abench-speckz 0.4.3

YAML-driven benchmark sweeps: generate env-file combinations, execute a tool across each, and query DuckDB-backed aggregate stats.

abench-speckz

Generate Docker env-file combinations from a YAML benchmark spec, execute a benchmark tool across every combination, and query the results.

Install

Requires Python 3.10+.

python -m venv .venv && source .venv/bin/activate
pip install -e '.[dev]'

Note on examples: files under examples/ reference paths like python examples/sample_bench.py. Those paths are relative to the repo root, so the examples run only from a checkout — not from an arbitrary working directory after pip install. Clone the repo and cd into it to follow the examples verbatim.

Workflow

spec.yaml  →  abench-speckz gen  →  out/ (env-files + manifest.json)
                                    ↓
              abench-speckz run  →  results/ (runs.jsonl + aggregates.jsonl)
                                    ↓
              abench-speckz stats →  table / JSON / TSV

Commands

gen — generate env-file combinations

abench-speckz gen spec.yaml --out out/           # write env-files
abench-speckz gen spec.yaml --dry-run            # print summary table
abench-speckz gen spec.yaml --list               # print TSV
abench-speckz gen spec.yaml --profile smoke --out out/
abench-speckz gen spec.yaml --tag stress --out out/
abench-speckz gen spec.yaml --exclude-tag slow --out out/

Each combination is written as a Docker env-file (KEY=value per line). A manifest.json in the output directory maps each filename back to its full variable assignment and tags.

run — execute a tool across every combination

abench-speckz run out/ --tool oha.tool.yaml
abench-speckz run out/ --tool oha.tool.yaml --repeat 5 --warmup 1
abench-speckz run out/ --tool oha.tool.yaml --filter workload=read
abench-speckz run out/ --tool oha.tool.yaml --filter-tag stress
abench-speckz run out/ --tool oha.tool.yaml --filter-exclude-tag slow
abench-speckz run out/ --tool oha.tool.yaml --skip-existing --keep-raw
abench-speckz run out/ --tool oha.tool.yaml --dry-run   # print planned commands

Results are written to results/ (configurable with --results).

stats — aggregate and display results

abench-speckz stats results/
abench-speckz stats results/ --group-by workload --group-by concurrency
abench-speckz stats results/ --metric requests_per_sec --metric p50_ms
abench-speckz stats results/ --where workload=read
abench-speckz stats results/ --filter-tag stress
abench-speckz stats results/ --filter-exclude-tag slow
abench-speckz stats results/ --format json
abench-speckz stats results/ --format tsv
abench-speckz stats results/ --pretty            # use display names from tool YAML
abench-speckz stats results/ --from-raw          # recompute from runs.jsonl
abench-speckz stats results/ --report report.html              # self-contained Chart.js HTML
abench-speckz stats results/ --report report.html --plots plots.yaml  # override tool YAML plots

--report writes a self-contained HTML file with Chart.js plots. Plot definitions come from the tool YAML's plots: list (see below), or from a separate YAML file via --plots. When no plots are defined, a default per-metric bar chart is rendered.

rebuild-aggregates — regenerate aggregates from raw runs

abench-speckz rebuild-aggregates results/

Spec format

static:
  IMAGE: myapp:latest
  REGION: us-east-1

variables:
  workload:    [read, write, mixed]
  concurrency: [1, 8, 64]
  backend:     [postgres, mysql]

# conditional overrides and tagging
when:
  - if:  { workload: write, backend: mysql }
    set: { LOCK_TIMEOUT: "30s" }
    tag: [slow, write-heavy]
  - if:  { concurrency: 64 }
    set: { THREAD_POOL: "${concurrency}" }
    tag: [stress]

# combos to drop entirely
exclude:
  - { backend: mysql, concurrency: 1 }

# tags applied to every combo
tags: [bench]

profiles:
  smoke:
    variables:
      concurrency: [1]
      workload: [read]
  full: {}

default_profile: smoke

Interpolation: use ${var} to reference other variables and ${env:VAR} to read from the process environment. Use $$ for a literal $.

Variable names starting with _ are reserved and will be rejected at load time. Built-in synthetic variables:

Variable	Available in	Description
${_envfile}	command, setup, teardown, post_run, monitor, output_file	Absolute path to the current combo's env file
${_run_id}	command, setup, teardown, post_run, monitor	UUID for this rep — same value written to runs.jsonl
${_exit_code}	post_run	Benchmark exit code
${_started_at}	post_run	ISO timestamp when the benchmark started
${_finished_at}	post_run	ISO timestamp when the benchmark finished
${_duration_ms}	post_run	Wall-clock duration in milliseconds

Profiles overlay the base spec — variables, static, when, and exclude lists are merged. The default_profile is used when --profile is not specified.

