PREPARE FOR AIOPS-FOUNDATION WITH PEOPLECERT'S REALISTIC EXAM QUESTIONS AND GET ACCURATE ANSWERS

Prepare for AIOps-Foundation with Peoplecert's Realistic Exam Questions and Get Accurate Answers

Prepare for AIOps-Foundation with Peoplecert's Realistic Exam Questions and Get Accurate Answers

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Tags: Test AIOps-Foundation Sample Questions, AIOps-Foundation New Practice Questions, Certification AIOps-Foundation Dumps, Test AIOps-Foundation Quiz, Dump AIOps-Foundation File

AIOps-Foundation practice exam will provide you with wholehearted service throughout your entire learning process. This means that unlike other products, the end of your payment means the end of the entire transaction our Peoplecert AIOps-Foundation Learning Materials will provide you with perfect services until you have successfully passed the DevOps Institute AIOps Foundation V1.0 AIOps-Foundation exam.

Peoplecert AIOps-Foundation Exam Syllabus Topics:

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

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AIOps-Foundation New Practice Questions - Certification AIOps-Foundation Dumps

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Peoplecert DevOps Institute AIOps Foundation V1.0 Sample Questions (Q27-Q32):

NEW QUESTION # 27
What impact on incident related metrics is the desired outcome from AlOps implementation?

  • A. Decrease in MTTA. Decrease in MTTR and Increase in MTBF
  • B. Decrease in MTTA, Increase in MTTR and Decrease in MTBF
  • C. Decrease in MTTA. Decrease in MTTR and Decrease in MTBF
  • D. Increase in MTTA, Increase in MTTR and Decrease in MTBF

Answer: A

Explanation:
AIOps aims to improve incident-related metrics by:
* Decreasing Mean Time to Acknowledge (MTTA): Faster detection and acknowledgment of issues.
* Decreasing Mean Time to Resolve (MTTR): Quicker resolution through automation and actionable insights.
* Increasing Mean Time Between Failures (MTBF): Enhanced system reliability and reduced frequency of failures.
These improvements lead to more reliable IT operations, as highlighted in the DevOps Institute's AIOps Foundation course.


NEW QUESTION # 28
Reactive Operations rely on:

  • A. Leading indicators
  • B. Prediction and inference
  • C. Lagging indicators
  • D. Big Data

Answer: C

Explanation:
Reactive operations focus on responding to incidents after they have occurred, relying on lagging indicators- metrics that reflect past events or performance. These indicators, such as system downtime reports or post- incident analyses, provide insights into issues that have already impacted the system. While useful for understanding and addressing past problems, reliance solely on lagging indicators can lead to delayed responses and prolonged downtime. AIOps aims to shift operations from reactive to proactive by utilizing leading indicators and predictive analytics to anticipate and prevent issues before they occur.


NEW QUESTION # 29
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. Structured data
  • B. Unstructured data
  • C. Time-series data
  • D. Semi-structured data

Answer: B

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 # 30
Which Al models can mimic human narrative?

  • A. AlOps
  • B. Large language
  • C. Generative
  • D. Big data

Answer: C

Explanation:
In the realm of artificial intelligence (AI), various models are designed to perform specific tasks.
Understanding these models is crucial, especially in the context of AIOps (Artificial Intelligence for IT Operations). Here's a breakdown of the options provided:
* Big Data: This term refers to the vast volumes of structured and unstructured data generated daily. Big Data itself is not an AI model but serves as a foundational element for AI and machine learning models, providing the necessary data for analysis and learning.
DevOps Institute
* Large Language Models: These are AI models trained on extensive text data to understand and generate human-like language. While they can produce coherent text, their primary function is to process and generate language based on input data. They are a subset of generative models but not the only type capable of mimicking human narratives.
* Generative Models: These AI models are designed to create new data instances that resemble a given dataset. In the context of language, generative models can produce human-like narratives, making them capable of mimicking human storytelling and conversation. Generative models encompass various architectures, including Generative Adversarial Networks (GANs) and certain types of Large Language Models.
* AIOps: This refers to the application of AI in IT operations to enhance and automate processes.
AIOps itself is not an AI model but a practice that leverages AI models, including generative models, to improve IT operations.
DevOps Institute
Therefore, the AI models that can mimic human narrative are Generative Models. These models are specifically designed to generate new, human-like content, making them suitable for tasks involving the creation of narratives.
For a more in-depth understanding of AI models and their applications in IT operations, the DevOps Institute's AIOps Foundation course provides comprehensive insights into how AI, including generative models, can be integrated into organizational frameworks to enhance IT operations.


NEW QUESTION # 31
With AlOps, offering aggressive SLAs results in:

  • A. Increased risk
  • B. There is no relation
  • C. No change to risk
  • D. Decreased risk

Answer: A

Explanation:
Offering aggressive Service Level Agreements (SLAs) with AIOps can lead to increased risk if the organization lacks the necessary infrastructure and processes to meet these stringent targets. Unrealistic SLAs may result in overcommitment, leading to potential service breaches, customer dissatisfaction, and reputational damage. It's essential to set achievable SLAs that align with the organization's capabilities, even when leveraging advanced tools like AIOps.


NEW QUESTION # 32
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