├── .gitignore
├── LICENSE
├── README.md
├── buildkite_benchmarks.xlsx
├── requirements.txt
├── serve.py
└── update_data.py
/.gitignore:
--------------------------------------------------------------------------------
1 | # Byte-compiled / optimized / DLL files
2 | __pycache__/
3 | *.py[cod]
4 | *$py.class
5 |
6 | # C extensions
7 | *.so
8 |
9 | # Distribution / packaging
10 | .Python
11 | build/
12 | develop-eggs/
13 | dist/
14 | downloads/
15 | eggs/
16 | .eggs/
17 | lib/
18 | lib64/
19 | parts/
20 | sdist/
21 | var/
22 | wheels/
23 | share/python-wheels/
24 | *.egg-info/
25 | .installed.cfg
26 | *.egg
27 | MANIFEST
28 |
29 | # PyInstaller
30 | # Usually these files are written by a python script from a template
31 | # before PyInstaller builds the exe, so as to inject date/other infos into it.
32 | *.manifest
33 | *.spec
34 |
35 | # Installer logs
36 | pip-log.txt
37 | pip-delete-this-directory.txt
38 |
39 | # Unit test / coverage reports
40 | htmlcov/
41 | .tox/
42 | .nox/
43 | .coverage
44 | .coverage.*
45 | .cache
46 | nosetests.xml
47 | coverage.xml
48 | *.cover
49 | *.py,cover
50 | .hypothesis/
51 | .pytest_cache/
52 | cover/
53 |
54 | # Translations
55 | *.mo
56 | *.pot
57 |
58 | # Django stuff:
59 | *.log
60 | local_settings.py
61 | db.sqlite3
62 | db.sqlite3-journal
63 |
64 | # Flask stuff:
65 | instance/
66 | .webassets-cache
67 |
68 | # Scrapy stuff:
69 | .scrapy
70 |
71 | # Sphinx documentation
72 | docs/_build/
73 |
74 | # PyBuilder
75 | .pybuilder/
76 | target/
77 |
78 | # Jupyter Notebook
79 | .ipynb_checkpoints
80 |
81 | # IPython
82 | profile_default/
83 | ipython_config.py
84 |
85 | # pyenv
86 | # For a library or package, you might want to ignore these files since the code is
87 | # intended to run in multiple environments; otherwise, check them in:
88 | # .python-version
89 |
90 | # pipenv
91 | # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
92 | # However, in case of collaboration, if having platform-specific dependencies or dependencies
93 | # having no cross-platform support, pipenv may install dependencies that don't work, or not
94 | # install all needed dependencies.
95 | #Pipfile.lock
96 |
97 | # poetry
98 | # Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
99 | # This is especially recommended for binary packages to ensure reproducibility, and is more
100 | # commonly ignored for libraries.
101 | # https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
102 | #poetry.lock
103 |
104 | # pdm
105 | # Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
106 | #pdm.lock
107 | # pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
108 | # in version control.
109 | # https://pdm.fming.dev/#use-with-ide
110 | .pdm.toml
111 |
112 | # PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
113 | __pypackages__/
114 |
115 | # Celery stuff
116 | celerybeat-schedule
117 | celerybeat.pid
118 |
119 | # SageMath parsed files
120 | *.sage.py
121 |
122 | # Environments
123 | .env
124 | .venv
125 | env/
126 | venv/
127 | ENV/
128 | env.bak/
129 | venv.bak/
130 |
131 | # Spyder project settings
132 | .spyderproject
133 | .spyproject
134 |
135 | # Rope project settings
136 | .ropeproject
137 |
138 | # mkdocs documentation
139 | /site
140 |
141 | # mypy
142 | .mypy_cache/
143 | .dmypy.json
144 | dmypy.json
145 |
146 | # Pyre type checker
147 | .pyre/
148 |
149 | # pytype static type analyzer
150 | .pytype/
151 |
152 | # Cython debug symbols
153 | cython_debug/
154 |
155 | # PyCharm
156 | # JetBrains specific template is maintained in a separate JetBrains.gitignore that can
157 | # be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
158 | # and can be added to the global gitignore or merged into this file. For a more nuclear
159 | # option (not recommended) you can uncomment the following to ignore the entire idea folder.
