Story: Draw the node heatmap and carry the engine run statistics
Table of Contents
This page documents a story in Sprint 30, carried unfinished from Sprint 28 at close. It captures the goal, current status, acceptance criteria, and the tasks that compose it.
1. Goal
The grid screen draws the node heatmap and state ribbon, a node sample states the engine's run time and peak memory, and the run statistics are measured, recorded and aggregated for the grid.
2. Status
| Field | Value |
|---|---|
| State | BACKLOG |
| Parent sprint | Sprint 30 |
| Now | The heatmap and the tenant and party grid views are built. The run statistics, the state ribbon and the cost are not. |
| Waiting on | Nothing. |
| Next | Record the run statistics on the result, then measure them in the wrapper. |
| Last touched | 2026-11-08 |
3. Acceptance
- The grid screen draws the node load heatmap and the node state ribbon from the node series, grouped by machine.
- The wrapper measures the engine run time and peak memory and sends them with the result.
- The result records its run statistics and a grouped read aggregates them per workunit and batch.
- A node sample carries the engine run time and peak memory of its jobs, and each host has a cost rate so the grid screens open to a tenant administrator.
4. Tasks
| Task | State | Start | End | Description |
|---|---|---|---|---|
| Draw the node heatmap and the state ribbon | BACKLOG | One row per node, one column per interval, grouped by machine. | ||
| Add the engine run time and peak memory to the node sample | BACKLOG | The wrapper reads ORE's runtimes.csv and its memory lines and reports them in the node sample. | ||
| Attribute job cost and show the grid to a tenant | BACKLOG | Give each host a cost rate and each result a cost, apportion idle cost, and open the grid screens to a tenant's administrator with a breakdown by party. Carries on from Operate the grid across tenants and by party. | ||
| Record the run statistics on the result | BACKLOG | Add started_at, finished_at, input_bytes, output_bytes and peak_memory_bytes to the result, and carry them in the submit message. | ||
| Measure the run statistics in the wrapper | BACKLOG | The wrapper measures the start and end of the engine run, the input and output bytes, and the engine's peak memory per job, and sends them with the result. | ||
| Aggregate the run statistics per workunit and batch | BACKLOG | A grouped read returns, for a workunit or a batch, the earliest start, the latest finish, the summed bytes and the largest peak memory of its results. |
5. Decisions
- 2026-10-21: The heatmap and the tenant and party grid views were built before the run statistics. The grid screen shows counts of batches, workunits and results. It shows no row of any of them, because the journeys that define those screens (Browse the grid's jobs, Follow a job) are not built.