New Relic Performance Engineer study plan

Map the APM 360 data model: trace, transaction, span, segment, error, and how they nest.

Instrument a sample app with an APM agent and verify data reaches the account.

Define custom attributes and a custom event to pass business context into telemetry.

Correlate an APM transaction with its logs in the log management UI.

Write a one-page glossary linking APM concepts to log and platform terms.

Build and interpret a service map, identifying upstream and downstream dependencies.

Configure an alert policy on error rate and response time with a multi-condition threshold.

Create a dashboard with NRQL widgets for throughput, latency percentiles, and error budget.

Trace a slow request through distributed tracing to the slowest span.

Document how to tune sampling and trace filters to control ingest cost.

Install browser monitoring on a page and verify Core Web Vitals and session data.

Analyze a synthetic monitor script and add a multi-step check with assertions.

Segment user sessions by geography, device, and release to find performance regressions.

Configure a browser alert for JS error rate and a synthetic alert for availability.

Compare real-user monitoring and synthetic data to explain a discrepancy.

Write NRQL queries to join browser and APM data for end-to-end latency.

Set up log parsing rules and a drop-filter to reduce noisy log volume.

Build a log-based alert and link it to the relevant APM entity.

Design a data retention and partitioning plan for logs and events.

Review role-based access controls for dashboards and log data.

Configure an anomaly detection alert on a baseline metric and tune sensitivity.

Apply applied intelligence to a service to surface correlated incidents.

Write a root-cause analysis using incident correlation and entity relationships.

Evaluate an alert noise reduction strategy using muting and suppression rules.

Document how automation rules can trigger a webhook on incident creation.

Install an infrastructure agent on a host and verify system metrics.

Integrate a cloud provider and validate EC2 or equivalent host metrics.

Create an infrastructure alert on CPU saturation and disk pressure.

Build a host dashboard with NRQL for memory, disk, and network.

Map an application service to its underlying hosts and dependencies.

Configure a Kubernetes or container integration and verify pod-level metrics.

Set up a log forwarding pipeline from infrastructure to the platform.

Write NRQL to correlate host metrics with application error spikes.

Review platform APIs for programmatic dashboard and alert creation.

Test a backup and export strategy for dashboards and alert policies.

Take a full-length timed practice exam and score each domain.

Re-review the two lowest-scoring domains with targeted labs.

Rehearse explaining alert design and NRQL trade-offs aloud.

Verify all deliverables are complete and organized in a portfolio.

Write a final weak-area checklist with remediation dates.