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Designing for Performance and Scalability (GCP PCA) Flashcards
GCP Professional Cloud Architect Flashcards
| Front | Back |
| Design considerations for globally distributed systems | Ensure consistent performance with low latency and regional autonomy using GCP’s global infrastructure |
| Design for scalability in GCP | Prioritize horizontal scaling using managed GCP services like Compute Engine and Kubernetes Engine |
| Difference between regional and zonal services in GCP? | Regional services span multiple zones for high-availability, zonal services are confined to a single zone |
| How can Global Load Balancing improve system scalability? | Directs user traffic efficiently using Anycast IP to maximize performance globally |
| How can partitioning help large datasets? | Improves query performance by dividing data into manageable sections based on criteria |
| How do service quotas affect scalability? | Limits resource usage to prevent overuse but may need adjustment for high workloads |
| How does caching improve performance? | Reduces latency and database load by storing frequently accessed data closer to the client |
| How does Cloud Pub/Sub support scalability? | By decoupling components to handle unpredictable and high-throughput workloads |
| How does Google Bigtable handle scalability? | Scales horizontally to handle petabytes of data for low-latency, high-throughput workloads |
| How does Google Kubernetes Engine ensure high availability? | By distributing workloads across multiple nodes and zones automatically |
| How does Google’s global network assist scalability? | By providing low-latency connections between regions and auto-scaling support |
| How does horizontal partitioning differ from vertical partitioning? | Horizontal partitioning divides data rows-wise, while vertical partitioning splits data column-wise |
| How does managed instance groups assist in scalability? | Scales compute instances up or down automatically based on load conditions |
| How does sharding improve scalability? | By splitting a database into smaller, manageable pieces distributed across different resources |
| How to achieve eventual consistency? | Use asynchronous replication and reconciliation mechanisms |
| Importance of fault tolerance in systems design | Ensures continuity of service in the event of infrastructure or component failure |
| What is a cold failover strategy? | A failover method where resources are provisioned only after a disaster occurs |
| What is a disaster recovery strategy in GCP? | A plan to recover services and data using backups, regions, and zones after a failure |
| What is a key principle for designing high-availability systems? | Eliminate single points of failure using managed services and redundancy |
| What is auto-scaling in GCP? | Auto-scaling dynamically adjusts compute resources based on traffic or workload |
| What is blue-green deployment? | A release strategy that ensures zero downtime by switching between two environments during updates |
| What is the benefit of preemptible VMs in scaling? | They offer cost-effective compute capacity for fault-tolerant and batch processing workloads |
| What is the CAP theorem? | States that a distributed system can only guarantee two of three: Consistency, Availability, and Partition tolerance |
| What is the importance of latency monitoring? | Identifies delays in system or network response to optimize user experience |
| What is the importance of SLAs in performance design? | Guarantees uptime and performance levels for GCP services |
| What is the purpose of Cloud Spanner? | To provide a fully managed, horizontal-scaling, and globally consistent database |
| What is the purpose of rate limiting in application design? | Prevents system overloading and ensures fair resource distribution to clients |
| What is the purpose of using a circuit breaker in cloud design? | To prevent cascading failures by stopping request forwarding during system overloads |
| What is the role of Cloud Interconnect in hybrid scaling? | Provides high-speed, secure connections between on-premise and Google Cloud resources |
| What is the role of Cloud Monitoring in performance tuning? | It helps track, visualize, and optimize metrics like latency, throughput, and errors |
| What is the role of VPC in scalability? | Allows you to design scalable and secure network architectures across regions |
| What is the significance of Backup and DR with Cloud Storage? | Ensures secure, scalable, and durable data storage for recovery in case of failures |
| When to use Cloud Functions over Compute Engine? | For event-driven tasks and lightweight compute needs without managing servers |
| Why choose multi-regional storage? | For high availability and data redundancy across multiple regions |
| Why implement a hybrid cloud architecture? | Combines on-premise and GCP resources to manage cost, speed, and scalability requirements |
| Why use Cloud CDN? | To cache content at the edge for lower latency and improved performance |
| Why use Cloud Run for scalable applications? | Provides serverless compute that automatically scales with incoming requests |
| Why use Cloud SQL for transactional workloads? | Provides managed relational databases with strong consistency and replication for reliable performance |
| Why use Google Cloud Load Balancer? | To distribute traffic globally and ensure high availability and scalability |
| Why use Read Replicas for databases? | To offload read-heavy workloads and improve database performance and scaling |
Front
What is the role of VPC in scalability?
Click the card to flip
Back
Allows you to design scalable and secure network architectures across regions
Front
What is the role of Cloud Interconnect in hybrid scaling?
