285 lines
17 KiB
Markdown
285 lines
17 KiB
Markdown
# Scanner Benchmark Runbook
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**Use this when:** you need reproducible before/after evidence that a scanner pacing or cycle change reduces background pressure without stalling lifecycle, replication, heal, or bitrot progress, or you are assembling evidence for a scanner-behavior PR.
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**Source of truth:** `scripts/run_scanner_validation_harness.sh` (collection, `scanner-summary.csv` columns), `scripts/run_object_batch_bench.sh` (workload), and [Scanner Runtime Controls](scanner-runtime-controls.md) for the meaning of every status field and configuration key.
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## Scope
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This runbook verifies that scanner pacing and cycle controls reduce background pressure while preserving maintenance progress. It covers mostly idle single-node deployments with many small objects, multi-disk or erasure-set nodes, distributed clusters where scanner pressure mixes with lifecycle, replication, heal, or bitrot queues, and backlog investigations for any of those subsystems.
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It does not prove full MinIO parity, site-replication correctness, or replaced-disk heal correctness. Those flows need dedicated distributed tests because their failure modes are not limited to scanner pacing.
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## Safety
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Run the workload only in a disposable test environment. The commands below can create many buckets and objects and overwrite runtime scanner settings. Record the current scanner and heal configuration before changing anything:
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```bash
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mkdir -p artifacts
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mc admin config get ALIAS scanner > artifacts/scanner-config.before.txt
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mc admin config get ALIAS heal > artifacts/heal-config.before.txt
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```
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The `scanner` and `heal` subsystems are served by `GetConfigKVHandler` (`rustfs/src/admin/handlers/config_admin.rs`, route `/v3/get-config-kv`); this was confirmed by code inspection, not by running `mc` against a live deployment. Replace `ALIAS`, endpoint, and credentials with values for the test deployment. Do not paste production credentials into saved artifacts.
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## Required Tools
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| Tool | Purpose |
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| `mc` or a compatible admin client | Config snapshots and changes. |
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| `awscurl` or another SigV4-capable HTTP client | `/v3/scanner/status` and admin metrics. |
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| `jq` | Status extraction. |
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| `pidstat`, `mpstat`, `iostat`, `top`, or equivalent | Host telemetry. |
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| `warp`, `s3bench`, or `scripts/run_object_batch_bench.sh` | Workload generation. |
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## Test Matrix
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Collect at least two runs on the same RustFS commit and the same workload. Keep hardware, commit, object count, object size, bucket count, scanner-enabled state, and foreground workload constant between runs.
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| Run | Purpose | Example scanner settings |
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| Baseline | Observe current behavior without additional pacing changes. | Existing config. |
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| Pacing override | Measure whether cooperative scanner sleeps reduce pressure. | `scanner.delay="30"` and `scanner.max_wait="15"`. |
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| Duration budget (when one cycle is too long) | Bound wall-clock time per cycle. | `scanner.cycle_max_duration="1800"`. |
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| Object budget | Bound objects processed per cycle. | `scanner.cycle_max_objects="1000000"`. |
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| Directory budget | Bound directories entered per cycle. | `scanner.cycle_max_directories="100000"`. |
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## Deployment Matrix
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Use the smallest deployment that reproduces the symptom. The single-node, single-disk run is the cheap, repeatable baseline; it is not sufficient for PRs that claim to improve distributed queue behavior, replication repair, or heal/bitrot admission.
