Cloud elasticity
Cloud elasticity is the ability of cloud infrastructure or services to dynamically increase or decrease resource capacity in response to changing workload demand.
Think Like a CTO
The ability of a system to automatically adjust provisioned resources in response to changing demand.
- How it is used
- Uses elasticity to assess whether cloud spending and capacity respond to changing demand.
- How deep it goes
- Provides operational warning signs but does not detail automatic scaling mechanisms.
- Examples
- Uses flat monthly bills in seasonal businesses, release downtime, and disk-space shortages as warning signs.
- What you can do after
- Evaluate/understand whether cloud operations adjust capacity and costs to demand.
Google Anthos in Action
Elasticity is the ability to automatically adjust resources or service capacity in response to changing demand.
- How it is used
- Deploys elasticity at the individual microservice level to match capacity with changing demand.
- How deep it goes
- Defines automatic scale-up and scale-down behavior, but does not detail metrics, thresholds, or configuration procedures.
- Examples
- Contrasts scaling an individual service with scaling an entire virtual machine during demand changes.
- What you can do after
- Operate services that scale capacity with demand and reduce capacity during idle periods.
Read how Google Anthos in Action explains cloud elasticity →
Amazon Web Services in Action, Third Edition: An in-depth guide to AWS
Elasticity is the ability of a system to increase or decrease resource capacity in response to changing demand.
- How it is used
- Replaces fixed capacity planning with on-demand resource adjustment for changing application loads.
- How deep it goes
- Explains the motivation and AWS implementation with EC2 Auto Scaling groups and policies, without detailing policy configuration.
- Examples
- Uses a web shop's daytime, weekend, weekday, and seasonal traffic to illustrate adding and removing EC2 capacity.
- What you can do after
- Operate/configure EC2 Auto Scaling groups and scaling policies to adjust a virtual-machine fleet to current demand.
Kafka for Architects
Elasticity is the ability of a system to dynamically add or remove resources in response to changing workload demand.
- How it is used
- Frames deployment and storage architecture as choices affecting Kafka’s ability to match capacity to workload demand.
- How deep it goes
- Defines elasticity and explains broker scaling through remote storage, while noting diskless topics’ current feature limitations.
- Examples
- Uses on-premises versus cloud deployment and diskless topics writing records to shared object storage.
- What you can do after
- Evaluate Kafka deployment and storage designs against scaling needs, compliance constraints, cost, and feature limitations.
Related concepts
- reactive systempart of · A reactive system is a distributed software system designed to remain responsive through resiliency, elasticity, and asynchronous message-driven communication.
- reliabilityaddresses · Reliability is the ability of a system or process to perform its intended functions consistently and dependably under specified conditions and over time.
- scalabilityaddresses · Scalability is the ability of a system, process, or method to accommodate increasing workload, size, or demand while maintaining acceptable operation.
- resource allocationuses · Resource allocation is the assignment of limited resources among competing activities, workloads, or components according to requirements, priorities, and constraints.
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