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count trigger suspend, resume and discard (#11405)
* feat(telemetry): count trigger suspend, resume and discard Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> * refactor: shorten the telemetry disclosure to one line per category Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> * docs: correct the resume branch comments and note the pre-commit fire count Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> * fix: name feature adoption in the telemetry disclosure Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> * chore: update ee-repo-ref to 9855e1b7a43a0a33e04f8accf1c497af3fd9b139 This commit updates the EE repository reference after PR #834 was merged in windmill-ee-private. Previous ee-repo-ref: 1d5b128ec956c156fe549cf099ba0dbc1b6467bf New ee-repo-ref: 9855e1b7a43a0a33e04f8accf1c497af3fd9b139 Automated by sync-ee-ref workflow. --------- Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com> Co-authored-by: windmill-internal-app[bot] <windmill-internal-app[bot]@users.noreply.github.com>
This commit is contained in:
hugocasa
co-authored by
Claude Opus 5.5
windmill-internal-app[bot]
Claude Opus 5.5
windmill-internal-app[bot]
parent
f367eaf6d0
commit
17448c97d3
@@ -119,8 +119,8 @@ Form components (TextInput, Toggle, Select, etc.) should use the unified size sy
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New user-facing UX is the main source of `feature_usage` counters — propose them in the plan, not
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as a separate question, and read `docs/feature-telemetry.md` first. `logFeatureUsage()` from
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`$lib/utils/featureUsage` is only half the change: the `(feature, kind)` pair must also be
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registered in the backend allowlist or every event is silently discarded, and the disclosure copy
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in `InstanceSettings.svelte` must name what you added.
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registered in the backend allowlist or every event is silently discarded. The disclosure copy in
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`InstanceSettings.svelte` stays at the category level; see the recipe's step 3.
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## Svelte MCP Server
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-26
@@ -1,26 +0,0 @@
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{
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"db_name": "PostgreSQL",
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"query": "\n SELECT 'schedule' AS \"kind!\", COUNT(*)::BIGINT AS \"count!\" FROM schedule\n UNION ALL SELECT 'http', COUNT(*)::BIGINT FROM http_trigger\n UNION ALL SELECT 'websocket', COUNT(*)::BIGINT FROM websocket_trigger\n UNION ALL SELECT 'kafka', COUNT(*)::BIGINT FROM kafka_trigger\n UNION ALL SELECT 'nats', COUNT(*)::BIGINT FROM nats_trigger\n UNION ALL SELECT 'postgres', COUNT(*)::BIGINT FROM postgres_trigger\n UNION ALL SELECT 'mqtt', COUNT(*)::BIGINT FROM mqtt_trigger\n UNION ALL SELECT 'sqs', COUNT(*)::BIGINT FROM sqs_trigger\n UNION ALL SELECT 'gcp', COUNT(*)::BIGINT FROM gcp_trigger\n UNION ALL SELECT 'azure', COUNT(*)::BIGINT FROM azure_trigger\n UNION ALL SELECT 'amqp', COUNT(*)::BIGINT FROM amqp_trigger\n UNION ALL SELECT 'email', COUNT(*)::BIGINT FROM email_trigger\n -- Grouped, not a single 'native' key: these fire as nextcloud/google/github,\n -- so a lone key would not line up with the `trigger`/`fired` series.\n UNION ALL SELECT service_name::text, COUNT(*)::BIGINT FROM native_trigger GROUP BY service_name\n ",
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"describe": {
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"columns": [
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{
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"ordinal": 0,
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"name": "kind!",
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"type_info": "Text"
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},
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{
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"ordinal": 1,
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"name": "count!",
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"type_info": "Int8"
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}
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],
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"parameters": {
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"Left": []
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},
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"nullable": [
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null,
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null
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]
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},
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"hash": "1d346a14ad5586af347b8e7ac413500a39efa20e4915ffa56fd40537597db36e"
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}
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+32
@@ -0,0 +1,32 @@
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{
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"db_name": "PostgreSQL",
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"query": "\n SELECT 'schedule' AS \"kind!\", COUNT(*)::BIGINT AS \"count!\", 0::BIGINT AS \"suspended!\" FROM schedule\n UNION ALL SELECT 'http', COUNT(*)::BIGINT, COUNT(*) FILTER (WHERE mode = 'suspended')::BIGINT FROM http_trigger\n UNION ALL SELECT 'websocket', COUNT(*)::BIGINT, COUNT(*) FILTER (WHERE mode = 'suspended')::BIGINT FROM websocket_trigger\n UNION ALL SELECT 'kafka', COUNT(*)::BIGINT, COUNT(*) FILTER (WHERE mode = 'suspended')::BIGINT FROM kafka_trigger\n UNION ALL SELECT 'nats', COUNT(*)::BIGINT, COUNT(*) FILTER (WHERE mode = 'suspended')::BIGINT FROM nats_trigger\n UNION ALL SELECT 'postgres', COUNT(*)::BIGINT, COUNT(*) FILTER (WHERE mode = 'suspended')::BIGINT FROM postgres_trigger\n UNION ALL SELECT 'mqtt', COUNT(*)::BIGINT, COUNT(*) FILTER (WHERE mode = 'suspended')::BIGINT FROM mqtt_trigger\n UNION ALL SELECT 'sqs', COUNT(*)::BIGINT, COUNT(*) FILTER (WHERE mode = 'suspended')::BIGINT FROM sqs_trigger\n UNION ALL SELECT 'gcp', COUNT(*)::BIGINT, COUNT(*) FILTER (WHERE mode = 'suspended')::BIGINT FROM gcp_trigger\n UNION ALL SELECT 'azure', COUNT(*)::BIGINT, COUNT(*) FILTER (WHERE mode = 'suspended')::BIGINT FROM azure_trigger\n UNION ALL SELECT 'amqp', COUNT(*)::BIGINT, COUNT(*) FILTER (WHERE mode = 'suspended')::BIGINT FROM amqp_trigger\n UNION ALL SELECT 'email', COUNT(*)::BIGINT, COUNT(*) FILTER (WHERE mode = 'suspended')::BIGINT FROM email_trigger\n -- Grouped, not a single 'native' key: these fire as nextcloud/google/github,\n -- so a lone key would not line up with the `trigger`/`fired` series.\n UNION ALL SELECT service_name::text, COUNT(*)::BIGINT, 0::BIGINT FROM native_trigger GROUP BY service_name\n ",
