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Monitoring and Optimization of Resources Flashcards
Microsoft Fabric Data Engineer Associate DP-700 Flashcards
| Front | Back |
| Best practice for monitoring data pipelines | Regularly check data pathway performance and identify bottlenecks |
| Best way to identify resource hotspots | Use monitoring tools to analyze patterns and pinpoint overused resources |
| How can automation aid in optimization efforts | Automating routine tasks reduces manual workload and ensures consistent results |
| How do caching strategies improve performance | By reducing the need to retrieve data repeatedly from slow storage |
| How does performance monitoring work in Microsoft Fabric | It tracks system metrics like memory usage, CPU load, and query performance |
| How does proper indexing improve performance | Speeds up data retrieval and reduces processing time in databases |
| Key benefit of optimizing resources | Improved efficiency and reduced operational costs |
| Key metric to track for query optimization | Query duration and resource utilization |
| Purpose of resource tagging | Categorize and track resources for better management and monitoring |
| Role of predictive analytics in optimization | Anticipating future usage trends to allocate resources accordingly |
| What is a resource pool in Microsoft Fabric | A shared pool of CPU and memory resources for tasks across a workload |
| What is capacity planning | Estimating resources required to meet future demand |
| What is governance in resource monitoring | Policies and controls to ensure efficient, secure, and compliant resource use |
| What is load balancing | Distributing workloads across multiple resources to improve performance and fault tolerance |
| What is monitoring in resource optimization | Tracking system performance to identify issues and areas for improvement |
| What is the difference between vertical and horizontal scaling | Vertical scaling adds resources to a single system, while horizontal scaling adds systems to the pool |
| What is throttling in resource management | Reducing resource usage when system limits are reached to maintain stability |
| What to do when a system experiences high latency | Analyze resource usage and optimize queries or increase allocated resources |
| What tools are used for monitoring in Microsoft Fabric | Power BI, Fabric Monitoring Dashboard, and built-in analytics features |
| Why is scaling important in resource optimization | It ensures systems can handle increased workloads without performance degradation |
Front
What is throttling in resource management
Click the card to flip
Back
Reducing resource usage when system limits are reached to maintain stability
Front
What is the difference between vertical and horizontal scaling
Back
Vertical scaling adds resources to a single system, while horizontal scaling adds systems to the pool
Front
What tools are used for monitoring in Microsoft Fabric
Back
Power BI, Fabric Monitoring Dashboard, and built-in analytics features
Front
How does performance monitoring work in Microsoft Fabric
Back
It tracks system metrics like memory usage, CPU load, and query performance
Front
How do caching strategies improve performance
Back
By reducing the need to retrieve data repeatedly from slow storage
Front
How does proper indexing improve performance
Back
Speeds up data retrieval and reduces processing time in databases
Front
Why is scaling important in resource optimization
Back
It ensures systems can handle increased workloads without performance degradation
Front
How can automation aid in optimization efforts
Back
Automating routine tasks reduces manual workload and ensures consistent results
Front
Purpose of resource tagging
Back
Categorize and track resources for better management and monitoring
Front
What is capacity planning
Back
Estimating resources required to meet future demand
Front
Best practice for monitoring data pipelines
Back
Regularly check data pathway performance and identify bottlenecks
Front
What to do when a system experiences high latency
Back
Analyze resource usage and optimize queries or increase allocated resources
Front
Best way to identify resource hotspots
Back
Use monitoring tools to analyze patterns and pinpoint overused resources
Front
Role of predictive analytics in optimization
Back
Anticipating future usage trends to allocate resources accordingly
Front
Key benefit of optimizing resources
Back
Improved efficiency and reduced operational costs
Front
What is a resource pool in Microsoft Fabric
Back
A shared pool of CPU and memory resources for tasks across a workload
Front
What is governance in resource monitoring
Back
Policies and controls to ensure efficient, secure, and compliant resource use
Front
Key metric to track for query optimization
Back
Query duration and resource utilization
Front
What is monitoring in resource optimization
Back
Tracking system performance to identify issues and areas for improvement
Front
What is load balancing
Back
Distributing workloads across multiple resources to improve performance and fault tolerance
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This deck explores methods for monitoring system performance and optimizing resources to ensure efficient data engineering operations within Microsoft Fabric.