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| Deployment | What it validates | Minimum evidence | Workload shape |
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| Single-node, single-disk | Small-object scanner pressure, pacing, cycle interval, basic progress. | Scanner status time series plus host CPU and disk telemetry. | One node, one data disk, several buckets, at least 100,000 small objects, scanner enabled, no sustained foreground workload during observation. |
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| Single-node, multi-disk or erasure set | Set and disk scan concurrency, cycle budgets, checkpoint movement, usage cache persistence, active path age. | Scanner status time series, per-disk host telemetry, before/after data usage freshness. | Same as above across all disks. |
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| Distributed cluster | Lifecycle transition queues, bucket replication repair admission, scanner-originated heal and bitrot admission, queue/backlog pressure under cross-node work. | Scanner status time series from the cluster, host telemetry from each node, subsystem-specific queued/skipped/missed counters. | Same structure plus the relevant subsystem condition (lifecycle rules, a replication target, a heal/bitrot scenario); keep status and telemetry cadence identical to the baseline. |
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Generate object traffic with the repository script if `warp` or `s3bench` is installed; repeat with new buckets or prefixes if one run cannot create enough objects, and record the final object count:
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```bash
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scripts/run_object_batch_bench.sh \
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--tool warp \
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--endpoint http://127.0.0.1:9000 \
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--access-key "$RUSTFS_ACCESS_KEY" \
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--secret-key "$RUSTFS_SECRET_KEY" \
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--bucket scanner-bench \
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--auto-new-bucket \
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--concurrency 64 \
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--duration 10m \
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--sizes 1KiB,4KiB,16KiB \
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--warp-mode put \
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--out-dir artifacts/object-load
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```
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## Status Collection
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Capture scanner status before the workload, after the workload finishes, and throughout the idle observation window. The validation harness does this repeatably and writes scanner/heal config snapshots, scanner status samples, background heal status samples, host telemetry when available, run metadata, `scanner-summary.csv`, and `scanner-validation-report.md`:
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```bash
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export RUSTFS_ACCESS_KEY="<admin-access-key>"
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export RUSTFS_SECRET_KEY="<admin-secret-key>"
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scripts/run_scanner_validation_harness.sh \
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--alias ALIAS \
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--endpoint http://127.0.0.1:9000 \
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--deployment single-disk \
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--workload-label small-object-idle \
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--samples 30 \
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--interval-secs 60 \
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--out-dir artifacts/scanner-validation
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```
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For per-node distributed evidence pass `--metrics-endpoints` (comma-separated). Each sample then stores `/v3/scanner/status`, one `/v3/background-heal/status` response per listed endpoint, and one by-host admin metrics response per listed endpoint; without it, background-heal status is captured only from `--endpoint`:
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```bash
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scripts/run_scanner_validation_harness.sh \
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--alias ALIAS \
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--endpoint http://node-a:9000 \
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--deployment distributed \
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--workload-label lifecycle-replication-heal-backlog \
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--metrics-endpoints http://node-a:9000,http://node-b:9000,http://node-c:9000,http://node-d:9000 \
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--samples 30 \
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--interval-secs 60 \
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--out-dir artifacts/scanner-validation-distributed
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```
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For ad hoc per-node snapshots outside the harness window, use the by-host `awscurl` loop in [Reading Distributed Metrics](scanner-runtime-controls.md#reading-distributed-metrics); the metrics endpoint reports only the node that handles the request.
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### Bucket metrics freshness validation
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Use the harness around a post-start bucket creation workload to cover the timing where scanner startup sees no buckets, a bucket is created afterwards, and the first metrics collection must not confuse a cold usage cache with real zero usage:
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1. Start RustFS from an empty data path.
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2. Start the harness before creating buckets.
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3. Create a bucket, upload objects, and keep the harness running until at least one usage save is observed.
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4. Compare `scanner-summary.csv` with `/rustfs/admin/v3/metrics?types=1&n=1` bucket metrics.
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Expected evidence: dirty usage is marked, `life_time_scan_cycle` or `life_time_scan_bucket_drive` advances, `life_time_scan_object` advances for object workloads, and `life_time_save_usage` plus `usage_last_save_result=success` appear before non-zero bucket usage metrics are accepted as fresh.
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### Manual status sampling
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Single snapshot:
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```bash
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awscurl \
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--service s3 \
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--region us-east-1 \
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--access_key "$RUSTFS_ACCESS_KEY" \
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--secret_key "$RUSTFS_SECRET_KEY" \
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--request GET \
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'http://127.0.0.1:9000/rustfs/admin/v3/scanner/status' \
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| jq . > "artifacts/scanner-status.$(date -u +%Y%m%dT%H%M%SZ).json"
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```
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Time series (stop after the planned observation window):
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```bash
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mkdir -p artifacts/status
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while sleep 60; do
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ts="$(date -u +%Y%m%dT%H%M%SZ)"
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awscurl \
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--service s3 \
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--region us-east-1 \
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--access_key "$RUSTFS_ACCESS_KEY" \
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--secret_key "$RUSTFS_SECRET_KEY" \
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--request GET \
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'http://127.0.0.1:9000/rustfs/admin/v3/scanner/status' \
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| jq . > "artifacts/status/scanner-status.${ts}.json"
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done
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```
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## Host Telemetry
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Collect host metrics over the same window as scanner status. If `pidstat` is unavailable, use `top`, `ps`, or the platform monitoring system, but record the sampling interval and window in the report.
