2814f421 Andy McCall 25 days ago ↶
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# Jetstream
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* Design and architecture decision, 2026-10-11 (oxygenflow#38). Builds on
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spec §11, runner capabilities and placement (#36). Crate and CLI: ` jet` .*
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** Flow** says what to run: a pipeline of hermetic jobs, each in a sandbox,
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with its outputs, reports and signed receipt. ** Jet** carries each job to
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where it should run: a fleet of runners on your own machines, on
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Kubernetes or in the cloud, that measure themselves, explain every choice
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they make, and fetch what they need on their own.
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## 1. The decision
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** Context.** Today OxygenHub holds the job queue and talks to runners
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directly (` /api/v1/flow/claim` , logs, outputs, finish). Runners are
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configured by hand: images are copied onto each machine, labels steer
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jobs, and a job that cannot run anywhere simply waits. Every
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self-hosted CI system has the same shape and the same problems (§2), and
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none of it is specific to Oxygen.
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** Decision.** The fleet becomes a service of its own, ** Jetstream** :
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- Jetstream owns the queue, the runners and their measured facts,
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placement and its explanations, pools (hosts, Kubernetes, cloud
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providers) and images. It knows nothing about repositories.
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- The ** forge** owns pipelines, runs, checks, receipts, artifacts,
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reports and the UI. It hands Jetstream jobs and receives their events.
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- ** OxygenHub embeds Jetstream** in its own process by default, so nothing
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changes for anyone who never configures it, and can instead point at a
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standalone ` jet server` shared by several forges.
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- ** Sources are pluggable** : an Oxygen repository is mounted lazily
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through flow-casfs; a Git repository is checked out.
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- ** ` flow run` ** runs a pipeline on your own machine through an
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in-process Jetstream with one local runner: the same code path as CI.
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** Consequences.**
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- Jetstream can be reused by others, and could later run jobs for forges
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that are not OxygenHub (§12) without a rewrite.
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- One more boundary to keep stable: the forge contract (§4) is versioned.
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- Oxygen's advantage becomes visible: the same fleet runs both kinds of
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source, and an Oxygen job starts without a checkout (§5).
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``` mermaid
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flowchart LR
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subgraph Forges
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OH["OxygenHub<br/>pipelines · runs · checks<br/>receipts · reports"]
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OTHER["another forge<br/>(an adapter, later)"]
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end
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subgraph JS["Jetstream (jet)"]
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Q["queue"]
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P["placement<br/>+ why"]
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F["runner facts"]
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I["images"]
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D["demand"]
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end
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subgraph Pools
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H["hosts<br/>earth-1 · plex-1 · narvi-1"]
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K["Kubernetes<br/>controller, pod per job"]
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C["cloud<br/>GCP · AWS · Azure"]
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end
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OH -- "jobs" --> Q
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OTHER -. "jobs" .-> Q
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Q -- "events: logs, outputs,<br/>finish, receipt" --> OH
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Q --> P
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F --> P
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H -- "claim + facts" --> P
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K -- "claim + facts" --> P
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C -- "claim + facts" --> P
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I -- "by hash" --> H
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I -- "by hash" --> K
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I -- "by hash" --> C
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D -- "how many, of what" --> K
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D -- "how many, of what" --> C
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```
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## 2. What it fixes
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Research into self-hosted runners (GitHub Actions, GitLab, Buildkite,
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Jenkins, Forgejo; 2023–2026) found the same complaints everywhere. Most of
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them are fleet problems, not pipeline problems.
