Developer Platform Observability
Full-stack monitoring for the platform serving 100M+ developers. APM across Ruby on Rails services, real user monitoring for GitHub.com, and custom dashboards for engineering productivity metrics.
Live Streaming Observability
Real-time monitoring for game-day streaming serving millions of concurrent viewers. Traffic spike preparation, video quality metrics, multi-CDN monitoring, and broadcast operations dashboards.
Entertainment Platform Monitoring
Observability for Xfinity streaming and connectivity services. Cross-team standards for 1,000+ engineers, customer experience metrics, and infrastructure monitoring at enterprise scale.
Omnichannel Retail Observability
E-commerce platform monitoring connecting online and in-store systems. Peak season readiness, mobile app performance, and inventory system health monitoring.
What New Relic Engineers Actually Build
Before writing your job description, understand what New Relic observability work looks like at different companies. Here are real examples from industry leaders:
Developer Tools & Platforms
GitHub relies on New Relic for monitoring their developer platform serving 100M+ developers. Their observability engineers handle:
- APM tracing across their Ruby on Rails monolith and microservices
- Custom dashboards for pull request and CI/CD pipeline performance
- Real user monitoring (RUM) for GitHub.com performance insights
- Alerting strategies that balance coverage with engineer sanity
Media & Entertainment
Major League Baseball (MLB) uses New Relic to monitor their streaming platform during game days. Their team builds:
- Traffic spike preparation for playoff games and World Series
- Video streaming quality metrics (buffering, bitrate, latency)
- Multi-CDN monitoring for global content delivery
- Real-time dashboards for broadcast operations teams
Comcast monitors their entertainment and connectivity platforms:
- Xfinity streaming app performance across devices
- Network infrastructure monitoring at massive scale
- Customer experience metrics tied to business KPIs
- Cross-team observability standards for 1,000+ engineers
E-Commerce & Retail
REI uses New Relic to monitor their e-commerce platform:
- Peak season readiness for outdoor gear sales (holiday, summer)
- Omnichannel monitoring connecting online and in-store systems
- Mobile app performance tracking for the REI Co-op app
- Inventory system health for real-time availability
Understanding New Relic's Platform Scope
New Relic ONE: The Unified Platform
New Relic has consolidated its products into New Relic ONE, a unified observability platform with these core capabilities:
| Capability | What It Does | Key Use Case |
|---|---|---|
| APM | Code-level performance monitoring | "Which endpoint is slow and why?" |
| Infrastructure | Server, container, and cloud metrics | "Are our hosts healthy?" |
| Logs | Centralized log management | "What happened at 3:14 AM?" |
| Browser | Real user monitoring for web apps | "How fast is the site for actual users?" |
| Mobile | iOS/Android app performance | "Why are users experiencing crashes?" |
| Synthetics | Proactive availability testing | "Is checkout working right now?" |
| Distributed Tracing | Request flow across services | "Where's the bottleneck in this transaction?" |
| Errors Inbox | Error grouping and triage | "What's the highest-impact error to fix?" |
New Relic vs. Legacy APM Mindset
A critical distinction for hiring: traditional APM focused on server metrics (CPU, memory, response times). Modern observability, as New Relic now positions it, connects application performance to business outcomes and user experience.
Traditional APM Engineer:
- Monitors server health and response times
- Creates dashboards for infrastructure metrics
- Alerts on threshold violations
Modern Observability Engineer:
- Connects technical metrics to business KPIs
- Implements SLOs tied to customer experience
- Uses distributed tracing to understand complex systems
- Thinks about cost and data retention strategies
When hiring, look for the modern mindset regardless of specific tool experience.
