Compare Scenarios

Migration Step 1

Both scenarios define a migration step at this stage. Event-Driven Analytics Pipeline: triggered by 'OLTP query performance degrading due to analytics query inte'. API Gateway Platform: triggered by 'PostgreSQL hot path query p99 > 2ms under sustained request '.

Migration Step 2

Both scenarios define a migration step at this stage. Event-Driven Analytics Pipeline: triggered by 'Sub-minute analytics latency required; ETL scheduling overhe'. API Gateway Platform: triggered by 'Rate limit enforcement allowing requests above the configure'.

Migration Step 3

API Gateway Platform has a defined migration; Event-Driven Analytics Pipeline does not at this stage.

pg_replication_slots shows growing pg_wal_lsn delta for CDC slot; PostgreSQL WAL directory growing faster than expected

Tier 1: CDC Slot Lag: Debezium / CDC connector not keeping up with write volume. Recommended evolution: Increase CDC connector parallelism; review filtered topics vs full-table CDC; monitor slot lag as a first-class SLA .

Kafka consumer group lag growing; analytics dashboards increasingly stale; consumer CPU and network I/O near ceiling

Tier 2: Kafka Consumer Lag: Insufficient consumer parallelism or insufficient Kafka partitions. Recommended evolution: Increase topic partition count (note: keyed messages lose ordering when partitions added); add consumer replicas up to partition count .

Redis command latency p99 > 0.5ms; gateway hot path p99 exceeding 2ms with Redis as the bottleneck (not upstream service); Redis CPU > 60% sustained; Lua script execution visible in SLOWLOG at > 0.1ms frequency

Tier 1: Redis Rate Limit Throughput: Single Redis instance processing all rate limit Lua scripts serially for all tenants across all gateway replicas. Recommended evolution: Shard rate limit counters across Redis Cluster nodes by hashing tenant_id to a cluster slot; this distributes Lua script execution across nodes proportional to tenant count; ensure tenant_id-keyed counters use hash tags ({tenant_id}) so all keys for a tenant land on the same slot and Lua scripts can operate on them atomically; do not use Redis Cluster without testing Lua script compatibility against your cluster topology first .

Tenant reports that rate limit increase takes > 30 seconds to take effect across all gateway replicas; configuration change audit log shows primary PostgreSQL write completing, but gateway replicas still routing to old backend endpoints beyond the expected cache TTL window

Tier 2: Configuration Propagation Latency: Local in-process cache TTL too long, or cache invalidation signal (Redis pub/sub or Kafka) not reaching all replicas. Recommended evolution: Implement configuration change notification via Redis pub/sub: PostgreSQL configuration writes also publish a config_invalidated event to a Redis channel; each gateway replica subscribes to this channel and flushes the affected local cache key on receipt; this reduces propagation latency from TTL duration to sub-second pub/sub delivery without eliminating the local cache that protects Redis from per-request configuration lookups .