Compute Options and Trade Offs Questions

Covers the core compute models and how to evaluate them for application workloads. Candidates should be able to explain virtual machines where operators manage the operating system and runtime and which provide maximum control but require operating system patching capacity planning and infrastructure maintenance. Candidates should understand container technologies and container orchestration patterns that enable packaging portability and efficient resource use for microservices while introducing operational concerns around orchestration networking storage and deployment. The topic includes managed platform as a service offerings that abstract runtime and deployment responsibilities to reduce infrastructure management at the cost of lower level control and customization. It also covers serverless function models that provide event driven automatic scaling and pay per execution billing while presenting constraints such as cold start latency execution time limits and challenges for long running or highly stateful workloads. Candidates should know instance type selection and resource profiles such as general purpose compute optimized and memory optimized options; autoscaling strategies and performance and cost trade offs; startup latency and cold start implications; state management and persistence patterns; monitoring and observability complexity; security and operational responsibilities; and how team expertise application architecture and cost considerations influence the best choice of compute option for a given workload.