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New Relic Reliability Engineer study materials
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New Relic Reliability Engineer practice questions

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Question 1Application Performance Monitoring (APM 360)

In New Relic APM, which component is responsible for collecting and sending data from your application to New Relic?

  1. The alert policy
  2. The APM agent Correct answer.
  3. The NRQL query
  4. The dashboard widget

Explanation

The APM agent is the language-specific library installed in your application that instruments code and transmits telemetry to New Relic. Alert policies, dashboards, and NRQL queries consume data after it reaches the platform.

Question 2Application Performance Monitoring (APM 360)

A transaction shows a high response time in APM, but the application code appears fast. Which APM feature helps break the transaction time into segments such as database calls and external services?

  1. Synthetic monitor
  2. Transaction trace Correct answer.
  3. Service level objective
  4. Deployment marker

Explanation

A transaction trace captures a detailed timeline of a slow transaction, showing how time is distributed across database calls, external requests, and application code. This is the primary tool for locating where latency originates within a transaction.

Question 3Application Performance Monitoring (APM 360)

What does the Apdex score in New Relic APM measure?

  1. The percentage of failed requests
  2. User satisfaction based on response time thresholds Correct answer.
  3. The average CPU usage of the host
  4. The number of unique users per hour

Explanation

Apdex is a standardized user-satisfaction metric derived from response times compared against a target threshold T, classifying requests as satisfied, tolerating, or frustrated. It is not a failure rate, host metric, or user count.

Question 4Application Performance Monitoring (APM 360)

Which New Relic feature lets you view the end-to-end path of a request as it travels across multiple services and hosts?

  1. Distributed tracing Correct answer.
  2. Alert conditions
  3. Log parsing rules
  4. Infrastructure inventory

Explanation

Distributed tracing follows a single request across service boundaries, stitching together spans from each service to reveal the full call path and per-service timing. This is distinct from host inventory, log parsing, or alerting.

Question 5Application Performance Monitoring (APM 360)

In New Relic APM, what is the purpose of a custom event?

  1. To configure the agent's license key
  2. To record application-specific business data as a queryable event type Correct answer.
  3. To replace transaction traces for slow requests
  4. To override the agent's default sampling rate

Explanation

Custom events let you send structured business or application data to New Relic so it can be queried with NRQL alongside other telemetry. They do not control sampling, replace traces, or configure credentials.

Question 6Application Performance Monitoring (APM 360)

Which NRQL clause is used to aggregate transaction durations into time buckets for a chart?

  1. LIMIT
  2. SINCE
  3. FACET
  4. TIMESERIES Correct answer.

Explanation

TIMESERIES groups aggregated results into time buckets so a query produces a time-based chart. FACET splits results by attribute, LIMIT caps rows, and SINCE sets the time window.

Question 7Application Performance Monitoring (APM 360)

In APM, what does the throughput metric represent?

  1. Requests or transactions processed per unit of time Correct answer.
  2. The count of distinct error classes
  3. The number of active database connections
  4. The total bytes transferred by the application

Explanation

Throughput measures the rate at which your application processes requests, typically expressed as requests per minute (rpm). It reflects volume rather than data size, connection counts, or error variety.

Question 8Application Performance Monitoring (APM 360)

What is the role of the New Relic APM agent's error collector?

  1. To capture and report exceptions and error details from your application Correct answer.
  2. To automatically restart crashed application processes
  3. To block malicious requests at the network layer
  4. To compress log files before storage

Explanation

The error collector captures exceptions and error events raised in your application and reports them to New Relic for analysis and alerting. It does not manage process lifecycle, perform network filtering, or handle log compression.

Question 9Application Performance Monitoring (APM 360)

You want to identify which specific external API call is slowing a web transaction. Which APM data source most directly shows time spent per external call?

