claude-code-system-prompts/system-prompts/data-managed-agents-scheduled-deployments.md
2026-06-10 13:10:24 -06:00

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Managed Agents — Scheduled Deployments

A scheduled deployment runs an agent on a recurring cron schedule — each firing creates a session autonomously. Use it for predictable-cadence work: nightly triage, weekly compliance scans, hourly monitors.

Requires the managed-agents-2026-04-01 beta header (the SDK sets it automatically for client.beta.deployments.* / client.beta.deployment_runs.* calls).

Create a deployment

A deployment bundles everything a session needs (agent, environment, optional files / GitHub / memory stores / vaults) plus a schedule and the initial_events that kick off each run:

  • agent and environment_id are required — same shapes as sessions.create (see shared/managed-agents-core.md).
  • initial_events must contain the starting user.message.
  • schedule takes a cron expression and an IANA timezone. Minute-level granularity is the maximum.
curl -fsSL https://api.anthropic.com/v1/deployments \
  -H "x-api-key: $ANTHROPIC_API_KEY" \
  -H "anthropic-version: 2023-06-01" \
  -H "anthropic-beta: managed-agents-2026-04-01" \
  -H "content-type: application/json" \
  -d @- <<EOF
{
  "name": "Weekly compliance scan",
  "agent": "$AGENT_ID",
  "environment_id": "$ENVIRONMENT_ID",
  "initial_events": [
    {"type": "user.message", "content": [{"type": "text", "text": "Run the weekly compliance scan."}]}
  ],
  "schedule": {
    "type": "cron",
    "expression": "0 20 * * 5",
    "timezone": "America/New_York"
  }
}
EOF
deployment = client.beta.deployments.create(
    name="Weekly compliance scan",
    agent=agent.id,
    environment_id=environment.id,
    initial_events=[
        {
            "type": "user.message",
            "content": [{"type": "text", "text": "Run the weekly compliance scan."}],
        },
    ],
    schedule={
        "type": "cron",
        "expression": "0 20 * * 5",
        "timezone": "America/New_York",
    },
)

The response is a deployment object (depl_ ID prefix). Check schedule.upcoming_runs_at — the next fire times — to confirm the schedule parses the way you intended:

{
  "id": "depl_01xyz",
  "status": "active",
  "paused_reason": null,
  "schedule": {
    "type": "cron",
    "expression": "0 20 * * 5",
    "timezone": "America/New_York",
    "last_run_at": null,
    "upcoming_runs_at": ["2026-05-09T00:00:00Z", "2026-05-16T00:00:00Z", "2026-05-23T00:00:00Z"]
  }
}

Deployments may apply up to 10 seconds of jitter to distribute load. Maximum 1000 scheduled deployments per organization (contact Anthropic support for more).

Cron and timezone semantics

  • Expression: standard POSIX cron (minute hour day-of-month month day-of-week).
  • Timezone: IANA identifier (e.g. "America/Los_Angeles").
  • DST: literal wall-clock matching — "0 20 * * *" in America/New_York fires at 8:00 PM local regardless of EST/EDT.

⚠️ DST edge: wall-clock times that don't exist on a spring-forward day (e.g. 2AM) are skipped; times that occur twice on a fall-back day fire twice. Schedule outside the 13AM local window, or use UTC, when missed or duplicate executions are unacceptable.

Deployment runs

Every trigger attempt — successful or not — writes a deployment run record (drun_ prefix), so you can audit failures independent of the session lifecycle. A successful run carries the created session_id; follow that session via the event stream (shared/managed-agents-events.md) or webhooks (shared/managed-agents-webhooks.md) as usual. A failed run carries an error whose type explains why session creation was rejected.

# All runs for a deployment
for run in client.beta.deployment_runs.list(deployment_id=deployment.id):
    print(run.created_at, run.session_id or run.error.type)

# Failures only
for run in client.beta.deployment_runs.list(deployment_id=deployment.id, has_error=True):
    print(run.created_at, run.error.type, run.error.message)
for await (const run of client.beta.deploymentRuns.list({
  deployment_id: deployment.id,
  has_error: true,
})) {
  console.log(run.created_at, run.error?.type, run.error?.message);
}

Raw HTTP: GET /v1/deployment_runs?deployment_id=...&has_error=true.

A failed run looks like:

{
  "type": "deployment_run",
  "id": "drun_01abc124",
  "deployment_id": "depl_01xyz",
  "trigger_context": { "type": "schedule", "scheduled_at": "2026-05-09T00:00:00Z" },
  "session_id": null,
  "error": { "type": "environment_archived", "message": "environment `env_01abc` is archived" },
  "agent": { "type": "agent", "id": "agent_01ghi789", "version": 3 },
  "created_at": "2026-05-09T00:00:01Z"
}

Error types include environment_archived, agent_archived, vault_not_found, session_rate_limited, and service_unavailable.

Lifecycle: pause / unpause / archive

Operation SDK Effect
Pause client.beta.deployments.pause(id) Suppresses scheduled triggers go-forward. Sessions already running continue. Manual runs are still permitted while paused. Sets paused_reason: {"type": "manual"}.
Unpause client.beta.deployments.unpause(id) Resumes from the next scheduled occurrence. Missed triggers are not backfilled. Clears paused_reason.
Archive client.beta.deployments.archive(id) Terminal — the schedule stops and the deployment can no longer be modified. Use pause for anything reversible.

Raw HTTP: POST /v1/deployments/{deployment_id}/pause (likewise /unpause, /archive).

Failure behavior

  • Rate-limited: recorded immediately as a session_rate_limited run, no retry — the schedule simply tries again at the next occurrence. (Rate limits on API calls inside a session are handled by the session itself.)
  • Other failed runs (e.g. environment_archived, vault_not_found, service_unavailable): the run records the error.type — monitor runs and fix the referenced resource, or pause the deployment.
  • Agent archived or deleted: the deployment is automatically archived (terminal) and no further sessions are created.

Manual runs

POST /v1/deployments/{deployment_id}/run (SDK: client.beta.deployments.run(id)) creates a session immediately and writes a run with trigger_context.type: "manual". Use it to test a deployment before committing to the schedule — and remember it works even while the deployment is paused.