CoffeeKnyte
ecb4555eec
Five defects that all produced a WRONG over-cap count, which is why they land before the revocation batch: decision A1 raises the over-cap revocation TTL from 5m to ~24h, removing the self-healing that currently limits the damage of a miscount. A false positive after A1 blocks a legitimate stream for a day, so the count has to be trustworthy first. #1 -- overlapping edge requests deleted a live stream. Tracker.sessions was a set and Remove tore down all state plus the Redis key, while both proxy pour handlers deferred removal unconditionally. Two overlapping Range GETs on one session id -- ordinary seek behaviour -- meant the first to finish deleted the record while the second was still pouring, and later AddBytes calls were then dropped because AddBytes ignores bytes for a session with no live record. The stream went invisible to authoritative monitoring while still serving. Track now returns a Lease that the request-scoped caller releases exactly once; teardown happens when the last live lease is released. A plain refcount would have been wrong: Track(A) -> Remove -> Track(B) -> Release(A) decrements B, and clamping at zero does not help because the count legitimately belongs to B. That is not hypothetical -- the transcode node deliberately replaces sessions under the same id so a quality switch does not orphan ffmpeg, and it calls unconditional Remove from its reaper and stop paths. So each generation carries an epoch, Remove and Cleanup bump it, and a release from a superseded generation is a logged no-op. Lease identity is a set rather than a counter, which makes a duplicate release detectable instead of silently destructive. The transcode node keeps using Remove: its Track calls are not request-scoped and are correctly owned by session lifecycle. "Every Track needs a paired Release" is true only of the request-scoped callers. #8 -- async transcode tracking could leave a permanent ghost. The tracking write ran as a bare goroutine with a WithoutCancel context, so if stop won the race the delayed Track recreated the record after cleanup -- and because it landed in sessions, Snapshot treated it as live until Remove and it NEVER idle-expired. A permanent phantom inflating its owner's count, able to trigger false over-cap kills of that user's real streams. The write now takes the per-session lifecycle lock that stop and reap already hold, and re-checks session pointer identity before writing, so a stopped or replaced generation cannot resurrect a record. Pointer identity rather than id equality is what makes same-id replacement safe. The write stays off the request path -- the API server and the playback client are blocked on the 202. #9 + M3 -- protocol-v3 counted one stream twice. The stream token carries a transport id distinct from the logical session id, and the node tracked under the transport id while the API/proxy record used the logical one, so mergeStreams saw two streams. M3 was the reason this had not yet bitten: the v3 fresh-start caller sent no owner attribution at all, so the transport record landed under user 0, which the enforcer skips -- silently exempting the stream from the cap entirely. Fresh v3 starts now carry the logical session id and full owner attribution (both were already in scope at the call site), and merging is keyed on logical identity where present via one shared helper used by both merge functions, which had already drifted apart once. The enforcer view resolves SessionID to the logical id so a kill targets the real session rather than a replaceable transport generation. The raw admin view keeps the transport id and exposes logical_session_id as an additive omitempty field, advertised on the node-sessions capability endpoint, so the v1 response shape is unchanged. GAP-15 -- edge transcode liveness was request-observed. touchTranscodeSession fired before proxying, so hammering dead segment URLs advanced LastServedAt with zero bytes served. Visibility and liveness are now separate operations: EnsureEphemeral makes a session visible without claiming bytes were served, and served-byte liveness advances only from a 2xx/206 upstream response. Previously the proxy metered every upstream body regardless of status, so a node 404's error body counted as served bytes -- moving the touch later would not have fixed it. S4 -- LiveLocalSessions moved from the HTTP handlers package to streammonitor, which owns monitoring. A background enforcer importing api/handlers was backwards. Pure move; its existing mapping assertions moved with it. The LastActivityAt fallback inside it is left as-is -- decision A5 removes it in the liveness batch. Verified with go test -race across nodesessions, proxy and transcodenode; the overlap regression test was confirmed to fail under the old unconditional teardown. Part of #305.
Silo
Silo is a self-hosted media streaming server for your movies, shows, music, and books. Point it at your media folders and stream to your devices — at home or away — with direct play, remuxing, and hardware-accelerated transcoding handled automatically.
Join the community on Discord. If Silo is useful to you, consider sponsoring the project — see Supporting Silo.
Highlights
- Plays your media, your way — direct play when the device supports it, remux or hardware-accelerated transcode (including NVENC) when it doesn't.
- Web app included — a full-featured web client and admin interface ship with the server.
- Works with apps you already use — optional Jellyfin/Emby-compatible API supports clients such as VidHub, Findroid, and Infuse.
- Household profiles — multiple profiles per account, with per-profile watch state and parental controls.
- Plugin-driven metadata — match and enrich your libraries with providers like TMDB and TVDB, installed as plugins.
- Fast setup — one
docker compose up -dbrings up the whole stack; everything else is configured in the admin UI.