  1. Deployment marker timeline
  2. Host CPU utilization chart
  3. Transaction trace segment breakdown Correct answer.
  4. Apdex score trend

Explanation

Transaction traces segment a slow transaction and list each external call with its own duration, making the slow dependency easy to isolate. Apdex, CPU charts, and deployment markers offer context but not per-call timing within a transaction.

Question 10Application Performance Monitoring (APM 360)

A team wants to be alerted when the error rate of a specific web transaction exceeds a threshold. What should they create in New Relic?

  1. An alert policy with a condition scoped to that transaction Correct answer.
  2. A dashboard with a single widget
  3. A custom event type
  4. A synthetic monitor for the homepage

Explanation

Alerting requires an alert policy containing a condition that evaluates the chosen metric, such as error percentage, against a threshold for the target transaction. Dashboards, synthetic monitors, and custom events display or add data but do not trigger threshold-based notifications.

Question 11Application Performance Monitoring (APM 360)

In NRQL, which function would you use to count the number of distinct user sessions in a transaction event?

  1. rate()
  2. percentile()
  3. average()
  4. uniqueCount() Correct answer.

Explanation

uniqueCount() returns the number of distinct values for an attribute, so applying it to a session identifier yields distinct session counts. average(), percentile(), and rate() compute other statistics and do not count distinct values.

Question 12Application Performance Monitoring (APM 360)

What distinguishes a browser (Browser monitoring) event from an APM transaction event?

  1. Browser events are captured in the user's browser, while APM transactions are captured server-side by the agent Correct answer.
  2. APM transactions are collected by synthetic monitors
  3. Browser events are only available for mobile apps
  4. Browser events cannot be queried with NRQL

Explanation

Browser monitoring instruments the client-side page in the end user's browser, capturing page load and interaction timing, whereas APM transactions are recorded server-side by the language agent. Both event types are queryable with NRQL.

Question 13Application Performance Monitoring (APM 360)

A developer wants to add a custom attribute to all transactions from a particular service. Which agent capability should they use?

  1. A deployment marker
  2. Custom attributes added via the agent API Correct answer.
  3. An alert policy
  4. A synthetic script

Explanation

Custom attributes are added through the agent's API so they attach to transactions and become queryable and facetable in NRQL. Deployment markers, synthetic scripts, and alert policies do not attach metadata to transaction events.

Question 14Application Performance Monitoring (APM 360)

What is the primary purpose of the New Relic APM service map?

  1. To visualize dependencies and communication between services and external systems Correct answer.
  2. To show historical deployment records
  3. To configure data retention settings
  4. To list all installed agents and their versions

Explanation

The service map displays services and their upstream and downstream dependencies, helping you understand architecture and spot problem areas. It does not inventory agent versions, list deployments, or manage retention.

Question 15Application Performance Monitoring (APM 360)

A transaction's response time spikes only during certain hours. Which approach best isolates whether a downstream database is responsible?

  1. Disable the error collector
  2. Increase the Apdex threshold
  3. Add more dashboard widgets
  4. Compare database call segments in transaction traces during spike versus normal periods Correct answer.

Explanation

Examining database segments in transaction traces across both periods reveals whether the database call duration grows during spikes. Adjusting Apdex, disabling error collection, or adding widgets does not identify the responsible dependency.

Question 16Application Performance Monitoring (APM 360)

Which NRQL query correctly returns the average duration of transactions faceted by app name over the past hour?

  1. SELECT average(duration) FROM Transaction TIMESERIES 1 hour
  2. SELECT count(*) FROM Transaction WHERE duration > 1
  3. SELECT max(duration) FROM Transaction LIMIT 1
  4. SELECT average(duration) FROM Transaction FACET appName SINCE 1 hour ago Correct answer.

Explanation

The query selects average(duration), facets results by appName, and sets the window with SINCE 1 hour ago, producing per-app averages. The other options filter, use a different aggregation, or restrict rows rather than faceting by app.

Question 17Application Performance Monitoring (APM 360)

What does the New Relic agent's transaction naming determine?

