Real-Time Fastly Interview Questions [2025]

Fastly Core Concepts

1. What is the core function of Fastly in edge computing?

Fastly operates as an edge cloud platform, enabling developers to run custom code at the edge for low-latency processing. It accelerates content delivery, enhances security, and supports serverless functions, integrating with cloud-native observability to monitor performance in multi-cloud DevOps environments.

2. Why is Fastly chosen for real-time edge logic?

Fastly’s Varnish Configuration Language (VCL) enables instant edge code execution, minimizing latency for tasks like personalization or A/B testing. It supports CI/CD integration, ensuring rapid deployments and scalability for high-traffic applications in cloud-native architectures.

3. When should Fastly be used for CDN acceleration?

Use Fastly for CDN acceleration when applications demand dynamic caching, low-latency delivery, and custom routing. It’s ideal for e-commerce or media platforms, integrating with automated security workflows in DevOps pipelines for reliable performance.

4. Where does Fastly integrate in cloud-native setups?

• Edge Caching Layer: Stores content near users.
• Traffic Routing Engine: Optimizes cross-cloud paths.
• Security Gateway: Filters threats before origin.
• Load Balancer System: Distributes global traffic.
• Monitoring Integration Hub: Connects to observability tools.
• Serverless Compute Module: Executes edge logic.

5. Who manages Fastly configurations?

DevOps engineers, network specialists, and security teams manage Fastly configurations, setting VCL rules, caching policies, and security behaviors. They collaborate with platform teams to meet SLAs in cloud-native DevOps workflows.

6. Which protocols does Fastly support?

• HTTP/2 and HTTP/3: Supports multiplexed transfers.
• QUIC Protocol: Reduces connection setup time.
• TLS 1.3 Encryption: Secures data in transit.
• WebSocket Connections: Enables real-time applications.
• DNS over HTTPS: Enhances query privacy.
• gRPC Optimization: Boosts microservices communication.

7. How does Fastly optimize traffic routing?

Fastly uses real-time network intelligence to select optimal paths based on latency and congestion. Its Anycast IP and dynamic mapping ensure efficient delivery, minimizing delays in cloud-native applications.

8. What is Fastly’s Compute@Edge platform?

Compute@Edge enables serverless code execution at the edge using languages like Rust or JavaScript, reducing latency for dynamic tasks. It aligns with CI/CD pipelines for automated deployments in cloud-native setups.

• Language Support: Rust, JavaScript, Go, WebAssembly.
• Serverless Execution: Runs code without servers.
• Edge Location Deployment: Global low-latency processing.
• API Integration: Connects to backend services.
• Custom Runtime: Tailored for high-performance tasks.
• Monitoring and Logging: Tracks execution metrics.

9. Why use Fastly for API acceleration?

Fastly accelerates APIs by caching responses, compressing payloads, and optimizing routing. It reduces latency for microservices, supporting high-throughput applications in cloud-native DevOps environments.

10. When should you implement Fastly’s VCL?

Implement VCL for custom edge logic like header manipulation or conditional caching. It’s ideal for dynamic applications, integrating with CI/CD for automated updates in cloud-native systems.

11. Where are Fastly VCL scripts deployed?

• Fastly Control Center: Manages VCL configurations.
• Git Repositories: Enables version control.
• Terraform Configuration Files: Defines scripts as code.
• API Endpoint Calls: Programmatic script updates.
• CI/CD Pipeline Scripts: Automates VCL deployments.
• Kubernetes Manifests: Integrates with clusters.

12. Who develops Fastly VCL scripts?

DevOps engineers and developers write VCL scripts for edge customization, collaborating with security teams for compliance. They ensure performance in cloud-native DevOps workflows.

13. Which languages support Fastly Compute?

• Rust Programming Language: High-performance edge code.
• JavaScript ES Modules: Familiar web development syntax.
• Go Language Support: Efficient for backend logic.
• WebAssembly Binaries: Cross-language execution.
• AssemblyScript: TypeScript-like WebAssembly.
• Wasm Extensions: Custom runtime capabilities.

14. How does Fastly handle content caching?

Fastly manages caching with dynamic VCL rules, enabling conditional storage to minimize origin requests. It ensures low-latency delivery, supporting high-performance applications in cloud-native environments.