Deploy with Docker (recommended)
The easiest way to run Silo is with Docker Compose. The default stack assumes you do not already have PostgreSQL and Redis available, so it bundles PostgreSQL, Redis, FFmpeg, and the application for a one-command start.
-
Create a
.envfilecp .env.example .env -
Set your media path
Edit
.envand set:MEDIA_ROOT=/path/to/your/mediaMEDIA_ROOTis the one value most users need to change. You can also overrideSILO_DATA_ROOTif you do not want bind mounts under/opt/silo, and change ports if the defaults conflict with something else on the host. -
Start the default integrated stack
docker compose up -dThis starts PostgreSQL, Redis, and the integrated Silo server. The app is available at
http://localhost:8090. Jellyfin-compatible app support is disabled until an administrator enables it in onboarding or admin settings.If you already have PostgreSQL and Redis available, omit those bundled service examples from compose and point Silo at your existing
DATABASE_URLandREDIS_URLinstead.Optional NVIDIA/NVENC
GPU support is kept out of the default compose file so hosts without NVIDIA drivers work unchanged.
Install the NVIDIA Container Toolkit and use a Docker Compose version with GPU reservation support before enabling this override.
Use the optional override file when you want NVENC:
docker compose -f docker-compose.yml -f docker-compose.nvidia.yml up -dIf you want this controlled from
.env, setCOMPOSE_FILE:COMPOSE_FILE=docker-compose.yml:docker-compose.nvidia.yml NVIDIA_GPU_COUNT=1Windows uses
;instead of:between compose files.Then
docker compose up -dwill include the NVIDIA override automatically. -
Configure through the admin UI
Add libraries, users, metadata providers, and playback settings from the web interface.
Bind Mount Layout
The deploy-oriented compose files use host folder mappings rather than Docker-managed volumes.
By default, data is stored under /opt/silo:
/opt/silo/postgres/opt/silo/redis/opt/silo/transcode/opt/silo/catalog-seeds
Media is mounted into the container at /mnt/media from the host path you set in MEDIA_ROOT.
Optional Profiles
The main compose file is integrated-first. These profiles exist for operators testing distributed mode or mirroring a split deployment shape. Most single-host installs should stay on the default integrated service, because it already includes proxying and transcoding.
| Profile | Command | Description |
|---|---|---|
| default | docker compose up -d |
Integrated server plus bundled PostgreSQL and Redis |
proxy |
docker compose --profile proxy up -d |
Start a standalone proxy service for distributed-mode testing |
transcode |
docker compose --profile transcode up -d |
Start a standalone transcode service for distributed-mode testing |
You can enable both optional examples together:
docker compose --profile proxy --profile transcode up -d
If you are splitting workers across multiple hosts, use the separate remote worker example instead of trying to stretch the main compose file across machines.
Advanced Remote Node Example
For a dedicated remote transcode worker, use docker-compose.remote-transcode.yml. That file is intended for a separate worker host that connects back to an existing Silo deployment using shared PostgreSQL and Redis.
Deployment Notes
The default compose stack intentionally bundles PostgreSQL and Redis for ease of setup and assumes a fresh install without those services already available. If you already operate PostgreSQL and Redis, omit those examples from compose and point Silo at your existing infrastructure instead. For serious installs, PostgreSQL is better on a separate VM or a managed service so upgrades, tuning, and backups are isolated from the app host. Redis can stay local for many installs, but externalizing it is also reasonable if you already operate shared infrastructure.
Silo is externally stateful by default rather than fully stateless. Durable application state lives in PostgreSQL. Redis only stores coordination and cache-style data. Silo still writes transient transcode output locally under /tmp/silo-transcode. If you switch userdb.backend=sqlite, Silo also becomes locally stateful at /var/lib/silo/userdb.
Migrating an existing Continuum Docker install should be done with the preflight helper and cutover guide in docs/continuum-to-silo-docker-migration.md.
Configuration
Silo requires only a DATABASE_URL when running from source or against external infrastructure. In the default Docker Compose path, the stack wires the database and Redis URLs for you. All other settings — libraries, metadata providers, transcoding, users — are managed through the admin UI after first launch.
Server Modes
| Mode | Description |
|---|---|
integrated |
Full server: API + frontend + scanner + transcode (default) |
api |
API server only, no local transcoding |
proxy |
Stream proxy node that connects to the shared deployment database and Redis |
transcode |
HLS transcode worker node that connects to the shared deployment database and Redis |
PostgreSQL Auto-Tuning
The default Docker Compose stack does not require a checked-in postgresql.conf.
It enables Silo's pgtune-style OLTP tuning
by default:
POSTGRES_TUNE: auto
When enabled, Silo connects with DATABASE_URL and applies recommendations with
ALTER SYSTEM, which writes to PostgreSQL's postgresql.auto.conf inside the
database data directory. Reloadable settings are applied immediately with
pg_reload_conf(). Settings that PostgreSQL marks as restart-only are written
too, and Silo logs the setting names so you can restart PostgreSQL once:
docker compose restart postgres
The default Compose database user has the required PostgreSQL permissions. If
you use an external PostgreSQL server, make sure the configured DATABASE_URL
user can run ALTER SYSTEM, or set POSTGRES_TUNE=off and manage
PostgreSQL yourself.
