Free PDF 2025 Peoplecert AIOps-Foundation: DevOps Institute AIOps Foundation V1.0 Newest Questions Exam

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Peoplecert DevOps Institute AIOps Foundation V1.0 Sample Questions (Q25-Q30):

NEW QUESTION # 25
The effectiveness of an AlOps implementation is dependent on what performances?

A. Machine Learning Model Performance
B. System complexity
C. In-houseAl skills
D. Number of data sources

Answer: A

Explanation:
The effectiveness of an AIOps implementation is significantly influenced by the performance of its machine learning (ML) models. These models are central to analyzing vast amounts of data, identifying patterns, and making predictions that enhance IT operations. Key factors include:
* Accuracy: The precision of the ML model in identifying and predicting issues directly impacts the reliability of the AIOps system.
* Training Data Quality: High-quality, relevant data is essential for training effective ML models.
* Model Adaptability: The ability of the model to adapt to new data and evolving system behaviors ensures sustained effectiveness.
Therefore, optimizing machine learning model performance is crucial for a successful AIOps deployment.

NEW QUESTION # 26
Targets of acceptable performance are defined in;

A. SLOs
B. KPIs
C. SLAs
D. SLIs

Answer: A

Explanation:
Service Level Objectives (SLOs)define specific, measurable targets for acceptable performance of a service.
They are critical components ofService Level Agreements (SLAs), providing clear benchmarks for service reliability and availability. By setting SLOs, organizations can align operational performance with business goals and customer expectations. The DevOps Institute's AIOps Foundation course outlines how establishing and monitoring SLOs is essential for effective service management and how AIOps can assist in meeting these objectives through enhanced monitoring and predictive analytics.

NEW QUESTION # 27
Data that does not have a predefined structure or format and is usually in the form of text-heavy content is usually described as:

A. Unstructured data
B. Structured data
C. Time-series data
D. Semi-structured data

Answer: A

Explanation:
Unstructured data lacks a predefined structure or format and is often text-heavy, including documents, emails, social media posts, and multimedia content. Unlike structured data, which resides in fixed fields within databases, unstructured data does not fit neatly into relational databases. The DevOps Institute's AIOps Foundation course highlights the challenges and importance of processing unstructured data in IT operations, as it contains valuable insights that can enhance decision-making and operational efficiency.

NEW QUESTION # 28
What can one use to track system status if applying SRE principles?

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

Answer: B

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 # 29
Which of the following is a characteristic of Machine Learning?

A. Uses small amounts of historical data to generate accurate inferences or prediction
B. A superset of Al
C. Gradually improves accuracy through iterative optimization
D. Requires explicit programming to learn

Answer: C

Explanation:
Machine Learning (ML) involves algorithms that learn from data and improve their performance over time through iterative optimization. Unlike traditional programming, where explicit instructions are coded, ML models identify patterns and make predictions based on historical data, refining their accuracy as they process more information.
The AIOps Foundation course covers core technologies of machine learning, emphasizing how these models enhance IT operations by automating tasks and providing predictive insights.

NEW QUESTION # 30
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