# Overprovisioned Memory in Cloud Run Services

Canonical: https://www.pointfive.co/efficiency-hub/inefficiencies/overprovisioned-memory-in-cloud-run-services

[Cloud Efficiency Hub](https://www.pointfive.co/efficiency-hub) 

# Overprovisioned Memory in Cloud Run Services

## Explanation

Cloud Run allows users to allocate up to 8 GB of memory per container instance. If memory is overestimated - often as a buffer or based on unvalidated assumptions - customers pay for more than what the workload consumes during execution. Unlike in VM-based environments where memory might be shared or underutilized without direct cost impact, in Cloud Run, you're billed precisely for what you allocate. This inefficiency often results from: \* Defaulting to high memory values for "safety" \* Not using monitoring tools to assess actual memory usage \* Lack of clear ownership over service tuning

## Relevant Billing Model

Charged based on: \* Allocated memory and CPU per instance \* Execution duration (rounded up to the nearest 100ms) \* Number of requests and networking egress (if applicable) Even unused allocated memory is fully billed per 100ms of execution time, making memory overprovisioning a direct driver of excess cost.

## Detection

- Identify Cloud Run services with high memory allocation (e.g., \\\>1 GB)

- Compare against actual memory usage (visible in Cloud Monitoring or Cloud Trace)

- Review historical memory usage variance across multiple invocations

- Flag workloads with stable memory use but large memory headroom

- Check for default templates or configurations that may enforce high memory settings

## Remediation

- Reduce memory allocation to match observed memory usage with a buffer for spikes

- Continuously monitor function-level memory metrics to right-size allocations over time

- Set up proactive alerts for services with memory allocation far exceeding usage

- Refactor container images or code to optimize memory consumption

- Establish governance policies or templates that encourage conservative starting values

## Relevant Documentation

[Submit Feedback](https://hub.pointfive.co/inefficiencies/overprovisioned-memory-in-cloud-run-services)

## At a glance

Reference

CER-0163

Cloud provider

GCP

Service

GCP Cloud Run

Category

[Compute](https://www.pointfive.co/efficiency-hub/service-category/compute)

Inefficiency type

Overprovisioned Resource

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Source: the public page above. Product screenshots and illustrative interfaces are examples, not live customer data.