Key Takeaways
- Secure isolation is non-negotiable for code migration agents: Refactoring agents execute AI-generated code that modifies production codebases. Modal uses gVisor containers for isolation, while E2B employs Firecracker microVMs for hardware-level security boundaries
- Session persistence determines migration scope: Multi-day legacy system migrations benefit from long-running sessions. Northflank advertises no forced time limits, while Daytona supports persistent sandboxes and can disable auto-stop, though its default auto-stop is 15 minutes. Modal and E2B cap sessions at 24 hours, with snapshotting options for longer workflows
- GPU support enables ML-powered code analysis: Code representation models such as CodeBERT and GraphCodeBERT can support code understanding tasks such as code search, clone detection, translation, and refinement; task-specific systems are needed for breaking-change detection or refactoring recommendation. Modal supports a broad GPU lineup including T4, L4, A10, L40S, A100 40GB/80GB, RTX PRO 6000, H100, H200, and B200, with request aliases such as
H100! and B200+ documented in the GPU guide - Production-proven platforms reduce migration risk: Modal powers over 10,000 teams including Ramp and Lovable, demonstrating enterprise-scale reliability for agent infrastructure
1. Modal
Modal delivers serverless compute for secure code execution at massive scale, the core sandbox workload for code migration agents, with on-demand GPU access for ML-powered code analysis and refactoring validation. The platform takes your code, containerizes it, and executes it in the cloud with automatic scaling. Modal provides code-first SDKs in Python, TypeScript, and Go for defining applications and infrastructure, using Sandboxes, calling Modal Functions, and managing resources, and Sandboxes can run code in any programming language the workload requires.
Core Capabilities
- gVisor container isolation: Secure sandboxed execution for running AI-generated refactoring code with workload-level isolation
- 100k+ concurrent sandbox sessions: Modal advertises support for 100k+ concurrent sandboxes. In Lovable's June 2025 promotional weekend, Modal ran over 1 million sandboxes in 48 hours and powered up to 20,000 concurrent sandboxes at peak, essential for enterprise-wide code migrations
- Fast cold starts: Engineered for fast cold starts and faster feedback loops, with an optimized filesystem that helps containers come online quickly without letting large images slow startup down, and Memory Snapshots can further reduce initialization-heavy Function cold starts for refactoring agents
- Broad GPU lineup: T4, L4, A10, L40S, A100 40GB/80GB, RTX PRO 6000, H100, H200, and B200, with request aliases such as
H100! and B200+ documented in the GPU guide, for running code analysis models
Security and Compliance
Modal maintains SOC 2 Type II certification and supports HIPAA-compliant workloads on Enterprise plans via a BAA. The platform uses gVisor-based sandboxing for compute isolation, TLS 1.3 for public APIs, and encryption for data in transit and at rest.
Production-Proven Results
Modal powers production workloads for notable AI companies:
- Ramp uses Modal Sandboxes to power Ramp Inspect, an internal background coding agent; Modal reports that roughly half of merged pull requests across Ramp's frontend and backend repos were started by Inspect
- Lovable ran over 1 million sandboxes in 48 hours, peaking at up to 20,000 concurrent sandboxes without on-call incidents
- Sync Labs processes over 100 hours of video daily with 95 deployments per day
What Makes Modal Unique
- AI-native container runtime: Modal's Core Platform highlights an AI-native container runtime, optimized filesystem, and multi-cloud capacity pool, with Modal Images providing code-defined image-building primitives
- Memory snapshotting: CPU Memory Snapshots capture CPU memory state to reduce initialization-heavy Function cold starts, with Modal reporting practical 3 to 10x speedups; GPU Memory Snapshots are Alpha. For Sandboxes that need to span more than 24 hours, Modal recommends Filesystem Snapshots
- Multi-cloud capacity pool: Deep CPU and GPU capacity across major cloud providers ensures availability without reservations
- Code-first SDKs: Modal provides code-first SDKs in Python, TypeScript, and Go for defining applications and infrastructure, using Sandboxes, calling Modal Functions, and managing resources, while Sandboxes run code in any programming language the workload requires
Best For: Teams building code migration agents that need secure execution at scale, ML-powered code analysis with GPU acceleration, and production-grade infrastructure with proven enterprise reliability.
2. Northflank
Northflank provides full-stack AI infrastructure with self-serve bring-your-own-cloud (BYOC) deployment and no forced session time limits, positioned for enterprise teams with strict data residency requirements and multi-day migration projects.
