Datadog Fundamentals Exam Flashcards

Q: What is the Datadog Fundamentals exam format?

Datadog Fundamentals is a proctored multiple-choice exam with 90 total questions (75 scored, 15 unscored pretest) and a 2-hour time limit. It is delivered through Kryterion Webassessor with both online and onsite proctoring. The exam is available in English, Japanese, Korean, Brazilian Portuguese, French, and Spanish.

Q: What is the passing score for the Datadog Fundamentals exam?

Datadog does not publicly disclose the passing score for its certification exams. The company states only that passing is determined by the percentage of correct answers. Candidates should build confidence across all six official domains rather than targeting an unofficial cutoff.

Q: How much does the Datadog Fundamentals exam cost and what is the retake policy?

The exam fee is $100 USD per attempt. You can take up to three attempts within a 180-day period, with a 24-48 hour wait between attempts. After three attempts, a 180-day waiting period applies. Each retake requires a separate payment.

Q: How long is the Datadog Fundamentals certification valid?

Datadog certifications are valid for 3 years from the date you pass. After that period, you must retake the current exam to renew your credential. Staying current with Datadog's evolving platform, UI, and Learning Center materials is recommended rather than relying on older screenshots.

Q: Are there prerequisites for taking the Datadog Fundamentals exam?

There are no formal prerequisites, and the exam is open to everyone. Datadog recommends at least a few months of hands-on experience using Datadog with live systems. In practice, candidates do best after installing the Agent, using tags, building dashboards, and configuring basic monitors before scheduling.

Question 1

Datadog Agent as a background daemon

Accepted Answer

The Agent runs as a system service or daemon so it can continuously collect and forward metrics, logs, traces, and events without requiring an interactive user session. This keeps monitoring alive through reboots and logouts.

Question 2

datadog.yaml on Linux

Accepted Answer

The main Agent configuration file on Linux lives at /etc/datadog-agent/datadog.yaml. It holds host-wide settings such as the API key, site parameter, proxy configuration, and global tags.

Question 3

YAML indentation sensitivity

Accepted Answer

YAML is whitespace-sensitive: nested keys must use consistent spaces, and tabs break parsing. A single mismatched indent in datadog.yaml can prevent the Agent from starting.

Question 4

Environment variable (DD_API_KEY)

Accepted Answer

Supplies configuration values to a process from the environment instead of hardcoding them in files or commands. This is the standard way to pass secrets and site settings to containerized Agent deployments.

Question 5

Metadata in observability

Accepted Answer

Descriptive key-value context (such as host, env, service, or region) attached to telemetry. Metadata lets you filter, group, and correlate metrics, logs, and traces across dashboards and monitors.

Question 6

CPU utilization metric

Accepted Answer

Measures sustained processor load. Consistently high CPU utilization indicates the server cannot keep up with workload demand and may need scaling or optimization.

Question 7

TCP vs UDP

Accepted Answer

TCP is connection-oriented and reliable, guaranteeing ordered, retransmitted delivery. UDP is connectionless and lightweight with no delivery guarantee, making it suitable for fast, fire-and-forget telemetry like DogStatsD packets.

Question 8

Port number

Accepted Answer

A logical identifier that lets two programs on the same host multiplex network traffic. Each service binds to its own port so traffic reaches the correct destination application.

Question 9

sudo for editing datadog.yaml

Accepted Answer

The /etc/datadog-agent/ directory is owned by root, so editing datadog.yaml requires elevated privileges. Using sudo grants the temporary root access needed to modify the file.

Question 10

Shell redirect > vs >>

Accepted Answer

The > operator overwrites the target file, replacing its contents. The >> operator appends to the end, preserving existing content. Use >> when adding lines to config or log files without destroying prior data.

Question 11

RAM vs disk for running processes

Accepted Answer

RAM holds the data and instructions a running process needs immediately. Disk stores data persistently and serves as swap space when RAM is exhausted, but disk access is far slower.

Question 12

JSON in Datadog APIs

Accepted Answer

JSON is the standard request and response format for Datadog's HTTP APIs and most modern web services. It is human-readable, language-agnostic, and easy to parse programmatically.