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| Persistent runners leak state; fork PRs and compromised actions reach other jobs' secrets | A fresh microVM per job (or the syscall tier); nothing survives a job |
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| A job waits for hours, then fails, with no reason given | Every waiting job says why, in terms of facts (§7) |
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| Disk fills mid-job; an OOM kill shows up as a "lost runner" | Disk and memory checked on every claim against what the job needed last time; OOM reported as OOM |
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| Images copied to each machine by hand; slow pulls | Images served by hash, fetched by the runner on demand, chunked so a rebuild moves only what changed (§8) |
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| Exact-match labels that sprawl | Facts measured by the runner; labels only steer (§7) |
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| Lost runners and spot reclaims leave jobs hanging | Requeue on a lost runner or a reclaim notice (§11) |
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| Forced runner upgrades with a cut-off date | Runners update themselves between jobs; the contract is versioned |
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| Ephemeral runners start cold, 30–60 s and no caches | Firecracker boots in about a second; images and caches stay warm by hash |
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| Multi-arch builds through QEMU, 5–30× slower; no RISC-V runner at all | Native runners per architecture, RISC-V included (narvi) |
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| No queue, utilisation or cost figures | Queue time, utilisation and cost by job, pool and region, built in (§11) |
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## 3. Responsibilities
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| Pipeline from the repository | | ✔ |
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| Runs, jobs, ` needs` , the run page | | ✔ |
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| Queue, placement, why a job waits | ✔ | shows it |
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| Runners, their facts and tokens | ✔ | shows them |
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| Pools: hosts, Kubernetes, cloud | ✔ | |
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| Images | ✔ (by hash) | |
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| Secrets and variables | carries them to the job | ✔ (stores them) |
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| Job identity (OIDC) | carries the token | ✔ (issues it) |
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| Logs | streams them | ✔ (keeps them) |
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| Outputs, reports, receipts | carries them | ✔ (keeps, checks, shows) |
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| Checks on a change | | ✔ |
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## 4. The contracts
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Two contracts, both HTTPS and JSON, versioned from the start.
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** Forge ↔ Jetstream.** The forge submits a job and follows it.
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- ` submit` : the job's spec (sandbox, image hash per architecture, exec,
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outputs, time limit), its ** source** (§5), its secrets and OIDC token,
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the forge's run and job ids, and optional steering (` runs-on` ,
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` prefer` ).
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- ` events` : a stream per forge of ` placed` (where, and why), ` started` ,
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` log` , ` output` (a file or blob), ` finished` (exit code, peak disk and
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memory, duration), ` receipt` (signed by the runner), and ` waiting`
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(why, when nothing fits).
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- ` cancel` , and ` queue` (what is waiting, for the forge's pages).
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** Runner ↔ Jetstream.** What runners already do with the hub today, moved:
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` claim` (with its facts, §6), ` log` , ` output` , ` finish` , ` decline` (with a
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reason). A runner talks only to Jetstream, never to a forge: moving from
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embedded to external Jetstream is a URL change for it.
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``` mermaid
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sequenceDiagram
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participant Forge as OxygenHub
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participant Jet as Jetstream
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participant R as earth-1
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Forge->>Jet: submit(job, source, secrets, token)
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Note over Jet: queued: needs x86_64, microvm,<br/>~6 GiB disk (from its last run)
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R->>Jet: claim(facts: idle, 41 GiB free, holds image)
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Jet->>Forge: placed on earth-1 (holds the image, idle, score 100)
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Jet->>R: job
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R->>Jet: log, log, output
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Jet->>Forge: log, log, output
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R->>Jet: finish(exit 0, peak 5.2 GiB disk, 3.1 GiB memory)
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Jet->>Forge: finished + receipt
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```
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## 5. Sources: mounted, or checked out
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A job's source says how a runner gets its files.
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- ** Oxygen** (` oxy://HUB/OWNER/NAME@STATE` ): flow-casfs mounts the state
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read-only and reads objects as the job touches them (spec §5.1). Nothing
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is checked out; a job that reads 50 files of a 100,000-file repository
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fetches 50 files. Jobs whose scope a change does not touch keep their
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previous result (spec §6), and receipts name the exact state.
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- ** Git** (` git+https://…@COMMIT` ): the runner clones or fetches the
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commit into the job's disk before it starts, as every CI system does.
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Both run through the same fleet, so the difference is measured, not
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claimed: the job page shows how long the source took.
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``` mermaid
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flowchart TB
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subgraph O["Oxygen source"]
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O1["job starts"] --> O2["mount state (ms)"] --> O3["read files as used"]
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end
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subgraph G["Git source"]
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G1["clone / fetch commit"] --> G2["check out every file"] --> G3["job starts"]
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end
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```
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## 6. Facts: runners know what they are
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A runner measures itself, and sends what it measured ** with every claim** .
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Idle runners claim every few seconds, so Jetstream always holds every idle
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runner's facts from moments ago; there is no separate audit channel to go
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stale.
