ILay 554c92ec92 [SIMPL-30451] Run T1 and T4 on the sandbox
Executed from a pod in dataprovider01 with a local SQLite instance, deliberately not the platform's Postgres. T1 reachability passes: check_tcp_reachable against pg-cluster.common01.svc.cluster.local:5432 returned True. T4 passes: tightly_coupled_local_job reached RUN_SUCCESS with one entry in contributing_hosts and four distinct PIDs in contributing_workers, which is what the row predicts. Torn down afterwards.

The run exposed a defect in this service. report_execution_target warns that DAGSTER_POSTGRES_HOST, DAGSTER_POSTGRES_USER and DAGSTER_POSTGRES_DB are missing and calls that a tightly coupled misconfiguration, but the Simpl chart never sets them - it injects DAGSTER_PG_PASSWORD and bakes host, user and database into dagster.yaml. TIGHTLY_COUPLED_ENV_VARS therefore reports a misconfiguration that is not one, and would do so on a correctly configured platform run pod.

It also made the T6 obstacle concrete rather than theoretical: step outputs were written to /dagster-home/storage via PickledObjectFilesystemIOManager, which under k8s_job_executor lands on a volume no other step pod can read.

Changelog: added
2026-08-31 20:17:45 +02:00
2026-08-31 09:40:56 +00:00
2026-08-31 09:39:11 +00:00
2026-08-31 09:41:39 +00:00

Distributed Execution

Canonical location for documentation, example workflows and reference service implementations covering distributed execution patterns in the Simpl orchestration platform.

The service answers one question for every workflow: where does the compute actually run, and how does runtime information get back to the control plane?

Contents

Area Location Status
User guide documents/user-guide/distributed-execution-guide.md Complete
Readiness checklist documents/user-guide/readiness-checklist.md Complete
Tightly coupled reference src/distributed_execution/tightly_coupled/jobs.py Runnable
Loosely coupled reference src/distributed_execution/loosely_coupled/jobs.py Runnable (subprocess verified)
External payload payload/work.py Runnable
Example configuration yaml/ Complete

Project structure

distributed-execution/
├── src/
│   └── distributed_execution/
│       ├── repository.py           # Dagster definitions (entry point)
│       ├── ops.py                  # Shared ops used by both patterns
│       ├── preflight.py            # Readiness checks backing the checklist
│       ├── tightly_coupled/
│       │   └── jobs.py             # in_process / multiprocess / k8s_job_executor
│       └── loosely_coupled/
│           └── jobs.py             # PipesSubprocessClient / PipesK8sClient
├── payload/                        # External workload: dagster-pipes ONLY
│   ├── work.py
│   ├── requirements.txt
│   └── Dockerfile
├── documents/user-guide/           # AC1-AC4 documentation
├── yaml/                           # Working example configuration
├── tests/
├── Dockerfile
├── pyproject.toml
└── workspace.yaml

Getting started

Prerequisites: Python 3.12+ and uv.

uv sync --dev
uv run dagster dev -f src/distributed_execution/repository.py

The Dagster UI is then available at http://localhost:3000. Two jobs run end to end on a laptop with no cluster: tightly_coupled_in_process_job and loosely_coupled_subprocess_job. The Kubernetes variants of each require a cluster and are documented in the user guide.

tightly_coupled_local_job uses multiprocess_executor. It did not complete on a Windows development machine during authoring — see the Windows note in the user guide's section 5.5.

Running tests

uv run pytest

Building the images

Two images, deliberately: the code location and the external payload are versioned and scanned independently.

docker build -t distributed-execution:0.1.0 .
docker build -f payload/Dockerfile -t distributed-execution-payload:0.1.0 payload/

Both images build and have been smoke tested locally: the code location image loads its definitions, and the payload image contains dagster_pipes without dagster — check L11 in the readiness checklist.

Both must be tagged from the same commit. That shared tag is what keeps a code location and the payload it dispatches on the same version, and nothing at runtime checks the pairing — see the Outstanding work section for what the pipeline still has to learn.

Status

Both execution targets are implemented. The tightly coupled jobs and the loosely coupled subprocess transport are verified by the test suite. The loosely coupled Kubernetes transport is implemented but has not yet been run against a cluster; see the guide's Outstanding work section.

Licence

European Union Public Licence v1.2 — see LICENSE.

Description
Execution targets and integration patterns for Dagster workflows on the Simpl orchestration platform (SIMPL-30451).
Readme 1 MiB
Languages
Python 92.9%
Dockerfile 7%
Shell 0.1%