160 | #.idea/
161 |
--------------------------------------------------------------------------------
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/README.md:
--------------------------------------------------------------------------------
1 | # dashboard
2 |
3 | vLLM performance dashboard
4 |
5 | ## Install requirements
6 |
7 | ```shell
8 | pip install -r requirements.txt
9 | ```
10 |
11 | ## (For Maintainers) Run `update_data.py` periodically
12 |
13 | ```shell
14 | export BUILDKIT_API_TOKEN=""
15 | python update_data.py
16 | ```
17 |
18 | ## (For Users) Serve the data and view it locally
19 |
20 | ```shell
21 | python serve.py
22 | ```
23 |
--------------------------------------------------------------------------------
/buildkite_benchmarks.xlsx:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/vllm-project/dashboard/9d6e04aaf2f04a621df667f7e802c63bd87efb39/buildkite_benchmarks.xlsx
--------------------------------------------------------------------------------
/requirements.txt:
--------------------------------------------------------------------------------
1 | flask
2 | pandas
3 | openpyxl
4 | requests
5 | dash
6 | plotly
7 |
--------------------------------------------------------------------------------
/serve.py:
--------------------------------------------------------------------------------
1 | import os
2 | import dash
3 | import pandas as pd
4 | import plotly.express as px
5 | from plotly.subplots import make_subplots
6 | from dash import html, dcc, Input, Output, dash_table, clientside_callback
7 | from datetime import datetime
8 | from zoneinfo import ZoneInfo # This is for Python 3.9 and later
9 | from flask import request
10 |
11 | tz = 'America/Los_Angeles'
12 | local_tz = ZoneInfo(tz) # Change this to your timezone, e.g., 'Europe/London', 'Asia/Tokyo'
13 |
14 | # Load your Excel file
15 | file_path = "buildkite_benchmarks.xlsx"
16 | df = pd.read_excel(file_path)
17 | metrics = [col for col in df.columns if df[col].dtype in ['float64', 'int64']]
18 |
19 | timestamp = os.path.getmtime(file_path)
20 | last_modified_time = datetime.fromtimestamp(timestamp).astimezone(local_tz)
21 | readable_time = last_modified_time.strftime('%Y-%m-%d %H:%M:%S') + ' ' + tz
22 |
23 | # Create a column with the commit link as text (since Plotly hover can't render HTML)
24 | df['commit_link'] = df['commit_url'].apply(lambda x: f"URL: {x}")
25 |
26 | # Create a Dash application
27 | app = dash.Dash(__name__)
28 |
29 | def create_metric_figure(metric):
30 | # Create a subplot figure for each metric, as there is only one metric per plot here
31 | fig = make_subplots(rows=1, cols=1, shared_xaxes=True)
32 | trace = px.line(
33 | df,
34 | x='build_datetime',
35 | y=metric,
36 | title=f'Trend of {metric}',
37 | text='commit_link' # This is where the hover text comes from
38 | ).data[0]
39 | fig.add_trace(trace, row=1, col=1)
40 |
41 | fig.update_traces(
42 | mode='markers+lines',
43 | hovertemplate='Time:%{x}
Value: %{y}' # Customize hover text
44 | )
45 | fig.update_layout(
46 | height=300, # Fixed height as each metric is in a separate plot now
47 | title_text=f"Performance Metrics for {metric}",
48 | hovermode='closest'
49 | )
50 | return fig
51 |
52 | # Dropdown to select the metric for plotting
53 | app.layout = html.Div([
54 | html.H1('Performance Metrics Over Time'),
55 | dcc.Markdown("Click on data point to show commit url.", id='url-click-output'), # Use dcc.Markdown to handle HTML
56 | dcc.Dropdown(
57 | id='metric-select',
58 | options=[{'label': metric, 'value': metric} for metric in metrics],
59 | value=metrics,
60 | multi=True
61 | ),
62 | # Generate a plot for each metric, hidden by default
63 | html.Div([dcc.Graph(id=f'graph-{metric}', figure=create_metric_figure(metric))
64 | for metric in metrics]),
65 | dcc.Store(id='plot-visibility'),
66 | html.Div(f"Last Updated: {readable_time}", style={'position': 'fixed', 'bottom': '10px', 'right': '10px'}),
67 | ])
68 |
69 | clientside_callback(
70 | """
71 | function(selectedMetrics, ...plotIds) {
72 | // Loop through all plot IDs and set visibility
73 | plotIds.forEach((plotId) => {
74 | const plotElement = document.getElementById(plotId);
75 | if (plotElement) {
76 | plotElement.style.display = selectedMetrics.includes(plotId.replace('graph-', '')) ? 'block' : 'none';
77 | }
78 | });
79 | return null;
80 | }
81 | """,
82 | Output('plot-visibility', 'data'),
83 | Input('metric-select', 'value'),
84 | state=[Input(f'graph-{metric}', 'id') for metric in metrics] # Passing plot IDs as state
85 | )
86 |
87 | for metric in metrics:
88 | clientside_callback(
89 | """
90 | function(clickData) {
91 | if (clickData) {
92 | var url = clickData.points[0].text.split("URL: ")[1];
93 | return `[Open Commit ${url}](${url})`;
94 | }
95 | return "Click on a point to see the URL.";
96 | }
97 | """,
98 | Output('url-click-output', 'children', allow_duplicate=True),
99 | Input(f'graph-{metric}', 'clickData'),
100 | prevent_initial_call=True,
101 | )
102 |
103 | # Flask request logging
104 | @app.server.before_request
105 | def log_request():
106 | # This will print the request details before each request is processed.
