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AIOps-Foundation exam guide: DevOps Institute AIOps Foundation V1.0 & AIOps-Foundation actual test & AIOps-Foundation pass-for-sure

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Peoplecert AIOps-Foundation Exam Syllabus Topics:

Topic
Details

Topic 1

Implementing AIOps: This section of the exam measures the skills of project managers and covers challenges, trends, and ethical considerations organizations may face when deploying an AIOps initiative. It emphasizes strategic planning for successful implementation while addressing potential risks.

Topic 2

AIOps in the Organisation: This section of the exam measures the skills of organizational leaders and covers how AIOps can be integrated into existing frameworks. It discusses the impact of AIOps on DevOps practices, site reliability, security measures, and managing system complexity. A critical skill evaluated is recognizing the organizational changes required for successful AIOps implementation.

Topic 3

AIOps Fundamentals: This section of the exam measures the skills of IT operations professionals and covers the evolution of AIOps, differentiating it from IT Operations Analytics. It also explores the current stages of an AIOps system and its significance in modern IT environments. A key skill assessed is understanding the foundational concepts that drive AIOps adoption.

Topic 4

AIOps Use Cases and Organisational Mindset: This section of the exam measures the skills of the target audience and covers the challenges and opportunities associated with applying AIOps within organizations. It focuses on fostering an organizational mindset that embraces innovation through AIOps.

Topic 5

AIOps and Operations Metrics: This section of the exam measures the skills of performance analysts and covers industry-standard metrics used to quantify the outcomes of implementing AIOps solutions.

Topic 6

Core Technologies: Big Data: This section of the exam measures the skills of data engineers and covers an introduction to Big Data, including its definition, characteristics, and the Five V's (Volume, Velocity, Variety, Veracity, and Value). It also addresses various data sources and types relevant to AIOps. A key skill assessed is identifying different types of data utilized in AIOps environments.

Topic 7

Evaluating AIOps Impact: This section of the exam measures the skills of professionals and covers methods for measuring the effectiveness of AIOps deployments. It discusses how to assess potential benefits such as improved efficiency and reduced operational costs.

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Peoplecert DevOps Institute AIOps Foundation V1.0 Sample Questions (Q22-Q27):

NEW QUESTION # 22
A system that, given consistent input, may produce different outputs is called:

A. Random
B. Deterministic
C. Probabilistic
D. Algorithmic

Answer: C

Explanation:
Aprobabilisticsystem is one that may produce different outputs even with consistent input, due to inherent randomness or probabilistic decision-making mechanisms.
This behavior contrasts with deterministic systems, which always produce the same output for the same input.
Probabilistic systems are common in AI/ML models, where outcomes are based on statistical probabilities and training data.

NEW QUESTION # 23
Discovering unexpected changes in system behavior or performance is satisfied by this use case:

A. Event correlation
B. Anomaly detection
C. Alert noise reduction
D. Root cause analysis

Answer: B

Explanation:
Anomaly detectionrefers to identifying unexpected changes or deviations in system behavior or performance.
This use case is essential for proactively detecting issues that may not have predefined patterns or signatures, enabling faster incident resolution.
The DevOps Institute's AIOps Foundation materials describe anomaly detection as a key feature of AIOps platforms to enhance monitoring capabilities.

NEW QUESTION # 24
What can one use to track system status if applying SRE principles?

A. Error budgets
B. Number of alerts
C. User defect reports
D. Number of commits to a repo

Answer: A

Explanation:
In Site Reliability Engineering (SRE), error budgets are a key metric for tracking system status and balancing reliability with the pace of innovation.
* Error Budgets: An error budget quantifies the acceptable level of system unreliability over a specific period. It represents the permissible amount of downtime or failures, allowing teams to make informed decisions about deploying new features versus focusing on system stability.
By monitoring error budgets, organizations can effectively manage trade-offs between releasing new functionalities and maintaining system reliability, a practice supported by the DevOps Institute's AIOps Foundation principles.

NEW QUESTION # 25
Which of the following describes MLOps?

A. Implementing CI/CD. testing and accelerated development lifecycle to the machine learning model development
B. Applying artificial intelligence to IT Operations
C. A set of capabilities that primarily focuses on the governance and the full life cycle management of all Al and decision models
D. Software that thinks like a human through analysis and reasoning to perform complex tasks

Answer: A

Explanation:
MLOps, or Machine Learning Operations, applies DevOps principles such as Continuous Integration and Continuous Deployment (CI/CD) to the development and deployment of machine learning models. This approach emphasizes automation, testing, and streamlined workflows to accelerate the machine learning lifecycle, ensuring models are reliable, reproducible, and maintainable in production environments.
The AIOps Foundation course discusses the relationship between AIOps and MLOps, highlighting how integrating these practices can enhance IT operations.

NEW QUESTION # 26
Which of the 5Vs is concerned with data quality, missing data or false positive alerts?

A. Value
B. Volume
C. Veracity
D. Velocity

Answer: C

Explanation:
Veracity refers to the quality and trustworthiness of data, addressing issues such as data accuracy, consistency, and the presence of noise or false positives. In the context of AIOps, ensuring high data veracity is essential for effective machine learning and analytics, as poor-quality data can lead to incorrect insights and suboptimal decision-making.
The AIOps Foundation course highlights the significance of data veracity in building reliable AI-driven IT operations.

NEW QUESTION # 27
......

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