100+ Free AIOps Foundation Practice Questions

Pass your DevOps Institute AIOps Foundation (AIOF) exam on the first try — instant access, no signup required.

✓ No registration✓ No credit card✓ No hidden fees✓ Start practicing immediately

Not published Pass Rate

100+ Questions

100% Free

1 / 100

Question 1

Score: 0/0

How does Gartner originally define AIOps?

A new programming language used to script IT automation tasks

Combining big data and machine learning to automate and enhance IT operations processes

A subset of DevOps that focuses exclusively on container orchestration

A vendor-specific tool for replacing traditional monitoring dashboards

to track

2026 Statistics

Key Facts: AIOps Foundation Exam

Exam Questions

DevOps Institute

65%

Passing Score

DevOps Institute

60 min

Exam Duration

DevOps Institute

$395

Exam Voucher Fee

PeopleCert

Syllabus Domains

AIOps Foundation V1.0

3 years

Certification Validity

PeopleCert CPD

The AIOps Foundation exam has 40 multiple-choice questions in 60 minutes with a 65% passing score (26 of 40). It is open book and covers 8 domains: AIOps fundamentals, AIOps in the organization, core technologies (data), core technologies (ML and GenAI), AIOps and operations metrics, AIOps use cases, evaluating AIOps impact, and implementing AIOps. Certification is valid for 3 years under PeopleCert's CPD program.

Sample AIOps Foundation Practice Questions

Try these sample questions to test your AIOps Foundation exam readiness. Each question includes a detailed explanation. Start the interactive quiz above for the full 100+ question experience with AI tutoring.

1How does Gartner originally define AIOps?

A.A new programming language used to script IT automation tasks

B.Combining big data and machine learning to automate and enhance IT operations processes

C.A subset of DevOps that focuses exclusively on container orchestration

D.A vendor-specific tool for replacing traditional monitoring dashboards

Explanation: Gartner introduced AIOps as 'Artificial Intelligence for IT Operations' — the use of big data analytics and machine learning to automate, enhance, and augment IT operations functions such as monitoring, event correlation, and incident response. AIOps is a category of capability, not a single product or language.

2Which acronym best summarizes the four telemetry data types AIOps platforms ingest?

A.ACID

B.MELT

C.SOLID

D.REST

Explanation: MELT stands for Metrics, Events, Logs, and Traces — the four core telemetry data types that AIOps platforms ingest and correlate. Each provides a different lens on system behavior: metrics for trends, events for state changes, logs for context, and traces for request flow.

3What is the primary business driver behind organizations adopting AIOps?

A.To eliminate the need for any human IT operations staff

B.To handle the growing volume, variety, and velocity of operational data that humans cannot analyze in real time

C.To replace ITIL with a more modern framework

D.To remove the need for monitoring tools entirely

Explanation: Modern IT environments produce far more telemetry than humans can analyze manually. AIOps adoption is driven by the need to process large volumes of metrics, events, logs, and traces in real time so teams can detect issues, correlate events, and respond proactively.

4Which statement best describes the relationship between AIOps and MLOps?

A.AIOps and MLOps are different names for the same discipline

B.AIOps applies ML to IT operations problems, while MLOps operationalizes ML models across their lifecycle

C.MLOps is a subset of AIOps used only for log analysis

D.AIOps replaces MLOps in modern enterprises

Explanation: AIOps and MLOps are complementary disciplines. AIOps consumes machine learning to solve operations problems (event correlation, anomaly detection). MLOps focuses on the lifecycle of ML models themselves — training, deployment, monitoring, and retraining — regardless of the use case.

5Which of the following is NOT one of the three core technologies that AIOps relies on according to the AIOps Foundation V1.0 syllabus?

A.Big Data

B.Machine Learning

C.Generative AI

D.Blockchain

Explanation: The AIOps Foundation V1.0 syllabus lists three core technologies that AIOps relies on: Big Data (to generate and store data), Machine Learning (for inference, classification, and prediction), and Generative AI (to automate responses and assist operators). Blockchain is not part of the AIOps core technology stack.

6In MELT data, what does the 'E' represent?

A.Errors

B.Events

C.Endpoints

D.Emissions

Explanation: In MELT, the E stands for Events — discrete records of state changes such as a service starting, a deployment completing, or an alert firing. Events differ from metrics (numeric trends), logs (textual context), and traces (request paths).

7Which observability data type is best suited to representing time-series numeric measurements like CPU utilization?

A.Logs

B.Traces

C.Metrics

D.Events

Explanation: Metrics are numeric measurements collected at regular intervals, ideal for representing values like CPU utilization, memory consumption, request rate, or latency. Logs are textual, traces follow request paths, and events represent discrete state changes.

8What is the main purpose of data normalization in an AIOps pipeline?

A.To delete data older than 24 hours

B.To convert data from different sources into a common, consistent format for analysis

C.To encrypt data at rest in storage

D.To compress logs to reduce disk usage

Explanation: Normalization transforms data from heterogeneous sources (different vendors, formats, naming conventions) into a consistent schema so ML models and correlation engines can compare and combine signals. Without normalization, AIOps cannot reliably correlate across tools.