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| Architecture, CPU model, cores | ` uname` , ` /proc/cpuinfo` | at start |
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| Tiers: microvm (KVM opened, not assumed), syscall (Landlock ABI), wasm | probing | at start, then hourly |
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| Memory free, disk free where jobs run | ` /proc/meminfo` , ` statvfs` | every claim |
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| Load, jobs running | ` /proc/loadavg` , its own state | every claim |
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| Images held | its image store | every claim |
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| Speed score | a fixed few-second benchmark (hashing, compression, a small compile), normalised so earth-1 ≈ 100 | at start, then about every 15 minutes while idle |
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| Where it runs | the pool: host, cluster and node, or cloud, region, instance type, spot | at start |
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The score is checked against reality: Jetstream compares each runner's
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claimed speed with how fast its jobs actually ran, and ranks a runner
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whose real timings drift (thermal throttling, noisy neighbours) by what
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it achieved.
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## 7. Placement: requirements, ranking, and why
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** A job's requirements are mostly derived** , never typed by the user:
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- architecture from its image;
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- tier from its sandbox;
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- disk and memory ** learned from its own past runs** (peak plus
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headroom); a new job goes to the roomiest runner the first time;
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- an explicit floor when the pipeline gives one.
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** Placement** filters, then ranks:
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1. ** Filter on hard facts:** architecture, tier, enough free disk and
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memory now, steering that requires a pool or label.
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2. ** Rank on soft ones:** already holds the image (warm), idle, speed
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score, the shortest estimated finish.
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3. ** A short hold for the best fit:** when the runner asking is a poor
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fit and a better one claimed seconds ago, the job is held a few seconds
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for it, then goes to whoever is next.
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4. ** The runner has the last word:** it checks again on accept and
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declines with a reason if its disk filled meanwhile.
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** Every decision explains itself** , on the job and through the API:
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> ran on ** earth-1** : holds the image, idle, score 100, estimated 4 min
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> ** waiting** : needs ~12 GiB disk (its last run used 10.4); plex-1 has 9;
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> earth-1 is busy until about 11:40
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** Labels only steer.** ` runs-on "plex"` pins, ` prefer "fast"` biases. A
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user who never writes one never needs to.
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## 8. Images
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- ** Content-addressed.** An image is an ext4 root file system named by
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its BLAKE3 hash (` cas://blob/…` ), as today. A sandbox may name one per
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architecture.
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- ** Served by Jetstream.** A runner that lacks an image fetches it by hash
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and verifies it; nobody copies images between machines. Images are
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chunked, so a rebuilt image moves only its changed chunks.
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- ** Built by Flow.** An image is a job's output: a project's
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` .flow/image/` becomes a job, its image is kept and served, and the
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sandbox's pin follows it (a proposal: "image changed: af3c… → 91be…").
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- ** Architecture recorded at build** , so an x86 image never reaches a
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RISC-V runner.
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b14aeaae Andy McCall 24 days ago ↶
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### 8.1 The swarm: runners share images
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Runners that are configured for it fetch image chunks from each other as
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well as from the hub (oxygenflow #47, oxygenhub #144). Fifty fresh
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runners asking for the same 2 GiB image then cost the hub about one copy,
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not fifty, and a site behind a thin link pulls each chunk across it once.
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- ** Trust comes from the hashes.** The manifest comes from the hub, and
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every chunk is checked against its name before it is kept. A peer can
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fail to help; it can never change what a job runs.
ecce3719 Andy McCall 24 days ago ↶
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- ** The hub is the tracker.** A runner reports its swarm address, its site
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and its certificate's fingerprint with every claim. ` POST /api/v1/flow/swarm/announce {image, state}`
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(` fetching` , ` done` or ` stopped` ) returns the peers in the same site that
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hold the image or are fetching it, and a ** ticket** .
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- ** Tickets admit peers.** A ticket names the runner, its site and an
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expiry (15 minutes), signed with the hub key that ` /.well-known/oxyhub-key`
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publishes. A runner shows its ticket once to each peer
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(` POST /swarm/v1/hello` ) and gets a session for the ticket's life; no
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other runner and no account can take chunks from a peer.
ecce3719 Andy McCall 24 days ago ↶
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- ** Encrypted, and pinned by the hub.** Each runner makes its own TLS
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certificate on first use (` swarm/cert.der` , its key readable by the
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runner alone) and keeps it, so its fingerprint (BLAKE3 of the
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certificate) holds across restarts. The tracker hands each peer out with
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that fingerprint, and a fetcher talks only to a peer showing that
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certificate and proving its key in the handshake; no CA is involved. A
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peer at another address, or a stranger at a peer's, gets nothing and
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sees nothing: chunks, tickets and sessions all travel inside TLS.