107 | if request.path != '/_reload-hash':
108 | print(f"Request received at: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}")
109 | print(f"Request path: {request.path}")
110 | print(f"Request method: {request.method}")
111 | print(f"Request headers: {request.headers}")
112 | print(f"Request body: {request.get_data(as_text=True)}")
113 |
114 | if __name__ == '__main__':
115 | app.run_server(debug=True)
116 |
--------------------------------------------------------------------------------
/update_data.py:
--------------------------------------------------------------------------------
1 | import os
2 | import requests
3 | from datetime import datetime, timedelta
4 |
5 | import subprocess
6 |
7 | def run_curl_command(token, url):
8 | command = [
9 | "curl",
10 | "-H", f"Authorization: Bearer {token}",
11 | "-X", "GET",
12 | url
13 | ]
14 |
15 | try:
16 | result = subprocess.run(command, check=True, text=True, capture_output=True)
17 | return result.stdout # Returns the content of the log file
18 | except subprocess.CalledProcessError as e:
19 | raise Exception(f"Command failed with return code {e.returncode}: {e.output}")
20 |
21 |
22 | def get_builds(org_slug, branch, token, days=30):
23 | url = f"https://api.buildkite.com/v2/organizations/{org_slug}/builds"
24 | headers = {
25 | "Authorization": f"Bearer {token}",
26 | "Content-Type": "application/json"
27 | }
28 |
29 | # Calculate the date 30 days ago from today
30 | date_from = (datetime.utcnow() - timedelta(days=days)).isoformat() + "Z"
31 |
32 | params = {
33 | "branch": branch,
34 | "created_from": date_from,
35 | "per_page": "100",
36 | }
37 |
38 | all_builds = []
39 | while url:
40 | response = requests.get(url, headers=headers, params=params)
41 | if response.status_code == 200:
42 | all_builds.extend(response.json())
43 | # Parse the Link header and look for a 'next' relation
44 | link_header = response.headers.get('Link', None)
45 | url = None
46 | if link_header:
47 | links = link_header.split(',')
48 | next_link = [link for link in links if 'rel="next"' in link]
49 | if next_link:
50 | next_url = next_link[0].split(';')[0].strip('<>')
51 | url = next_url
52 | params = {} # Clear params because next URL will have necessary params
53 | else:
54 | raise Exception(f"Failed to get builds: {response.status_code} - {response.text}")
55 |
56 | return all_builds
57 |
58 | import re
59 |
60 | # Define a list of dictionaries for patterns
61 | log_patterns = [
62 | {'key': 'Average Latency', 'pattern': re.compile(r"Avg latency: ([\d.]+) seconds")},
63 | {'key': '10% Percentile Latency', 'pattern': re.compile(r"10% percentile latency: ([\d.]+) seconds")},
64 | {'key': '25% Percentile Latency', 'pattern': re.compile(r"25% percentile latency: ([\d.]+) seconds")},
65 | {'key': '50% Percentile Latency', 'pattern': re.compile(r"50% percentile latency: ([\d.]+) seconds")},
66 | {'key': '75% Percentile Latency', 'pattern': re.compile(r"75% percentile latency: ([\d.]+) seconds")},
67 | {'key': '90% Percentile Latency', 'pattern': re.compile(r"90% percentile latency: ([\d.]+) seconds")},
68 | {'key': 'Throughput', 'pattern': re.compile(r"Throughput: ([\d.]+) requests/s")},
69 | {'key': 'Token Throughput', 'pattern': re.compile(r"Throughput: [\d.]+ requests/s, ([\d.]+) tokens/s")},
70 | {'key': 'Successful Requests', 'pattern': re.compile(r"Successful requests: +(\d+)")},
71 | {'key': 'Benchmark Duration', 'pattern': re.compile(r"Benchmark duration \(s\): +([\d.]+)")},
72 | {'key': 'Total Input Tokens', 'pattern': re.compile(r"Total input tokens: +(\d+)")},
73 | {'key': 'Total Generated Tokens', 'pattern': re.compile(r"Total generated tokens: +(\d+)")},
