Alluxio Confidential
AI 3.7 Launch
Universal S3 + POSIX cache for end-to-end AI workloads.
AI at Full Throughput
and Ultra Low Latency
Jingwen Ouyang
Senior Product Manager
Alluxio Confidential
AI Data Life Cycle
Data
Collection
Data
Preprocessing
Model
Training
Model
Verification
Model
Loading
Inference
Data
Archiving
Data is everywhere in every stage of the journey.
Data needs to be accessed fast, friction free, and low cost.
Alluxio Confidential
Alluxio makes it easy to share and
manage data from
any storage
to any compute engine
in any environment
with high performance and low cost.
Alluxio Confidential
Alluxio as the Universal Cache
for S3 and POSIX Workloads
AI 3.7 Highlight
Alluxio Confidential
Alluxio as the Universal Cache for S3 and POSIX Workloads
THROUGHPUT LATENCY
Simplified example: application throughput =100 MB/s, T_setup=200 ms
● Large dataset: 1 GB → ~10.2 s (throughput dominates)
● Small dataset: 128 KB → ~0.201 s (latency dominates).
Training & rollout love throughput; inference loves latency!
T_total ≈ T_setup (≈ TTFB) + (data_size / application throughput)
Alluxio Confidential
THROUGHPUT
Alluxio has always been a leader in high throughput.
Enables customers to rapidly load massive quantities
of data into GPU memory for AI training and model
deployment/cold starts.
NEW in AI 3.7… Alluxio also delivers
Ultra Low Latency Caching for data
stored on cloud storage (e.g. AWS S3).
LATENCY
Alluxio as the Universal Cache for S3 and POSIX Workloads
Alluxio Confidential
Alluxio as the Universal Cache for S3 and POSIX Workloads
● A Single Alluxio Worker achieved a high throughput comparing to HPC Storage Solutions:
○ Up to 81.6 Gbps (or 9.5 GiB/s) w/ 100 Gbps network - 2.5 GiB/s(@1 thread) to 9.5 GiB/s(@32 threads)
○ Up to 352.2 Gbps (or 41 GiB/s) w/ 400 Gbps network
Setup
● Alluxio:
1 Alluxio worker (i3en.metal)
● FIO Benchmark:
Sequential Read
bs = 256KB
Note: an Alluxio fuse client (c5n.metal) co-located
with training servers is responsible for POSIX API
access to Alluxio Workers which actually cache the
data
Throughput Microbenchmark: Reads from A Single Worker
Alluxio Confidential
Alluxio is the industry-leading
sub-ms time to first byte (TTFB) solution on S3-class storage
How much better is Alluxio? (Details next slide)
➔ 45x Lower Latency than S3 Standard
➔ 5x Lower Latency than S3 Express One Zone
➔ Unlimited, linear scalability
Alluxio as the Universal Cache for S3 and POSIX Workloads
Alluxio Confidential
Test environment references
Alluxio EE
● Version/Spec: Alluxio Enterprise AI 3.6 (50TB
cache)
● Test env: 1 FUSE (C5n.metal, 100Gbps
network) and 1 Worker (i3en.metal)
AWS S3
● Version/Spec: AWS S3 bucket (Standard Class)
● Test env: 1 FUSE (C5n.metal, 100Gbps
network)
AWS S3 Express One Zone
● Version/Spec: AWS bucket (S3 Express One
Zone Class)
● Test env: 1 FUSE (C5n.metal, 100Gbps
network)
Alluxio as the Universal Cache for S3 and POSIX Workloads
➔ 45x Lower Latency than S3 Standard
➔ 5x Lower Latency than S3 Express One Zone
Alluxio Confidential
But that’s not all…
➔ Alluxio is 100% transparent to AI workloads
➔ S3 API & POSIX API
◆ Broad application support PyTorch, Python, AWS SDK, Boto3 …
◆ NO code changes
◆ NO workflow changes
➔ NO data imports or migrations
Drop in Alluxio as the transparent S3 caching layer
for faster and more scalable AI!
Alluxio as the Universal Cache for S3 and POSIX Workloads
Alluxio Confidential
What the Public Results Show — MLPerf Training v2.0
Alluxio Achieves Exceptional GPU Utilization
Alluxio
DDN
Nutanix
Hammerspace
HPE
Source: MLCommons MLPerf Training v2.0 (retrieved 08/12/2025).
MLPerf®/MLCommons® are trademarks of MLCommons.
Alluxio Confidential
What the Public Results Show — MLPerf Training v2.0
Linear scale-out: clients↑ workers↑ throughput↑
Source: MLCommons MLPerf Training v2.0 (retrieved 08/12/2025).
MLPerf®/MLCommons® are trademarks of MLCommons.
