New Relic Verified Foundation study plan
New Relic Verified Foundation · Give each week a clear focus.
8 weeks · About 7 hours per week
Application Performance Monitoring
Define APM fundamentals in your own words: transactions, traces, spans, segments, errors, and throughput versus response time versus Apdex.
Explain how distributed tracing propagates context across services and identify what a cross-application trace reveals that a single-app view cannot.
Configure a synthetic or free-tier account so a sample application reports transactions, then locate the transaction breakdown and trace detail views.
Distinguish Apdex thresholds from error rate and throughput when judging service health, and state one scenario where Apdex misleads.
Your checkpoint
A one-page APM cheat sheet mapping each core APM concept to where it appears in the product UI, plus three annotated screenshots or notes from your own sample app showing a transaction trace.
Application Performance Monitoring
Diagnose a slow transaction by reading a trace waterfall and naming the segment that dominates latency.
Interpret error analytics: group errors by class, identify error rate trends, and explain how error profiles differ from raw error counts.
Describe how the APM agent instruments common frameworks and what configuration options change data volume or sampling behavior.
Practice writing a structured incident narrative from APM evidence alone: symptom, scope, suspected cause, next diagnostic step.
Your checkpoint
A written root-cause walkthrough (roughly 300 words) of one simulated slow or failing transaction, citing the specific trace segments and error attributes that support your conclusion.
Infrastructure Monitoring
Map the infrastructure monitoring data model: hosts, system samples, processes, network metrics, and the role of the infrastructure agent.
Explain how cloud integrations and the entity model connect host-level signals to the applications they support.
Build one alert condition on a host metric and justify the threshold, evaluation window, and notification destination.
Compare infrastructure monitoring with APM when triaging a production slowdown, and state which signal you would check first and why.
Your checkpoint
A working alert policy on a host metric with a short design note explaining threshold choice, expected false-positive rate, and the runbook step it triggers.
Infrastructure Monitoring & Log Management
Instrument log forwarding from a host or container and confirm logs arrive with correct attributes and timestamps.
Correlate a log line with the trace and host it originated from, and explain which attributes make that correlation possible.
Apply parsing and attribute-extraction rules to turn unstructured log text into queryable fields.
Explain log sampling, retention, and partition behavior and how each affects query results and cost.
Your checkpoint
A correlation demo: one trace ID traced to its logs and host metrics, documented in a short write-up with the exact queries used.
Log Management
Write NRQL queries using FACET, TIMESERIES, SINCE, COMPARE WITH, and percentile functions to summarize log and event data.
Distinguish event types and attribute types, and predict when a query returns null versus zero.
Build a dashboard widget that surfaces log error trends segmented by service.
Explain how log parsing rules and drop filters change what a downstream query can see.
Your checkpoint
A five-query NRQL portfolio with expected output described for each query and one dashboard built from at least three of them.
Digital Experience Monitoring
Compare browser monitoring, synthetic monitoring, and mobile monitoring by the question each answers and the data each produces.
Interpret Core Web Vitals and page-load timing breakdowns, and identify which phase dominates a slow page load.
Configure a simple synthetic monitor (ping or scripted browser) and explain how it detects availability versus performance failures.
Explain session tracking, user interaction data, and privacy considerations such as masking sensitive content.
Your checkpoint
A digital experience comparison matrix covering the three monitoring types plus a configured synthetic monitor with a note on what alert it should feed.
AI and Intelligent Automation & Platform Capabilities
Describe how applied intelligence features surface anomalies, correlate incidents, and reduce alert noise, and state their limits.
Explain the role of machine-learning-driven baselines versus static thresholds in alerting decisions.
Navigate platform capabilities: entity relationships, dashboards, alert policies and workflows, and role-based access.
Explain how data ingest, sampling, and aggregation choices affect what dashboards and alerts can later show.
Your checkpoint
An alerting design document for one service that combines a static threshold, an anomaly-based condition, and a workflow routing rule, with rationale for each.
Pricing and Account Tiers & Platform Capabilities
Compare account tiers and pricing dimensions: data ingest, user seats, retention, and feature gating.
Explain how ingest volume and retention drive cost, and list three concrete levers to reduce spend without losing observability.
Review all seven domains and list your three weakest areas with a targeted remediation action for each.
Complete a timed practice set and analyze every missed question by domain and root cause.
Your checkpoint
A cost-and-tier summary table plus a prioritized remediation list of your three weakest domains with specific next actions.
Milestones
Week 2: You can read an unfamiliar trace waterfall and explain the dominant latency source and any errors without outside help.
Week 4: You can move from a log line to its trace and host in one continuous investigation, and you have a live alert firing correctly.
Week 6: You can write NRQL from memory for faceted timeseries and percentile comparisons, and you can explain when to choose synthetic versus browser monitoring.
Week 8: You score at least 80 percent on a timed mixed-domain practice set and can justify a tier and ingest plan for a stated scenario.