74 | {'key': 'Request Throughput', 'pattern': re.compile(r"Request throughput \(req/s\): +([\d.]+)")},
75 | {'key': 'Input Token Throughput', 'pattern': re.compile(r"Input token throughput \(tok/s\): +([\d.]+)")},
76 | {'key': 'Output Token Throughput', 'pattern': re.compile(r"Output token throughput \(tok/s\): +([\d.]+)")},
77 | {'key': 'Mean TTFT', 'pattern': re.compile(r"Mean TTFT \(ms\): +([\d.]+)")},
78 | {'key': 'Median TTFT', 'pattern': re.compile(r"Median TTFT \(ms\): +([\d.]+)")},
79 | {'key': 'P99 TTFT', 'pattern': re.compile(r"P99 TTFT \(ms\): +([\d.]+)")},
80 | {'key': 'Mean TPOT', 'pattern': re.compile(r"Mean TPOT \(ms\): +([\d.]+)")},
81 | {'key': 'Median TPOT', 'pattern': re.compile(r"Median TPOT \(ms\): +([\d.]+)")},
82 | {'key': 'P99 TPOT', 'pattern': re.compile(r"P99 TPOT \(ms\): +([\d.]+)")}
83 | ]
84 |
85 | # Function to process log entries using defined patterns
86 | def extract_data_from_logs(logs, patterns=log_patterns):
87 | results = {}
88 | for line in logs.split('\n'):
89 | for pattern_dict in patterns:
90 | match = pattern_dict['pattern'].search(line)
91 | if match:
92 | results[pattern_dict['key']] = match.group(1)
93 | return results
94 |
95 | # Replace 'your_token_here' with your actual Buildkite API token
96 | API_TOKEN = os.environ.get("BUILDKIT_API_TOKEN") # or 'your_token_here'
97 | ORG_SLUG = "vllm" # Replace 'vllm' with the actual slug of your organization if different
98 | BRANCH = "main"
99 | cache_dir = ".cache"
100 | os.makedirs(cache_dir, exist_ok=True)
101 |
102 | columns = [
103 | 'commit',
104 | 'commit_url',
105 | 'build_datetime',
106 | 'Average Latency',
107 | '10% Percentile Latency',
108 | '25% Percentile Latency',
109 | '50% Percentile Latency',
110 | '75% Percentile Latency',
111 | '90% Percentile Latency',
112 | 'Throughput',
113 | 'Token Throughput',
114 | 'Successful Requests',
115 | 'Benchmark Duration',
116 | 'Total Input Tokens',
117 | 'Total Generated Tokens',
118 | 'Request Throughput',
119 | 'Input Token Throughput',
120 | 'Output Token Throughput',
121 | 'Mean TTFT',
122 | 'Median TTFT',
123 | 'P99 TTFT',
124 | 'Mean TPOT',
125 | 'Median TPOT',
126 | 'P99 TPOT'
127 | ]
128 | values = []
129 |
130 | builds = get_builds(ORG_SLUG, BRANCH, API_TOKEN)
131 | for build in builds:
132 | commit = build['commit']
133 | commit_url = f"{build['pipeline']['repository'].replace('.git', '')}/commit/{build['commit']}"
134 | raw_log_url = None
135 | for job in build.get('jobs', []):
136 | if 'name' in job and job['name'] == "Benchmarks":
137 | raw_log_url = job['raw_log_url']
138 | break
139 | if raw_log_url is None:
140 | continue
141 | build_datetime = build['created_at']
142 | filename = f"{build_datetime}_{commit}.log"
143 | filepath = os.path.join(cache_dir, filename)
144 | if os.path.exists(filepath):
145 | print(f"Skipping downloading {filepath} for commit {commit} because it already exists")
146 | else:
147 | data = run_curl_command(API_TOKEN, raw_log_url)
148 | if len(data) <= 100:
149 | print(f"Skipping processing {filepath} for commit {commit} because the log is empty")
150 | continue
151 | with open(filepath, "w") as f:
152 | f.write(data)
153 | print(f"Saved {filepath} for commit {commit}")
154 | with open(filepath, "r") as f:
155 | logs = f.read()
156 | results = extract_data_from_logs(logs)
157 | values.append([commit, commit_url, build_datetime] + [results.get(col, "") for col in columns[3:]])
158 |
159 | import pandas as pd
160 | df = pd.DataFrame(values, columns=columns)
161 | df.to_excel("buildkite_benchmarks.xlsx", index=False)
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