Automated configuration values for high-performance machine types
This document describes how to automatically set default Cloud Storage FUSE values usedfor high-performance Compute Engine machine types, which are designed tooptimize performance for demanding, high-throughput workloads.Values that are manually set at the time of mount will override these defaults.
Machine types
Configuration values are automated for the following high-performanceCompute Engine machine types:
| Series type | Machine type |
|---|---|
| A2 machine series | |
a2-megagpu-16g | |
a2-ultragpu-8g | |
| A3 machine series | |
a3-edgegpu-8g | |
a3-highgpu-8g | |
a3-megagpu-8g | |
a3-ultragpu-8g | |
| A4 machine series | |
a4-highgpu-8g-lowmem | |
| TPU v5e | |
ct5l-hightpu-8t | |
ct5lp-hightpu-8t | |
| TPU v5p | |
ct5p-hightpu-4t | |
ct5p-hightpu-4t-tpu | |
| TPU v6e (Trillium) | |
ct6e-standard-4t | |
ct6e-standard-4t-tpu | |
ct6e-standard-8t | |
ct6e-standard-8t-tpu |
Automated configuration values
When a supported machine type is detected, Cloud Storage FUSE automatically appliesthe following configuration values:
| Cloud Storage FUSE configuration file field | Cloud Storage FUSE CLI option | Automated configuration value |
|---|---|---|
metadata-cache:negative-ttl-secs | --metadata-cache-negative-ttl-secs | 0 |
metadata-cache:ttl-secs1 | --metadata-cache-ttl-secs1 |
|
metadata-cache:stat-cache-max-size-mb | --stat-cache-max-size-mb | 1024 |
metadata-cache:type-cache-max-size-mb | --type-cache-max-size-mb | 128 |
implicit-dirs | --implicit-dirs | true |
file-system:rename-dir-limit | --rename-dir-limit | 200000 |
write:global-max-blocks | --write-global-max-blocks | 1600 |
1Setting this configuration to-1 significantly boostsperformance by always serving files from the cache. Be aware that thisconfiguration bypasses consistency checks, which can lead to servingoutdated data. For details on managing data consistency, refer toOverview of caching in Cloud Storage FUSE.
Further performance tuning
When you use a high-performance Google Cloud machine type, theconfiguration values detailed on this page are automatically applied. However, youcan further fine-tune your machine for optimal performance using thefollowing methods:
Use thePerformance tuning best practices guide to improve Cloud Storage FUSEusing key Cloud Storage FUSE features and configurations to achieve maximumthroughput and optimal performance.
If you're running training, serving, or checkpointing and Just in Time (JIT)cache workloads on Google Kubernetes Engine clusters that use Cloud GPUs or Cloud TPUto access large datasets in Cloud Storage, you can streamline your setupby utilizing pre-configured YAML files to mount your Cloud Storage bucketsdirectly into your pods more efficiently. For more information andinstructions on how to use pre-configured GKE YAML files, seeUse pre-configured GKE YAML files to optimize Cloud Storage FUSE performance.
If you're running training, serving, or checkpointing workloads usingCloud Storage FUSE, you can use the
profilefield or--profilecommand optionto automatically adjust specific Cloud Storage FUSE configurations for optimalperformance based on the specific workload type. For more information, seeProfile-based configurations for AI/ML workloads.
What's next
Learn how totune Cloud Storage FUSE for optimal performance.
Use apre-configured GKE YAML file to configure tuning best practices.
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Last updated 2025-12-15 UTC.