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"describe": {
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"columns": [
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{
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"ordinal": 0,
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"name": "kind!",
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"type_info": "Text"
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},
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{
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"ordinal": 1,
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"name": "count!",
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"type_info": "Int8"
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},
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{
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"ordinal": 2,
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"name": "suspended!",
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"type_info": "Int8"
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}
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],
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"parameters": {
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"Left": []
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},
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"nullable": [
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null,
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null,
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null
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]
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},
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"hash": "872c06b3098cf59797bcaa90d6da5c6acbf5468c190fa72b6b6707d950267752"
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}
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@@ -1 +1 @@
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421cf2a8b4f98b421e93c0fc7c1c378314a66e50
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9855e1b7a43a0a33e04f8accf1c497af3fd9b139
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@@ -6869,9 +6869,19 @@ async fn push_inner<'c, 'd>(
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// `schedule_path` (see `FlowJob::schedule_path`), so counting per push would
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// score one run as a fire per step job — a loop pushes two of those per
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// iteration — burying every other kind, and would sit on the per-step path.
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//
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// A job a suspended trigger parks is not a fire: it counts as `fired` only
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// when `resume_suspended_trigger_jobs` releases it, or never if discarded.
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// Both are counted before the queue caps below and the caller's commit, so a
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// rejected push still counts; accepted for a telemetry counter.
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if flow_step_id.is_none() {
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if let Some(kind) = trigger_kind.as_ref() {
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windmill_common::feature_usage::log_feature_usage("trigger", "fired", kind.as_str());
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let action = if suspended_mode.unwrap_or(false) {
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"suspended"
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} else {
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"fired"
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};
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windmill_common::feature_usage::log_feature_usage("trigger", action, kind.as_str());
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}
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}
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@@ -14,6 +14,7 @@ use windmill_api_jobs::execution::cancel_jobs;
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use windmill_common::{
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db::{UserDB, DB},
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error::{self, Error, Result},
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feature_usage::log_feature_usage,
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jobs::{delete_jobs, JobTriggerKind},
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triggers::TriggerMetadata,
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};
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@@ -168,14 +169,16 @@ pub async fn resume_suspended_trigger_jobs(
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.await?
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};
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let trigger_metadata = TriggerMetadata::new(Some(trigger_path.clone()), trigger_kind);
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let trigger_metadata = TriggerMetadata::new(Some(trigger_path.clone()), trigger_kind.clone());
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let l = jobs.len();
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let mut unsuspended_in_place = 0;
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for job in jobs {
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// If job was created before trigger was edited, simply update it to unsuspend
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// If job was created after trigger was edited, simply update it to unsuspend
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// instead of deleting and repushing
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if job.created_at > trigger.edited_at {
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unsuspended_in_place += 1;
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// Map the placeholder unassigned kind back to its assigned counterpart so
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// singlestepflow wrappers (retry/error_handler/skip_handler) keep their
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// flow-orchestrator identity.
