
Cloud container environment with filesystem, shell, and AI agent support.
Upstash Box provisions self-contained Docker containers with independent filesystems, process trees, and network stacks. Each box includes five core capabilities: Agent (running Claude Code or Codex with full shell/filesystem access), Git (cloning repos, inspecting diffs, opening pull requests), Shell (executing OS-level commands), Filesystem (uploading, reading, writing files), and Snapshots (capturing and restoring box state). Boxes are billed per active CPU hour rather than idle time, making them cost-effective for intermittent AI workloads.
The platform is designed for AI-driven development workflows, automated code review, test execution, data processing, and long-running agent tasks. Boxes can connect over SSH using the Box API key as credentials, stream stdout/stderr in real time, and maintain full state between sessions including installed packages, git history, and file modifications. Network policies control outbound access, and boxes are fully isolated from each other and from Upstash infrastructure. Three sizes are available: small (2 vCPU, 4 GB), medium (4 vCPU, 8 GB), and large (8 vCPU, 16 GB).


Persistent hosted Linux sandboxes for long-horizon agents, billed per actively-used compute, with pause, resume, and fork.


High-scale distributed storage built on Git for machine-generated code, with native git remotes, SDKs, and sync for AI coding platforms.


Isolated, audit-ready application deployments on AWS with zero-downtime deploys and no AWS configuration required.


Open-source cloud sandboxes for AI agents and data applications, providing isolated compute environments for code interpretation.


Isolated environments for reinforcement learning, agent tool use, and model evaluation on GPU infrastructure.


S3-compatible object storage for AI datasets, model artifacts, and unstructured data at scale.


Managed cloud execution service running durable AI agents and background tasks with retries, checkpointing, monitoring, and elastic scaling.

Persistent hosted Linux sandboxes for long-horizon agents, billed per actively-used compute, with pause, resume, and fork.

High-scale distributed storage built on Git for machine-generated code, with native git remotes, SDKs, and sync for AI coding platforms.

Vast.ai Serverless runs autoscaling GPU inference endpoints on managed capacity.


Cloudflare R2: egress-free S3-compatible object storage with native Workers integration and Iceberg data catalog.


Cloudflare Workers: global serverless edge compute with zero cold starts, V8 isolates, and native R2/AI bindings.


Modal is a high-performance AI infrastructure cloud for online, batch, and multi-modal inference with instant autoscaling.



ByteNite's serverless container platform distributes compute-intensive workloads across pre-warmed cloud machines for AI and data apps.


High-performance cloud storage optimized for AI training and inference workloads.


Managed durable execution service supporting hosted environments and deployments inside customers' own cloud accounts.
Isolated, audit-ready application deployments on AWS with zero-downtime deploys and no AWS configuration required.

Open-source cloud sandboxes for AI agents and data applications, providing isolated compute environments for code interpretation.

Isolated environments for reinforcement learning, agent tool use, and model evaluation on GPU infrastructure.

S3-compatible object storage for AI datasets, model artifacts, and unstructured data at scale.

Managed cloud execution service running durable AI agents and background tasks with retries, checkpointing, monitoring, and elastic scaling.

Vast.ai Serverless runs autoscaling GPU inference endpoints on managed capacity.

Cloudflare R2: egress-free S3-compatible object storage with native Workers integration and Iceberg data catalog.

Cloudflare Workers: global serverless edge compute with zero cold starts, V8 isolates, and native R2/AI bindings.

Modal is a high-performance AI infrastructure cloud for online, batch, and multi-modal inference with instant autoscaling.

Managed cloud service for the Qdrant vector database.

ByteNite's serverless container platform distributes compute-intensive workloads across pre-warmed cloud machines for AI and data apps.

High-performance cloud storage optimized for AI training and inference workloads.

Managed durable execution service supporting hosted environments and deployments inside customers' own cloud accounts.
