# Overprovisioned Memory Allocation in Cloud Run Services

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

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

# Overprovisioned Memory Allocation in Cloud Run Services

## Explanation

In Cloud Run, each revision is deployed with a fixed memory allocation (e.g., 512MiB, 1GiB, 2GiB, etc.). These settings are often overestimated during initial development or copied from templates. Unlike auto-scaling platforms that adapt instance size based on workload, Cloud Run continues to bill per the allocated amount regardless of actual memory used during execution. If a service consistently uses significantly less memory than allocated, it results in avoidable overpayment per request - especially for high-throughput or long-running services. Since memory and CPU are billed together based on configured values, this inefficiency compounds quickly at scale.

## Relevant Billing Model

Billed based on: \* Allocated vCPU and memory (GiB) per request \* Duration of request execution (per 100ms increment) \* Number of requests \* Additional charges for egress and requests beyond free tier

## Detection

- Review actual memory usage per request over a representative time window

- Identify services with consistently low memory utilization relative to their configured limits

- Evaluate whether higher memory tiers were chosen to solve startup latency or cold start issues that no longer apply

- Cross-reference high-throughput services where per-request efficiency has significant cost impact

## Remediation

- Reconfigure services with right-sized memory allocations aligned to observed usage patterns

- Test progressively smaller memory configurations to find a stable baseline without introducing latency or OOM errors

- Implement monitoring for memory pressure or failures to validate new settings

- Use performance benchmarks and load tests in lower environments before promoting configuration changes to production

## Relevant Documentation

[Cloud Run Pricing](https://cloud.google.com/run/pricing?hl=en) 
[Cloud Run Resource Allocation](https://cloud.google.com/run/docs/configuring/memory-limits)

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

## At a glance

Reference

CER-0179

Cloud provider

GCP

Service

GCP Cloud Run

Category

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

Inefficiency type

Overprovisioned Resource Allocation

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