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- ** The peer protocol** is HTTPS on the runner's swarm address:
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- ` POST /swarm/v1/hello` with the ticket: a session token.
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- ` GET /swarm/v1/images/{image}/have` : ` complete` , or two bit maps over
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the manifest's needed list (` Manifest::needed` ), in its order: the
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chunks it has, then the chunks it is fetching now.
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- ` GET /swarm/v1/chunks/{chunk}` : the chunk's bytes, from the chunk
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cache or read out of a whole image; ` 503` when the peer is at its
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connection limit, and the fetcher asks it again shortly.
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- ** Rarest first.** The fetcher refreshes every peer's maps twice a
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second and asks each peer, four requests at a time, for the chunk the
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fewest peers hold. The hub is a seed that holds everything: it is asked
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only for chunks no peer has or is fetching, or any chunk once the peers
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have made no progress for two seconds. Runners that start together so
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split the hub's chunks between them rather than each taking them all. When every missing chunk is already asked
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for, idle workers ask a second source for it (the endgame; the hub joins
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it only once the peers stall). A peer that
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fails is dropped and its chunks go back to the pool.
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- ** Serving while fetching.** A chunk is offered to others as soon as it
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is checked and kept, so runners starting together share the load.
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- ** Bounded.** A runner serves at most 16 connections and ` upload_mib_s`
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(default 50 MiB/s), so serving never starves its own jobs.
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- ** Configured, never assumed.** Without a ` [runner.swarm]` section a
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runner neither listens nor asks peers. Peers are not offered across
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sites, so a site is the network its runners can reach each other on.
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In flow.toml (or as ` [swarm]` in runner.toml, which stands in for the
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` [runner]` section):
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``` toml
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[runner.swarm]
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listen = "0.0.0.0:7401" # where peers reach this runner
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advertise = "10.0.0.5:7401" # the address peers are given (default: listen)
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site = "home" # peers are only ever in the same site
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upload_mib_s = 50
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```
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c90dd8d5 Andy McCall 10 days ago ↶
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### 8.2 Runners update themselves
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Proposed 2026-10-25 from Andy's experience: keeping a large fleet's
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runners up to date by hand is one of the biggest costs of running CI.
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Runners fetch new runner builds the way they fetch images, from each other
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through the swarm, check them as strictly as a release, and swap
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themselves in without losing work, under a policy the organisation sets,
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testing on a few runners before the rest.
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** A runner build** is a ` flow` binary from an OxygenFlow release, one per
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target (linux-x86_64, linux-arm64, linux-riscv64; Windows and macOS when
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those runners exist), built by Flow from the tagged state with a signed
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receipt, as oxy's and OxygenHub's releases are. The hub serves it as a
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blob with a chunk manifest, so the swarm (§8.1) carries it unchanged: one
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runner of a site fetches each chunk from the hub and the rest from it.
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** Off unless chosen, nearest wins.** The policy is set for the site, an
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organisation, a test group and a runner; the nearest setting wins:
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- ` updates` : ` off` (the default) or ` on` ;
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- ` channel` : ` stable` , ` canary` , or a pinned version (` 0.3.4` );
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- ` window` : hours in which a runner may update (outside them it waits);
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- ` dry_run` : fetch and check, say what would happen, do not swap.
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A runner's own ` flow.toml` has the last word: ` [runner.update] allow =
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false` refuses every update whatever the hub says, so a site can hold a
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machine back while it tests.
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** Test groups and waves.** A test group is a named set of runners: chosen
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by name, by label or by pool. A rollout is a release and its waves, in
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order; each wave is a group and its share of it, ** a percentage or chosen
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runners** . A percentage is taken by a stable hash of each runner's id, so
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"10% of build-farm" is the same machines every rollout, the ones the
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organisation watches. A wave starts when the one before has been healthy
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for its soak time (say 24 hours) or when an admin promotes it. For
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example: canary (two chosen runners), then build-farm at 10%, then
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build-farm at 100%, then everyone.
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** Healthy** means the updated runners came back on the new version within
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ten minutes, claim jobs, and their jobs' infrastructure errors (` lost` ,
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` error` , declines) over the soak are no worse than the same runners' on
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the version before, over enough jobs to tell. A wave that is not healthy
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halts the rollout, and its runners roll back. Job failures from the
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pipelines themselves do not count.
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** On the runner,** in order:
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1. The hub's answer to a claim or heartbeat names an update when the
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policy says so: the version, its blob and manifest, its receipt.
