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Cloud Compute Cheat Sheet

Cloud Compute Cheat Sheet

Back to Cloud Computing
Updated 2026-03-17
Next Topic: Cloud Computing Basics Cheat Sheet

Cloud compute refers to the on-demand provisioning of computing resources (processors, memory, storage, and networking) from cloud providers as virtual machines or bare metal instances. It enables organizations to scale computational capacity dynamically without upfront hardware investment, paying only for what they use. At its core, cloud compute transforms fixed infrastructure costs into variable operational expenses while offering unprecedented flexibility in resource allocation. The fundamental distinction between instance types — general purpose, compute optimized, memory optimized, storage optimized, and accelerated computing — determines workload performance and cost efficiency, making instance selection the single most important decision in cloud architecture.

What This Cheat Sheet Covers

This topic spans 14 focused tables and 93 indexed concepts. Below is a complete table-by-table outline of this topic, spanning foundational concepts through advanced details.

Table 1: Instance Type FamiliesTable 2: Pricing ModelsTable 3: Processor ArchitecturesTable 4: Scaling StrategiesTable 5: Instance Lifecycle OperationsTable 6: Instance ConfigurationTable 7: Burstable PerformanceTable 8: Enhanced NetworkingTable 9: Storage OptionsTable 10: Network & IP ManagementTable 11: Health & MonitoringTable 12: Rightsizing & OptimizationTable 13: Security & ComplianceTable 14: Specialized Workloads

Table 1: Instance Type Families

FamilyExampleDescription
General Purpose
AWS m7i.xlarge
Azure D-series
GCP n2-standard-4
• Balanced CPU-to-memory ratio (typically 1:4) suitable for web servers, small databases, and development environments
• provides consistent baseline performance without specialization.
Compute Optimized
AWS c7g.2xlarge
Azure F-series
GCP c2-standard-8
• High CPU-to-memory ratio (1:2) for batch processing, HPC, and CPU-intensive workloads
• delivers up to 30% better compute performance than general purpose at similar cost.
Memory Optimized
AWS r7g.4xlarge
Azure E-series
GCP m2-ultramem-208
• High memory-to-CPU ratio (1:8 or higher) for in-memory databases, real-time analytics, and large-scale caching
• optimized for memory-intensive workloads requiring fast data access.
Storage Optimized
AWS i4i.8xlarge
Azure L-series
GCP n2-highmem-80
• High-performance NVMe SSD storage with low-latency random I/O
• designed for NoSQL databases, data warehousing, and log processing requiring sustained IOPS.

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