PASS PEOPLECERT AIOPS-FOUNDATION EXAM EASILY WITH QUESTIONS AND ANSWERS

Pass Peoplecert AIOps-Foundation Exam Easily With Questions And Answers

Pass Peoplecert AIOps-Foundation Exam Easily With Questions And Answers

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Tags: Valid AIOps-Foundation Exam Guide, AIOps-Foundation Exam Quick Prep, Reliable AIOps-Foundation Exam Prep, Cheap AIOps-Foundation Dumps, AIOps-Foundation Reliable Torrent

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Peoplecert AIOps-Foundation Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 2
  • 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 3
  • 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 4
  • 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 5
  • 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.

Peoplecert DevOps Institute AIOps Foundation V1.0 Sample Questions (Q30-Q35):

NEW QUESTION # 30
Which pattern requires Bib Data?

  • A. Both a and b
  • B. ITOA
  • C. None of the above
  • D. AlOps

Answer: A

Explanation:
Both AIOps (Artificial Intelligence for IT Operations) and ITOA (IT Operations Analytics) require the utilization of big data to function effectively.
AIOps and Big DataAIOps combines big data and machine learning to automate IT operations processes, including event correlation, anomaly detection, and causality determination. By analyzing large volumes of data from various IT operations sources, AIOps provides real-time insights and alerts, enabling IT teams to identify and address issues proactively.
IT Operations Analytics (ITOA) and Big DataITOA involves gathering, processing, analyzing, and interpreting data from various IT operations sources to guide decisions and predict potential issues. It applies big data analytics to large datasets to produce business insights, enhancing the ability to manage complex IT environments.
ConclusionBoth AIOps and ITOA leverage big data to enhance IT operations by providing deeper insights and enabling proactive management of IT systems. Therefore, the correct answer is C. Both a and b.


NEW QUESTION # 31
What is the meaning of Digital Transformation?

  • A. Replacing all analog systems with digital equivalents
  • B. Adoption of digital technologies for accelerated Innovation and improved customer experience
  • C. Refactoring all software to a newer technology stack
  • D. Replacing all human operators with artificial Intelligence

Answer: B

Explanation:
Digital Transformation refers to the strategic adoption of digital technologies to fundamentally change how organizations operate, deliver value to customers, and foster innovation.
It is not about simply replacing analog systems or eliminating human operators but integrating technology to improve efficiency, decision-making, and customer satisfaction.
DevOps Institute defines it as leveraging tools, automation, and cultural shifts to enable faster and more effective innovation cycles.
References highlight improved agility, scalability, and customer-focused outcomes as key objectives of Digital Transformation.


NEW QUESTION # 32
The effectiveness of an AlOps implementation is dependent on what performances?

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

Answer: C

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 # 33
What is Step 1 in the AlOps Capability Scale?

  • A. Automate toils using Al Insights
  • B. Add automation for self-healing
  • C. Reduce MTTR through noise reduction
  • D. Use chaos engineering for antifragility

Answer: C

Explanation:
In the AIOps Capability Scale,Step 1focuses on reducing Mean Time to Repair (MTTR) by minimizing alert noise. This initial phase involves implementing AIOps solutions to filter and correlate alerts, thereby decreasing the volume of irrelevant notifications. By reducing noise, IT teams can concentrate on critical issues, leading to faster incident resolution and improved system reliability. This foundational step sets the stage for more advanced AIOps capabilities.


NEW QUESTION # 34
Which of the 5Vs is concerned with data quality, missing data or false positive alerts?

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

Answer: A

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 # 35
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