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```bash
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pidstat -p "$(pidof rustfs)" 60 > artifacts/pidstat.txt
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iostat -xz 60 > artifacts/iostat.txt
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mpstat 60 > artifacts/mpstat.txt
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```
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## Runtime Tuning Examples
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Persistent scanner config values use seconds for time fields; use numeric strings, not duration suffixes. The canonical persistent bitrot cadence belongs to the `heal` subsystem.
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```bash
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mc admin config set ALIAS scanner delay="30" max_wait="15"
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mc admin config set ALIAS scanner cycle="3600"
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mc admin config set ALIAS scanner cycle_max_duration="1800"
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mc admin config set ALIAS scanner cycle_max_objects="1000000"
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mc admin config set ALIAS scanner cycle_max_directories="100000"
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mc admin config set ALIAS heal bitrot_cycle="2592000"
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```
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Environment variables take precedence over persisted config and should be recorded separately:
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```bash
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RUSTFS_SCANNER_DELAY=30
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RUSTFS_SCANNER_MAX_WAIT_SECS=15
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RUSTFS_SCANNER_CYCLE=3600
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RUSTFS_SCANNER_CYCLE_MAX_DURATION_SECS=1800
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RUSTFS_SCANNER_CYCLE_MAX_OBJECTS=1000000
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RUSTFS_SCANNER_CYCLE_MAX_DIRECTORIES=100000
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RUSTFS_SCANNER_BITROT_CYCLE_SECS=2592000
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```
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After each config change, read scanner status and confirm the effective value and `source` under `runtime_config`.
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## Observation Window
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Use the same window for each run:
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1. Generate or verify the object namespace.
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2. Wait until foreground workload is idle.
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3. Save scanner and heal config.
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4. Save one scanner status snapshot.
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5. Collect scanner status and host telemetry for at least 30 minutes, or for one complete scanner cycle when practical.
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6. Save one final scanner status snapshot.
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Longer windows are better for cycle interval comparisons. Short windows are acceptable for quick pressure checks only if the conclusion avoids changing defaults.
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## Fields To Compare
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Field semantics are defined in [Scanner Runtime Controls](scanner-runtime-controls.md); the decision fields for a before/after comparison are:
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| Field | Decision it supports |
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| `runtime_config.*.value` and `runtime_config.*.source` | The tested settings actually took effect. |
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| `metrics.pacing_pressure.primary_pressure`, `last_cycle_total_pause_ratio` | Where pressure comes from and how much of the cycle was cooperative pause. |
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| `metrics.maintenance_control.primary_control`, `metrics.maintenance_control.sources` | Whether a maintenance source is blocked, deferred, active, or only pacing-limited. |
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| `metrics.current_cycle_objects_scanned`, `metrics.current_cycle_directories_scanned` | Scan progress continues. |
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| `metrics.last_cycle_result`, `last_cycle_partial_reason`, `last_cycle_partial_source` | Whether the previous cycle completed, which budget stopped it, and which source consumed it. |
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| `metrics.source_work`, `metrics.current_cycle_source_work`, `metrics.last_cycle_source_work` | `missed` growth per source is a downstream admission problem, not pacing. |
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| `metrics.replication_repair` (and current/last-cycle variants) | Repair kind, `scanner_role`, and `execution_owner` for replication backlog runs. |
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| `metrics.lifecycle_expiry.{current_queued,current_active,queue_missed,scanner_missed}` | Expiry backlog and admission failures. |
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| `metrics.lifecycle_transition.{scanner_missed,queue_full,compensation_pending,failed}` | Transition backlog, queue pressure, and worker failures. |
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| `metrics.usage_freshness.*`, `metrics.current_cycle_usage_saves`, `metrics.last_cycle_usage_saves` | Bucket metrics freshness; `last_usage_save_result` must be `success`. |
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| `metrics.life_time_ops.{scan_cycle,scan_bucket_drive,scan_object,save_usage}` | Cycles, bucket-drive scans, object scans, and `DataUsageInfo` saves actually happened after the workload. |
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| `metrics.scan_checkpoint`, `metrics.oldest_active_path_age_seconds` | Partial cycles preserve resume context; stuck paths. |
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Do not use a single CPU spike as the conclusion; compare average and p95 CPU over the same observation window.