Skills by Experience Level
Junior New Relic Engineer
- Installs and configures New Relic agents (APM, infrastructure)
- Creates basic dashboards from existing metrics
- Sets up threshold-based alerts
- Uses the UI to investigate performance issues
- Understands basic NRQL (New Relic Query Language)
Mid-Level New Relic Engineer
- Designs monitoring strategies for new services
- Implements distributed tracing with proper context propagation
- Creates effective alerting with minimal noise
- Builds custom attributes and events for business metrics
- Manages costs through data retention and cardinality
- Implements synthetic monitors for critical workflows
Senior New Relic Engineer
- Architects full-stack observability for complex systems
- Establishes SLI/SLO frameworks with service level management
- Optimizes New Relic spend while maintaining visibility
- Leads incident response using observability data
- Implements New Relic-as-Code with Terraform
- Evaluates New Relic vs. alternatives for specific use cases
- Mentors teams on observability best practices
New Relic vs. Datadog vs. Open Source
This is one of the most common questions in observability hiring. Here's an honest comparison:
New Relic vs. Datadog
| Aspect | New Relic | Datadog |
|---|---|---|
| Pricing model | Data ingestion + users | Per-host + per-feature |
| Pricing predictability | Easier to estimate | Can have billing surprises |
| APM maturity | Longer track record | Caught up significantly |
| Kubernetes native | Pixie integration (newer) | More established |
| AI capabilities | Applied Intelligence | Watchdog |
| Free tier | Generous (100GB/month) | Limited |
| UI/UX | Recently modernized | Generally preferred |
When New Relic fits better:
- Budget-conscious teams (free tier, predictable pricing)
- Organizations already invested in New Relic ecosystem
- Teams prioritizing APM depth over breadth
- Environments with highly variable infrastructure
When Datadog fits better:
- Kubernetes-heavy environments
- Teams wanting unified logs + metrics + APM + security
- Organizations prioritizing UI polish and developer experience
- Companies where per-host pricing works well
New Relic vs. Open Source (Prometheus + Grafana + Jaeger)
| Aspect | New Relic | Open Source Stack |
|---|---|---|
| Setup time | Hours | Days to weeks |
| Operational burden | Managed by New Relic | Your team manages it |
| Cost model | Consumption-based | Infrastructure + engineering time |
| Cost at scale | Predictable but can grow | Lower floor, engineering ceiling |
| Correlation | Built-in across pillars | Manual integration |
| Vendor lock-in | Yes (but better than some) | Open standards |
| Customization | Platform-bound | Fully customizable |
For hiring decisions: Candidates with either background can transfer skills. New Relic experience indicates enterprise observability exposure; open-source experience shows self-reliance and customization skills. Both are valuable.
Recruiter's Cheat Sheet: Spotting Great Candidates
Conversation Starters That Reveal Skill Level
| Question | Junior Answer | Senior Answer |
|---|---|---|
| "How do you approach setting up monitoring for a new service?" | "Install the agent and create a dashboard" | "Start with SLOs based on user expectations, instrument critical paths, set up alerts that minimize noise, then add dashboards for debugging" |
| "Tell me about reducing alert noise" | Generic or vague | "Reduced on-call pages 50% by switching from threshold to baseline alerts, implementing alert conditions on error budgets, and consolidating redundant monitors" |
| "How do you handle New Relic costs?" | "That's a finance problem" | "Monitor data ingest by source, implement sampling for high-cardinality data, use drop rules for low-value logs, and review retention policies quarterly" |
Resume Signals That Matter
✅ Look for:
- Specific scale metrics ("Monitored 200+ services, 10M+ transactions daily")
- Incident response experience ("Reduced MTTR from 30 min to 10 min")
- Cost optimization ("Reduced New Relic spend 35% while expanding coverage")
- NRQL expertise for custom analysis
- Integration experience (Terraform, PagerDuty, CI/CD)
🚫 Be skeptical of:
- Only lists "New Relic" without context
- Claims expertise in New Relic AND Datadog AND Splunk AND Dynatrace (tool collectors)
- No mention of incident response or production debugging
- "5+ years New Relic experience" without specific implementations
Portfolio Red Flags
- Can't explain their alerting philosophy
- Never been part of incident response
- Dashboards are metric dumps without clear purpose
- No understanding of New Relic's pricing model
Common Hiring Mistakes
1. Requiring Specific APM Platform Experience
New Relic, Datadog, and Dynatrace share 80% of concepts. Someone with 3 years of Datadog experience becomes productive in New Relic within 2-3 weeks. Hire for observability philosophy, not specific platforms.
Better approach: Ask about monitoring principles, incident response methodology, and how they've improved system visibility—regardless of which tool they used.
2. Ignoring the Pricing Awareness Gap
New Relic's consumption-based pricing means costs scale with data volume. Engineers who don't understand this create monitoring strategies that blow budgets. Senior hires should understand:
- Data ingest costs per GB
- User-based pricing tiers
- When to sample vs. collect everything
- Retention policy trade-offs
3. Conflating APM with Full-Stack Observability
Some candidates only know traditional APM (server metrics, response times). Modern New Relic usage requires:
- Browser and mobile RUM
- Synthetic monitoring for proactive testing
- Log correlation with APM traces
- Business metrics alongside technical metrics
4. Overvaluing Certifications
New Relic offers certifications, but passing an exam doesn't equal production experience. Someone who's debugged a major incident using New Relic data is more valuable than someone who memorized certification materials.
Better approach: Ask about real incidents they've diagnosed, dashboards they've built with purpose, and alerts that actually saved the team from customer-facing issues.