  1. The frequency of synthetic checks
  2. The retention period for event data
  3. How transactions are grouped and reported in APM Correct answer.
  4. Which users are allowed to access the app

Explanation

Transaction naming controls how requests are aggregated into named transactions, which affects how metrics, traces, and errors are grouped and displayed. It has no bearing on access control, retention, or synthetic scheduling.

Question 18Application Performance Monitoring (APM 360)

A team notices many transactions with no meaningful name, all grouped under a generic default. What is the most likely cause?

  1. The dashboard has too many widgets
  2. The agent cannot determine a naming scheme for those requests and falls back to a default Correct answer.
  3. The license key is invalid
  4. The alert policy is misconfigured

Explanation

When the agent cannot derive a transaction name from routing or framework metadata, it assigns a generic default, causing unrelated requests to be grouped together. Invalid keys, alert configuration, and dashboard size do not affect transaction naming.

Question 19Application Performance Monitoring (APM 360)

Which metric best indicates that an application is spending excessive time waiting on external HTTP services rather than executing its own code?

  1. A decreasing throughput with stable error rate
  2. A high proportion of transaction time attributed to external service segments Correct answer.
  3. A flat host memory chart
  4. A rising Apdex score

Explanation

When external call segments dominate total transaction time, the application is waiting on downstream services rather than running its own logic. Apdex, throughput, and memory do not attribute time to external calls.

Question 20Application Performance Monitoring (APM 360)

What is the effect of enabling high-security mode on an APM agent?

  1. It prevents the agent from sending certain potentially sensitive data such as query parameters Correct answer.
  2. It doubles the sampling rate of transaction traces
  3. It converts transactions into custom events
  4. It disables all NRQL querying for the account

Explanation

High-security mode restricts the agent from transmitting potentially sensitive details, such as query parameters and request attributes, to protect data. It does not alter sampling, disable querying, or transform event types.

Question 21Application Performance Monitoring (APM 360)

An engineer wants to correlate a performance regression with a code release. Which New Relic capability is designed for this?

  1. Deployment markers overlaid on APM charts Correct answer.
  2. Synthetic monitor scripting
  3. Custom event sampling
  4. Apdex threshold tuning

Explanation

Deployment markers record release events and can be overlaid on charts so you can visually correlate a change with shifts in performance metrics. Apdex tuning, event sampling, and synthetic scripts do not annotate releases.

Question 22Application Performance Monitoring (APM 360)

A service shows low Apdex while error rate is near zero and throughput is steady. Which explanation is most consistent with these signals?

  1. The host has run out of disk space
  2. Response times have increased beyond the tolerating threshold for many requests Correct answer.
  3. Requests are failing frequently
  4. Traffic volume has collapsed

Explanation

With steady throughput and negligible errors, a low Apdex points to slower response times pushing requests into the tolerating or frustrated buckets. Failures, traffic collapse, or disk exhaustion would show as error spikes, throughput drops, or host alerts instead.

Question 23Application Performance Monitoring (APM 360)

In a distributed trace, what does a span represent?

  1. The license key used by the agent
  2. A single unit of work within the request path, with its own timing and attributes Correct answer.
  3. The entire account's data retention window
  4. A configured alert threshold

Explanation

A span is one timed operation in a trace, such as a database query or service call, carrying attributes and parent-child relationships that build the full request path. Retention windows, alert thresholds, and license keys are unrelated to spans.

Question 24Application Performance Monitoring (APM 360)

A team observes that only a subset of slow requests appear in transaction traces. What is the most likely explanation?

  1. Traces require an active synthetic monitor
  2. Traces are only generated for failed requests
  3. The agent cannot trace requests over one second
  4. Trace collection is sampled based on configured thresholds and rates Correct answer.

Explanation

The agent samples transaction traces according to settings such as the slow-request threshold and harvest cycle, so not every slow request is captured. Traces are not limited to failures, are not blocked by duration, and do not require synthetic monitors.