Core Capabilities
- Isolation options: Northflank advertises microVM-backed isolation and currently markets Kata Containers or gVisor on its sandboxes product page; some Northflank blog content also references Firecracker
- No forced time limits: Northflank advertises sandboxes that can run for seconds or weeks, enabling multi-week legacy system migrations without interruption
- Self-serve BYOC: Deploy across AWS, GCP, Azure, Oracle, CoreWeave, or bare-metal without enterprise sales cycles, per Northflank's bring-your-own-cloud materials
- GPU support: Includes L4, A100, H100, H200, B200, GB300, RTX Pro 6000, and other GPU types, per Northflank's current GPU pages
Production Scale
Northflank advertises millions of isolated workloads and maintains SOC 2 Type 2 certification, demonstrating enterprise compliance readiness for regulated code migration projects.
Architecture Approach
Northflank positions itself as a "full execution layer" combining sandboxes with databases, APIs, workers, and CI/CD pipelines. This integrated approach benefits teams that need to coordinate refactoring agents across multiple infrastructure components.
Best For: Enterprise teams requiring VPC deployment, no forced session time limits for multi-day migrations, and flexibility to choose their preferred isolation technology.
3. E2B
E2B specializes in secure sandboxes for AI agents, focusing on ephemeral code execution with Firecracker microVM isolation. The platform reports usage by 94% of Fortune 100 companies and states it has started over 1 billion sandboxes to date.
Core Capabilities
- Firecracker microVMs: Hardware-level isolation providing a strong security boundary for running untrusted AI-generated refactoring code, with E2B stating each sandbox is powered by Firecracker
- Sandbox startup: E2B supports sandbox startup and snapshot template loading for iteration cycles
- Open-source option: Self-hosting available via E2B's open-source repository for organizations with data sovereignty requirements
- Multi-language SDKs: Support for Python and TypeScript/JavaScript integration patterns
Use Case Focus
E2B excels at ephemeral code execution, spinning up isolated environments for agents to run generated refactoring code, then tearing them down. The platform supports up to 1,100 concurrent sandboxes on higher-tier plans, with a 24-hour session limit on Pro plans and a 1-hour limit on the Hobby (free) tier.
Enterprise Adoption
E2B is used by notable companies including Perplexity, Hugging Face, and Groq for AI agent workloads requiring strong isolation guarantees.
Best For: Teams building code migration agents that prioritize hardware-level isolation security and ephemeral execution patterns, particularly for shorter refactoring tasks that complete within 24 hours.
4. Daytona
Daytona provides persistent development environments and supports sandbox cold starts. The platform raised a $24M Series A in February 2026 and maintains 72,300+ GitHub stars on its open-source repository.
Core Capabilities
- Cold start support: Daytona supports sandbox cold starts for high-frequency refactoring operations
- Customer-managed BYOC: Sandboxes run on-premises or in customer cloud for data residency compliance
- Configurable runtime persistence: Daytona supports persistent sandboxes and can disable auto-stop, though its default auto-stop is 15 minutes of inactivity
- GPU support: Daytona documents GPU sandboxes, including H100 and RTX-PRO-6000 options
Architecture Approach
Daytona describes its sandboxes as isolated full computer environments with a dedicated kernel, filesystem, network stack, vCPU, RAM, and disk. The platform focuses on persistent workspaces that maintain state across sessions, benefiting agents that need to preserve cached dependencies and intermediate refactoring results.
Computer Use Support
Daytona offers Computer Use support for Linux desktop UI testing, with Windows and macOS in private alpha, enabling refactoring agents to validate visual changes in desktop applications.
Best For: Teams building high-frequency refactoring agents requiring sandbox provisioning and persistent state across sessions, particularly those with customer-managed infrastructure requirements.
5. Fly.io Sprites
Fly.io Sprites provides stateful sandbox VMs with checkpoint/restore capabilities and a 100GB persistent filesystem, suited for code migration agents that maintain large codebases across multiple sessions.
Core Capabilities
- 100GB persistent filesystem: Each Sprite provides a 100GB persistent filesystem; active execution uses NVMe-backed storage, with durable state backed by object storage
- Checkpoint/restore with wake and resume: Sprites supports checkpoint/restore and wake/resume behavior, though restore latency depends on state size and workflow
- Firecracker microVMs: Hardware-level isolation for running untrusted code
- Idle billing stops: Cost-efficient for intermittent refactoring agents that don't run continuously
Architecture Approach
Sprites emphasizes persistent state rather than purely ephemeral execution. The platform's checkpoint/restore capability enables agents to suspend mid-migration and resume their work, which is valuable for multi-day legacy system modernization.
Use Case Focus
The 100GB persistent filesystem and state persistence make Sprites particularly valuable for:
- Large monolith-to-microservices migrations requiring full codebase access
- Framework upgrades spanning multiple repositories
- Legacy system modernization with extensive intermediate state
Best For: Teams running code migration agents on large codebases requiring persistent storage and the ability to suspend/resume across multiple sessions.
