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.
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.
You may want to optimize the content serving a bit, since it's currently hotlinking multiple large (30MB) videos at 2K resolution from https://svs.gsfc.nasa.gov.
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.
SlateDB offers different durability levels for writes. By default writes are buffered locally and flushed to S3 when the buffer is full or the client invokes flush().
While your technical analysis is excellent, making judgements about workload suitability based on a Preview release is premature. Preview services have historically had significantly lower performance quotas than GA releases. Lambda for example was limited to 50 concurrent executions during Preview, raised to 100 at GA, and now the default limit is 1,000.
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.