.
• Security: ensure read-only endpoints have correct access controls and do not accidentally allow writes.
• Logging and tracing: include routing decisions in logs and correlate client requests to backend nodes for troubleshooting.
• Graceful degradation: implement fallback rules so critical reads can be served by the primary if no up-to-date replica is available.

Monitoring and metrics

Track:

• Replication lag (bytes/transactions/seconds)
• Replica apply rate
• Read latency per replica and overall
• Connection counts and pool saturation
• SQL error rates and retries
• Failover duration and success/failure rates

Use dashboards and alerts to detect slow replication, overloaded replicas, or misrouted write requests.

Common pitfalls

• Sending implicit writes to replicas due to misdetected read-only queries (e.g., functions that perform writes).
• Not handling read-your-write requirements, causing surprising stale reads.
• Long-running read transactions preventing replication cleanup, increasing disk usage and lag.
• Single-proxy bottleneck: if the routing proxy isn’t scaled/redundant, it becomes the HA weak point.
• DNS-based approaches with long TTLs slowing failover.

Example decision matrix

Summary

Read Only Routing is a practical and powerful tool for scaling read-heavy applications and improving resilience in high-availability architectures. The right approach depends on application consistency needs, operational discipline, and the database platform. Prioritize correct detection of read-only work, monitor replication lag, and automate failover and routing changes to maintain both performance and correctness.