Alluxio Confidential
AI 3.7 Key Features: Operations & Management
Deploy & Configure Alluxio in WebUI
After installing the Alluxio K8s Operator, the intuitive WebUI can be used to configure cluster
parameters, allocate resources, and customize deployments, making Alluxio deployment faster,
simpler, and more accurate than ever before.
Alluxio Confidential
AI 3.7 Key Features: Operations & Management
FUSE Non-Disruptive Upgrade: Rolling, K8s-native FUSE upgrades; mounts stay live.
Alluxio's innovative FUSE Online Upgrades feature allows admins to upgrade FUSE services
without interrupting active AI workloads
Alluxio's FUSE Online Upgrade capability maintains data accessibility throughout the upgrade
process by:
● Preserving active file handles and connections
● Queuing operations during the brief transition period
● Automatically resuming operations within tens of seconds
In this release, read operations (read, stat) are fully retained, while write operations will be
supported in future updates. This ensures your critical AI workloads keep running even during
necessary system maintenance.
Alluxio Confidential
AI 3.7 Key Features: Security & Compliance
Role Based Access Controls for S3 Data
● Define who can access which data
● Define what they can do with that data
● Integrations with Authentication &
Authorization providers
○ OIDC based Providers
(Okta, Cognito, Microsoft AD)
○ Apache Ranger, Open Policy Agent (OPA)
Audit & Analyze User Data Access & Operations
Now, every interaction is automatically recorded
with:
● User identities and authentication details
● Operations performed (read, write, delete, etc.)
● Precise timestamps
● Accessed resources and paths
Enables security teams to detect anomalies,
investigate incidents, and demonstrate compliance
with regulatory requirements, which are essential
for enterprise AI deployments handling sensitive
data.
Alluxio Confidential
Demo
Accelerate AI.
Alluxio Confidential
Demo: Transparent S3 Cache
Link 4:23
This demo showcases how to seamlessly accelerate a PyTorch data loading script using the Alluxio S3 API without any code modifications.
The presenter first runs a Python script that uses the s3torchconnectorlibrary to read data directly from an S3 bucket, establishing a
baseline performance of about 25 seconds. Then, by simply setting the S3_ENDPOINT_URLenvironment variable to point to the Alluxio S3
API endpoint, the exact same script is run again. This time, Alluxio serves the data from its cache, reducing the read time to about 15
seconds. The performance improvement is visually confirmed using a Grafana dashboard, which shows the data is now cached in Alluxio
and the cache hit rate is 100%.
● Objective (0:01): Accelerate PyTorch data pipelines that use S3 by leveraging the Alluxio S3 API, without requiring any changes to
the existing application code.
● The Mechanism (0:26): The integration works by redirecting S3 traffic to the Alluxio cluster. This is achieved by setting the
S3_ENDPOINT_URLenvironment variable to the Alluxio S3 endpoint address.
● Baseline Performance - Cold Read (1:03): The first run of the script with the endpoint URL unset reads data directly from AWS S3,
establishing a "cold read" benchmark of approximately 25 seconds.
● Accelerated Performance - Hot Read (1:52): For the second run, the S3_ENDPOINT_URLis set to the Alluxio endpoint. The exact
same script now reads the data from the Alluxio cache in about 15 seconds, demonstrating a significant performance improvement.
● Verification with Metrics (3:25): The performance gain is visually confirmed using a Grafana dashboard, which shows that 3 GiB of
data is now cached in Alluxio and the cache hit rate for the second run is 100%.
Alluxio Confidential
Demo: WebUI - Cluster Deployment
link 4:17
This demo introduces the new features of the Alluxio Management Console in version 3.7. The presenter walks through how to access
the console and use its new graphical user interface to deploy and manage Alluxio clusters. He demonstrates the two methods for
cluster creation: a manual, form-based configuration and a streamlined YAML upload option. The demo highlights how the console
provides a detailed, real-time status view of cluster resources, including workloads and individual pods, and shows how to easily
access pod logs for quick troubleshooting.
● Accessing the Console (0:11): The Alluxio Operator now deploys a dedicated alluxio-consolepod and service, which can
be accessed locally by port-forwarding its service to your machine.
● Cluster Creation (0:55): The console offers two ways to deploy a new Alluxio cluster: a step-by-step "Manual Configuration"
form or by simply uploading an existing YAML configuration file.
● Live Status Monitoring (2:56): The "View Status" page provides a real-time dashboard showing the creation progress and
health of all cluster workloads and their associated pods.
● Simplified Troubleshooting (3:29): Users can now view the logs of any pod directly from the console's UI with a single click,
making it easy to diagnose issues like a pod in an error state.
● Integrated Cluster Management (3:52): For existing clusters, the "View Console" button provides a direct link to that specific
cluster's traditional Alluxio UI, allowing for more detailed management operations like preloading data and managing storage.
Alluxio Confidential
Thanks.