15. What is Fastly’s role in edge computing?

Fastly enables edge computing by executing custom code at edge locations, reducing latency for dynamic tasks. It supports serverless functions, aligning with edge deployments in cloud-native environments.

16. Why is Fastly’s Anycast network critical?

Fastly’s Anycast network routes traffic to the nearest edge server, minimizing latency and enhancing DDoS resilience. It ensures high availability and performance for cloud-native applications.

Fastly Configuration and VCL

17. Why use VCL for Fastly customization?

VCL provides fine-grained control over edge logic for routing, caching, and security, enabling tailored configurations. It integrates with CI/CD, supporting automated updates in cloud-native DevOps workflows.

18. When should you use Fastly’s Next-Gen WAF?

Use Next-Gen WAF for advanced threat protection, leveraging machine learning and rulesets. It’s ideal for APIs and web applications, integrating with automated security in DevOps pipelines.

19. Where are VCL scripts defined?

• Fastly Control Center: Manages VCL configurations.
• Git Repositories: Tracks script versions.
• Terraform Configuration Files: Defines scripts as code.
• API Endpoint Calls: Programmatic script updates.
• CI/CD Pipeline Scripts: Automates VCL deployments.
• Kubernetes Manifests: Integrates with clusters.

20. Who configures Fastly VCL?

DevOps engineers configure VCL, writing scripts for edge behaviors like caching or routing. They collaborate with security teams to ensure compliance in cloud-native environments.

21. Which VCL subroutines are key?

• vcl_recv: Processes incoming requests.
• vcl_hash: Determines caching keys.
• vcl_hit: Handles cache hits.
• vcl_miss: Manages cache misses.
• vcl_deliver: Prepares response delivery.
• vcl_error: Handles error conditions.

22. How do you test VCL scripts?

Test VCL scripts in Fastly’s staging environment using tools like curl to simulate traffic. Validate logic, monitor metrics, and deploy via CI/CD for reliability in cloud-native ecosystems.

23. Why use Fastly for content personalization?

Fastly personalizes content at the edge using VCL to tailor responses based on user data, reducing origin load. It enhances user experiences in cloud-native e-commerce applications.

24. When would you use Fastly’s Image Optimizer?

Use Image Optimizer for automatic resizing and format conversion, reducing payload sizes. It’s ideal for mobile sites, integrating with CI/CD for performance tuning.

25. Where are image configs defined?

• Fastly Control Center: Sets optimization rules.
• Terraform Configuration Files: Manages as code.
• Git Repositories: Tracks image policy versions.
• API Endpoint Calls: Programmatic config updates.
• CI/CD Pipeline Scripts: Automates image deployments.
• Kubernetes Manifests: Integrates with clusters.

26. Who optimizes image delivery?

Performance engineers optimize image delivery, tuning resizing and caching rules. They collaborate with DevOps to ensure fast loading in cloud-native media workflows.

27. Which metrics track image performance?

• image_requests_total: Counts image requests.
• image_optimization_savings: Measures bandwidth reduction.
• image_latency_seconds: Tracks delivery time.
• image_cache_hit_ratio: Monitors caching efficiency.
• image_error_rate: Logs optimization failures.
• image_traffic_by_format: Analyzes format distribution.

28. How do you scale image optimization?

Scale image optimization by configuring rules for multiple formats, enabling edge caching, and load-testing in staging. Monitor metrics and update via CI/CD for performance.

29. What is the impact of poor image optimization?

Poor image optimization increases load times and bandwidth usage, degrading user experience. Tune settings, test in staging, and update via Git for smooth delivery in cloud-native workflows.

30. Why use Fastly’s real-time logging?

Real-time logging provides instant visibility into edge traffic, enabling rapid issue detection. It integrates with observability tools, supporting proactive monitoring in cloud-native DevOps environments.

31. When should you analyze Fastly logs?

Analyze logs during performance degradation or security incidents to identify issues. It ensures optimal user experiences, aligning with CI/CD monitoring in DevOps workflows.

32. Where are Fastly logs stored?

• Fastly Log Delivery: Streams to SIEMs.
• External Log Aggregators: Integrates with Splunk.
• Prometheus Metrics Endpoints: Exposes performance data.
• Grafana Dashboard Visuals: Displays real-time logs.
• Kubernetes Log Systems: Captures containerized logs.
• Cloud Logging Services: Centralizes for analysis.

