Workflow orchestration / Trainy Konduktor and Pluto alternative

A Trainy Konduktor alternative for the agent around training jobs

Trainy offers Konduktor for GPU cluster scheduling and management and Pluto for experiment tracking. Konduktor runs on customer cloud or on-premise infrastructure; Pluto stores experiment records and artifacts. These products serve training operations rather than one standard persistent whole-OS agent computer.

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Reviewed 2026-10-19 · Published by the Sandbox0 team

When Trainy Konduktor and Pluto fits

Trainy fits teams managing GPU training queues, preemption, networking, health checks and experiment records. Keep required cluster operations and experiment tracking when moving a compatible Linux agent workflow.

When to consider Sandbox0

Consider Sandbox0 for the agent that prepares and coordinates training with a complete durable writable RootFS, automatic online growth and supported files while guest compute stays paused. GPU clusters, schedulers and experiment tracking remain separate.

Capabilities

Trainy Konduktor and Pluto and Sandbox0: what persists?

Feature comparison with documentation and verification status
Environment and runtime lifetimeTrainy Konduktor and PlutoNot established in this reviewSandbox0ttl and hard_ttl default to 0 (disabled). Configure idle pause and deletion policies for the same persistent sandbox identity; an idle running sandbox still accrues compute charges.Read documentation →
Persistent filesTrainy Konduktor and PlutoObject-store inputs and Pluto experiment artifacts retain application data, but a standard persistent writable guest disk contract is not established.View evidence ↗Sandbox0The writable RootFS survives successful checkpoints, including software, system configuration, dependencies, and user data.Read documentation →
Whole RootFSTrainy Konduktor and PlutoConfigured workdir/file synchronization and scheduler restart do not establish complete mutable OS filesystem retention.View evidence ↗Sandbox0Persistence extends beyond /workspace to paths such as /usr/local, /etc, and /home. Runtime tmpfs and virtual filesystems are excluded.Read documentation →
Release compute, keep stateTrainy Konduktor and PlutoKonduktor workloads can be suspended and unsuspended under scheduler control; exact process-memory continuation is not established.View evidence ↗Sandbox0Pause compute between tasks; resume on available capacity. Default resume starts fresh processes from the saved filesystem.Read documentation →
Memory and process stateTrainy Konduktor and PlutoPluto run resume/fork concerns experiment records, not documented arbitrary guest RAM/process snapshots.View evidence ↗Sandbox0Experimental memory checkpoints can preserve compatible process state. Use memory: true on both pause and resume on a compatible deployment. A filesystem checkpoint alone does not preserve running processes.Read documentation →

Online RootFS growth

On growth-enabled images, Sandbox0 automatically expands the writable RootFS as free space runs low, within a configured sparse logical ceiling up to 64 TiB. Agent processes keep running. Growth is enabled in the qualified Cloud region; confirm activation for other regions. Existing images and snapshots retain their captured storage geometry. The ceiling is logical capacity, not preallocated host disk.

Cluster scheduling, per-node scale and experiment storage allowances do not establish automatic online expansion of a complete durable agent RootFS.

Files while compute is paused

Sandbox0's Files API reads persistent files without resuming compute. Filesystem-only pauses also permit edits; retained-memory pauses are read-only and reject mutations with 409. SSH, SFTP, file watching, and runtime-only mounts require running compute.

See paused file operations →

Konduktor suspension is a scheduler lifecycle

A user can stop and restart a workload, and the system can suspend it for quota or higher-priority work. On activation, configured workdir/files are synchronized and the run script begins. This supports resumable scheduling but does not establish that every process resumes from captured RAM or every mutable OS path returns.

Source 1 ↗

Pluto resume reopens an experiment record

Pluto can reopen a finished run to append metrics, and its close and finish operations have different effects on server status. This is experiment-record continuity, not evidence of a running machine memory checkpoint. Forked experiment history and container/GPU process state should be evaluated separately.

Source 1 ↗

The two products have separate fees and infrastructure costs

Konduktor uses a platform fee plus per-node pricing sized to the cluster and support needs. Pluto’s hosted Pro tier is $250 per seat-month, with a limited free hosted tier; free self-hosted Pluto still uses customer infrastructure. The hosted tracking subscription is not a GPU-hour or general VM bundle.

Source 1 ↗

Pricing

Compare billing models, then price your workload

CPU allocation, memory, billing minimums, disk, plan fees, and supported workload differ. These meters are not equal-performance machine quotes. Confirm region, resource units, and included allowances before estimating a total.

Trainy Konduktor and Pluto

Pricing reviewed 2026-10-19

Konduktor
Custom platform fee plus per-node pricing
Deployed into the customer’s cloud or on-premise cluster.
Rate source ↗
Pluto hosted Free
$0 with 2 seats and 2 GB storage
Rate source ↗
Pluto hosted Pro
$250 per seat/month
Published tier supports up to 10 seats, with tracking and storage allowances.
Rate source ↗
Pluto self-hosted software
Free; customer infrastructure is separate
Rate source ↗

Do not use the Pluto seat price as Konduktor or GPU pricing. Confirm Pro’s published 10 billion data points/month, 10 TB storage and other allowances, Enterprise terms above 10 seats, and the underlying cluster/cloud bill. Academic and current YC-batch discounts have eligibility conditions.

Check current Trainy Konduktor and Pluto pricing ↗

Sandbox0

$0.015/GiB-hour compute (billed by the second at approximately $0.000004167/GiB-second), plus $0.02/GiB-month of retained incremental RootFS and memory checkpoint data. Shared base images and platform recovery retention are excluded; paused sandboxes accrue storage charges only.

Compute / GiB-hour
$0.015
Retained data / GiB-month
$0.02
Paused compute
$0.00

A 4 GiB agent, 100 running hours

$6.00 compute

4 GiB × 100 hours, billed by the second. Keeping 20 GiB of billable incremental data for a full billing month adds $0.40. CPU is derived from memory by the platform; choose a tier that fits your workload.

Understand storage billing →

Before migrating from Trainy Konduktor and Pluto

  1. Separate Konduktor clusters/queues, configured workdirs, external object data and Pluto metrics/artifacts with their distinct fees.
  2. Keep required GPU operations and tracking, and export compatible Linux agent tools, configurations and files.
  3. Test training behavior separately from agent system retention, growth, supported paused files and complete infrastructure plus platform costs.

Common questions

Is Sandbox0 a drop-in Trainy Konduktor and Pluto replacement?

Evaluate API compatibility and product scope. These products serve different core workflows, so a change may require a different architecture.

Does keeping files also keep a running agent?

Filesystem state and volatile process state are separate. Sandbox0 requires explicit compatible memory checkpoints to preserve running processes; its default filesystem resume starts fresh processes.

Sources and review scope

The Boat team's Battleships directory is the discovery source. References below describe the product and plan discussed on this page. Check current availability, regional terms and billing units before migrating. Where the cited material does not establish a capability or price, the comparison identifies that uncertainty.

Battleships research record ↗docs.trainy.ai/lifecycle.md ↗docs.trainy.ai/pluto/run-lifecycle.md ↗www.trainy.ai/pricing ↗Sandbox0 RootFS capacity →

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