Question 13

API key

Accepted Answer

The credential the Datadog Agent must have to submit metrics, events, and logs to your Datadog organization. It authorizes data ingestion and is required for every Agent installation.

Question 14

Application key (APP key)

Accepted Answer

Paired with an API key to access Datadog's management APIs for programmatic automation, including creating dashboards, managing monitors, and querying resources. The API key authenticates data submission; the app key authorizes management actions.

Question 15

Service account application key

Accepted Answer

Safer for shared automation than a personal user's app key because it persists even after individual users are deactivated. It avoids tying critical automation to one person's access.

Question 16

DD_ environment variables in containers

Accepted Answer

Agent v6+ accepts most datadog.yaml settings as environment variables with a DD_ prefix (e.g., DD_API_KEY, DD_SITE). This enables containerized deployments without mounting config files.

Question 17

Restarting the Agent after config changes

Accepted Answer

Editing datadog.yaml or an integration's conf.yaml does not apply settings immediately. You must restart the Agent service for new configuration to take effect.

Question 18

Agent hostname override

Accepted Answer

Setting hostname explicitly in datadog.yaml makes Datadog report that fixed name instead of the OS-detected hostname. This provides stable identity but can cause duplicate host entries if the same name is reused across hosts.

Question 19

User deactivation and API/app keys

Accepted Answer

When a user who created API or application keys is deactivated, those keys are deactivated by default. Automation relying on those keys will break unless keys are transferred to a service account beforehand.

Question 20

Browser-side API key risk

Accepted Answer

Embedding an organization API key in browser JavaScript exposes it to anyone viewing the page. Use server-side calls with application keys and restricted scopes instead of client-side ingestion.

Question 21

DogStatsD default port

Accepted Answer

The Agent listens for DogStatsD custom metric packets on UDP port 8125 by default. Applications send metrics to this local port, which the Agent then forwards to Datadog.

Question 22

APM trace receiver port

Accepted Answer

The Agent's APM trace receiver listens on TCP port 8126 by default. Application trace libraries send span data to this port for the Agent to forward to Datadog.

Question 23

Outbound Agent traffic

Accepted Answer

Most outbound Agent traffic uses HTTPS over TCP port 443 to send metrics, logs, traces, and events to Datadog intake endpoints. This port must be open for the Agent to function.

Question 24

Domain-based firewall allowlisting

Accepted Answer

Use domain-based allowlisting (e.g., *.datadoghq.com or site-specific domains) rather than hardcoding IP addresses. Datadog's IP ranges change over time, and static IPs can cause silent data loss.

Question 25

Autodiscovery

Accepted Answer

Lets the Agent automatically detect and monitor containers and services using Docker labels or Kubernetes annotations. Configuration follows workloads instead of requiring manual edits each time a container starts.

Question 26

DogStatsD

Accepted Answer

A statsd-compatible protocol for submitting custom metrics from application code to the Agent over UDP. Supports gauges, counts, timers, and sets without needing direct API calls.

Question 27

Gauge vs count metric type

Accepted Answer

A gauge represents a snapshot value at a point in time (e.g., memory used). A count represents an accumulated value or rate that resets periodically (e.g., requests per second).

Question 28

Timeseries rollup on zoom-out

Accepted Answer

When you zoom a graph from one hour to one week, Datadog aggregates data points into bins to fit the display width. Each bin shows an averaged value, making the graph appear smoother at longer time ranges.

Question 29

Cloud crawler latency

Accepted Answer

Cloud integration metrics (such as AWS or Azure) arrive later than host Agent metrics because crawlers poll cloud provider APIs on intervals rather than streaming continuously. Expect a delay of minutes, not seconds.

Question 30

Direct metric submission via Datadog API

Accepted Answer

If you cannot run the Agent, submit custom metrics by POSTing to the Datadog API metrics endpoint with your API key. This is useful for serverless or short-lived environments where the Agent is impractical.

Question 31

Space aggregation: avg vs max

Accepted Answer

In Metrics Explorer, avg smooths across tagged sources by averaging values. Max shows the highest value across all sources, surfacing spikes and outliers that avg can hide.

