Resource Allocation During Low Traffic Periods in ElastiCache Serverless

Question

In the discussion on [this AWS forum post](https://repost.aws/questions/QU_mUvs_SuSiW-1tESHo60bQ/elasticache-serverless-scaling-characteristics), Mr. Abhay mentions that ElastiCache Serverless can handle traffic bursts by increasing RPS and data storage by 25-35% instantly and doubling RPS and memory storage every 10-12 minutes.

I have a specific use case where I’m concerned about how ElastiCache Serverless manages resource allocation during periods of minimal traffic. In non-serverless configurations, we have predefined instance sizes like t3.micro, t3.medium, etc., which we can adjust based on expected traffic. For example, in an event registration system project, resource usage is minimal before the event opens, but spikes dramatically once it starts. Typically, we use 4 to 8 ElastiCache instances with t3.large specs, and during low-traffic periods, even a t3.micro suffices.

Could you clarify what baseline specifications ElastiCache Serverless operates at during low traffic? Additionally, how reliable is the scale-up process in handling sudden, significant traffic spikes? My concern is that the scale-up may not be fast enough to cope with the abrupt increase in demand.

Thanniru Anil Kumar · Accepted Answer

**Baseline Specifications During Low Traffic**

ElastiCache Serverless doesn't operate on fixed instance sizes like the t3.micro or t3.large in a non-serverless environment. Instead, it scales resources based on demand. During periods of minimal traffic, ElastiCache Serverless minimizes resource allocation, effectively reducing memory and CPU usage to the lowest level required to handle the ongoing operations. This means that during low traffic, the underlying infrastructure scales down to use only the necessary resources, which could be equivalent to or even lower than a t3.micro instance, but it's not tied to a specific instance size.

**Reliability of Scale-Up Process**

ElastiCache Serverless is designed to handle sudden traffic spikes by quickly allocating additional resources. The scaling behavior mentioned—such as increasing RPS and data storage by 25-35% instantly and doubling RPS and memory storage every 10-12 minutes—is intended to provide rapid scaling. However, the speed and reliability of this scale-up process depend on the magnitude of the traffic spike and how quickly the system can provision additional resources.

For scenarios like an event registration system where traffic spikes can be very abrupt and substantial, it's important to account for the potential latency in the scale-up process. While ElastiCache Serverless is generally reliable in handling these spikes, there might be a brief period during which the system is catching up with the sudden demand. To mitigate this, you might consider configuring your system to anticipate such spikes, possibly by pre-warming the cache or implementing a traffic-smoothing mechanism, if feasible.

**Recommendations**

**Pre-Warming:** If you expect a significant traffic spike, you might want to manually increase resource allocation ahead of time or use a scheduled event to trigger a scale-up.

**Monitoring:** Continuously monitor performance metrics and set up alerts to respond quickly if the scale-up process is slower than expected.
Testing: Conduct load testing to understand how quickly ElastiCache Serverless scales in your specific environment and adjust your strategy accordingly.

Resource Allocation During Low Traffic Periods in ElastiCache Serverless

Relevant content