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System Design for Platform Engineers

System design interviews for platform engineering roles focus on building reliable, scalable, and maintainable infrastructure. Unlike product-focused system design, you'll need to demonstrate deep understanding of distributed systems, infrastructure components, and operational excellence.

Platform Engineering System Design Focus Areas

What Makes Platform Engineering Design Different

  1. Infrastructure First: Design systems that other teams build upon
  2. Operational Excellence: Consider monitoring, debugging, and maintenance from day one
  3. Cost Optimization: Balance performance with resource efficiency
  4. Multi-tenancy: Design for multiple teams and applications
  5. Security and Compliance: Build security into the platform layer

System Design Interview Framework

1. Requirements Gathering (5-10 minutes)

Functional Requirements:

  • What services need to be supported?
  • What are the SLAs/SLOs?
  • What scale are we designing for?
  • What are the integration points?

Non-Functional Requirements:

  • Availability targets (99.9%, 99.99%?)
  • Latency requirements
  • Throughput expectations
  • Security and compliance needs
  • Cost constraints

Example Questions to Ask:

  • "What's our target availability?"
  • "What's the expected request rate?"
  • "What regions do we need to support?"
  • "What's our budget constraint?"
  • "What compliance requirements exist?"

2. Capacity Estimation (5 minutes)

Calculate:

  • Requests per second (RPS)
  • Storage requirements
  • Bandwidth needs
  • Server/container count
  • Cost estimates

Example Calculation:

Daily Active Users: 10M
Requests per user: 100/day
Total requests: 1B/day = 11,574 RPS
Peak traffic: 3x average = 34,722 RPS
With 20% headroom: 41,666 RPS needed

3. High-Level Design (10-15 minutes)

Start with major components:

  • Load balancers
  • API gateways
  • Service mesh
  • Data stores
  • Message queues
  • Caching layers
  • Monitoring stack

4. Detailed Design (15-20 minutes)

Deep dive into:

  • Data flow
  • API design
  • Database schema
  • Caching strategy
  • Security measures
  • Monitoring and alerting

5. Scale and Optimize (10 minutes)

Discuss:

  • Bottlenecks
  • Scaling strategies
  • Performance optimization
  • Cost optimization
  • Disaster recovery

Common Platform Engineering System Design Questions

1. Design a CI/CD Platform

Requirements:

  • Support 1000+ developers
  • Multiple programming languages
  • 10,000 builds/day
  • Artifact storage
  • Security scanning

Key Components:

┌─────────────┐     ┌──────────────┐     ┌──────────────┐
│ Git Repo │────▶│ Webhook/API │────▶│ Build Queue │
└─────────────┘ └──────────────┘ └──────────────┘


┌─────────────┐ ┌──────────────┐ ┌──────────────┐
│ Builders │◀────│ Scheduler │ │ Orchestrator │
└─────────────┘ └──────────────┘ └──────────────┘


┌─────────────┐ ┌──────────────┐ ┌──────────────┐
│ Artifacts │ │Test Results │ │ Deployment │
└─────────────┘ └──────────────┘ └──────────────┘

Design Considerations:

  • Build isolation (containers/VMs)
  • Queue management (Kafka/RabbitMQ)
  • Artifact storage (S3/Artifactory)
  • Secret management
  • Build caching
  • Monitoring and metrics

Resources:

2. Design a Container Orchestration Platform

Requirements:

  • Manage 10,000+ containers
  • Multi-region deployment
  • Auto-scaling
  • Service discovery
  • Zero-downtime deployments

Key Components:

┌─────────────────┐
│ Control Plane │
├─────────────────┤
│ • API Server │
│ • Scheduler │
│ • Controller │
│ • etcd │
└────────┬────────┘

┌────┴────┐
▼ ▼
┌────────┐ ┌────────┐
│ Node 1 │ │ Node 2 │
├────────┤ ├────────┤
│ Kubelet│ │ Kubelet│
│ Proxy │ │ Proxy │
│Runtime │ │Runtime │
└────────┘ └────────┘

Design Considerations:

  • Control plane high availability
  • Network policies and CNI
  • Storage orchestration
  • Resource allocation
  • Security policies
  • Multi-tenancy

Resources:

3. Design a Monitoring and Observability Platform

Requirements:

  • 1M metrics/second
  • 100TB logs/day
  • Distributed tracing
  • 99.9% availability
  • 30-day retention

Key Components:

┌─────────────┐     ┌──────────────┐     ┌──────────────┐
│ Agents │────▶│ Collectors │────▶│ Storage │
└─────────────┘ └──────────────┘ └──────────────┘
│ │
▼ ▼
┌──────────────┐ ┌──────────────┐
│ Querying │◀─────│ Aggregation │
└──────────────┘ └──────────────┘


┌──────────────┐
│Visualization │
└──────────────┘

Design Considerations:

  • Time-series database selection
  • Data retention policies
  • Sampling strategies
  • Query performance
  • Alert management
  • Data compression

Resources:

4. Design a Service Mesh

Requirements:

  • Handle 100K RPS
  • mTLS between services
  • Traffic management
  • Circuit breaking
  • Observability

Key Components:

┌────────────────┐
│ Control Plane │
├────────────────┤
│ • Config Mgmt │
│ • Cert Mgmt │
│ • Policy Engine│
└───────┬────────┘

┌───────▼────────┐
│ Data Plane │
├────────────────┤
│ Sidecar Proxies│
│ (Envoy) │
└────────────────┘

Resources:

5. Design a Multi-Region Database Platform

Requirements:

  • Global distribution
  • Strong consistency options
  • 99.99% availability
  • Automatic failover
  • Compliance with data residency

Key Components:

┌─────────────────────────────────────┐
│ Global Coordinator │
└─────────────┬───────────────────────┘

┌─────────┴─────────┬─────────────┐
▼ ▼ ▼
┌─────────┐ ┌─────────┐ ┌─────────┐
│Region 1 │ │Region 2 │ │Region 3 │
├─────────┤ ├─────────┤ ├─────────┤
│ Primary │◀────▶│ Replica │◀─▶│ Replica │
└─────────┘ └─────────┘ └─────────┘

Resources:

Platform-Specific Design Patterns

1. Reliability Patterns

Circuit Breaker

class CircuitBreaker:
def __init__(self, failure_threshold=5, recovery_timeout=60):
self.failure_threshold = failure_threshold
self.recovery_timeout = recovery_timeout
self.failure_count = 0
self.last_failure_time = None
self.state = 'CLOSED'

Bulkhead Pattern

  • Isolate resources to prevent cascade failures
  • Use connection pools with limits
  • Implement thread pool isolation

Resources:

2. Scalability Patterns

Horizontal Scaling

  • Stateless services
  • Shared-nothing architecture
  • Database sharding

Caching Strategies

  • Cache-aside
  • Write-through
  • Write-behind
  • Refresh-ahead

Resources:

3. Security Patterns

Zero Trust Architecture

  • Verify explicitly
  • Least privilege access
  • Assume breach

Secret Management

  • Centralized secret store
  • Dynamic secret generation
  • Secret rotation

Resources:

System Design Resources

Books

Online Courses

Practice Resources

Mock Interviews

Common Pitfalls to Avoid

  1. Over-engineering: Don't design for 1B users when asked for 1M
  2. Ignoring constraints: Always consider cost, team size, timeline
  3. Missing monitoring: Every design needs observability
  4. Forgetting security: Security should be built-in, not bolted-on
  5. Neglecting operations: Consider how the system will be maintained

Tips for Success

  1. Think out loud: Verbalize your thought process
  2. Start simple: Begin with a basic design and iterate
  3. Draw diagrams: Visual representations help communicate ideas
  4. Consider trade-offs: Every decision has pros and cons
  5. Ask questions: Clarify requirements and constraints
  6. Know your numbers: Memorize common latency and capacity figures

Latency Numbers Every Platform Engineer Should Know

L1 cache reference                           0.5 ns
Branch mispredict 5 ns
L2 cache reference 7 ns
Mutex lock/unlock 25 ns
Main memory reference 100 ns
Compress 1K bytes with Zippy 3,000 ns
Send 1K bytes over 1 Gbps network 10,000 ns
Read 4K randomly from SSD 150,000 ns
Read 1 MB sequentially from memory 250,000 ns
Round trip within same datacenter 500,000 ns
Read 1 MB sequentially from SSD 1,000,000 ns
Disk seek 10,000,000 ns
Read 1 MB sequentially from disk 20,000,000 ns
Send packet CA->Netherlands->CA 150,000,000 ns

Remember: System design for platform engineering is about building the foundation that enables other teams to succeed. Focus on reliability, scalability, and operational excellence in every design decision.