For POSTGRES_TUNE_MEMORY=auto, Silo uses the first trustworthy memory source:
a finite Docker cgroup limit, the read-only /host/proc/meminfo mount supplied
by the bundled Compose file, then /proc/meminfo with container safety guards.
Auto-detected memory is treated as a PostgreSQL budget, defaulting to 75% of
detected RAM so Silo, Redis, plugins, transcodes, and the OS retain headroom.
POSTGRES_TUNE_DB_SIZE=auto queries pg_database_size(current_database()) and
classifies the workload by comparing the database size to that memory budget.
Optional tuning overrides:
| Variable | Default | Description |
|---|---|---|
POSTGRES_TUNE_PROFILE |
oltp |
Tuning profile. Only oltp is currently supported. |
POSTGRES_TUNE_MEMORY |
auto |
Server/container RAM, such as 8GB or 32GB; explicit values are used as-is. |
POSTGRES_TUNE_MEMORY_BUDGET_PERCENT |
75 |
Percent of auto-detected RAM used for PostgreSQL recommendations. |
POSTGRES_TUNE_CPUS |
auto |
CPU count used for worker recommendations. |
POSTGRES_TUNE_STORAGE |
ssd |
One of hdd, ssd, san, or nvme. |
POSTGRES_TUNE_DB_SIZE |
auto |
Use less_ram when the database comfortably fits in RAM, mid_ram, or greater_ram for very large databases. |
POSTGRES_TUNE_CONNECTIONS |
100 |
PostgreSQL max_connections; automatically raised if Silo's app pool is configured higher. |
POSTGRES_SHM_SIZE |
8gb |
Docker /dev/shm size for the bundled PostgreSQL container. |
Advanced operators can still supply their own PostgreSQL configuration or
override these env vars. Set POSTGRES_TUNE=off when you do not want Silo to
change PostgreSQL server settings. Settings already written with ALTER SYSTEM
remain in postgresql.auto.conf; reset those PostgreSQL parameters if you later
move fully to a custom postgresql.conf.
Build from Source
If you prefer running Silo without Docker:
-
Install prerequisites: Go 1.24+, Bun 1.0+, PostgreSQL 18+, and FFmpeg.
-
Start PostgreSQL and Redis (skip if you already have them running)
docker compose up -d postgres redisThe main compose file still expects
MEDIA_ROOTto be set even if you only want the bundled PostgreSQL and Redis services, so set that in.envfirst. -
Configure the database connection
cp .env.example .envEdit
.envand setDATABASE_URLto point to your PostgreSQL instance. -
Build and run
make build ./siloThe server starts at
http://localhost:8080by default. All other settings are configured through the admin UI.
Reporting Issues
If you are reporting a bug, install problem, or performance issue, start with the admin workflow and reproduction steps, not Claude/Codex analysis.
Please include:
- What you were trying to do
- Exact steps you took
- What you expected to happen
- What actually happened
- What exact action is slow or broken (
save,scan,browse,import,playback, etc.) - Whether it happens every time or only sometimes
- The library, media type, filter, setting, or value involved
- Version, branch, commit, and deployment details if you know them
- Screenshots, recordings, or log snippets if relevant
If you used Claude/Codex for debugging, put that under Technical notes at the end. Suspected files, SQL output, stack traces, and root-cause theories can be helpful, but only after the workflow and repro steps are clear.
Use this template:
Goal:
Steps:
Expected:
Actual:
What is slow/broken:
Scope:
Version/branch:
Deployment:
Technical notes:
Contributing & Development
Silo is open source and contributions are welcome. See DEVELOPMENT.md for building from source in a dev workflow, running tests, database migrations, and project layout, and CONTRIBUTING.md for contribution expectations, merge request guidance, and the policy for AI-assisted submissions.
Supporting Silo
Silo is an open-source hobby project, developed in spare time and funded out of pocket. If you'd like to support development, you can sponsor via GitHub Sponsors.
Donations go directly toward the costs of building and running the project:
- AI development tooling subscriptions (Claude, Codex) used to build and maintain Silo
- Push notification relay infrastructure
- Future development costs
Sponsoring is entirely optional — Silo is and will remain free and open source. Bug reports, contributions, and feedback are just as valuable.
License & Trademarks
Silo's source code is licensed under the GNU Affero General Public License
v3.0 or later (AGPL-3.0-or-later) — see LICENSE.
The Silo name, logo, and wordmark are trademarks of Silo Media L.L.C. and are not covered by the AGPL. You're free to fork and redistribute the code, but forks and redistributions must not use the Silo brand as their identity and must remove or replace the brand assets. Publishing a Silo-branded app to an app store requires written permission. See TRADEMARK.md for what's permitted — including referential use like "compatible with Silo."