Schedule Demo at alluxio.io/demo

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  • 1.
    Alluxio Confidential AI 3.7Launch Universal S3 + POSIX cache for end-to-end AI workloads. AI at Full Throughput and Ultra Low Latency Jingwen Ouyang Senior Product Manager
  • 2.
    Alluxio Confidential AI DataLife Cycle Data Collection Data Preprocessing Model Training Model Verification Model Loading Inference Data Archiving Data is everywhere in every stage of the journey. Data needs to be accessed fast, friction free, and low cost.
  • 3.
    Alluxio Confidential Alluxio makesit easy to share and manage data from any storage to any compute engine in any environment with high performance and low cost.
  • 4.
    Alluxio Confidential Alluxio asthe Universal Cache for S3 and POSIX Workloads AI 3.7 Highlight
  • 5.
    Alluxio Confidential Alluxio asthe Universal Cache for S3 and POSIX Workloads THROUGHPUT LATENCY Simplified example: application throughput =100 MB/s, T_setup=200 ms ● Large dataset: 1 GB → ~10.2 s (throughput dominates) ● Small dataset: 128 KB → ~0.201 s (latency dominates). Training & rollout love throughput; inference loves latency! T_total ≈ T_setup (≈ TTFB) + (data_size / application throughput)
  • 6.
    Alluxio Confidential THROUGHPUT Alluxio hasalways been a leader in high throughput. Enables customers to rapidly load massive quantities of data into GPU memory for AI training and model deployment/cold starts. NEW in AI 3.7… Alluxio also delivers Ultra Low Latency Caching for data stored on cloud storage (e.g. AWS S3). LATENCY Alluxio as the Universal Cache for S3 and POSIX Workloads
  • 7.
    Alluxio Confidential Alluxio asthe Universal Cache for S3 and POSIX Workloads ● A Single Alluxio Worker achieved a high throughput comparing to HPC Storage Solutions: ○ Up to 81.6 Gbps (or 9.5 GiB/s) w/ 100 Gbps network - 2.5 GiB/s(@1 thread) to 9.5 GiB/s(@32 threads) ○ Up to 352.2 Gbps (or 41 GiB/s) w/ 400 Gbps network Setup ● Alluxio: 1 Alluxio worker (i3en.metal) ● FIO Benchmark: Sequential Read bs = 256KB Note: an Alluxio fuse client (c5n.metal) co-located with training servers is responsible for POSIX API access to Alluxio Workers which actually cache the data Throughput Microbenchmark: Reads from A Single Worker
  • 8.
    Alluxio Confidential Alluxio isthe industry-leading sub-ms time to first byte (TTFB) solution on S3-class storage How much better is Alluxio? (Details next slide) ➔ 45x Lower Latency than S3 Standard ➔ 5x Lower Latency than S3 Express One Zone ➔ Unlimited, linear scalability Alluxio as the Universal Cache for S3 and POSIX Workloads
  • 9.
    Alluxio Confidential Test environmentreferences Alluxio EE ● Version/Spec: Alluxio Enterprise AI 3.6 (50TB cache) ● Test env: 1 FUSE (C5n.metal, 100Gbps network) and 1 Worker (i3en.metal) AWS S3 ● Version/Spec: AWS S3 bucket (Standard Class) ● Test env: 1 FUSE (C5n.metal, 100Gbps network) AWS S3 Express One Zone ● Version/Spec: AWS bucket (S3 Express One Zone Class) ● Test env: 1 FUSE (C5n.metal, 100Gbps network) Alluxio as the Universal Cache for S3 and POSIX Workloads ➔ 45x Lower Latency than S3 Standard ➔ 5x Lower Latency than S3 Express One Zone
  • 10.
    Alluxio Confidential But that’snot all… ➔ Alluxio is 100% transparent to AI workloads ➔ S3 API & POSIX API ◆ Broad application support PyTorch, Python, AWS SDK, Boto3 … ◆ NO code changes ◆ NO workflow changes ➔ NO data imports or migrations Drop in Alluxio as the transparent S3 caching layer for faster and more scalable AI! Alluxio as the Universal Cache for S3 and POSIX Workloads
  • 11.
    Alluxio Confidential What thePublic Results Show — MLPerf Training v2.0 Alluxio Achieves Exceptional GPU Utilization Alluxio DDN Nutanix Hammerspace HPE Source: MLCommons MLPerf Training v2.0 (retrieved 08/12/2025). MLPerf®/MLCommons® are trademarks of MLCommons.
  • 12.
    Alluxio Confidential What thePublic Results Show — MLPerf Training v2.0 Linear scale-out: clients↑ workers↑ throughput↑ Source: MLCommons MLPerf Training v2.0 (retrieved 08/12/2025). MLPerf®/MLCommons® are trademarks of MLCommons.
