BLUEPRINT #01Core Infrastructure
Design a Distributed Key-Value Store
Referenced Architecture Primitives (5)
Click any primitive to study its algorithmic deep dive10-Stage Structure:1. Requirementsβ2. Sizingβ3. Topologyβ4. Data Modelβ5. AWS Topologyβ6. Deep-Diveβ7. Failuresβ8. SRE Playbooks
1. Problem Statement & Scope
System Mission
Design a distributed, highly available, fault-tolerant Key-Value Store (similar to Amazon DynamoDB or Apache Cassandra) capable of storing petabytes of structured and unstructured key-value data with single-digit millisecond latency at massive global scale.
Functional Requirements
put(key, value): Atomically store or update a binary/JSON payload associated with a partition key.get(key): Retrieve the latest value associated with a partition key.delete(key): Remove a key-value record (supporting tombstones and TTL).- Tunable Consistency: Support configurable read/write consistency levels per request (
EVENTUAL,STRONG,ALL_QUORUM).
Non-Functional Requirements (SLAs/SLOs)
- Availability: uptime SLA (AP system under CAP Theorem with multi-AZ quorum).
- Latency: P99 Read latency , P99 Write latency .
- Durability: (11 9s) zero data loss guarantee via write-ahead logging and 3-AZ quorum replication.
- Scalability: Linear horizontal scalability to and petabytes of data.
2. Capacity & Scale Estimation
Traffic Calculations
- Total Registered Keys: 10 Billion Keys ().
- Average Item Size: (Key: , Value: ).
- Total Raw Storage:
- Storage with 3x Multi-AZ Replication:
- Query Throughput (QPS):
- Total Average QPS: ( Reads, Writes).
- Average Read QPS = , Average Write QPS = .
- Peak QPS (): (Read Peak: , Write Peak: ).
- Network Bandwidth:
- Ingress: .
- Egress: .
3. AWS-First High-Level Architecture
Interactive Architecture DiagramSynthesizing vector architecture diagram...
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