Cloud-native AI platforms
GPU-ready clusters on GCP with opinionated defaults: VPC, IAM, autoscaling, checkpointing, and cost controls.
Performance-first architectures for real workloads.
We design, tune, and operationalize AI/HPC platforms—cloud-native storage, low-latency networking, and MLOps that actually ship. Velocity without the mystery meat.
Solutions
Storage performance engineering
Design for throughput and tail latency. NVMe, RDMA/RoCE, and object tiers without the foot-guns.
MLOps & data pipelines
Reproducible training and serving, artifact lineage, and on-call friendly ops. No yak shaving.
Lab notes
Throughput vs. client count
Why 800 Mb/s per client can waste backbone capacity—and how to right-size CPU, queues, and NICs.
Read the note →Checkpointing on preemptibles
Resilient training on spot GPUs with snapshot-aware pipelines and SLA-aware rebuild logic.
Read the note →From the blog
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