ARCHIL

Shared SSD caching, for every workload, automatically

Archil unlocks compute flexibility and efficiency by building a shared SSD cache across your fleet that eliminates cold start latencies, drives higher resource utilization, and enables containerization.

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Stop moving data to the compute

Today, teams use local SSD caching to reduce object storage edges like per-request charges and high time-to-first-byte latencies. Archil eliminates these edges.

The way it works today

A cache you build and run yourself

  • Provision EBS or local NVMe on every instance and pay for peak capacity on each one — whether or not it is reading.
  • Maintain sync code that stages the right data onto the right disk, and track thousands of volumes across the fleet.
  • Size instances around the disks they carry and pin workloads to an availability zone to stay close to their volumes.
  • Every new instance sits idle hydrating its own local copy before it can do work — the tax you pay to scale out.
With Archil

One shared cache, managed for you

  • One cache, shared by every instance in the region and backed by SSDs automatically. Pay for what you read, not what you provision.
  • Point Archil at your existing buckets. No sync code, no volumes to size, no fleet of disks to babysit.
  • Containerize freely — no locally-attached disks to size around and no AZ affinity, so the scheduler places work anywhere.
  • New instances mount a cache that is already warm and start reading immediately. No hydration, no cold start.

Built for data-intensive workloads

Anything that keeps petabytes in object storage and reads them at high throughput from a fleet of compute runs faster on a shared cache.

Model training

Stream shards and checkpoints to thousands of GPUs without staging datasets onto every node first.

Genomics

Process large sequencing datasets directly from the buckets where they already live, with no copying step in between.

Data analytics

Back Spark, Trino, and warehouse engines with a cache that serves hot Parquet to every worker at once — no rehydration.

Local-disk speed, without the local disks

<1ms
time to first byte
warm SSD reads, without provisioning local NVMe or EBS
7 GB/s
sustained throughput
per client, to thousands of concurrent readers — no hydration
75%
lower cost than EBS
elastic, pay for what you read — not what you provision
Ready when your fleet is

Run every workload against a cache that’s already warm.

Bring the buckets you already have. Give every GPU and worker fast shared access without provisioning local disks or waiting for data to hydrate.

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