Fastly Security and WAF

33. Why is Fastly’s Next-Gen WAF effective?

Next-Gen WAF protects against OWASP threats using machine learning and rulesets, filtering malicious traffic at the edge. It ensures secure applications in cloud-native environments.

34. When should you enable Bot Management?

Enable Bot Management for sites facing scraping or automated abuse, using behavioral analysis to block malicious bots. It protects resources, integrating with DevOps security pipelines.

35. Where are WAF rules configured?

• Fastly Control Center: Defines managed rulesets.
• Terraform Configuration Files: Manages rules as code.
• API Endpoint Calls: Programmatic rule updates.
• Git Repositories: Tracks rule versions.
• CI/CD Pipeline Scripts: Automates rule deployments.
• Kubernetes Manifests: Integrates with clusters.

36. Who configures Fastly WAF rules?

Security engineers configure WAF rules, defining protections for OWASP threats. They collaborate with DevOps to ensure compliance in cloud-native architectures.

37. Which threats does Next-Gen WAF block?

• SQL Injection Attacks: Prevents database exploits.
• Cross-Site Scripting: Blocks script injections.
• File Inclusion Exploits: Stops unauthorized access.
• Cross-Site Request Forgery: Mitigates CSRF attacks.
• Bot-Driven Abuses: Filters automated traffic.
• Zero-Day Vulnerabilities: Uses behavioral detection.

38. How do you test WAF rule effectiveness?

Test WAF rules using penetration testing tools and simulated attacks in staging. Validate with CI/CD pipelines to ensure protection without blocking legitimate traffic.

39. What is Fastly’s role in DDoS protection?

Fastly mitigates DDoS by filtering traffic at the edge, using rate limiting and IP reputation. It ensures uptime, integrating with DevOps for automated security responses.

40. Why use Fastly for API security?

Fastly secures APIs with rate limiting, WAF rules, and threat intelligence, preventing abuse. It ensures reliable delivery for microservices in cloud-native DevOps environments.

41. When should you use Fastly’s Shielding?

Use Shielding to reduce origin server load by caching at a parent server. It’s ideal for high-traffic sites, integrating with DevOps for performance optimization.

42. Where are Shielding configs defined?

• Fastly Control Center: Sets parent shielding.
• Terraform Configuration Files: Manages as code.
• Git Repositories: Tracks shielding policies.
• API Endpoint Calls: Programmatic config updates.
• CI/CD Pipeline Scripts: Automates shielding deployments.
• Kubernetes Manifests: Integrates with clusters.

43. Who optimizes shielding performance?

Performance engineers optimize shielding, tuning parent servers and caching rules. They collaborate with DevOps to ensure low-latency delivery in secure environments.

44. Which metrics track shielding effectiveness?

• shielding_cache_hit_ratio: Measures parent cache efficiency.
• shielding_origin_requests_total: Counts origin calls.
• shielding_latency_seconds: Tracks delivery time.
• shielding_error_rate: Logs shielding failures.
• shielding_traffic_volume: Analyzes data flow.
• shielding_parent_uptime: Monitors parent availability.

45. How do you scale shielding?

Scale shielding by configuring multiple parent servers, enabling edge caching, and load-testing in staging. Monitor metrics and update via CI/CD for performance.

46. What is the impact of misconfigured shielding?

Misconfigured shielding increases origin load, slowing delivery. Tune settings, test in staging, and update via Git to ensure reliability in cloud-native applications.

47. Why implement rate limiting in Fastly?

Rate limiting prevents API abuse and DDoS attacks by throttling requests based on IP or token. It ensures resource availability for high-traffic cloud-native applications.

48. When do you adjust rate limiting thresholds?

Adjust thresholds during traffic surges or false positives to balance access and security. Test in staging and deploy via CI/CD for optimized cloud-native workflows.

49. Where are threat intelligence feeds integrated?

• Fastly Control Center: Imports feeds for rules.
• External SIEM Systems: Correlates with security data.
• Prometheus Metrics Endpoints: Exposes threat metrics.
• Grafana Dashboard Visuals: Displays real-time threats.
• Cloud Logging Services: Centralizes for analysis.
• API Query Responses: Retrieves feed updates.