6. CodeSandbox
CodeSandbox brings a snapshot-first approach to sandbox infrastructure, enabling parallel testing of multiple refactoring approaches from the same codebase state. CodeSandbox was acquired by Together AI in December 2024 and is now part of Together AI.
Core Capabilities
- Snapshot and forking: Branch from the same base state for parallel agent runs testing different refactoring strategies
- Snapshot restore: CodeSandbox supports snapshot restore and cloning, and Together's Code Sandbox docs describe startup from a template
- Dev Container support: Accepts standard devcontainer.json formats for reproducible environments
- microVM isolation: Secure execution with versioning capabilities
Architecture Approach
CodeSandbox's snapshot/forking model enables a workflow well-suited for code migration:
- Create a snapshot of the codebase pre-refactoring
- Fork multiple sandboxes to test different migration approaches in parallel
- Compare results and select the optimal refactoring path
- Roll back if a migration attempt fails
Use Case Focus
This approach benefits teams that need to:
- A/B test multiple refactoring strategies simultaneously
- Validate migrations across different dependency versions
- Maintain rollback capability throughout the migration process
Best For: Teams building code migration agents that benefit from parallel testing workflows, particularly for web application modernization where multiple migration paths need evaluation.
7. Cloudflare Sandboxes
Cloudflare Sandboxes provides container-based code execution built on Cloudflare Containers, running on Cloudflare's global network spanning 330+ cities.
Core Capabilities
- Globally distributed platform: Cloudflare Sandboxes run on Cloudflare's container infrastructure and integrate with a globally distributed platform
- TypeScript-first SDK: Native integration with modern JavaScript/TypeScript toolchains
- Multi-language execution: A TypeScript SDK/API for running Python scripts and Node.js/JavaScript applications; TypeScript workloads can be supported through the Node.js toolchain where configured
- Configurable persistence: keepAlive option for sandboxes that need to remain active
Architecture Approach
Cloudflare Sandboxes uses Linux containers with indefinite session support via the keepAlive option. Each sandbox has an isolated filesystem and maintains state while active, enabling agents to preserve context across operations.
Use Case Focus
Cloudflare's globally distributed platform makes Cloudflare Sandboxes potentially useful for code migration agents that need to:
- Validate application behavior across different geographic regions
- Test latency-sensitive code in multiple deployment locations
- Ensure migrated code performs consistently worldwide
Best For: Teams running code migration agents that need to validate performance and behavior across different geographic regions, particularly for internationally deployed applications.
Why Modal Stands Out for Code Migration and Refactoring Agents
Purpose-Built for Agent Workloads
Modal's architecture is specifically engineered for agentic and machine learning workloads. The platform's AI-native container runtime, optimized filesystem, and multi-cloud capacity pool are built for the unique demands of secure code execution, GPU-accelerated computation, and dynamic scaling that code migration agents require.
Secure Sandboxed Execution at Scale
Code migration agents generate and execute code that directly modifies production codebases, making isolation critical. Modal's sandboxes support 100k+ concurrent sessions with fast cold starts, gVisor isolation, and full observability for monitoring agent behavior during complex refactoring operations.
GPU-Powered Code Analysis
What separates Modal from CPU-only sandbox platforms is the ability to run ML models for code analysis within the same infrastructure. Code representation models such as CodeBERT and GraphCodeBERT can support code understanding tasks such as code search, clone detection, translation, and refinement; task-specific systems are needed for breaking-change detection or refactoring recommendation. Modal's broad GPU lineup, including T4, L4, A10, L40S, A100 40GB/80GB, RTX PRO 6000, H100, H200, and B200, enables teams to run these models alongside their refactoring agents without managing separate infrastructure.
Developer Experience Without Compromise
Modal provides code-first SDKs in Python, TypeScript, and Go for defining applications and infrastructure, using Sandboxes, calling Modal Functions, and managing resources, and Sandboxes can run code in any programming language the workload requires. Teams define compute requirements, container images, and scaling behavior directly in code. This approach enables the rapid iteration that code migration projects demand, without the friction of YAML-based configuration or manual infrastructure provisioning.
Production-Proven Scale
Modal powers cloud infrastructure for over 10,000 teams, including AI companies running production-critical agent workloads. Lovable's run of over 1 million sandboxes in 48 hours demonstrates the platform's ability to handle enterprise-scale migration projects without operational incidents.
Enterprise Security and Compliance
With SOC 2 Type II certification, HIPAA support via BAA on Enterprise plans, and comprehensive security practices including gVisor sandboxing and TLS 1.3, Modal meets the compliance requirements that enterprise code migration deployments demand.
For teams building code migration and refactoring agents that require secure execution, ML-powered analysis, and production-grade reliability, Modal's combination of AI-native infrastructure, massive sandbox scale, and proven enterprise track record makes it the clear choice.
