Hands-on training to deploy and operate MinIO AIStor, the industry-leading S3-compatible object store built for AI and analytics at scale. Learn how to design, manage, and scale object storage across modern data and AI workloads.
Explore featured role-based learning paths designed to build practical MinIO skills, from foundational training to advanced certification readiness. MinIO Academy also includes individual courses, guided video instruction, hands-on labs, and on-demand resources.
Learning paths combine expert-led courses, hands-on labs, real-world scenarios, and knowledge assessments that prepare learners for real-world success. Complete eligible programs to earn shareable digital badges that recognize verified achievement.
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Deploy and Operate AIStor
For Administrators
Deploy and manage high-performance object storage across Kubernetes and bare metal. Build scalable, production-ready infrastructure.
MinIO Academy focuses on how AIStor is used in real-world environments. Learn how to deploy and operate object storage as the foundation for modern data platforms, including lakehouse architectures and AI pipelines.
Curriculum engineer support answers typically within one business day
Role-Based
Learning paths for developers and enterprise admin
Get Certified
Validate Your AIStor Expertise
Earn a MinIO digital badge to demonstrate your ability to deploy and operate AIStor in real-world environments. Share your credential to show expertise in object storage, data infrastructure, and AI workloads.
Hands-on training webinars covering real-world operations with MinIO AIStor—from capacity expansion and natural language management to seamless data lake migration with Apache Iceberg.
Join this MinIO training webinar to learn how to leverage AI assistance in handling a common administrative operation - reclaiming storage from your versioned AIStor buckets. Discover how AI-assisted analysis can identify reclaimable space and help you move beyond blunt lifecycle rules or hand-written cleanup scripts with precise, prefix-level cleanup strategies.See how the “plan, confirm, act” pattern enables safe, repeatable operations through live demonstrations. Walk away with practical AI-augmented techniques to reduce storage costs, improve efficiency, and stay in control of your versioned data at scale.
Deploying MinIO MemKV for Inference Context Memory Performance
Presenter: Ravind Kumar, MinIO Curriculum Engineer and Phil Sweany, MinIO Curriculum Engineer
Join this MinIO training webinar to learn how MemKV eliminates the critical bottleneck in your high performance inference servers. As inference models scale to longer contexts and higher concurrency, the context memory becomes the physical limitation to maintaining high throughput with the fastest Time to First Token (TTFT) and consistently speedy Time Per Output Token (TPOT). When GPU memory fills up, prefill latency and context recompute dominates and throughput collapses. MemKV provides a distributed shared context memory store that bridges GPU memory and memory-mapped NVMe drives to massively increase context memory space and avoid active context eviction and recompute. See how MinIO MemKV implements zero-copy RDMA, native NIXL integration, parallelized extent-based block store, and shared-nothing linear scalability to deliver massively increased aggregate throughput with sub-millisecond latency using existing commodity hardware.
Architecting AIStor Table Sharing with Databricks for Scale and Performance
Presenter: Smarika Pathak, MinIO Curriculum Engineer and Will Dinyes, Head of Certification
Join this MinIO training webinar to learn how to leverage AI assistance in handling a common administrative operation - reclaiming storage from your versioned AIStor buckets. Discover how AI-assisted analysis can identify reclaimable space and help you move beyond blunt lifecycle rules or hand-written cleanup scripts with precise, prefix-level cleanup strategies. See how the “plan, confirm, act” pattern enables safe, repeatable operations through live demonstrations. Walk away with practical AI-augmented techniques to reduce storage costs, improve efficiency, and stay in control of your versioned data at scale.
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