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AIOps-Foundation最新題庫，AIOps-Foundation在線題庫

在這個資訊時代，IT行業被很多人關注，但是在如今人才濟濟的社會裏任然比較缺乏IT人。很多公司都招聘IT人才，他們一般考察IT人才的能力會參考他們擁有的IT相關認證證書，所以擁有一些IT相關的認證證書是受很多公司歡迎的。但是這些認證證書也不是很容易就能拿到的。Peoplecert AIOps-Foundation 就是一個相當有難度的認證考試，雖然很多人報名參加Peoplecert AIOps-Foundation考試，但是通過率並不是很高。

Peoplecert AIOps-Foundation 考試大綱：

主題
簡介

主題 1

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.

主題 2

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.

主題 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.

主題 4

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.

主題 5

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.

主題 6

Core Technologies: Machine Learning (ML): This section of the exam measures the skills of machine learning practitioners and covers the role of AI and machine learning in AIOps. It includes discussions on supervised versus unsupervised learning, differences between ML and analytics, and training models for practical applications. A vital skill evaluated is understanding how to apply machine learning techniques to enhance operational efficiency.

>> AIOps-Foundation最新題庫 <<

AIOps-Foundation在線題庫 - AIOps-Foundation考古題介紹

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最新的 PeopleCert DevOps AIOps-Foundation 免費考試真題 (Q39-Q44):

問題 #39
Which of the following describes MLOps?

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

答案：B

解題說明：
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.

問題 #40
The incident related metric MTTD means:

A. Mean Time to Distribution
B. Mean time to Detect
C. Mean Time to Deployment
D. Mean Time to Delivery

答案：B

解題說明：
Mean Time to Detect (MTTD)is an incident management metric that measures the average time taken to identify an issue within a system. A lower MTTD indicates a more responsive monitoring system, allowing for quicker remediation and minimizing potential impact. Improving MTTD is crucial for maintaining system reliability and performance. The DevOps Institute's AIOps Foundation course emphasizes the importance of MTTD in evaluating the effectiveness of IT operations and the implementation of AIOps solutions to enhance detection capabilities.

問題 #41
At which stage does the data pipeline deduplicate data?

A. Cleaning/integration
B. Enrichment/filtering
C. Storage
D. Extraction/collection

答案：A

解題說明：
In a data pipeline, deduplication occurs during the cleaning and integration stage. This process involves identifying and removing duplicate records to ensure data quality and accuracy. By eliminating redundancies, organizations can maintain a single source of truth, leading to morereliable analytics and decision-making.
The DevOps Institute's AIOps Foundation course underscores the importance of data cleaning and integration in preparing data for effective analysis and operational use.

問題 #42
How should the initial AlOps scope be defined?

A. Small but meaningful scope that will provide data points to validate success
B. AlOps implementation is iterative and should not have a defined scope
C. All inclusive of organizational wide long term objectives
D. All of the above

答案：A

解題說明：
Defining an initial AIOps scope that is small yet meaningful allows organizations to pilot the implementation, gather valuable data, and assess its effectiveness. This approach facilitates:
* Validation: Assessing the success of the AIOps deployment in a controlled environment.
* Iterative Improvement: Making informed adjustments before broader implementation.
* Resource Management: Efficient allocation of resources and minimizing potential risks.
Starting with a focused scope enables organizations to build confidence and expertise, paving the way for successful, scaled AIOps adoption.
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.

問題 #43
Which definition BEST describes Big Data?

A. Data sets thatlive in data warehouses or lakes
B. Data sets that are "too large" or diverse causing traditional data processing techniques to be ineffective
C. Data sets of structured data that have grown over time
D. Data sets that are so large they can only be interrogated using Al

答案：B

解題說明：
Big Data refers to data sets that are so large, fast, or complex that traditional data processing methods are inadequate to handle them. This concept is characterized by the Five V's:
* Volume: The sheer amount of data generated.
* Velocity: The speed at which new data is produced and needs to be processed.
* Variety: The different types of data (structured, unstructured, semi-structured).
* Veracity: The quality and accuracy of the data.
* Value: The usefulness of the data for decision-making.
In the context of AIOps, understanding Big Data is crucial as it involves combining big data analytics with machine learning algorithms to enhance IT operations.

問題 #44
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AIOps-Foundation在線題庫: https://www.testpdf.net/AIOps-Foundation.html