50. Who monitors Fastly security events?

Security operations teams monitor events, analyzing logs and metrics for threats. They integrate with DevOps for automated responses in real-time DevOps environments.

51. Which metrics track security performance?

• security_requests_blocked_total: Counts blocked threats.
• security_rule_triggered_count: Tracks rule activations.
• security_latency_seconds: Measures rule processing.
• security_bot_score_distribution: Analyzes bot detection.
• security_ip_blocked_total: Logs blocked IPs.
• security_rate_limit_exceeded: Tracks throttling events.

52. How do you debug security false positives?

Debug false positives by reviewing logs, adjusting rule thresholds, and testing in staging. Update via Git and CI/CD to balance security and usability in applications.

Fastly Performance Optimization

53. Why monitor cache hit ratios?

Monitoring cache hit ratios ensures efficient content delivery, reducing origin load. It identifies optimization opportunities, aligning with DevOps for high-performance applications.

54. When should you purge Fastly’s cache?

Purge cache when updating content or fixing corrupted assets. Use selective purges for URLs or full purges for sites, ensuring freshness in high-traffic applications.

55. Where are cache policies defined?

• Fastly Control Center: Sets cache levels.
• Terraform Configuration Files: Manages as code.
• Git Repositories: Tracks policy versions.
• API Endpoint Calls: Programmatic cache updates.
• CI/CD Pipeline Scripts: Automates cache policies.
• Kubernetes Manifests: Integrates with clusters.

56. Who tunes Fastly cache settings?

Performance engineers tune cache settings, analyzing hit ratios and latency metrics. They collaborate with DevOps to meet SLAs in cloud-native environments.

57. Which behaviors improve caching performance?

• Compression Behaviors: Reduces payload sizes.
• Caching TTL Settings: Controls content expiry.
• Routing Optimizations: Selects fastest paths.
• Header Manipulation: Customizes response headers.
• Origin Shield: Protects origin servers.
• Error Handling: Manages response codes.

These behaviors optimize cache efficiency, reducing latency and origin load in cloud-native workflows.

58. How do you debug cache misses?

Debug cache misses by checking headers, reviewing VCL rules, and analyzing logs. Test configurations in staging and update via Git to optimize hit ratios in deployments.

59. What is Fastly’s Real User Monitoring (RUM)?

RUM tracks real-user performance metrics like page load times, identifying bottlenecks. It optimizes user experiences, integrating with DevOps for cloud-native application monitoring.

60. Why integrate RUM with CI/CD?

Integrate RUM with CI/CD to track performance changes in builds, alerting on regressions. It ensures continuous optimization in cloud-native DevOps workflows.

61. When should you analyze RUM metrics?

Analyze RUM metrics during performance issues or post-deployment to detect regressions. It ensures optimal user experiences, aligning with CI/CD monitoring in DevOps.

62. Where are RUM data analyzed?

• Fastly Control Center: Displays performance dashboards.
• External BI Tools: Integrates with Tableau.
• Prometheus Metrics Endpoints: Exposes RUM data.
• Grafana Visualization Panels: Shows real-time metrics.
• Cloud Logging Services: Centralizes for analysis.
• API Query Responses: Retrieves custom data.

63. Who analyzes RUM metrics?

Performance analysts review RUM metrics to identify bottlenecks and user issues, collaborating with DevOps to optimize applications in cloud-native environments.

64. Which RUM features aid optimization?

• Real-User Monitoring: Tracks actual experiences.
• Session Replay Tools: Replays user sessions.
• Performance Scoring: Grades application speed.
• Anomaly Alerting: Notifies on degradation.
• RUM Integration: Combines with synthetic tests.
• Custom Dashboards: Tailors to team needs.

These features enhance performance analysis, supporting secure DevOps practices.

65. How do you handle cache purge delays?

Handle purge delays by using API-driven purges, monitoring status, and testing in staging. Optimize purge scope and update via Git to ensure freshness in deployments.

66. What is the impact of low cache hit ratios?

Low cache hit ratios increase origin load, slowing delivery and raising costs. Tune policies, test in staging, and deploy via CI/CD to improve performance.

