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Scheduler Reference


Schedulers provide a mechanism for throttling and scheduling requests based on importance when service resources are limited. The throttling is achieved through token buckets. To gain admittance, each request must obtain tokens from the bucket. When tokens are depleted, incoming requests enter a queue, awaiting admittance based on a weighted fair queuing algorithm. This algorithm ensures equitable resource allocation across workloads, factoring in the priority and weight (tokens) of each request.

This diagram illustrates the working of a scheduler for workload prioritization.

Scheduler Scheduler

Aperture offers two variants of scheduler: Load Scheduler and Quota Scheduler. While both use the same weighted fair queuing-based scheduling algorithm, they differ in the throttling mechanism by employing distinct types of token buckets. The Load Scheduler uses a token bucket local to each agent, which gets adjusted based on the past token rate at the agent. This is useful for service protection scenarios since it provides a robust mechanism to relatively adjust the token rate. The Quota Scheduler, uses a centralized token bucket within an agent group. This is useful for scenarios involving known limits, such as third-party API rate limits or inter-service API quotas.


Workloads are groups of requests based on common Flow Labels. Workloads are expressed by label matcher rules in the Scheduler definition. Aperture Agents schedule workloads based on their priorities and tokens.


Priority represents the importance of a request compared to the other requests in the queue. It varies from 0 to an unlimited positive integer, indicating the urgency level, with higher numbers denoting higher priority. The position of a flow in the queue is computed based on its virtual finish time using the following formula:

inverted_priority=1priorityinverted\_priority = {\frac {1} {priority}}
virtual_finish_time=virtual_time+(tokensinverted_priority)virtual\_finish\_time = virtual\_time + \left(tokens \cdot inverted\_priority\right)

To manage prioritized requests, the scheduler seeks tokens from the token bucket. If tokens are available, the request gets admitted. In cases where tokens are not readily available, requests are queued, waiting either until tokens become accessible or until a timeout occurs - the latter being dependent on the workload or flowcontrol.v1.Check call timeout.


Tokens represent the cost for admitting a specific request. Typically, tokens are based on the estimated response time of a request. Estimating the number of tokens for each request within a workload is critical for making effective flow control decisions.

Aperture can automatically estimate the tokens for each workload based on historical latency measurements. See the workload_latency_based_tokens configuration for more details. The latency based token calculation is aligned with Little's Law, which relates response times, arrival rate, and the system concurrency (number of in-flight requests).

Alternatively, tokens can also be represented as the number of requests instead of response times. For example, when scheduling access to external APIs that have strict rate limits (global quota). In this case, the number of tokens represents the number of requests that can be made to the API within a given time window.

Tokens are determined in the following order of precedence:

Queue Timeout

The queue timeout is determined by the gRPC timeout provided on the flowcontrol.v1.Check call. When a request is made, it includes a timeout value that specifies the maximum duration the request can wait in the queue. If the request receives the necessary tokens within this timeout duration, it is admitted. Otherwise, if the timeout expires before the tokens are available, the request is rejected.

The gRPC timeout on the flowcontrol.v1.Check call is set in the Envoy filter and the SDK during initialization. It serves as an upper bound on the queue timeout, preventing requests from waiting excessively long.