9Which type of machine learning is typically used to detect previously unknown anomalies in operational data without labeled examples?

A.Supervised learning

B.Unsupervised learning

C.Reinforcement learning

D.Federated learning

Explanation: Unsupervised learning identifies patterns and outliers without requiring labeled training data, making it well-suited to anomaly detection where novel issues lack prior examples. Algorithms like clustering, isolation forests, and autoencoders are common in unsupervised AIOps anomaly detection.

10What is the goal of event correlation in an AIOps platform?

A.To delete redundant events to free disk space

B.To group related events into a single incident or actionable signal, reducing noise

C.To encrypt event payloads

D.To rate-limit event ingestion at the source

Explanation: Event correlation aggregates related alerts and events that stem from a common underlying issue, presenting operators with a single actionable incident rather than a flood of duplicate notifications. This dramatically reduces alert fatigue and accelerates MTTR.

About the AIOps Foundation Exam

The DevOps Institute AIOps Foundation (AIOF) certification validates entry-level understanding of Artificial Intelligence for IT Operations. It covers the Gartner AIOps framework, big data and observability data (MELT), machine learning, generative AI, AIOps platform capabilities, event correlation, anomaly detection, automated remediation, operations metrics, and the strategy for implementing AIOps in the organization.

Questions

40 scored questions

Time Limit

60 minutes

Passing Score

65% (26 of 40)

Exam Fee

$395 (exam voucher) (DevOps Institute / PeopleCert)

AIOps Foundation Exam Content Outline

15%

AIOps Fundamentals

Gartner AIOps definition, history, AIOps capability chain, key principles, and relationship to MLOps, DevOps, and SRE

10%

AIOps in the Organization

Strategy, business drivers, stakeholders, organizational integration, adoption challenges, and OODA loop

15%

Core Technologies: Data

Big data foundations, MELT data (metrics, events, logs, traces), ingestion, normalization, and topology data

20%

Core Technologies: ML and GenAI

Supervised/unsupervised learning, anomaly detection, NLP, time-series forecasting, and generative AI for IT operations

10%

AIOps and Operations Metrics

MTTD, MTTR, MTBF, USE method, RED method, SLOs/SLIs, error budgets, and AIOps effectiveness measurement

15%

AIOps Use Cases

Event correlation, deduplication, noise reduction, capacity forecasting, root cause analysis, and automated remediation

Evaluating AIOps Impact

ROI assessment, value realization, AIOps maturity models, and benefits measurement

Implementing AIOps

Implementation roadmap, tooling selection, ITSM/CMDB integration, governance, and continuous improvement

How to Pass the AIOps Foundation Exam

What You Need to Know

Passing score: 65% (26 of 40)
Exam length: 40 questions
Time limit: 60 minutes
Exam fee: $395 (exam voucher)

Keys to Passing

Complete 500+ practice questions
Score 80%+ consistently before scheduling
Focus on highest-weighted sections
Use our AI tutor for tough concepts

AIOps Foundation Study Tips from Top Performers

1Memorize the Gartner AIOps definition: combining big data and machine learning to automate and enhance IT operations

2Learn the AIOps capability chain (formerly 'Stages of an AIOps system'): observe, engage, act — the updated 2025 terminology

3Master MELT data — Metrics, Events, Logs, Traces — and which observability source produces each type

4Understand the difference between supervised, unsupervised, and reinforcement learning and where each applies in AIOps

5Know common anomaly detection techniques: statistical thresholds, isolation forests, autoencoders, and seasonality decomposition

6Study event correlation approaches: rules-based, topology-based, temporal, and ML-based pattern discovery

7Memorize key SRE metrics: MTTD, MTTR, MTBF, SLO, SLI, error budget, and the USE/RED methods

8Understand the relationship between AIOps, MLOps, DevOps, and SRE — they are complementary, not competing

Frequently Asked Questions

What is the AIOps Foundation exam format?

The AIOps Foundation exam consists of 40 multiple-choice questions to be completed in 60 minutes. The passing score is 65% (26 out of 40). The exam is open book using only official training materials and is delivered online via the PeopleCert proctored platform.

How much does the AIOps Foundation certification cost?

The AIOps Foundation exam voucher is approximately $395 USD, though prices vary by country. Accredited training packages range from about $1,500 to $2,200 and typically include the exam voucher plus a Take2 retake. Confirm pricing on PeopleCert during checkout.

What is the difference between AIOps and MLOps?

AIOps applies AI and machine learning to IT operations problems such as event correlation, anomaly detection, and automated remediation. MLOps focuses on the lifecycle of machine learning models themselves — training, deployment, monitoring, and retraining. AIOps consumes ML, while MLOps operationalizes ML.

Is the AIOps Foundation exam open book?

Yes, the AIOps Foundation exam is open book. Candidates may use only the official training materials provided by their accredited training partner during the exam. Outside resources, internet searches, and personal notes are not permitted under PeopleCert's open-book rules.

How long is the AIOps Foundation certification valid?

AIOps Foundation certifications issued through PeopleCert are valid for 3 years under PeopleCert's Continuing Professional Development (CPD) program. To maintain certification, holders must accumulate CPD points or retake the exam before expiration.