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@@ -209,7 +212,7 @@ pub async fn resume_suspended_trigger_jobs(
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.execute(&mut *tx)
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.await?;
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} else {
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// Job was created after trigger edit - delete and repush with new configuration
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// Job was created before trigger edit - delete and repush with new configuration
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// Pass the transaction to trigger_runnable_inner so everything is in the same transaction
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let (_uuid, _delete_after_use, _early_return, _has_failure_module, tx_o) =
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trigger_runnable_inner(
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@@ -274,6 +277,16 @@ pub async fn resume_suspended_trigger_jobs(
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tx.commit().await?;
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// A repushed job is counted as `fired` inside `push`, before this commit, so
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// a resume that rolls back still counts it; accepted for a telemetry counter.
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// One unsuspended in place never goes through `push`, so it is counted here.
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for _ in 0..unsuspended_in_place {
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log_feature_usage("trigger", "fired", trigger_kind.as_str());
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}
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for _ in 0..l {
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log_feature_usage("trigger", "resumed", trigger_kind.as_str());
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}
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Ok(Json(format!("Reassigned {} jobs", l)))
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}
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@@ -334,6 +347,9 @@ pub async fn cancel_suspended_trigger_jobs(
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true,
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)
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.await?;
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for _ in 0..cancelled_jobs.0.len() {
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log_feature_usage("trigger", "discarded", trigger_kind.as_str());
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}
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Ok(Json(format!("Canceled {} jobs", cancelled_jobs.0.len())))
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} else {
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Ok(Json(format!("No jobs to cancel")))
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@@ -4,7 +4,7 @@
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anonymous usage-stats payload. It answers "does anyone use this, and which variant do they pick"
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without any identifying data leaving the instance.
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It currently carries 58 registered actions across twenty features (`ai_session`, `ai_chat`,
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It currently carries 61 registered actions across twenty features (`ai_session`, `ai_chat`,
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`ai_fix`, `ai_agent`, `ai_agent_eval`, `app_sandbox`, `datatable`, `db_manager`, `flow_editor`,
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`flow_run`, `flow_step`, `home`, `run_form`, `debugger`, `trigger`, `command_script`,
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`hub_script`, `usage_meter`, `sso_groups_claim`, `cloud_trial_offer`). Nearly all of the
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@@ -48,7 +48,7 @@ vocabulary closed and small — enumerate the values in a TS union next to the c
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## The recipe
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Four steps. Skipping step 1 or 3 fails quietly.
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Four steps. Skipping step 1 fails quietly.
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**1. Register the pair** in `FEATURE_USAGE_KINDS`
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(`backend/windmill-common/src/feature_usage_ee.rs`, tracked in `windmill-ee-private`). An
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@@ -68,9 +68,10 @@ Fire-and-forget. Events sum locally per `(workspace, feature, kind, key, entityI
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every 30s, on `visibilitychange` → hidden, and on `pagehide`; 50 events per request, and a failed
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batch is dropped rather than retried.
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**3. Update the disclosure.** `InstanceSettings.svelte` lists what a non-minimal payload contains
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(two places — the copy appears twice). A new counter that isn't named there means the instance
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under-discloses what it sends. This has already drifted once.
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**3. Check the disclosure.** `InstanceSettings.svelte` describes a non-minimal payload by
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category, not counter by counter (two places — the copy appears twice); keep it short. A plain
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counter needs no edit. Only a key that sends a new kind of value beyond a count — a name or an
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identifier, like the AI model and hub names it already lists — must be added there.