Fastly Load Balancing and Traffic Management

67. Why use Fastly for load balancing?

Fastly’s load balancing distributes traffic across origins, ensuring uptime and performance. It supports health checks and failover, optimizing resources in cloud-native applications.

68. When do you enable geo-steering?

Enable geo-steering to route traffic based on user location, reducing latency. It’s ideal for global applications, integrating with CI/CD for automated policy updates.

69. Where are load balancing rules defined?

• Fastly Control Center: Configures load balancers.
• Terraform Configuration Files: Manages as code.
• API Endpoint Calls: Programmatic rule updates.
• Git Repositories: Tracks rule versions.
• CI/CD Pipeline Scripts: Automates balancer configs.
• Kubernetes Manifests: Integrates with clusters.

70. Who configures load balancing policies?

Network engineers configure load balancing, setting health checks and failover rules. They align with DevOps to ensure scalability in DevOps configurations.

71. Which settings enhance load balancing?

• Health Check Intervals: Monitors server availability.
• Failover Pool Configs: Routes to backup servers.
• Geo-Steering Policies: Optimizes by location.
• Session Affinity: Maintains user sessions.
• Weighted Traffic: Balances load dynamically.
• Proximity Routing: Minimizes latency.

72. How do you debug load balancing issues?

Debug load balancing by analyzing health check logs, verifying server pools, and testing in staging. Update rules via Git and CI/CD for reliable deployments.

73. What is Fastly’s Global Traffic Management?

Global Traffic Management optimizes routing across origins, ensuring low-latency delivery. It supports high-availability applications, aligning with cloud-native DevOps strategies.

74. Why monitor load balancing metrics?

Monitoring load balancing metrics ensures optimal traffic distribution and uptime. It detects failover issues, aligning with DevOps for reliable cloud-native applications.

75. When do you adjust load balancing rules?

Adjust rules during traffic spikes or server failures to optimize distribution. Test in staging and deploy via CI/CD to ensure performance in cloud-native workflows.

76. Where are load balancing logs stored?

• Fastly Log Delivery: Sends to SIEMs.
• External Log Aggregators: Integrates with Splunk.
• Prometheus Metrics Endpoints: Exposes traffic data.
• Grafana Dashboard Visuals: Displays real-time logs.
• Kubernetes Log Systems: Captures containerized logs.
• Cloud Logging Services: Centralizes for analysis.

77. Who optimizes load balancing performance?

Network engineers optimize load balancing, tuning health checks and weights. They monitor metrics, ensuring efficient traffic flow in DevOps workflows.

78. Which metrics track load balancing?

• load_balancer_requests_total: Counts traffic volume.
• load_balancer_latency_seconds: Measures response times.
• load_balancer_failover_events: Tracks failover triggers.
• load_balancer_healthcheck_failures: Logs server issues.
• load_balancer_traffic_by_pool: Analyzes pool distribution.
• load_balancer_geo_steering: Monitors location-based routing.

79. How do you scale load balancing?

Scale load balancing by adding server pools, tuning weights, and load-testing in staging. Monitor metrics and update via CI/CD for performance in high-traffic scenarios.

80. What is the impact of misconfigured load balancers?

Misconfigured load balancers cause uneven traffic or downtime, degrading performance. Review configs, test in staging, and update via Git for reliability.

Fastly Video and Media Delivery

81. Why use Fastly for video delivery?

Fastly optimizes video with adaptive bitrate, edge caching, and global routing, ensuring smooth playback and reduced buffering in cloud-native media applications.

82. When do you use Adaptive Media Delivery?

Use Adaptive Media Delivery for dynamic video streaming, adjusting quality based on bandwidth. It’s ideal for live events, integrating with CI/CD for automated scaling.

83. Where are video configs defined?

• Fastly Control Center: Configures streaming behaviors.
• Terraform Configuration Files: Manages as code.
• Git Repositories: Tracks video policy versions.
• API Endpoint Calls: Programmatic config updates.
• CI/CD Pipeline Scripts: Automates video deployments.
• Kubernetes Manifests: Integrates with clusters.

84. Who optimizes video delivery?

Media engineers optimize video delivery, tuning bitrate and caching rules. They collaborate with DevOps to ensure smooth streaming in cloud-native media workflows.

