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Term
Capacity Planning
Definition
The ongoing process of matching organizational resources — people, technology, and infrastructure — to current and anticipated demand for services. Goal: exactly enough supply to meet demand. Too little = slowdowns and outages; too much = financial waste.
Concept
What are the two failure modes of capacity planning?
Answer
Undercapacity: demand exceeds supply → slowdowns, outages, lost revenue, SLA penalties.
Overcapacity: supply far exceeds demand → financial waste from idle hardware, idle cloud instances, over-hired staff.
Overcapacity: supply far exceeds demand → financial waste from idle hardware, idle cloud instances, over-hired staff.
Concept
Why is "people" the hardest dimension of capacity to scale?
Answer
Scaling up (hiring) requires recruiting → interviewing → onboarding → training: weeks to months before full productivity. Scaling down (layoffs) has financial, legal, and morale costs. Both directions are slow and expensive — unlike technology or cloud infrastructure which can change in minutes.
Concept
How does each service type scale for technology capacity?
Answer
Web services: Load balancer + multiple web servers; add/remove servers from pool.
Databases: Clustering (multiple SQL servers share load) or sharding/partitioning (split data across servers).
Cloud services: On-demand; provision in minutes; pay per use; elastic auto-scaling.
Databases: Clustering (multiple SQL servers share load) or sharding/partitioning (split data across servers).
Cloud services: On-demand; provision in minutes; pay per use; elastic auto-scaling.
Term
Database Sharding (Partitioning)
Definition
A database scaling technique that divides a single large database into smaller shards distributed across multiple servers. Each server handles a portion of the data (e.g., users A–M on server 1, N–Z on server 2). Horizontal scaling for databases. Tradeoff: cross-shard queries require application-layer joins; best designed from the beginning.
Concept
Physical infrastructure vs. cloud infrastructure — key differences?
Answer
Physical: Capital expense (CapEx); procurement takes weeks/months; exists regardless of utilization; can't scale quickly for unexpected demand.
Cloud: Operational expense (OpEx); provisioned in minutes; pay-per-use; instant scale up/down; ideal for variable or unpredictable workloads.
Cloud: Operational expense (OpEx); provisioned in minutes; pay-per-use; instant scale up/down; ideal for variable or unpredictable workloads.
Concept
Vertical scaling vs. horizontal scaling — key differences?
Answer
Vertical (scale up): Add CPU/RAM/storage to one server; no architectural change; has a ceiling; single point of failure remains.
Horizontal (scale out): Add more servers behind a load balancer; no ceiling; built-in redundancy; requires the workload to be distributable (stateless).
Horizontal (scale out): Add more servers behind a load balancer; no ceiling; built-in redundancy; requires the workload to be distributable (stateless).
Term
Elasticity (Auto-Scaling)
Definition
The ability of a system to automatically increase or decrease resources based on real-time demand without manual intervention. Cloud auto-scaling groups define min/max instances and scaling rules (e.g., add instance when CPU > 70% for 5 min). Resolves the fixed-capacity dilemma: pays only for what is actually needed, avoids both outages and waste.
Term
Right-Sizing
Definition
Matching provisioned resource size to actual usage — neither over-provisioned (wasting money) nor under-provisioned (causing performance problems). Involves reviewing actual CPU, memory, storage, and network utilization over time and selecting the smallest resource size that reliably meets performance requirements. Standard cloud cost optimization practice.
Concept
What roles do monitoring and forecasting play in capacity planning?
Answer
Monitoring: Collects real-time and historical metrics (CPU, memory, network, storage, response times); provides early warning before capacity is exhausted; identifies waste for right-sizing.
Forecasting: Uses trend analysis, seasonal patterns, and business growth projections to predict when capacity will be needed — enabling proactive planning before demand arrives, not reactive fire-fighting after outages.
Forecasting: Uses trend analysis, seasonal patterns, and business growth projections to predict when capacity will be needed — enabling proactive planning before demand arrives, not reactive fire-fighting after outages.