  • 13.
    Alluxio Confidential AI 3.7Key Features: Operations & Management Deploy & Configure Alluxio in WebUI After installing the Alluxio K8s Operator, the intuitive WebUI can be used to configure cluster parameters, allocate resources, and customize deployments, making Alluxio deployment faster, simpler, and more accurate than ever before.
  • 14.
    Alluxio Confidential AI 3.7Key Features: Operations & Management FUSE Non-Disruptive Upgrade: Rolling, K8s-native FUSE upgrades; mounts stay live. Alluxio's innovative FUSE Online Upgrades feature allows admins to upgrade FUSE services without interrupting active AI workloads Alluxio's FUSE Online Upgrade capability maintains data accessibility throughout the upgrade process by: ● Preserving active file handles and connections ● Queuing operations during the brief transition period ● Automatically resuming operations within tens of seconds In this release, read operations (read, stat) are fully retained, while write operations will be supported in future updates. This ensures your critical AI workloads keep running even during necessary system maintenance.
  • 15.
    Alluxio Confidential AI 3.7Key Features: Security & Compliance Role Based Access Controls for S3 Data ● Define who can access which data ● Define what they can do with that data ● Integrations with Authentication & Authorization providers ○ OIDC based Providers (Okta, Cognito, Microsoft AD) ○ Apache Ranger, Open Policy Agent (OPA) Audit & Analyze User Data Access & Operations Now, every interaction is automatically recorded with: ● User identities and authentication details ● Operations performed (read, write, delete, etc.) ● Precise timestamps ● Accessed resources and paths Enables security teams to detect anomalies, investigate incidents, and demonstrate compliance with regulatory requirements, which are essential for enterprise AI deployments handling sensitive data.
  • 16.
  • 17.
    Alluxio Confidential Demo: TransparentS3 Cache Link 4:23 This demo showcases how to seamlessly accelerate a PyTorch data loading script using the Alluxio S3 API without any code modifications. The presenter first runs a Python script that uses the s3torchconnectorlibrary to read data directly from an S3 bucket, establishing a baseline performance of about 25 seconds. Then, by simply setting the S3_ENDPOINT_URLenvironment variable to point to the Alluxio S3 API endpoint, the exact same script is run again. This time, Alluxio serves the data from its cache, reducing the read time to about 15 seconds. The performance improvement is visually confirmed using a Grafana dashboard, which shows the data is now cached in Alluxio and the cache hit rate is 100%. ● Objective (0:01): Accelerate PyTorch data pipelines that use S3 by leveraging the Alluxio S3 API, without requiring any changes to the existing application code. ● The Mechanism (0:26): The integration works by redirecting S3 traffic to the Alluxio cluster. This is achieved by setting the S3_ENDPOINT_URLenvironment variable to the Alluxio S3 endpoint address. ● Baseline Performance - Cold Read (1:03): The first run of the script with the endpoint URL unset reads data directly from AWS S3, establishing a "cold read" benchmark of approximately 25 seconds. ● Accelerated Performance - Hot Read (1:52): For the second run, the S3_ENDPOINT_URLis set to the Alluxio endpoint. The exact same script now reads the data from the Alluxio cache in about 15 seconds, demonstrating a significant performance improvement. ● Verification with Metrics (3:25): The performance gain is visually confirmed using a Grafana dashboard, which shows that 3 GiB of data is now cached in Alluxio and the cache hit rate for the second run is 100%.
  • 18.
    Alluxio Confidential Demo: WebUI- Cluster Deployment link 4:17 This demo introduces the new features of the Alluxio Management Console in version 3.7. The presenter walks through how to access the console and use its new graphical user interface to deploy and manage Alluxio clusters. He demonstrates the two methods for cluster creation: a manual, form-based configuration and a streamlined YAML upload option. The demo highlights how the console provides a detailed, real-time status view of cluster resources, including workloads and individual pods, and shows how to easily access pod logs for quick troubleshooting. ● Accessing the Console (0:11): The Alluxio Operator now deploys a dedicated alluxio-consolepod and service, which can be accessed locally by port-forwarding its service to your machine. ● Cluster Creation (0:55): The console offers two ways to deploy a new Alluxio cluster: a step-by-step "Manual Configuration" form or by simply uploading an existing YAML configuration file. ● Live Status Monitoring (2:56): The "View Status" page provides a real-time dashboard showing the creation progress and health of all cluster workloads and their associated pods. ● Simplified Troubleshooting (3:29): Users can now view the logs of any pod directly from the console's UI with a single click, making it easy to diagnose issues like a pod in an error state. ● Integrated Cluster Management (3:52): For existing clusters, the "View Console" button provides a direct link to that specific cluster's traditional Alluxio UI, allowing for more detailed management operations like preloading data and managing storage.
  • 19.