Switching tile formats on a LiDAR ingestion pipeline cut output object count by roughly 25x at the same data volume, independent of compression. Here is why object count is its own cost and performance axis on object storage, and what to check before you scale a pipeline that writes many small files.
A decision framework for choosing a message broker under a real-time control latency budget: acknowledgment mode, packet loss versus fixed delay, and when to skip the broker entirely.
MinIO site replication has no cross-site quorum, and its replication queue exists only inside the source cluster: lose that site and the un-replicated backlog is gone and un-enumerable. Sync mode costs latency without fixing that. The precise model, the RTO/RPO table, and the DR patterns that match real SLAs.
MinIO has no NameNode. It puts the namespace on XFS as real directories and xl.meta files. On Lots of Small Files that means you can exhaust inodes while df -h still looks fine, and a flat leaf can stall PUT, LIST, scanner, and ILM together. Here is the on-disk model, the inode math, and a prefix recipe that keeps XFS inside a regime you can operate.
MinIO fixed the HDFS NameNode limit, but it has no index: it writes one xl.meta per object on every drive of the erasure set. On 5 servers of 12 NVMe, MinIO picks a 15-wide set by default, so each small object is stored 15 times over. A worked sizing that looks fine for two years and dies in days.
Two MinIO platforms, same root cause: used as a NoSQL store. Field notes on LIST IOPS, XFS directory limits, scanner & heal SLAs, the erasure-coding storage-efficiency inversion on small objects, and why Apache Cassandra (or Ceph) is the right answer on-prem in 2026.
Note: This article was inspired by a LinkedIn post by Can Sinan A. on the hidden operational cost of an Iceberg migration, especially when governance moves from one access-control plane to several layers: catalog, storage and engine configuration Introduction Many organizations are modernizing their data platforms with lakehouse architectures. The Read more
When Tesla published patent WO2024073080 describing a new file format internally called “.smol”, the headline was simple: 4x reduction in IOPS for AI training. Most people read this as a hardware story. It isn’t. It’s a data architecture story. And it exposes a structural weakness in how most enterprise data Read more
Introduction Benchmarking remains a critical (and often underestimated) tool when designing or validating large-scale data platforms. While many teams rely on synthetic workloads or production replays, standardized benchmarks still play a key role when comparing architectures, tuning clusters, or validating infrastructure choices. TPCx-HS is one of those benchmarks: designed to Read more
Bring the IOPS dude ! As a solutions architect working with MinIO storage solutions, I’ve seen firsthand the challenges that come with on-premises deployments using hard disk drives (HDDs). While HDDs may seem like a cost-effective option initially, they can introduce significant performance bottlenecks that impact the overall efficiency and Read more