Question 25Application Performance Monitoring (APM 360)

An application reports high throughput and low average response time, yet some users complain about slowness. Which analysis technique best surfaces the affected requests?

  1. Reviewing the average Apdex only
  2. Inspecting host disk usage
  3. Checking the deployment marker list
  4. Examining percentile response times such as the 95th percentile Correct answer.

Explanation

Averages can hide a slow tail, so percentile metrics like p95 or p99 reveal that a minority of requests are much slower. Average Apdex, deployment lists, and disk usage do not expose the tail latency experienced by those users.

Question 26Application Performance Monitoring (APM 360)

In New Relic APM, which metric directly reflects the percentage of requests that completed without an error?

  1. Success rate Correct answer.
  2. Error rate
  3. Apdex score
  4. Throughput

Explanation

The success rate expresses the share of requests that finished without producing an error, so a value of 98% means roughly two requests in a hundred failed. It is derived from the ratio of error-free transactions to total transactions in the same window. Apdex measures satisfaction against a response-time threshold rather than success or failure.

Question 27Application Performance Monitoring (APM 360)

An APM agent is installed but the application's transactions appear under an unexpected name such as a raw URI with IDs. Which agent configuration area governs how transactions are grouped and named?

  1. The distributed tracing sampling configuration
  2. Transaction naming configuration, including transaction name priority and custom naming rules Correct answer.
  3. The browser monitoring injection settings
  4. The error collector's ignore-errors list

Explanation

Transaction naming determines the label used to group and roll up metrics, and agents expose priority ordering plus custom naming hooks so teams can normalize names. When default naming produces high-cardinality names containing identifiers, adjusting naming rules restores meaningful grouping. The other settings affect error reporting, trace sampling, or browser injection, not the transaction label.

Question 28Application Performance Monitoring (APM 360)

A reliability engineer wants a single number that summarizes how many users were satisfied with response time, tolerating slow and failed requests. Which APM metric should they use?

  1. Apdex score Correct answer.
  2. Requests per minute
  3. Average response time
  4. Host CPU utilization

Explanation

Apdex converts response times into satisfied, tolerating, and frustrating counts relative to a threshold T, then reports (satisfied + tolerating/2) / total. It therefore blends speed and failure into one satisfaction index between 0 and 1. Average response time hides the distribution, and throughput and CPU describe load rather than user satisfaction.

Question 29Application Performance Monitoring (APM 360)

Which APM feature lets you inspect the detailed timing breakdown of an individual slow transaction, including time spent in database and external calls?

  1. A transaction trace Correct answer.
  2. The service map
  3. The deployment marker timeline
  4. The alert policy summary

Explanation

A transaction trace captures one representative slow request and segments its duration into database, external service, and application code time. It is the primary tool for attributing latency within a single request. The service map shows dependency topology, deployment markers annotate releases, and alert policies define conditions.

Question 30Application Performance Monitoring (APM 360)

A team wants to record a business-specific value such as customer tier on every transaction so it can be faceted in NRQL. Which approach is appropriate?

  1. Lower the Apdex threshold T
  2. Increase the distributed tracing sample rate
  3. Enable high-security mode
  4. Add a custom attribute via the agent API on the current transaction Correct answer.

Explanation

Custom attributes added through the agent API attach arbitrary key-value metadata to the active transaction, which then becomes queryable and facetable in NRQL. This is the standard mechanism for carrying business context into APM data. Thresholds, security mode, and trace sampling do not create new queryable attributes.

Question 31Application Performance Monitoring (APM 360)

An engineer suspects a specific backend service is the bottleneck for a slow checkout flow. Which APM capability most directly shows the time contributed by each downstream service to the overall request?

  1. The error rate chart for the frontend app
  2. The throughput chart for the frontend app
  3. The Apdex score trend for the frontend app
  4. The transaction trace's segmented timing, showing time attributed to each downstream call Correct answer.