Question 32

Metric not appearing in query editor

Accepted Answer

A metric exists but does not appear in the Metrics Explorer because it has not received data recently. Datadog hides inactive metrics until they receive new points or you search for them explicitly.

Question 33

Recommended tag format

Accepted Answer

Tags should use key:value format (e.g., env:prod, service:web, role:database). This standard enables consistent filtering and grouping across dashboards, monitors, and infrastructure views.

Question 34

env:prod tag vs embedding environment in metric name

Accepted Answer

Putting the environment in a tag (env:prod) lets you filter dynamically without creating separate metric names. This keeps the metric namespace clean and allows cross-environment comparison.

Question 35

Unified service tagging (env, service, version)

Accepted Answer

Datadog's recommended standard of tagging every telemetry with env, service, and version. This trio correlates metrics, traces, and logs across the full stack, forming the foundation for unified observability.

Question 36

High-cardinality tag risk

Accepted Answer

Tags like request_id, user_id, or ephemeral container IDs create too many unique groupings. This degrades query performance, increases storage, and makes dashboards unreadable.

Question 37

Grouping by tag in a metric query

Accepted Answer

Grouping by a tag key (e.g., service) splits a single metric into one line per tag value. This reveals per-segment behavior instead of an aggregate that hides individual differences.

Question 38

Metrics Explorer 'from' box

Accepted Answer

Filters the metric pool to a subset matching a tag scope (e.g., from:env:prod). You only query metrics matching that tag, reducing noise and focusing on the relevant infrastructure.

Question 39

Activating a packaged Agent integration

Accepted Answer

Copy the integration's example file (conf.yaml.example) to conf.yaml, fill in connection parameters, then restart the Agent. The Agent reads active conf.yaml files from the conf.d directory.

Question 40

'Missing Data' integration status

Accepted Answer

Indicates the Agent is running but has not received data for that integration recently. Common causes include incorrect credentials, network connectivity issues, or the target service being down.

Question 41

Duplicate log source files

Accepted Answer

Two YAML log collection files pointing to the same log source cause the Agent to tail it twice, producing duplicate log entries. Consolidate into a single configuration to avoid this.

Question 42

Log lines without newline terminators

Accepted Answer

The Agent's tailer reads files line by line, using newlines as delimiters. Custom log files written without newline terminators can delay or break log ingestion because the Agent cannot separate entries.

Question 43

journalctl for Agent logs

Accepted Answer

On systemd-based Linux hosts, `journalctl -u datadog-agent` shows detailed Agent logs when `systemctl status` output is too terse. This is the primary way to inspect Agent errors on modern Linux.

Question 44

datadog-agent flare

Accepted Answer

Collects a diagnostic bundle containing logs, configuration, and system information for Datadog Support. Use this subcommand when troubleshooting requires assistance from Datadog's support team.

Question 45

datadog-agent configcheck

Accepted Answer

Validates and displays the Agent's resolved configuration. It shows whether settings parsed correctly and which integrations are active, helping catch YAML errors before they cause silent failures.

Question 46

datadog-agent status

Accepted Answer

Shows the Agent's running state, connected integrations, and recent errors in a single summary. This is the first command to run when verifying the Agent is healthy and collecting data.

Question 47

Host Map

Accepted Answer

A visual grid of all hosts colored by a selected metric (such as CPU or memory). It lets you spot outliers, patterns, and unhealthy hosts across infrastructure at a glance, without writing a query.

Question 48

Quick graph without a dashboard

Accepted Answer

Datadog lets you graph a metric directly from search or the Metrics Explorer without building a full dashboard first. This is the fastest way to investigate a single metric on the fly.

Question 49

Monitor 'avg by' field

Accepted Answer

Groups monitor evaluation by a tag key so the alert condition is checked per group (e.g., per host or per service) instead of globally. This ensures one failing instance triggers an alert without waiting for all instances to degrade.

Question 50

Monitor tags

Accepted Answer

Tags on monitors help route, filter, and organize alert notifications. They do not change the query itself but make it easier to find and manage monitors across teams and services.

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