Shakahs

This was Google's big announcement at their last I/O conference: That Google would become the agent handling all forms of commerce on behalf of the average person worldwide.

Not familiar with this particular library, but similar libraries use S3 Express One Zone which has write latency <10ms, so you can use that for the WAL and compaction can move data onto other storage classes in the background.

Regular S3 has write latency 100-150ms, which might be fine depending on your workload anyway.

Frontier model providers (Anthropic et al.) gate new accounts to impractically low rate limits and spending caps until clients unlock higher limits with cumulative usage, make equivalent cash deposits up front, or talk to a Sales department to work out some other arrangement. They are handicapped by the postpaid billing model.

It's an administrative burden to sign up very every model provider, and there are many independent inference providers now that serve only open source models.

OpenRouter provides a useful service by allowing easy prepaid model access with much higher rate limits, and they also aggregate different model providers to route queries by price, latency, etc.

JSON is okay most of the time, but I loath YAML.

How many Kubernetes administration headaches trace back to the need for automated systems to surgically edit YAML? It’s absurd and YAML may be the worst choice for this use case.

Enterprise adds IAM, logging, and analytics, all of which AWS provides for free or for metered usage without needing an enterprise plan.

If you are paying API rates (not using Max subscriptions) there's no reason to use Anthropic's API directly, the same models are hosted by both AWS and Google with better uptime than Anthropic.

AWS and GCP both have their own custom inference chips, so a better example for hosting Opus on commodity hardware would be Digital Ocean.

Sonnet/Claude Code may technically be "smarter", but Qwen3-Coder on Cerebras is often more productive for me because it's just so incredibly fast. Even if it takes more LLM calls to complete a task, those calls are all happening in a fraction of the time.