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AIOps-Foundation Valid Dumps Ppt - AIOps-Foundation Study Material

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AIOps-Foundation Study Material | AIOps-Foundation Exam Guide Materials

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Peoplecert AIOps-Foundation Exam Syllabus Topics:

Topic
Details

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

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 3

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 4

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 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.

Topic 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.

Topic 7

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 (Q20-Q25):

NEW QUESTION # 20
Which of the following is a characteristic of Machine Learning?

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

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 # 21
Surfacing relevant notifications and alerts from among large volumes of alerts is satisfied by this use case:

A. Alert noise reduction
B. Event correlation
C. Root cause analysis
D. Anomaly detection

Answer: A

Explanation:
Alert noise reductionis the use case focused on identifying and prioritizing relevant alerts from a large volume of notifications, which helps prevent alert fatigue for IT teams.
By reducing noise, AIOps enables teams to focus on significant issues that require immediate attention, improving operational efficiency.
The DevOps Institute's AIOps Foundation course highlights this capability as a core advantage of AIOps systems.

NEW QUESTION # 22
The various key areas in a system work together in the following loop:

A. Automate, iterate and fail fast
B. Observe, automate, act
C. Audit, document and restore
D. Observe, engage, act

Answer: D

Explanation:
In the context of AIOps, the system operates through a continuous loop comprising three key stages:
* Observe: This initial phase involves monitoring and collecting data from various IT environments. By gathering metrics, logs, and events, the system gains visibility into its operations, enabling the detection of anomalies or performance issues.
* Engage: Once data is collected, this stage focuses on analyzing and correlating the information to identify patterns or issues. Engagement involves applying machine learning algorithms and analytics to interpret the observed data, facilitating informed decision-making.
* Act: Based on the insights derived from the engagement phase, the system takes appropriate actions to resolve identified issues or optimize performance. This may include automated responses such as scaling resources, restarting services, or alerting IT personnel for further investigation.
This cyclical process ensures that IT operations are continuously monitored, analyzed, and improved, aligning with the principles outlined in the DevOps Institute's AIOps Foundation.

NEW QUESTION # 23
What is a big advantage of AlOps over ITOA?

A. It helps operations be reactive
B. It works with large datasets
C. It can predict the future
D. It can understand the past

Answer: C

Explanation:
A significant advantage ofAIOps (Artificial Intelligence for IT Operations)over traditionalIT Operations Analytics (ITOA)is its ability topredict future events. While ITOA focuses on analyzing historical data to understand past incidents, AIOps leverages advanced machine learning algorithms to forecast potential issues before they occur. This predictive capability enables proactive problem resolution, reducing downtime and improving system reliability. The DevOps Institute's AIOps Foundation course highlights this forward- looking approach as a key benefit of implementing AIOps in modern IT environments.

NEW QUESTION # 24
Which of the MELT data types is specific to a microservices based system?

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

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 # 25
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