85. Which metrics track video performance?

• video_bitrate_average: Measures quality levels.
• video_buffering_events: Logs buffering incidents.
• video_startup_time: Tracks initial load delays.
• video_traffic_by_quality: Analyzes resolution distribution.
• video_error_rate: Monitors playback failures.
• video_cache_hit_ratio: Tracks edge caching efficiency.

These metrics ensure optimal video delivery in scalable DevOps environments.

86. How do you scale video streaming?

Scale video streaming by adjusting bitrate ladders, enabling edge caching, and load-testing in staging. Monitor metrics and update via CI/CD for performance.

87. What is the impact of poor video optimization?

Poor optimization causes buffering and high abandonment rates, degrading user experience. Tune settings, test in staging, and update via Git for smooth delivery.

88. Why use Fastly for live streaming?

Fastly supports live streaming with low-latency delivery, adaptive bitrate, and global edge caching. It ensures reliable broadcasts for cloud-native media applications.

89. When do you configure adaptive bitrate?

Configure adaptive bitrate for variable network conditions, ensuring smooth playback. It’s critical for live events, aligning with CI/CD for automated scaling.

90. Where are live streaming logs stored?

• Fastly Log Delivery: Sends to SIEMs.
• External Log Aggregators: Integrates with Splunk.
• Prometheus Metrics Endpoints: Exposes streaming data.
• Grafana Dashboard Visuals: Displays real-time logs.
• Kubernetes Log Systems: Captures containerized logs.
• Cloud Logging Services: Centralizes for analysis.

Fastly Troubleshooting and Best Practices

91. Why monitor Fastly metrics in production?

Monitoring metrics detects anomalies like cache misses or attack spikes, ensuring performance and security. It supports proactive resolution in cloud-native DevOps environments.

92. When should you escalate Fastly issues?

Escalate issues when metrics show persistent latency, cache misses, or security breaches. Use incident tools and CI/CD alerts for quick resolution in cloud-native DevOps.

93. Where are Fastly logs analyzed?

• Fastly Log Delivery: Sends to SIEMs.
• External Log Aggregators: Integrates with Splunk.
• Prometheus Metrics Endpoints: Exposes performance data.
• Grafana Dashboard Visuals: Displays real-time logs.
• Kubernetes Log Systems: Captures containerized logs.
• Cloud Logging Services: Centralizes for analysis.

94. Who troubleshoots Fastly issues?

SREs troubleshoot issues, analyzing latency and security metrics. They collaborate with DevOps to update configs via Git, ensuring optimal delivery in cloud-native systems.

95. Which tools aid Fastly troubleshooting?

• Fastly Diagnostic Tools: Tests connectivity, DNS.
• Prometheus and Grafana: Visualizes performance metrics.
• Terraform Plan Outputs: Validates config changes.
• CI/CD Pipeline Logs: Tracks deployment issues.
• Splunk Log Analysis: Correlates security events.
• Fastly Log Delivery: Streams logs to SIEMs.

96. How do you handle SSL/TLS issues?

Handle SSL/TLS issues by verifying certificates, enabling HSTS, and checking cipher suites. Test in staging and update via CI/CD for secure connections in deployments.

97. What are best practices for Fastly configs?

Automate configs with Terraform, test in staging, and monitor metrics. Use Git for version control and CI/CD for updates, ensuring reliability in cloud-native systems.

98. Why use canary deployments with Fastly?

Canary deployments test VCL rules or cache settings on partial traffic, minimizing risks. They ensure stable rollouts, aligning with DevOps for cloud-native applications.

99. When should you rollback Fastly changes?

Rollback changes when metrics show degraded performance or security issues post-deployment. Use Git to revert configs and CI/CD to redeploy for stability in DevOps certification workflows.

100. How does Fastly support microservices?

Fastly supports microservices with WAF rules, load balancing, and caching, ensuring low-latency communication. It integrates with CI/CD for scalable, secure cloud-native deployments.

101. Why integrate Fastly with observability tools?

Integrating Fastly with observability tools provides end-to-end visibility, correlating edge metrics with backend performance. It supports proactive issue resolution in DevOps workflows.

102. What is the impact of misconfigured Fastly services?

Misconfigured services cause performance degradation or security risks, impacting user experience. Review configs, test in staging, and update via Git to ensure reliability in real-time DevOps.