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For heal or bitrot pressure investigations, also capture `/v3/background-heal/status` from every distributed endpoint and compare `healOperations.queueLength`, `activeTasks`, `queuedBySource`, `activeBySource`, `queuedByPriority`, and `activeByPriority` (see [Reading Heal Operations](scanner-runtime-controls.md#reading-heal-operations)).
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### `scanner-summary.csv` columns
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In distributed runs the heal columns are aggregated from the background-heal snapshots captured across `--metrics-endpoints`.
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| Column | Meaning |
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| `heal_queue_length` | Total queued heal requests at the same timestamp as the scanner status sample. |
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| `heal_active_tasks` | Total running heal tasks. |
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| `heal_scanner_queued` | Scanner-submitted heal or bitrot work waiting in the queue. |
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| `heal_admin_queued` | Manual/admin heal work waiting in the queue. |
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| `heal_auto_heal_queued` | Auto-heal work waiting in the queue, typically from disk/set recovery paths. |
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| `current_cycle_usage_saves` | Usage saves during the current cycle. |
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| `last_cycle_usage_saves` | Usage saves from the last finished or partial cycle. |
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| `usage_dirty_pending_buckets` | Dirty buckets still waiting for scanner refresh. |
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| `usage_last_cycle_dirty_buckets` | Dirty buckets selected by the last cycle. |
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| `usage_last_cycle_cleared_dirty_buckets` | Dirty bucket marks cleared by the last cycle. |
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| `usage_last_save_result` | Last `DataUsageInfo` save result. |
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| `usage_last_save_unix_secs` | Last `DataUsageInfo` save timestamp. |
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| `life_time_scan_cycle` | Total scanner cycles observed by the node. |
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| `life_time_scan_bucket_drive` | Total bucket-drive scans completed by the node. |
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| `life_time_scan_object` | Total object scan operations observed by the node. |
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| `life_time_save_usage` | Total usage save operations observed by the node. |
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## Interpreting Results
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A useful tuning result has all of these properties:
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- average or p95 scanner-related CPU and disk pressure decreases;
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- `current_cycle_objects_scanned` or `current_cycle_directories_scanned` continues to advance;
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- `source_work.missed` does not grow unexpectedly for lifecycle, replication, heal, or bitrot;
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- `last_cycle_result` is either `success` or a partial result with a clear budget reason and checkpoint;
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- data usage freshness remains acceptable for the tested deployment.
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Treat these as failure signals:
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| Signal | Reading |
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| CPU drops only because the scanner stops making progress | Not a tuning win. |
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| `primary_pressure` stays at `queued_scans` while queues grow | Concurrency, not pacing, is the constraint. |
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| `last_cycle_partial_reason` repeats forever with no checkpoint movement | Budget too small or checkpoint not advancing. |
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| Lifecycle expiry `queue_missed`, `scanner_missed`, `current_queued`, or `current_active` grows during a run meant to reduce expiry backlog | Downstream expiry pressure. |
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| Lifecycle transition `scanner_missed`, `queue_full`, `compensation_pending`, or `failed` grows during a run meant to reduce backlog | Downstream transition pressure. |
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| Bucket metrics show zero usage after post-start uploads while dirty usage remains pending and `life_time_save_usage` does not advance | Usage freshness regression. |
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| `bucket_replication` missed work with `scanner_role=repair_admission` grows while replication worker queues or target failures also grow | Downstream replication pressure, not only scanner pacing. |
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| `site_replication` `active_resync` grows and is read as scanner-owned repair execution | Misreading: `scanner_role=boundary_signal` and `execution_owner=site_replication_runtime` mean active resync remains owned by the site replication runtime. |
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| Heal or bitrot work moves from `queued` to `missed` after a scanner pacing change | Heal admission regression. |
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## PR Evidence Checklist
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For scanner behavior PRs, include when available:
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- RustFS commit SHA and branch.
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- Deployment shape: node count, disk count, disk type, CPU count, memory, object count.
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- Workload command or script and benchmark artifact path.
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- Scanner and heal config before and after tuning.
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- Observation window and sample interval.
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- Scanner status snapshots or time series.
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- Host CPU and disk telemetry.
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- Usage freshness fields from `scanner-summary.csv` when validating bucket metrics timing.
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- A short conclusion that separates pressure reduction from scanner progress.
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- `scanner-validation-report.md` from the harness when using the scripted collection path.
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