Explanation

A transaction trace breaks the request duration into segments, so time attributed to each database or external service call is visible and can be compared. That directly identifies which downstream dependency consumes the most time. Apdex, throughput, and error rate summarize outcomes but do not apportion time to individual dependencies.

Question 32Application Performance Monitoring (APM 360)

A developer wants to measure how long a specific internal method takes without it appearing as a separate transaction. Which agent capability should they use?

  1. A synthetic monitor for the endpoint
  2. A custom instrumentation segment or tracer around the method Correct answer.
  3. A deployment marker
  4. A browser monitoring page load timing

Explanation

Custom instrumentation wraps a method in a segment or tracer so its duration is recorded inside the enclosing transaction and appears in traces and timing breakdowns. This is the correct tool for internal code paths that are not their own transactions. Synthetic monitors, browser timings, and deployment markers operate at different layers.

Question 33Application Performance Monitoring (APM 360)

An APM app shows a rising error rate concentrated in one transaction. Which NRQL approach best lists the most frequent error messages for that transaction over the last hour?

  1. SELECT uniqueCount(session) FROM PageView WHERE appName = 'X' SINCE 1 hour ago
  2. SELECT average(duration) FROM Transaction WHERE appName = 'X' SINCE 1 hour ago
  3. SELECT max(duration) FROM Transaction FACET name SINCE 1 hour ago
  4. SELECT count(*) FROM TransactionError WHERE appName = 'X' AND name = 'Y' FACET error.message SINCE 1 hour ago Correct answer.

Explanation

TransactionError events carry error.message, and faceting by that attribute groups occurrences so the most frequent messages surface. Filtering by appName and transaction name scopes the result to the affected transaction. The other queries return latency or session statistics and never touch error messages.

Question 34Application Performance Monitoring (APM 360)

A team wants to see whether a recent release changed response time, using APM charts annotated with the release event. Which feature provides that annotation?

  1. Distributed trace sampling
  2. Alert conditions on error rate
  3. Deployment markers recorded through the agent or API Correct answer.
  4. The Apdex threshold setting

Explanation

Deployment markers record a timestamped release event that is overlaid on APM charts, making it easy to compare performance before and after a deploy. They are created through the agent API or the deployment API. Alert conditions, Apdex thresholds, and trace sampling do not annotate charts with release times.

Question 35Application Performance Monitoring (APM 360)

A web transaction's average response time is stable, but its 95th percentile has doubled. Which interpretation is most consistent with this pattern?

  1. All requests became uniformly slower by the same amount
  2. The error rate must have fallen to zero
  3. Throughput dropped sharply across the whole application
  4. A minority of requests became much slower while typical requests stayed the same Correct answer.

Explanation

A rising high percentile with a stable average indicates a heavier tail: a small share of requests got much slower while the bulk stayed unchanged. This is a classic sign of intermittent contention, retries, or a slow dependency affecting a subset of calls. Uniform slowdown would move the average too, and throughput or error rate are separate signals.

Question 36Application Performance Monitoring (APM 360)

An application uses a background worker that processes jobs from a queue. The team wants APM data for these jobs even though they are not HTTP requests. What should they do?

  1. Rely on browser monitoring to capture the jobs
  2. Disable APM for the worker and use only infrastructure monitoring
  3. Instrument the worker as non-web (background) transactions using the agent API Correct answer.
  4. Create synthetic monitors that poll the queue

Explanation

Agents distinguish web transactions from non-web (background) transactions, and the API lets a worker wrap job processing so it is reported as a background transaction. That yields throughput, duration, and error data for jobs in APM. Browser monitoring, synthetics, and infrastructure-only monitoring do not produce APM transaction data for the worker.

Question 37Application Performance Monitoring (APM 360)

A service calls an external payment API. The team wants APM to report the external call as its own segment with its own duration and error status. What is required?