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**4. Verify a row lands.** The silent-drop path means "no error" proves nothing:
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@@ -1065,54 +1065,19 @@
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Telemetry is required on Enterprise Edition for license compliance. When minimal telemetry
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is enabled, only the following data is sent:
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<ul class="list-disc list-inside pl-2">
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<li>version of your instance</li>
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<li>instance base URL</li>
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<li>login type usage (login type, count)</li>
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<li>worker usage (worker, worker instance, vCPUs, memory)</li>
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<li
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>user usage (author count, operator count, the distinct guests of the last 30 days,
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the seats they add past the free allowance, and the workspaces that allow guests)</li
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>
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<li>superadmin email addresses</li>
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<li>development instance status</li>
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<li>Instance version and base URL</li>
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<li>Login types, user and seat counts</li>
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<li>Worker count, vCPUs and memory</li>
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<li>Superadmin email addresses</li>
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<li>Development instance status</li>
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</ul>
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<br />When minimal telemetry is disabled, the following is also collected:
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<ul class="list-disc list-inside pl-2">
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<li>job usage (language, total duration, count)</li>
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<li>git sync repo count (sync vs promotion mode)</li>
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<li
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>feature usage (counts of which product features are used, including AI provider and
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model identifiers, the names of public hub scripts used, the languages debug sessions
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are started for, whether AI chat skills are turned on or off and how often one is
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loaded, whether an AI agent run narrows the tools it may call and whether that leaves
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it with none, whether SSO logins evaluate an IdP groups claim (SAML or OIDC) and
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change a membership, the plan tier and quota shown when the execution meter is opened,
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whether app sandbox isolation is turned on, whether a step's workspace script is
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edited from the flow editor, which skin approval steps are given, how many AI sessions
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are brought back from the workspace object storage backup, how data tables and their
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migrations are set up and used, how often the database manager is switched between its
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data and schema diagram views, how often an empty workspace home is seen, how often
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the home page’s create menu and hub-project picker are opened and from which entry
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point, the name of any public hub project imported from the home page and how far that
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import got, whether a pre-approved trial offer was opened, whether data tables are put
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under roles and whether callers name a role or take the default, which kinds of access
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change (grant, revoke, ownership, default privileges) are applied to data tables, and
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whether a data table under roles is cloned into a fork with its schema only or with
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its data, last 30 days)</li
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>
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<li
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>feature adoption (counts of which flow, script, trigger, worker and data table
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features your deployed items use, including how many apps run sandboxed, how many data
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tables exist per database kind, how many use migrations, and what references them)</li
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>
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<li
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>resource counts (workspaces, scripts per language, flows, workflows as code, low-code
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apps, raw apps)</li
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>
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<li
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>infrastructure info (container runtime, managed database provider, database version,
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size and cluster size, max and active connections, object storage backend)</li
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>
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<li>Job counts and durations per language</li>
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<li>Git sync repository counts</li>
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<li>Feature usage and adoption counts, including AI model and public Hub names</li>
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<li>Counts of workspaces, scripts, flows and apps</li>
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<li>Database, runtime and object storage details</li>
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</ul>
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<br />For air-gapped instances, you can download the telemetry data and send it manually.
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</div>
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@@ -1141,45 +1106,13 @@
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Anonymous usage data is collected to help improve Windmill.
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<br />The following information is collected:
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<ul class="list-disc list-inside pl-2">
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<li>version of your instance</li>
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<li>instance base URL</li>
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<li>job usage (language, total duration, count)</li>
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<li>login type usage (login type, count)</li>
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<li>worker usage (worker, worker instance, vCPUs, memory)</li>
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<li
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>user usage (author count, operator count, the distinct guests of the last 30 days,
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the seats they add past the free allowance, and the workspaces that allow guests)</li
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>
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<li>development instance status</li>
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<li
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>feature usage (counts of which product features are used, including AI provider and
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model identifiers, the names of public hub scripts used, the languages debug sessions
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are started for, whether AI chat skills are turned on or off and how often one is
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loaded, whether an AI agent run narrows the tools it may call and whether that leaves
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it with none, whether SSO logins evaluate an IdP groups claim (SAML or OIDC) and
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change a membership, the plan tier and quota shown when the execution meter is opened,
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whether app sandbox isolation is turned on, whether a step's workspace script is
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edited from the flow editor, which skin approval steps are given, how many AI sessions
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are brought back from the workspace object storage backup, how data tables and their
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migrations are set up and used, how often the database manager is switched between its
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data and schema diagram views, how often an empty workspace home is seen, how often
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the home page’s create menu and hub-project picker are opened and from which entry
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point, the name of any public hub project imported from the home page and how far that
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import got, whether a pre-approved trial offer was opened, whether data tables are put
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under roles and whether callers name a role or take the default, which kinds of access
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change (grant, revoke, ownership, default privileges) are applied to data tables, and
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whether a data table under roles is cloned into a fork with its schema only or with
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its data, last 30 days)</li
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>
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<li
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>feature adoption (counts of which flow, script, trigger, worker and data table
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features your deployed items use, including how many apps run sandboxed, how many data
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tables exist per database kind, how many use migrations, and what references them)</li
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>
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<li
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>resource counts (workspaces, scripts per language, flows, workflows as code, low-code
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apps, raw apps)</li
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>
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<li>Instance version and base URL</li>
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<li>Job counts and durations per language</li>
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<li>Login types, user and seat counts</li>
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<li>Worker count, vCPUs and memory</li>
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<li>Development instance status</li>
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<li>Feature usage and adoption counts, including AI model and public Hub names</li>
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<li>Counts of workspaces, scripts, flows and apps</li>
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</ul>
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</div>
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{/if}
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Reference in New Issue
Block a user