Tool YAML format

name: oha
command: "oha ${URL} -n ${REQUESTS} -c ${concurrency} --json"
# ${_envfile} is a built-in variable: absolute path to the current combo's env file.
# Example: docker run --env-file ${_envfile} myimage
timeout_seconds: 300
version_command: "oha --version"

# extract metrics from JSON stdout via JSONPath
capture:
  requests_per_sec: "$.summary.requestsPerSec"
  p50_ms: "$.latencyPercentiles.p50"
  errors[]: "$.errors[*].message"   # trailing [] collects all matches as a list

# alternative: a custom Python parser function
# parser: "mymodule:parse_fn"       # fn(stdout: str) -> dict

# read extraction input from a file the tool writes, instead of stdout
# output_file: "results.json"       # interpolates ${var} / ${env:VAR}
# output_format: jsonl              # "json" (default) or "jsonl" for one JSON object per line

pretty_names:
  requests_per_sec: "Requests/s"
  p50_ms: "p50 latency"
units:
  p50_ms: ms
higher_is_better:
  requests_per_sec: true
  p50_ms: false

# optional: run once at the start of the sweep; output captured into env.snapshot.json
# under a "probes" key. Non-zero exit or missing command stores null for that key.
env_probes:
  kernel:       "uname -r"
  cpu:          "sysctl -n machdep.cpu.brand_string"
  redis_version: "redis-cli --version"

# optional: run once per unique config hash (before the first rep for that combo);
# commands may reference combo vars. Results stored in combo_probes.json and
# embedded in every runs.jsonl row under "combo_probes".
combo_probes:
  effective_maxmemory: "redis-cli -p ${PORT} CONFIG GET maxmemory"
  row_count:           "psql ${DSN} -tAc 'SELECT count(*) FROM events'"

# optional: shell steps run around every rep (warmup and measured)
setup:
  - "docker compose up -d redis"
  - "sleep 1"
teardown:
  - "docker compose down -v"
setup_timeout_seconds: 120   # per-step timeout for setup/teardown/post_run (default 120)

# optional: shell steps run after teardown, always (even on benchmark failure)
# receives run-result vars: ${_run_id}, ${_exit_code}, ${_started_at}, ${_finished_at}, ${_duration_ms}
post_run:
  - "prom-query.sh ${_started_at} ${_finished_at} ${_run_id}"

# optional: background processes launched before the benchmark command and
# terminated after it completes (SIGTERM, then SIGKILL after 5s).
# Interpolates combo vars including ${_envfile} and ${_run_id}.
monitor:
  - "python collect-metrics.py --run-id ${_run_id}"
  - "perf stat -p $(cat service.pid)"

# optional: declarative plots used by `stats --report`
plots:
  - id: rps_by_workload
    type: bar                        # bar | stacked-bar | line | scatter
    title: "Throughput by workload"
    x: workload
    y: requests_per_sec
  - id: latency_breakdown
    type: stacked-bar
    title: "Latency percentiles"
    x: workload
    y: [p50_ms, p95_ms, p99_ms]
  - id: rps_vs_concurrency
    type: line
    title: "Throughput scaling"
    x: concurrency                        # combo variable on x-axis
    y: requests_per_sec
    group_by: workload                    # one line per workload value
  - id: rps_vs_concurrency_multi
    type: line
    title: "Throughput scaling by workload + backend"
    x: concurrency
    y: requests_per_sec
    group_by: [workload, backend]         # one line per workload+backend combo
  - id: throughput_vs_latency
    type: scatter
    title: "Throughput / latency tradeoff"
    x: requests_per_sec                  # metric on x-axis (not a variable)
    y: p95_ms                            # metric on y-axis
    group_by: workload                   # one labeled point per workload value

group_by in plots. Splits data into multiple series based on combo variable values. Accepts a single variable name or a list; multiple keys are joined with / in the legend label.

• bar / stacked-bar / line: without group_by, each y metric becomes one series. With group_by, you get one series per (metric, group-value) pair.
• scatter: x and y are both metric names (not variables). Each unique combination of group_by values becomes its own labeled point. Without group_by, all points collapse into a single "all" series.

Negation in group_by. Prefix a variable name with ! to mean "all variables except this one". Useful when you have many variables and don't want to list them all:

- id: rps_all_configs
  type: line
  x: concurrency
  y: rps
  group_by: "!concurrency"       # one line per every other variable combination

- id: rps_except_region
  type: line
  x: concurrency
  y: rps
  group_by: ["!concurrency", "!region"]   # exclude multiple vars; keep the rest

Negation is resolved at report time against the actual variable names in aggregates.jsonl. Unknown excluded names are silently ignored.

env_probes. A mapping of key → shell command run once at the very start of the sweep (before any rep). The trimmed stdout of each command is stored in env.snapshot.json under "probes". A non-zero exit code or missing command stores null for that key — probes never abort a sweep.

combo_probes. A mapping of key → command template run once per unique config hash, before the first rep for that combo (after per-sweep setup). Commands interpolate combo vars (${var}, ${_envfile}, ${env:VAR}). Results are stored in two places: combo_probes.json (keyed by config hash) and embedded in every runs.jsonl row under "combo_probes". Non-zero exit, missing command, timeout, or interpolation error stores null — probes never abort a sweep. Useful for capturing system or service state that varies per combo (e.g. effective DB config after per-sweep setup seeded a different dataset, kernel tuning parameters set per workload).