  1. The Apdex threshold must be set below the call's duration
  2. The agent must instrument the outbound HTTP client so the call is recorded as an external segment Correct answer.
  3. The call must be converted into a web transaction
  4. The external API must be registered as a browser application

Explanation

External segments are produced when the agent instruments the outbound HTTP client library, capturing the call's duration, target host, and error status inside the parent transaction. Without that instrumentation the time is only visible as generic application time. Browser registration, transaction conversion, and Apdex thresholds do not create external segments.

Question 38Application Performance Monitoring (APM 360)

A team enables distributed tracing across services. In the resulting trace, one span has a duration nearly equal to the whole trace and many child spans beneath it. What does this indicate?

  1. The root span is an error and must be filtered out
  2. The root span represents the entry-point service, and child spans show downstream work nested within it Correct answer.
  3. The trace was sampled incorrectly and should be discarded
  4. The child spans are unrelated background jobs that happened at the same time

Explanation

In a distributed trace the root span is the originating request, and its duration encompasses all downstream work represented by child spans. A root span nearly equal to the total with many children simply reflects the entry service waiting on downstream calls. It does not imply unrelated jobs, bad sampling, or an error.

Question 39Application Performance Monitoring (APM 360)

An engineer must decide whether slowness originates in application code or in a database. Which comparison from APM data best supports that decision?

  1. Apdex score versus throughput for the whole application
  2. Database segment time versus total transaction time in transaction traces for the slow transaction Correct answer.
  3. Error rate versus deployment marker count
  4. Host memory versus host CPU for the database server

Explanation

Transaction traces attribute time to database segments and to application code, so comparing database segment time against total transaction time shows which dominates the slow request. If database time is a small fraction, the code path is the likely source. Application-level Apdex and throughput, error counts, and host resource metrics cannot make that attribution.

Question 40Application Performance Monitoring (APM 360)

An APM agent reports that a transaction spends most of its time in a database segment, but the database server's own metrics show low query latency. Which explanation is most consistent with both observations?

  1. The application code is the dominant consumer of time
  2. Connection pool exhaustion or waiting for a connection inside the agent's database segment Correct answer.
  3. Apdex is misconfigured and inflating the segment
  4. The database is executing each query far more slowly than its metrics report

Explanation

Agent database segments can include time spent waiting to obtain a pooled connection before the query is sent, so the segment looks slow while server-side query latency stays low. Connection pool saturation is a common cause of this discrepancy. Server-side slowness would raise database metrics, code time would appear outside the database segment, and Apdex does not alter segment durations.

Question 41Digital Experience Monitoring

In New Relic Browser monitoring, what does the Browser Pro+SPA agent add beyond the Lite agent's page-load timing data?

  1. It disables sampling so every session is stored indefinitely
  2. It captures only server-side response times for backend services
  3. It records JavaScript errors, AJAX calls, and route changes as individual events Correct answer.
  4. It replaces the need for any JavaScript snippet in the page header

Explanation

The Pro+SPA agent instruments the browser runtime, capturing JavaScript errors, AJAX requests, and SPA route changes in addition to page-load timing. The Lite agent only reports page-load metrics and basic session data, so the richer event stream is what distinguishes the higher tier.

Question 42Digital Experience Monitoring

A team wants every browser session in a low-traffic internal app to be captured rather than a statistical sample. Which New Relic Browser setting controls this?

  1. The alert policy's evaluation window
  2. The data retention period in the account settings
  3. The session sample rate configured in the agent settings Correct answer.
  4. The Apdex threshold for the browser application

Explanation

The session sample rate determines what percentage of browser sessions are collected; setting it to 100 percent captures all sessions. Apdex thresholds, retention, and alert windows affect scoring and storage but do not change how many sessions the agent records.

Question 43Digital Experience Monitoring

Which New Relic Browser feature groups sessions by shared attributes such as user ID or account tier so you can compare their performance?

