Name cloud cost optimization strategies.

Name cloud cost optimization strategies.

• A. Right-sizing instances, reserved instances, auto-scaling, shutting down idle resources
• B. Migrating all workloads to a single region
• C. Enabling all features regardless of usage
• D. Increasing instance sizes without monitoring

Answer: (A)

Cost optimization in cloud computing hinges on matching resources to demand and eliminating waste. The strongest approach combines right-sizing, reserved pricing, automatic scaling, and shutting down unused resources. Right-sizing ensures you pick a machine size that fits the actual workload, avoiding paying for idle CPU or memory. Reserved pricing (or savings plans) provides lower hourly rates for predictable workloads in exchange for commitment, reducing costs over time. Auto-scaling adjusts capacity in real time, scaling out during high demand and back in when demand drops, so you don’t pay for idle servers. Shutting down idle resources stops charges for environments that aren’t in use, such as testing or non-business hours. Other options don’t address ongoing waste: moving everything to a single region can create latency, data transfer costs, and compliance or resilience issues; enabling every feature regardless of usage adds unnecessary charges; increasing instance sizes without monitoring leads to overspending without ensuring better performance.

Cost optimization in cloud computing hinges on matching resources to demand and eliminating waste. The strongest approach combines right-sizing, reserved pricing, automatic scaling, and shutting down unused resources. Right-sizing ensures you pick a machine size that fits the actual workload, avoiding paying for idle CPU or memory. Reserved pricing (or savings plans) provides lower hourly rates for predictable workloads in exchange for commitment, reducing costs over time. Auto-scaling adjusts capacity in real time, scaling out during high demand and back in when demand drops, so you don’t pay for idle servers. Shutting down idle resources stops charges for environments that aren’t in use, such as testing or non-business hours.

Other options don’t address ongoing waste: moving everything to a single region can create latency, data transfer costs, and compliance or resilience issues; enabling every feature regardless of usage adds unnecessary charges; increasing instance sizes without monitoring leads to overspending without ensuring better performance.