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Pass Guaranteed AIOps-Foundation - Trustable DevOps Institute AIOps Foundation V1.0 Latest Dumps Ebook

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Peoplecert AIOps-Foundation Exam Syllabus Topics:

Topic
Details

Topic 1

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 2

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.

Topic 3

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 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.

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Peoplecert DevOps Institute AIOps Foundation V1.0 Sample Questions (Q17-Q22):

NEW QUESTION # 17
Which pattern requires Bib Data?

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

Answer: B

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 # 18
Which algorithm Type is helpful in categorizing data in a supervised learning model?

A. Classification
B. Clustering
C. Association
D. Regression

Answer: A

Explanation:
In supervised learning models,classification algorithmsare employed to categorize data into distinct classes or labels. These algorithms learn from a labeled dataset, where the input data is paired with the correct output, enabling the model to make accurate predictions on new, unseen data. For instance, classification can be used to determine whether an email is 'spam' or 'not spam'. This method is fundamental in various applications, including fraud detection, image recognition, and medical diagnosis. The DevOps Institute's AIOps Foundation course emphasizes the importance of classification in building predictive models that enhance IT operations.

NEW QUESTION # 19
Systems operation became elastic and dynamic thanks to:

A. Adoption of thecloud
B. Machine Learning
C. Contamenzation
D. Linux

Answer: A

Explanation:
The adoption of cloud computing has transformed system operations, making them more elastic and dynamic.
Cloud platforms provide on-demand resource allocation, enabling systems to scale up or down based on workload requirements. This elasticity allows organizations to efficiently manage resources, reduce costs, and respond swiftly to changing demands. The dynamic nature of cloud services supports continuous integration and deployment, enhancing operational agility. The DevOps Institute's AIOps Foundation course emphasizes the significance of cloud adoption in modernizing IT operations and achieving operational excellence.

NEW QUESTION # 20
Which of the MELT data types is specific to a microservices based system?

A. Traces
B. Logs
C. Events
D. Metrics

Answer: A

Explanation:
In microservices-based systems, "Traces" are a specific MELT (Metrics, Events, Logs, Traces) data type.
Traces track the flow of requests through various services, providing visibility into the interactions and performance of microservices. This tracing is crucial for diagnosing issues, understanding system behavior, and optimizing performance in complex, distributed environments. The DevOps Institute's AIOps Foundation course emphasizes the role of traces in observability practices, enabling teams to monitor and improve microservices architectures effectively.
For more detailed information, refer to the DevOps Institute's AIOps Foundation course materials.

NEW QUESTION # 21
The incident related metric MTTD means:

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

Answer: A

Explanation:
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.

NEW QUESTION # 22
......

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