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2. Fetch the blob through the swarm (hub as seed); every chunk checked
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against the manifest from the hub.
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3. Check it as a release: its BLAKE3 matches the release asset the hub
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attests; the receipt is signed by an ` owned` build runner (trust
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classes, #79) and names the tagged state; the target is this machine's.
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A peer can only serve bytes; it cannot change what is installed.
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4. Stage it (` bin/flow.new` ) and run its self-check (` flow.new tiers` ,
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` --version` ).
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5. Drain with notice (` leave_within` , §11.5.2 of the spec): finish what
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fits, hand back the rest with its checkpoints.
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6. Swap: ` flow` → ` flow.prev` , ` flow.new` → ` flow` , and restart.
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7. Prove it: the first claim reports the new version. A runner that will
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not start, or that the hub does not hear from within ten minutes, goes
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back to ` flow.prev` (a start counter in the runner's home: three
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failed starts after an update restore the previous build).
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8. The runner's page shows its version, channel, group, last update and
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why; the audit log records every update and rollback.
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** Phones** take runner updates with the app's releases (Android updates an
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app only through its store or an install), so they follow the app.
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** Order of work:** (1) the runner side, with a local source (` flow runner
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update --from FILE` ): check, stage, drain, swap, prove, roll back (done,
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# 85: spec §11.5.3); (2) the
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policy on the hub (opt in and out, channels, windows, dry run) and the
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update in the claim answer; (3) test groups, waves and health; (4) the
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swarm as transport; (5) Admin › Runners › Updates and ` oh runner update` .
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2814f421 Andy McCall 25 days ago ↶
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## 9. Pools
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A ** pool** is one place runners come from. All pools report the same
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facts and follow the same placement.
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``` mermaid
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flowchart TB
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J["Jetstream"]
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subgraph Hosts["Host pool"]
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E["earth-1<br/>x86_64 · microvm"]
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PL["plex-1<br/>x86_64 · microvm"]
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N["narvi-1<br/>riscv64 · syscall"]
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end
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subgraph K8s["Kubernetes pool"]
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CTL["jet controller"]
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KP1["KVM node pool<br/>Firecracker in pod"]
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KP2["Kata / gVisor<br/>RuntimeClass"]
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KP3["ordinary pods<br/>syscall tier"]
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CTL --> KP1
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CTL --> KP2
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CTL --> KP3
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end
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subgraph Cloud["Cloud pool (europe-west2)"]
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PRV["jet provider"]
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VM1["warm VM, nested KVM<br/>several microVMs"]
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VM2["VM per job<br/>syscall tier"]
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PRV --> VM1
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PRV --> VM2
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end
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J --> Hosts
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J --> CTL
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J --> PRV
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```
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** Hosts.** Machines you own run ` jet runner` (today's ` flow runner` ).
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** Kubernetes.** ` jet controller` runs in the cluster, claims for it, and
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creates ** one pod per job** , the pattern every major CI system uses on
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Kubernetes. The tier follows what each node pool offers:
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| ` /dev/kvm` through a device plugin (a tainted pool) | microvm: Firecracker inside the pod |
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| A Kata or gVisor RuntimeClass (AKS Pod Sandboxing, GKE Sandbox) | syscall, inside the platform's sandbox |
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| Nothing special (GKE Autopilot included) | syscall, in an unprivileged pod |
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Dedicated KVM hosts beside a cluster stay first class: that is how
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microVM CI is run in practice.
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** Cloud providers.** ` jet provider` creates and removes VMs in a cloud
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account, keyless through OIDC (OxygenHub is already an issuer, OxygenHub spec
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§13.5):
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- ** Packing first:** a warm 8–16 vCPU VM with nested KVM runs several
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microVM jobs, saving the 30–60 s boot, the cold disk and per-VM minimum
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charges. Nested KVM: GCP Intel types and N4D, AWS C7i/C8i and newer
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(since 2026), Azure Dsv5.
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- ** One VM per job** with the syscall tier inside is the fallback where
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nested KVM is not offered.
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- ** Regions are pinned** per pool and never fall back outside the set:
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for the UK, ` europe-west2` , ` uksouth` , ` eu-west-2` . Every job records
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where it ran.
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- ** Spot** , with on-demand fallback; a reclaim notice requeues the job.
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- ** Scale-in** only of idle VMs near the end of their billing increment.
