System requirements

Functional:

• Topic & Partition Management — create, configure, and scale topics/partitions.
• Producer API — publish messages with batching, retries, compression, and idempotence.
• Consumer API — subscribe, poll, and commit offsets; support consumer groups.
• Messaging Patterns — pub/sub, queue, request/reply, streaming.
• Delivery Guarantees — at-most-once, at-least-once, and idempotent/exactly-once.
• Replication & Failover — multi-replica quorum with automatic leader election.
• Retention & Compaction — time/size-based retention, log compaction by key.
• DLQ & Retries — dead-letter queues and configurable retry policies.
• Admin & Monitoring — APIs for topics, partitions, offsets, health; metrics & tracing.
• Security — TLS, authentication, authorization (ACLs/RBAC), audit logging.

Non-Functional:

• Throughput — handle millions of msgs/sec cluster-wide.
• Latency — <10 ms.
• Availability — 99.95% per region (multi-AZ replication).
• Durability — quorum commits guarantee no data loss.
• Scalability — horizontal scale via partitions/brokers.
• Recoverability — failover in <30s; full broker recovery in <15 min.
• Observability — metrics, logs, traces, consumer lag tracking.

API design

Define what APIs are expected from the system...

High-level design

Producers — publish messages to topics/queues.

Brokers — cluster of servers responsible for storing and serving messages (log-based storage).

Metadata/Coordination service — leader election, cluster membership, topic metadata (can be consensus-based: Raft/ZooKeeper/etcd).

Consumers — pull or receive messages; support consumer groups (competing consumers).

Coordinator/Controller — manages partitions, rebalances consumers, enforces quotas, controller leader.

Storage layer — append-only log files per partition with segmenting, compaction, retention policies.

Replicator — intra-cluster replication (sync/async) for high availability.

Delivery & offset manager — track per-consumer offsets/ACKs.

Admin API & Management UI — create topics, set retention, view status.

Observability stack — metrics, tracing, logging, alerting.

Clients SDKs — for major languages, supporting batching, compression, retries, transactions.

Detailed component design

Brokers — cluster of servers responsible for storing and serving messages (log-based storage).

A broker is a server in a distributed messaging cluster that:

• Accepts messages from producers
• Stores them durably on disk
• Sends them to consumers
• Replicates messages to other brokers for high availability
• Coordinates with other brokers to balance load and ensure failover

Database design

Defining the system data model early on will clarify how data will flow among different components of the system. Also you could draw an ER diagram using the diagramming tool to enhance your design...