Telemetry volumes are exploding across microservices, Kubernetes, serverless, edge, and AI inference, turning root-cause analysis into a race against retention limits and runaway cloud ingest costs.
MinIO AIStor enables enterprises to retain and query up to 2–3X more logs, metrics, traces, events, and model signals for the same or lower budget, delivering smarter automation, faster incident response, and longer retention windows without compromising performance or SLAs.
High-performance storage for the full spectrum of observability workloads.
Centralized Log Search & Forensics
Consolidate logs from distributed systems into a single, searchable repository with full retention—eliminating the fragmentation that slows incident response.
Performance Optimization & Monitoring
Feed observability platforms at scale with consistent, low-latency data access to power application performance monitoring, microservices tracing, and CI/CD pipeline health.
Incident Response & Root Cause Investigation
Retrieve historical data in minutes, not hours, for faster root cause analysis, reduced MTTR and improved customer experience and SLA compliance.
Predictive Analytics & AIOps
Power ML models for capacity planning, cost optimization, anomaly detection, customer experience monitoring, and trend-based prevention.
How It Works
AIStor sits behind your observability platform as the high-performance storage backend to extend retention, accelerate queries, and eliminate the cost curve that forces trade-offs.
Native Tiered Storage Integration
Connects directly to your observability platform via S3—no custom connectors or middleware.
Works with Splunk SmartStore, Elastic ILM, and Grafana Mimir/Loki out of the box
Hot data on local SSDs or AIStor NVMe for real-time alerting; warm and cold tiers move to AIStor automatically with no rehydration delays
Warm and cold data stays queryable at dramatically faster retrieval than traditional archives, in minutes, not hours
Multi-TB/s Ingest, Linear Scaling
Stateless architecture with no centralized metadata server to bottleneck ingest or reads.
Each node operates independently at near line-speed
Store 2-3× more telemetry data for the same budget
Same protection guarantees at a fraction of the capacity cost
Query Historical Data in Warp Speed
Near line-speed reads mean your platform performs the same on old data and new.
No archive latency or cold-tier penalties
Full-speed forensics across your entire retention window
Search last quarter's logs as fast as yesterday's
Single Namespace, Any Scale
One logical namespace from your first terabyte to your first exabyte.
No 20-30 PB ceilings that force re-architecture
No cluster splits that fragment searchable history
Logs, metrics, and traces in one unified store
Deploy Anywhere Your Stack Runs
Software-defined and Kubernetes-native — runs on your hardware, your way.
Commodity hardware in your data center or at the edge
Air-gapped and sovereign deployment options
No proprietary appliances, no vendor lock-in
AIStor helped us turn what was once a fragile, monolithic system into a very forward looking Data Lakehouse that supports a true hybrid cloud.
Conor Brennan
Managing Director, Risk IT
Proven Results
Quantified outcomes from AIStor customer production deployments.
2-3× more data stored for the same cost
Nomura doubled usable storage capacity on existing hardware, avoided purchasing 20+ new servers, and replaced a fragile monolithic system with a hybrid cloud data lakehouse that cut daily risk processing by four hours.
AMD built a GraphRAG-powered data intelligence platform on AIStor that connects ServiceNow tickets, GitHub commits, infrastructure logs, and telemetry into a single queryable graph, enabling automated root cause tracing across previously siloed systems and accelerating issue resolution.
A global payment provider replaced Hitachi Content Platform used for merchant reporting, observability/log data, and analytics with MinIO—completing migration in 6 weeks vs. a projected timeline of nearly a year.
50% lower TCO and 86% faster deployment vs. Hadoop
A major global electric utility replaced Hadoop with AIStor for their smart meter telemetry data lakehouse. They successfully deployed on 90 servers in 10 weeks vs. 240 servers and 14 months estimated for Hadoop.
Organizations apply AIStor for observability across industries.
Media
Streaming quality analytics
CDN performance monitoring
Content delivery observability
Telecom
5G network telemetry
Customer experience monitoring
Network fault detection
Gaming
Player experience monitoring
Game server performance
Matchmaking system health
Financial Services
Transaction system health
API latency monitoring
Trading platform observability
Life Sciences
Clinical trial system monitoring
Lab instrument telemetry
Research pipeline observability
Manufacturing
Production line monitoring
Equipment telemetry collection
Supply chain system health
Full Retention. Lower Costs. Faster Insights.
Fewer outages, faster recovery, higher software delivery velocity, and more predictable customer experience. See how AIStor can transform observability economics.
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