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- Build order: GCP, then AWS, then Azure.
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The provider interface: ` create(n, spec)` , ` delete(ids)` , ` list()` ,
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` health(id)` , ` capabilities()` , ` quota()` .
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## 10. Demand and autoscaling
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Jetstream answers ** demand by pull** , so nothing needs a way into your
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network:
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- ` GET /demand?pool=…` (long-poll): waiting jobs grouped by architecture,
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tier and size, and the age of the oldest. Kubernetes pools scale on it
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through a KEDA scaler; cloud providers through their own loop.
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- ** One-shot runner tokens** for ephemeral runners and pods: issued for
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one start, never long-lived.
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## 11. Reliability and running it
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- ** Lost runner:** its jobs are requeued after a short grace; a spot
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reclaim notice requeues at once.
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- ** OOM** is reported as OOM, with the job's peak, and raises its learned
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memory need.
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- ** Updates:** a runner told of a newer version updates itself between
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jobs. No cut-off date; the contract is versioned and old runners keep
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working until they update.
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- ** Figures:** queue time (the single most useful CI metric), utilisation
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per runner and pool, and cost per job, pool and region where a provider
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knows its prices.
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## 12. Embedded or on its own
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``` mermaid
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flowchart LR
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subgraph A["Embedded (the default)"]
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OH1["OxygenHub process<br/>+ jet inside"]
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R1["runners"] --> OH1
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end
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subgraph B["On its own"]
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OH2["OxygenHub"] --> JS2["jet server"]
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OH3["another OxygenHub"] --> JS2
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R2["runners"] --> JS2
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end
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```
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- ** Embedded:** the same crate in OxygenHub's process, with no
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configuration. This is what OxygenHub does unless told otherwise.
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- ** On its own:** ` [flow] jetstream = "https://jet.example"` in the hub's
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configuration points it at a standalone ` jet server` ; several hubs may
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share one fleet.
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- ** Other forges, later:** the forge contract (§4) and Git sources (§5)
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are what an adapter needs, such as one that runs GitLab or GitHub jobs
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on Jetstream runners. That would be a contained piece of work, not a
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rewrite; it is not planned yet.
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## 13. Running a pipeline on your own machine
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``` sh
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flow run # every job of .flow/pipeline.kdl, on this directory's files
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flow run test # one job, and what it needs
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flow run --var X=1 --secret TOKEN=… # what the hub would supply
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```
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` flow run` exists today: it runs the pipeline's jobs in the same sandboxes
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CI uses, before anything is pushed. With Jetstream it becomes an
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in-process Jetstream with one local runner, the same placement and the
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same code path as CI, so passing locally means passing in CI. With images
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served by Jetstream (§8), the first local run fetches the pinned image by
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hash instead of needing it imported by hand.
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## 14. Security
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- ** Isolation per job:** a microVM where KVM exists, the syscall tier
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(Landlock and seccomp) elsewhere, a platform sandbox where a cluster
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offers one. No job ever shares a Docker daemon or a host socket.
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- ** Secrets** are mounted as files in the job and masked in logs (spec
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§9), never written to a runner's disk outside the job.
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- ** Cloud VMs** have no cloud identity of their own, the metadata service
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is blocked from inside job microVMs, and job subnets accept nothing
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inbound.
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- ** Runner tokens** are per runner, and one-shot for ephemeral ones.
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## 15. Order of work
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1. ** The boundary, inside the hub:** queue, placement and runners behind
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the Jetstream contract in a ` jet` crate, embedded; no behaviour change,
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CI proves it.
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2. ** Images served by Jetstream** , fetched by hash; images built by Flow
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jobs.
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3. ** Facts on every claim, learned requirements, placement with its
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explanation** , on the job page and the queue.
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4. ** narvi-1** , the first runner brought up this way (riscv64, syscall).
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5. ** ` jet server` ** , OxygenHub pointing at it.
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6. ** The Kubernetes controller** , with a KEDA scaler on ` /demand` .
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7. ** Cloud providers:** GCP, then AWS, then Azure.
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## 16. Open questions
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- Whether artifacts and report files travel through Jetstream or go
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straight from the runner to the forge (today: straight to the hub).
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- Multi-tenancy in a shared ` jet server` : pools per organisation, and
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who may submit to which.
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- How long the best-fit hold (§7) should be, and whether it should learn.
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- Receipts: the runner signs; whether Jetstream countersigns where it
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placed the job.