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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

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

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 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 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 6

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.

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

NEW QUESTION # 27
Which definition BEST describes Big Data?

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

Answer: B

Explanation:
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.

NEW QUESTION # 28
What is an effective way for an AlOps system to provide visibility?

A. Using Slack or Teams
B. Through dashboards and metrics
C. Via email
D. With a pub/sub architecture

Answer: B

NEW QUESTION # 29
What can one use to track system status if applying SRE principles?

A. Number of commits to a repo
B. User defect reports
C. Number of alerts
D. Error budgets

Answer: D

Explanation:
In Site Reliability Engineering (SRE), error budgets are a key metric for tracking system status and balancing reliability with the pace of innovation.
* Error Budgets: An error budget quantifies the acceptable level of system unreliability over a specific period. It represents the permissible amount of downtime or failures, allowing teams to make informed decisions about deploying new features versus focusing on system stability.
By monitoring error budgets, organizations can effectively manage trade-offs between releasing new functionalities and maintaining system reliability, a practice supported by the DevOps Institute's AIOps Foundation principles.

NEW QUESTION # 30
How should the initial AlOps scope be defined?

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

Answer: B

Explanation:
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.

NEW QUESTION # 31
How did systems architecture transform?

A. From object oriented languages to functional languages
B. From docker to OCI
C. From monoliths to microservices
D. From cloud to edge

Answer: C

Explanation:
System architecture has evolved significantly, transitioning from monolithic structures to microservices.
* Monolithic Architecture: In this traditional model, applications are built as a single, unified unit. While simpler to develop initially, monoliths can become cumbersome to manage, scale, and update as they grow in complexity.
* Microservices Architecture: This modern approach decomposes applications into smaller, independent services that communicate through APIs. Each microservice handles a specific function, allowing for greater flexibility, scalability, and ease of deployment.

NEW QUESTION # 32
......

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