JavaScript Runtime Production Guide: Node.js vs Deno vs Bun

Executive Summary

Critical Decision Point: Node.js remains the safest production choice despite performance disadvantages. Deno 2.0 offers security benefits with compatibility trade-offs. Bun provides significant speed improvements but introduces stability risks through segmentation faults.

Runtime Stability Assessment

Production Failure Modes

Runtime	Failure Type	Frequency	Recovery Method	Impact Severity
Node.js	Memory leaks, unhandled promises	Rare with proper coding	Restart service	Medium
Deno 2.0	Permission errors, npm compatibility issues	Moderate	Configuration adjustment	Low-Medium
Bun	Segmentation faults, core dumps	High under load	Container restart, no debugging	Critical

Critical Stability Warnings

Bun Production Risk: Segfaults occur unpredictably under concurrent load, especially with Redis clients and build processes. No debugging tools available for runtime crashes.

Deno Permission Debugging: Error messages provide insufficient context. Expect 2-4 hours debugging permission configurations due to trailing slash sensitivity and unclear error reporting.

Performance Benchmarks vs Real-World Impact

Synthetic Benchmarks (Misleading)

• Bun: 70k req/sec HTTP
• Deno: 40k req/sec HTTP
• Node.js: 25k req/sec HTTP

Production Reality (Database-Bound Applications)

• All Runtimes: 2-7k req/sec (PostgreSQL bottleneck)
• Performance Gain: 10-20% maximum in real applications

Development Productivity Impact

Task	Node.js	Deno 2.0	Bun
TypeScript compilation	45 seconds	8 seconds	6 seconds
Package installation	2 minutes	1.5 minutes	20 seconds
Docker build time	5 minutes	3 minutes	2 minutes

Security Configuration Requirements

Node.js Security Operational Overhead

• npm audit: Generates 80% false positives requiring triage
• Attack Surface: Full filesystem access by default
• Monitoring Tools: Complete ecosystem (Snyk, OWASP, DataDog)
• Supply Chain Defense: External tooling required

Deno Security Model Implementation

Effective Permissions Configuration:

--allow-net=api.internal.com,stripe.com
--allow-read=/app/config
--allow-write=/app/logs

Common Implementation Failure: Teams use --allow-all in development, then spend deployment day debugging production permissions.

Real Security Benefit: Stopped supply chain attacks where compromised packages attempted network access.

Bun Security Limitations

• No sandboxing: Malicious packages gain full system access
• Memory corruption vulnerabilities: Zig runtime bugs create potential exploits
• Limited security tooling: No mature scanning or monitoring solutions

Enterprise Adoption and Support

Production Usage Evidence

• Node.js: Netflix, PayPal, LinkedIn, Uber (mission-critical systems)
• Deno: Netlify edge functions, Supabase user functions (limited scope)
• Bun: Startups and development tooling only

Operational Support Quality

Runtime	Documentation	Community Support	Enterprise Tooling	Debugging Capability
Node.js	Complete	3M+ Stack Overflow answers	Full APM integration	Comprehensive diagnostics
Deno	Good	GitHub issues, limited	Partial APM support	Basic profiling
Bun	Basic	GitHub issues only	Minimal	Core dump analysis

Migration Decision Matrix

When to Migrate FROM Node.js

1. Lambda cold starts consuming significant AWS costs
2. TypeScript compilation exceeding CI timeout limits
3. Development feedback loops impacting productivity
4. Container size critical for deployment speed

When NOT to Migrate

• Existing production application working reliably
• Database bottlenecks limiting application performance
• Team lacks runtime expertise for debugging new issues
• Compliance requirements needing established audit patterns

Critical Implementation Warnings

Bun Production Deployment

Pre-Production Testing Requirements:

• Minimum 3 weeks load testing under production conditions
• Monitor for segfaults with actual concurrent workloads
• Test with all production dependencies, especially native modules
• Prepare fallback to Node.js containers

Known Crash Scenarios:

• Concurrent build processes (Issue #10843)
• Redis client connections under load (Issue #14145)
• Memory-intensive operations with garbage collection

Deno npm Compatibility Gotchas

Packages That Will Break:

• Any assuming __dirname exists
• Direct /dev/stdin readers
• Native modules expecting Node.js APIs
• CommonJS modules with complex require patterns

Debugging Permission Errors:

• Trailing slashes matter in path permissions
• Error messages don't specify which permission failed
• Development vs production permission differences cause deployment failures

Resource Requirements and Costs

Human Time Investment

Task	Node.js	Deno 2.0	Bun
Initial setup	1-2 days	3-5 days	2-3 days
Permission debugging	N/A	1-2 weeks	N/A
Production incident response	2-4 hours	4-8 hours	1-2 days (if segfault)
Team training	Minimal	Moderate	High (debugging skills)

Infrastructure Impact

• Container sizes: Node.js 150MB, Deno 80MB, Bun 50MB (before dependencies)
• Memory usage: Bun most efficient, Node.js predictable, Deno lightweight
• CPU overhead: Bun lowest, Deno moderate, Node.js highest

Compliance and Audit Considerations

SOC 2 Audit Implications

• Node.js: Established patterns, auditor familiarity, complete documentation
• Deno: Security model requires explanation, limited auditor knowledge
• Bun: Insufficient maturity for enterprise compliance requirements

Security Header and Monitoring

• Node.js: Helmet.js, complete APM integration, established patterns
• Deno: Basic security headers, limited monitoring integration
• Bun: Minimal security tooling, monitoring requires custom implementation

Recommended Implementation Strategy

Conservative Approach (Recommended)

1. Production services: Node.js 22.x LTS
2. Development tooling: Bun for speed (tests, builds)
3. Edge functions: Deno for security-sensitive microservices
4. Migration timeline: 6-12 months evaluation before production deployment

Risk-Tolerant Approach

1. New microservices: Deno with strict permission model
2. High-performance APIs: Bun with extensive monitoring and fallback plans
3. Gradual migration: One service at a time with production validation

Decision Criteria Checklist

• Database performance analysis completed
• Cold start costs quantified
• Team debugging expertise assessed
• Compliance requirements documented
• Fallback strategy prepared
• Load testing with production data completed

Critical Success Factors

1. Performance gains only matter if application is CPU-bound, not database-bound
2. Runtime stability more important than benchmark performance for production systems
3. Team expertise in debugging determines incident response effectiveness
4. Gradual adoption with fallback plans reduces migration risk
5. Compliance and audit requirements may dictate runtime choice regardless of performance