Run controlled workloads that demonstrate Forge's scheduling, dependency, retry, and recovery behavior.
Start with Parallel Processing to watch the DAG, then try Failure & Retry Recovery to inspect attempt history. The full showcase combines both with an intentionally failed branch.
This is a shared live demo: runs are visible to every visitor. Up to three workflows run at once, with a short pause between launches and a daily compute budget.
5 tasks
Distributed Video Processing
Inspect a 30-second Tears of Steel excerpt, transcode three segments in parallel with FFmpeg, then merge a playable MP4 with audio.
Real film footage
Three parallel segments
H.264 output
Playback & download
Expected result: All five tasks succeed and the finished video appears on the workflow page.
Runtime details
The Docker image includes a 30-second 1280×572 Tears of Steel excerpt with audio. Allow up to two minutes.
23 tasks
Full Orchestration Showcase
A 23-task release pipeline: merge three data streams, fan out a test matrix, recover an unstable integration, and publish to two destinations while an experimental branch exhausts its retries.
Nested fan-out / fan-in
Four test shards
Retry → recovery
Retry budget exhaustion
Cascading skips
Independent release & audit
Expected result: The main release and audit succeed. The experimental check fails after three attempts and its two descendants are skipped, so the overall workflow intentionally ends FAILED.
Runtime details
Uses the shared Docker volume for retry recovery across workers. Allow 1–3 minutes.
5 tasks
Distributed Build & Verification
Run Forge's Java, C++ and Python verification workload as a distributed DAG.
Parallel execution
Multi-worker scheduling
Dependency fan-out
Join / release gate
Expected result: Succeeds when all three verification branches pass.
Runtime details
Docker workers include the source and build tools. Runs Java unit tests and C++ tests plus Python syntax checks; allow up to ten minutes.
4 tasks
Failure & Retry Recovery
Inject a first-attempt failure and watch Forge recover through a durable retry.
Intentional failure
Retry backoff
Attempt history
Dependency recovery
Expected result: Succeeds after the unstable task recovers on its second attempt.
Runtime details
Uses the shared Docker volume so a retry can recover on another worker.
5 tasks
Parallel Processing Pipeline
One preparation step releases three independent branches, then a final gate joins their results.
Fan-out
Parallel branches
Fan-in gate
Dependency ordering
Expected result: All tasks succeed; publish waits for every processing branch.
Runtime details
Python 3 on workers. Parallelism depends on available capacity.
4 tasks
Wait for Every Parent
Three independent inputs finish at different times. Watch the join stay blocked until the slowest is ready.
Multiple roots
Staggered completion
All-parent barrier
Blocked → pending
Expected result: The join succeeds only after all three inputs succeed.
Runtime details
Python 3 on workers.
5 tasks
Failure Isolation
A failing quality check prevents a shared release gate from running while an independent branch finishes normally.
Mixed parent results
Skipped release
Independent progress
Failure timeline
Expected result: Intentionally fails: release is skipped, but the independent branch succeeds.
Runtime details
Python 3 on workers.
4 tasks
Cascading Dependency Skip
Fail the first stage of a four-stage pipeline and follow the skip through every downstream dependency.
Transitive failure
Three skipped stages
No downstream attempts
Durable event history
Expected result: Intentionally fails: the remaining three tasks are skipped without execution.
Runtime details
Python 3 on workers.
3 tasks
Retry Budget Exhaustion
A consistently failing task uses all three attempts before Forge skips its dependent publish step.
Three attempts
Retry backoff
Terminal failure
Skipped dependency
Expected result: Intentionally fails after three attempts; publish never runs.
Runtime details
Python 3 on workers. Allow time for retry backoff.
10 tasks
Worker Capacity & Load
Release eight bounded jobs together and watch available worker slots fill, then join at a final completion gate.
Eight runnable jobs
Capacity-aware dispatch
Worker telemetry
Completion barrier
Expected result: All tasks succeed. Jobs queue when available slots are fewer than eight.
Runtime details
Python 3 on workers. Open Workers during the run to watch load.