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Session 4: Production MCP Deployment - Test Solutions

📝 Multiple Choice Test - Session 4

Question 1: What is the primary difference between development and production MCP servers?

A) Production servers are slower than development servers
B) Production servers use different protocols
C) Production servers only work with specific LLMs
D) Production servers require observability, scalability, and reliability ✅

Explanation: Production environments require comprehensive observability (metrics, logs, traces), scalability to handle varying loads, and reliability through error handling and fault tolerance.

Question 2: What is the main advantage of containerizing MCP servers with Docker?

A) Improved performance
B) Better security by default
C) Automatic scaling capabilities
D) Consistent environments across development and production ✅

Explanation: Docker containerization ensures consistent environments across development, staging, and production, eliminating "works on my machine" problems and simplifying deployment.

Question 3: Which Prometheus metric type is best suited for tracking response times?

A) Histogram ✅
B) Counter
C) Gauge
D) Summary

Explanation: Histogram metrics are ideal for tracking response times as they measure distributions and provide percentiles, helping identify performance patterns and outliers.

Question 4: What information should a comprehensive health check endpoint provide?

A) Database connectivity and dependent services status ✅
B) Only HTTP 200 status
C) Server uptime only
D) Current server load only

Explanation: Health checks should verify all critical dependencies including database connectivity, external service availability, and resource utilization to provide comprehensive system status.

Question 5: What metric is most important for auto-scaling MCP servers?

A) CPU utilization only
B) Network bandwidth only
C) Request rate combined with response time ✅
D) Memory usage only

Explanation: Request rate combined with response time provides the best indicator of actual user demand and system performance, enabling more accurate scaling decisions than resource metrics alone.

Question 6: What type of caching is most effective for MCP server responses?

A) File-based caching
B) In-memory caching only
C) Redis distributed caching with TTL expiration ✅
D) Database-level caching only

Explanation: Redis distributed caching with TTL expiration provides fast access, data persistence, and automatic cleanup while supporting multiple server instances in production environments.

Question 7: When should a circuit breaker transition to the "open" state?

A) When the server starts up
B) When response times are slightly elevated
C) When memory usage is high
D) When error rates exceed the configured threshold ✅

Explanation: Circuit breakers open when error rates exceed configured thresholds, preventing cascade failures by temporarily stopping requests to failing services until they recover.

Question 8: What is the recommended approach for deploying MCP servers through CI/CD?

A) Direct deployment to production
B) Blue-green deployment with health checks ✅
C) Manual deployment verification
D) Rolling updates without testing

Explanation: Blue-green deployment with health checks ensures zero-downtime deployments by maintaining two identical environments and switching traffic only after verifying the new version's health.

Question 9: Which monitoring approach provides the most comprehensive observability?

A) The three pillars: metrics, logs, and distributed tracing ✅
B) Logs only
C) Metrics only
D) Health checks only

Explanation: The three pillars of observability (metrics, logs, and distributed tracing) provide comprehensive system visibility, enabling effective troubleshooting and performance optimization.

Question 10: What is the primary benefit of using Terraform for MCP server infrastructure?

A) Lower costs
B) Faster deployment
C) Reproducible and version-controlled infrastructure ✅
D) Improved security

Explanation: Infrastructure as Code with Terraform ensures reproducible, version-controlled infrastructure that can be reviewed, tested, and deployed consistently across environments.


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