Object Storage

Mental model

Object storage (S3/R2) is infinite, cheap, durable bytes — but with ~tens-of-ms latency and no in-place edits. Modern systems like Turbopuffer put cold data here and keep a hot cache in front. Storage and compute separate.

How to study Object Storage

Begin by restating the mental model in your own words, then connect it to a concrete system you have built or operated. Name the mechanism, the constraint it addresses, and the trade-off it introduces. Use Turbopuffer — Architecture to check details, but close the source before writing your explanation. Retrieval is the learning step; rereading is only preparation.

Next, compare Object Storage with Caching, LSM Tree. Ask what changes in correctness, latency, resource use, operability, and failure recovery. Complete Object key layout and preserve the command, input, output, and one failed attempt as evidence. Finish by explaining the idea without jargon to someone who has not studied the track.

Proof of understanding

• Explain the mechanism from first principles and identify the state it reads or changes.
• Give one situation where the concept is the right choice and one where it is not.
• Predict a realistic failure mode before running the drill, then compare the prediction with evidence.
• Connect the result to a roadmap or build artifact instead of treating the concept as isolated trivia.

Where it matters

S3, Cloudflare R2, GCS; the durable layer of object-storage-first databases.

Common mistakes

• Treating object storage like a low-latency disk
• Many tiny objects instead of batched segment files
• Ignoring request cost (GETs/PUTs are billed)

Learn from primary sources

• Turbopuffer — Architecture (article)

Practice and explain it back

Review prompts

• Why can't you treat object storage like a local disk?

Build evidence

Learning paths

• 90-Day AI Search & Infrastructure
• 12-Month Advanced AI Infrastructure
• Disk-First Databases & RAM
• HLD Practice