TechOps Examples
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🧠 USE CASE
Understanding AWS Lambda's Reserved Concurrency vs Provisioned Concurrency
Imagine you run a ticket booking system for live concerts.
You have two AWS Lambda functions:
function-orange Handles seat reservations.
function-blue Handles payment processing.
Everything runs smoothly until ticket sales open at midnight. Suddenly, traffic spikes as thousands rush in, making function orange surge.
If not managed properly, it could consume all concurrency, throttling function blue and failing payments.
To prevent this, AWS Lambda provides Reserved Concurrency and Provisioned Concurrency to control execution behavior and resource allocation.
1. Reserved Concurrency For Fair Resource Allocation
Reserved concurrency guarantees that a function always has access to a specific portion of concurrency, but also prevents it from exceeding that limit.
Look at this image:
Reference: AWS Perspective Guide
function-orange has 400 reserved concurrency (shaded orange).
function-blue has 400 reserved concurrency (shaded blue).
The remaining 200 concurrency is unreserved, available for any other function.
What’s Happening?
At t1, function orange starts handling seat bookings and scales normally.
By t3, it hits its 400 concurrency limit, throttling excess requests and cannot scale further.
Meanwhile, function-blue (payments) is also handling its own requests but stays within its own reserved 400 limit.
The remaining 200 concurrency is unreserved for other functions.
This way, reserved concurrency ensures that critical functions don’t get starved of execution capacity.
Heads Up: If reserved concurrency is set too low, your function might be throttled unnecessarily, even when there’s unused capacity elsewhere.
2. Provisioned Concurrency For Pre Warming Execution Environments
Unlike reserved concurrency, provisioned concurrency does not limit execution. Instead, it keeps Lambda prewarmed to avoid cold starts.
Look at this image:
Reference: AWS Perspective Guide
function-orange now has 400 provisioned concurrency (pre warmed instances).
The remaining 600 concurrency is unreserved, available for other functions.
What’s Happening?
At t1-t2, function-orange starts ramping up as ticket sales open.
At t3, it seamlessly scales to 400 requests without delays, thanks to pre warmed execution environments.
By t5, function-orange continues to scale beyond 400, using the unreserved concurrency pool (600).
Heads Up: Provisioned concurrency costs extra, even when idle. It’s best used for latency sensitive applications like real time transactions or user interactions.
In my experience, the most powerful strategy is combining both reserved and provisioned concurrency for high priority workloads.
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