DBRaven

Migration Playbooks

Structured, deterministic operational playbooks for architecture evolution transitions. Each playbook derives readiness checklists, ordered stages, rollback decision points, and success criteria from the knowledge base, grounded in documented migration complexity, operational risk, and topology mutations.

HighMedium risk

Batch ETL → Streaming CDC Pipeline

Replacing nightly or hourly batch ETL jobs with a continuous CDC pipeline that captures database writes from the source WAL, publishes change events to Kafka, and delivers updates to analytics systems within seconds: at the cost of significantly higher operational complexity, schema evolution management, and permanent consumer lag monitoring.

Nightly Batch ETL JobsContinuous CDC Streaming Pipeline

Complex Rollback

HighHigh risk

Direct DB Queries → CQRS Read Models

Separating the write model (commands to a normalized database) from the read model (denormalized projections optimized per query pattern), enabling independent read/write scaling at the cost of read model staleness and projection maintenance complexity.

Unified Read/Write DatabaseCQRS with Separate Read Projections

Complex Rollback

Very HighHigh risk

Modular Monolith → Event-Driven Services

Decomposing a modular monolith into independently deployed services communicating over an event stream, introducing async processing boundaries and eventual consistency in exchange for independent deployability and fault isolation.

Modular MonolithEvent-Driven Services

Rarely Possible

Very HighHigh risk

Monolith → Microservices via Strangler Fig

Incrementally extracting domains from a monolith into independently deployable services behind an API gateway using the strangler fig pattern: routing specific endpoint sets to new services while the monolith handles the remainder, until the monolith is replaced.

Monolithic ApplicationMicroservices with API Gateway

Complex Rollback

MediumLow risk

Monolith → Modular Monolith

Introducing internal module boundaries within a monolith to reduce deploy coupling, improve team autonomy, and establish ownership domains: without the operational overhead of distributed services.

Monolithic ApplicationModular Monolith

Always Possible

MediumMedium risk

OLTP Analytics Queries → OLTP + OLAP Separation

Separating analytical workloads from the OLTP database by introducing a columnar store (ClickHouse, Snowflake) fed by CDC or export pipelines, eliminating analytical query interference with transactional performance and enabling sub-second analytics on multi-year datasets.

Unified OLTP + Analytics on PostgreSQLSeparated OLTP (PostgreSQL) + OLAP (ClickHouse/Snowflake)

Always Possible

HighHigh risk

PostgreSQL → Partitioned PostgreSQL

Introducing horizontal table partitioning within PostgreSQL to distribute write load, reduce per-partition index size, enable partition pruning on range queries, and push single-node storage limits without leaving the PostgreSQL operational model.

Single-Node PostgreSQLPartitioned PostgreSQL

Rarely Possible

HighMedium risk

RabbitMQ → Kafka

Migrating from RabbitMQ's broker-centric push model to Kafka's log-based pull model to gain event replay, independent consumer scaling, fan-out without queue proliferation, and durable event retention: at the cost of higher operational complexity.

RabbitMQ Message QueueKafka Event Stream

Complex Rollback

Very HighCritical risk

Read Replicas → Application-Level Sharding

Horizontally distributing a PostgreSQL dataset across N independent shards so that write throughput and storage scale linearly with shard count: permanently changing the data access model, eliminating cross-shard ACID transactions, and making the shard key the most consequential and irreversible architectural decision in the system.

PostgreSQL Primary with Read ReplicasHorizontally Sharded Database

Not Possible

MediumMedium risk

PostgreSQL Full-Text Search → Dedicated Search Engine

Migrating from PostgreSQL ILIKE or tsvector full-text search to a dedicated search engine (Elasticsearch or OpenSearch) to enable relevance ranking, fuzzy matching, faceted filters, and sub-100ms query latency at scale: at the cost of index synchronization lag, Elasticsearch cluster operational burden, and eventual consistency between source and search index.

PostgreSQL ILIKE/tsvector Full-Text SearchElasticsearch or OpenSearch Dedicated Index

Complex Rollback

MediumMedium risk

Self-Hosted Infrastructure → Managed Cloud Services

Replacing self-hosted PostgreSQL, Redis, and Kafka with managed equivalents (RDS, ElastiCache, MSK) to eliminate infrastructure maintenance overhead: automated backups, managed failover, and compliance certifications: at the cost of reduced configuration control, vendor lock-in, and higher cost at very large scale.

Self-Hosted PostgreSQL + Redis + KafkaRDS + ElastiCache + MSK (or equivalent)

Complex Rollback

MediumMedium risk

Single Cache Layer → Distributed Cache

Evolving from a single Redis node (or small cluster) to a distributed cache topology using consistent hashing, enabling horizontal memory scaling, geographic distribution, and cache isolation between workload types: at the cost of increased operational complexity and potential hotspot concentration.

Single Redis Node / Sentinel ClusterDistributed Redis Cluster (Consistent Hash Ring)

Complex Rollback

MediumMedium risk

Single PostgreSQL → Read/Write Split with Replicas

Introducing streaming replication and a read routing layer so that read-only queries are served from one or more standby replicas, relieving the primary of read load : at the cost of replication lag, dual connection pool management, and the permanent operational requirement to monitor replica health.

Single PostgreSQL PrimaryPostgreSQL Primary with Read Replicas and Routing Proxy

Complex Rollback

Very HighCritical risk

Single Region → Multi-Region Replication

Expanding from a single-region deployment to active-passive or active-active multi-region replication to reduce read latency for global users, increase availability during regional failures, and meet geographic data residency requirements : at the cost of replication lag, consistency complexity, and operational burden.

Single-Region DeploymentMulti-Region Replication

Rarely Possible

HighHigh risk

Synchronous Service Calls → Event-Driven Messaging

Replacing synchronous HTTP service dependencies with an event-driven message broker so that producers publish events and consumers subscribe independently: eliminating synchronous call failure cascades at the cost of eventual consistency, idempotent consumer design, and permanent operational overhead for broker and pipeline health.

Synchronous HTTP Service DependenciesEvent-Driven Architecture with Message Broker

Complex Rollback