Cost optimization strategies in GCP - Practice Problems & Coding Challenges

Challenge - 5 Problems

🧠 Conceptual

intermediate

Understanding Committed Use Discounts

Which statement best describes how Committed Use Discounts (CUDs) help reduce costs in Google Cloud Platform?

A CUDs apply only to on-demand resources and increase costs if usage exceeds the commitment.

B CUDs provide a discount when you commit to using a specific amount of resources for a 1 or 3 year term, regardless of actual usage.

C CUDs automatically reduce costs based on the number of users accessing the service each month.

D CUDs are discounts given only when you use preemptible virtual machines.

💡 Hint

Think about committing to a fixed amount of resource usage over time to get a lower price.

Committed Use Discounts require you to commit to a certain amount of resource usage for 1 or 3 years. In exchange, Google Cloud offers a lower price regardless of whether you use all the committed resources or not.

❓ Architecture

intermediate

Choosing Storage Classes for Cost Savings

You have data that is accessed rarely but must be retained for years. Which Google Cloud Storage class should you choose to minimize costs while meeting this requirement?

A Coldline Storage

B Nearline Storage

C Archive Storage

D Standard Storage

💡 Hint

Consider the storage class designed for long-term data retention with the lowest cost.

Archive Storage is the lowest-cost storage class designed for data accessed less than once a year and retained for long periods. It is ideal for archival data.

❓ security

advanced

Impact of Overprovisioned Resources on Cost and Security

What is a key risk of overprovisioning virtual machines in Google Cloud beyond just increased cost?

A Overprovisioning can lead to increased attack surface and potential security vulnerabilities.

B Overprovisioning automatically disables firewall rules, reducing security.

C Overprovisioning causes Google Cloud to throttle network traffic, impacting performance.

D Overprovisioning results in automatic deletion of unused resources after 30 days.

💡 Hint

Think about how having more resources than needed might affect security exposure.

Having more virtual machines than necessary increases the number of systems exposed to potential attacks, increasing the attack surface and security risks.

❓ service_behavior

advanced

Effect of Autoscaling on Cost Optimization

How does enabling autoscaling on a Google Kubernetes Engine (GKE) cluster help optimize costs?

A Autoscaling adjusts the number of nodes based on workload demand, reducing costs during low usage periods.

B Autoscaling permanently increases the number of nodes to handle peak traffic at all times.

C Autoscaling disables billing alerts to prevent cost notifications during scaling events.

D Autoscaling converts all nodes to preemptible instances automatically.

💡 Hint

Consider how scaling resources up and down affects billing.

Autoscaling dynamically adjusts the number of nodes in the cluster based on workload demand, so you only pay for what you need, saving costs during low traffic.

✅ Best Practice

expert

Designing a Cost-Effective Multi-Region Architecture

You need a multi-region architecture for high availability but want to minimize costs. Which design choice best balances availability and cost?

A Deploy full active-active clusters in all regions with synchronous replication.

B Deploy active resources in all regions but disable load balancing to reduce costs.

C Deploy all resources only in one region and rely on backups for disaster recovery.

D Use a primary region with active resources and a secondary region with cold standby resources.

💡 Hint

Think about how to keep costs low while still having a backup ready in another region.

Using a primary region with active resources and a secondary region with cold standby reduces costs by not running full active resources everywhere, yet still provides failover capability.