Back
Provides high-speed, secure connections between on-premise and Google Cloud resources
Front
Difference between regional and zonal services in GCP?
Back
Regional services span multiple zones for high-availability, zonal services are confined to a single zone
Front
How does Google Bigtable handle scalability?
Back
Scales horizontally to handle petabytes of data for low-latency, high-throughput workloads
Front
What is the purpose of rate limiting in application design?
Back
Prevents system overloading and ensures fair resource distribution to clients
Front
What is the CAP theorem?
Back
States that a distributed system can only guarantee two of three: Consistency, Availability, and Partition tolerance
Front
What is the importance of latency monitoring?
Back
Identifies delays in system or network response to optimize user experience
Front
What is blue-green deployment?
Back
A release strategy that ensures zero downtime by switching between two environments during updates
Front
Why use Google Cloud Load Balancer?
Back
To distribute traffic globally and ensure high availability and scalability
Front
How to achieve eventual consistency?
Back
Use asynchronous replication and reconciliation mechanisms
Front
How does managed instance groups assist in scalability?
Back
Scales compute instances up or down automatically based on load conditions
Front
How can partitioning help large datasets?
Back
Improves query performance by dividing data into manageable sections based on criteria
Front
Design considerations for globally distributed systems
Back
Ensure consistent performance with low latency and regional autonomy using GCP’s global infrastructure
Front
What is the purpose of using a circuit breaker in cloud design?
Back
To prevent cascading failures by stopping request forwarding during system overloads
Front
What is the benefit of preemptible VMs in scaling?
Back
They offer cost-effective compute capacity for fault-tolerant and batch processing workloads
Front
What is a disaster recovery strategy in GCP?
Back
A plan to recover services and data using backups, regions, and zones after a failure
Front
How does caching improve performance?
Back
Reduces latency and database load by storing frequently accessed data closer to the client
Front
Why use Cloud SQL for transactional workloads?
Back
Provides managed relational databases with strong consistency and replication for reliable performance
Front
Why choose multi-regional storage?
Back
For high availability and data redundancy across multiple regions
Front
How do service quotas affect scalability?
Back
Limits resource usage to prevent overuse but may need adjustment for high workloads
Front
What is a cold failover strategy?
Back
A failover method where resources are provisioned only after a disaster occurs
Front
Importance of fault tolerance in systems design
Back
Ensures continuity of service in the event of infrastructure or component failure
Front
How does Google Kubernetes Engine ensure high availability?
Back
By distributing workloads across multiple nodes and zones automatically
Front
How does Cloud Pub/Sub support scalability?
Back
By decoupling components to handle unpredictable and high-throughput workloads
Front
What is the importance of SLAs in performance design?
Back
Guarantees uptime and performance levels for GCP services
Front
How does Google’s global network assist scalability?
Back
By providing low-latency connections between regions and auto-scaling support
Front
Design for scalability in GCP
Back
Prioritize horizontal scaling using managed GCP services like Compute Engine and Kubernetes Engine
Front
Why use Cloud Run for scalable applications?
Back
Provides serverless compute that automatically scales with incoming requests
Front
How does sharding improve scalability?
Back
By splitting a database into smaller, manageable pieces distributed across different resources
Front
How can Global Load Balancing improve system scalability?
Back
Directs user traffic efficiently using Anycast IP to maximize performance globally
Front
What is the role of Cloud Monitoring in performance tuning?
Back
It helps track, visualize, and optimize metrics like latency, throughput, and errors
Front
Why use Read Replicas for databases?
Back
To offload read-heavy workloads and improve database performance and scaling
Front
When to use Cloud Functions over Compute Engine?
Back
For event-driven tasks and lightweight compute needs without managing servers
Front
What is auto-scaling in GCP?
Back
Auto-scaling dynamically adjusts compute resources based on traffic or workload
Front
How does horizontal partitioning differ from vertical partitioning?
Back
Horizontal partitioning divides data rows-wise, while vertical partitioning splits data column-wise
Front
What is the purpose of Cloud Spanner?
Back
To provide a fully managed, horizontal-scaling, and globally consistent database
Front
What is the significance of Backup and DR with Cloud Storage?
Back
Ensures secure, scalable, and durable data storage for recovery in case of failures
Front
Why use Cloud CDN?
Back
To cache content at the edge for lower latency and improved performance
Front
Why implement a hybrid cloud architecture?
Back
Combines on-premise and GCP resources to manage cost, speed, and scalability requirements
Front
What is a key principle for designing high-availability systems?
Back
Eliminate single points of failure using managed services and redundancy
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This deck emphasizes designing scalable and reliable systems, factoring in performance, availability, and disaster recovery strategies with GCP tools.