  1. Workloads
  2. Synthetic monitors
  3. Service levels
  4. Browser Segments Correct answer.

Explanation

Browser Segments let you define cohorts of sessions by attribute and compare their performance metrics side by side. Synthetic monitors generate traffic, service levels track objectives, and workloads group entities, so none of them segment user sessions.

Question 44Digital Experience Monitoring

What is the primary purpose of a New Relic Synthetic monitor?

  1. To aggregate browser sessions into cohorts for comparison
  2. To capture uncaught JavaScript exceptions in real user sessions
  3. To define reliability objectives for a service
  4. To proactively test an endpoint or user flow on a schedule from selected locations Correct answer.

Explanation

Synthetic monitors run scripted checks on a schedule from chosen locations to detect availability and performance problems before users encounter them. They generate their own traffic rather than observing real users.

Question 45Digital Experience Monitoring

Which synthetic monitor type is best suited to validating that a multi-step login flow completes successfully?

  1. A broken links monitor
  2. A scripted API test using a headless browser Correct answer.
  3. A simple ping monitor
  4. A certificate check monitor

Explanation

A scripted browser test executes a sequence of interactions such as filling fields and clicking buttons, which is required to validate a multi-step login flow. Ping, broken-link, and certificate checks verify reachability or link integrity but cannot drive form interactions.

Question 46Digital Experience Monitoring

In New Relic, which metric best represents the percentage of page loads that users consider satisfactory using a threshold-based score?

  1. JavaScript error count
  2. Throughput in requests per minute
  3. Apdex score for the browser application Correct answer.
  4. Total page views

Explanation

Apdex classifies response times against a satisfaction threshold to produce a normalized score between 0 and 1. Throughput, page views, and error counts are raw volume metrics that do not encode user satisfaction thresholds.

Question 47Digital Experience Monitoring

A developer wants to see which AJAX endpoints a single-page application calls most slowly from the browser. Which data source should they query?

  1. Infrastructure host samples
  2. BrowserInteraction and AjaxRequest events in the Browser event data Correct answer.
  3. Synthetic monitor results
  4. APM transaction traces only

Explanation

The Browser agent emits interaction and AJAX event types that include per-request duration and endpoint details, making them the right source for client-side AJAX timing. Infrastructure samples and APM traces describe server and host behavior, and synthetic results reflect scripted probes rather than real users.

Question 48Digital Experience Monitoring

Which New Relic capability lets you record and replay the sequence of user interactions leading to a JavaScript error?

  1. Alert policies
  2. Dashboards
  3. Session replay Correct answer.
  4. Service levels

Explanation

Session replay captures a reconstruction of the user's interactions and DOM changes so you can see what preceded an error. Dashboards visualize data, service levels track objectives, and alert policies notify on conditions, but none replay the session.

Question 49Digital Experience Monitoring

A synthetic monitor reports failures only from the Frankfurt location while other locations succeed. What is the most useful next step?

  1. Delete the Frankfurt location to stop false alerts
  2. Increase the monitor's frequency to every minute
  3. Disable the monitor's alert condition
  4. Compare the monitor's results across locations and inspect the failing location's resource waterfall Correct answer.

Explanation

Location-specific failures usually indicate a regional network, DNS, or CDN issue, so comparing per-location results and examining the failing run's resource timing isolates the cause. Removing the location or muting alerts hides a potentially real regional problem.

Question 50Digital Experience Monitoring

How does the Browser agent's page view event differ from a BrowserInteraction event?

  1. PageView records server response codes, while BrowserInteraction records database queries
  2. PageView is generated only by synthetic monitors, while BrowserInteraction is generated by real users
  3. PageView stores session replay footage, while BrowserInteraction stores JavaScript stack traces
  4. PageView represents a document load, while BrowserInteraction represents an in-page interaction such as a route change Correct answer.

Explanation

PageView events are emitted for each document load, whereas BrowserInteraction events capture in-page activity like SPA route changes or user-triggered actions. This distinction lets you separate initial load performance from subsequent interaction performance.