// env.snapshot.json (excerpt)
{
  "host": "...",
  "probes": {
    "kernel": "24.2.0",
    "redis_version": "Redis server v=7.2.3 sha=...",
    "cpu": null
  }
}

Setup / teardown / post_run / monitor. The full per-rep lifecycle is:

setup  →  [monitor start]  →  command  →  [monitor stop]  →  teardown  →  post_run

Teardown runs in a finally block, so it fires even on benchmark failure or Ctrl-C. Combo vars (${var}), ${_envfile}, ${_run_id}, and ${env:VAR} interpolate in all phases. Steps are split with shlex.split and executed without a shell, so chain via multiple list entries rather than &&.

• Setup failure → the command is skipped, monitor is not started, teardown still runs best-effort, post_run is skipped, and failure_reason is recorded as setup[i]: ….
• Teardown failure → the benchmark's exit_code and metrics are preserved, but teardown[i]: … is appended to failure_reason.
• post_run → runs after teardown completes, always — including when the benchmark exits non-zero. In addition to combo vars, it receives ${_exit_code}, ${_started_at}, ${_finished_at}, and ${_duration_ms}. Useful for collecting time-windowed metrics from external systems (Prometheus, InfluxDB, etc.) keyed to the exact run via ${_run_id}. post_run failure is appended to failure_reason but does not suppress the benchmark result or its metrics.
• monitor → each command is launched as a background process immediately after setup succeeds. Processes receive SIGTERM once the benchmark command finishes; any that don't exit within 5 seconds receive SIGKILL. A monitor that fails to start is recorded but never aborts the run. Interpolates combo vars including ${_run_id} and ${_envfile}. Start and stop records are written to raw/{run_id}.json under --keep-raw or when any monitor fails to start.

Sweep-scoped setup / teardown. setup_per_sweep and teardown_per_sweep run outside the per-rep loop, useful for expensive prep like seeding a database. By default each fires exactly once for the whole sweep. Set per_sweep_var: <name> to scope each fire to a single variable: combos are stably grouped by that variable's value, and the phases fire once per distinct value (around the reps for that group).

setup_per_sweep:    ["seed-db.sh"]              # fires once before any rep
teardown_per_sweep: ["drop-db.sh"]
per_sweep_var:      workload                    # optional; one var only

• Without per_sweep_var: only ${env:VAR} can be referenced; any ${combo_var} rejected at sweep start.
• With per_sweep_var: X: only ${X} and ${env:VAR} can be referenced; the current group's value of X is substituted.
• --skip-existing: if every rep in a group is already recorded, both phases are skipped for that group.
• Setup failure: all planned reps in that group get a failure row with failure_reason="per_sweep_setup[i]: …"; teardown still runs best-effort. Next group proceeds.
• Teardown failure: appended to the last rep row in the group's failure_reason.
• Raw record: raw/sweep.json (Mode A) or raw/sweep-{slug(value)}.json (Mode B) — same shape as per-rep raw files.

Raw output records. When a raw record is written, raw/{run_id}.json is a JSON object with:

• stdout, stderr — the tool's own streams (always present).
• output_file — {path, content} when output_file is configured in the tool YAML, so the tool's stdout/stderr stay separate from the file content used for extraction.
• setup, teardown, post_run — one entry per step that ran, each with command, exit_code, stdout, stderr.
• monitor_start — one entry per monitor command with command, pid (or error if it failed to start).
• monitor_stop — one entry per running monitor process with pid, exit_code, stdout, stderr.

Results directory layout

results/
  runs.jsonl              # append-only log, one JSON object per run
  aggregates.jsonl        # per-combo stats (n, mean, stddev, p50/95/99, CI95)
  manifest.snapshot.json  # copy of the manifest used
  tools/{name}.yaml       # copy of the tool YAML used
  env.snapshot.json       # host info (OS, CPU, git SHA) + env_probes results under "probes"
  combo_probes.json       # combo_probes results keyed by config hash
  pretty_names.json       # merged metric display names
  raw/{run_id}.json       # structured raw record (see below); written with
                          # --keep-raw, on extract failure, on tool failure,
                          # or when setup/teardown/post_run failed
  raw/sweep[-{slug}].json # per_sweep setup/teardown records; written on
                          # --keep-raw or any per_sweep phase failure