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SentryFlow logo

SentryFlow

A self-hosted API gateway with rate limiting, request logging, and usage analytics.

BackendFrontendAnalyticsLicense

SentryFlow sits in front of your APIs as a gateway: it authenticates requests by API key, enforces per-endpoint rate limits, and streams every request through Kafka into ClickHouse so usage patterns, error rates, and latency are queryable after the fact instead of only visible in scattered logs.

Features

  • API key management: issue, scope, and revoke keys per user.
  • Rate limiting: sliding-window and token-bucket algorithms, configurable per endpoint.
  • Request logging: every request is logged with timing, status, and caller identity for auditing and debugging.
  • Streaming analytics: request logs are published to Kafka and batch- consumed into ClickHouse, so the dashboard queries pre-aggregated metrics instead of scanning raw logs.
  • Dashboard: usage charts, a per-user view, a live rate-limit monitor, and a logs explorer, all in one React app.

Architecture

flowchart LR
CLIENT[API caller] -->|API key| BACKEND
subgraph BACKEND["Backend (FastAPI)"]
AUTH[Auth middleware]
RATE[Rate limiter\nsliding window / token bucket]
LOG[Logging middleware]
end
BACKEND --> UPSTREAM[Your API]
BACKEND -->|request events| KAFKA[(Kafka)]
KAFKA --> AGG[Aggregator\nbatch consumer]
AGG --> CH[(ClickHouse)]
DASH[React Dashboard] -->|metrics queries| CH
DASH -->|key mgmt, config| BACKEND
Loading

Backend: FastAPI, SQLAlchemy, Redis (rate-limit counters), Kafka producer. Aggregator: a standalone Kafka consumer that batches request events into ClickHouse. Frontend: React + Chart.js + Tailwind, talking to both the backend (auth, key management, rate-limit config) and ClickHouse-backed analytics endpoints (dashboards, logs explorer).

Quickstart

Docker (fastest)

git clone https://github.com/Heet852003/SentryFlow.git
cd SentryFlow
docker compose up -d

From source

# Backendcd backend
python -m venv venv &&source venv/bin/activate # Windows: venv\Scripts\activate
pip install -r requirements.txt
cp .env.example .env
uvicorn main:app --reload
# Aggregator (separate terminal)cd aggregator
pip install -r requirements.txt
cp .env.example .env
python batch_consumer.py
# Frontend (separate terminal)cd frontend
npm install
npm start

Prerequisites: Python 3.9+, Node 16+, PostgreSQL, Redis, Kafka, ClickHouse (or just use docker compose up -d, which brings up all of them).

Usage

  1. Register/log in, then create an API key from the API Keys page. It's shown once, store it client-side.
  2. Configure per-endpoint rate limits from the Rate Limit Monitor: pick sliding-window or token-bucket, set the limit and window.
  3. Watch traffic land in the Dashboard, drill into a specific user from User View, or inspect raw requests in the Logs Explorer.

Repository layout

backend/ FastAPI gateway: auth, rate limiting, request logging
aggregator/ Kafka consumer that batches request logs into ClickHouse
frontend/ React dashboard
docs/ API, deployment, and rate-limiting docs
scripts/ dev/docker startup and mock-data helpers

See docs/api.md, docs/deployment.md, and docs/rate-limiting.md for details.

Testing

cd backend
pytest

Contributing

Contributions are welcome. Fork the repo, create a feature branch, and open a pull request. See CONTRIBUTING.md.

License

MIT. See LICENSE for details.

About

A comprehensive API monitoring and management system

Resources

Readme
MIT license

Contributing

Contributing
Activity

Stars

0 stars

Watchers

0 watching

Forks

0 forks
Report repository

Releases

Packages

Contributors

Languages

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var __re = new RegExp('^' + "github\\.com" + '
GitHub - Heet852003/SentryFlow: A comprehensive API monitoring and management system · GitHub
Skip to content
BranchesTags
Repository files navigation
SentryFlow logo
SentryFlow
A self-hosted API gateway with rate limiting, request logging, and usage analytics.
BackendFrontendAnalyticsLicense
SentryFlow sits in front of your APIs as a gateway: it authenticates requests
by API key, enforces per-endpoint rate limits, and streams every request
through Kafka into ClickHouse so usage patterns, error rates, and latency
are queryable after the fact instead of only visible in scattered logs.
Features
  • API key management: issue, scope, and revoke keys per user.
  • Rate limiting: sliding-window and token-bucket algorithms, configurable
per endpoint.
  • Request logging: every request is logged with timing, status, and
caller identity for auditing and debugging.
  • Streaming analytics: request logs are published to Kafka and batch-
consumed into ClickHouse, so the dashboard queries pre-aggregated metrics
instead of scanning raw logs.
  • Dashboard: usage charts, a per-user view, a live rate-limit monitor,
and a logs explorer, all in one React app.
Architecture
flowchart LR
CLIENT[API caller] -->|API key| BACKEND
subgraph BACKEND["Backend (FastAPI)"]
AUTH[Auth middleware]
RATE[Rate limiter\nsliding window / token bucket]
LOG[Logging middleware]
end
BACKEND --> UPSTREAM[Your API]
BACKEND -->|request events| KAFKA[(Kafka)]
KAFKA --> AGG[Aggregator\nbatch consumer]
AGG --> CH[(ClickHouse)]
DASH[React Dashboard] -->|metrics queries| CH
DASH -->|key mgmt, config| BACKEND

Loading
Backend: FastAPI, SQLAlchemy, Redis (rate-limit counters), Kafka producer.
Aggregator: a standalone Kafka consumer that batches request events into
ClickHouse. Frontend: React + Chart.js + Tailwind, talking to both the
backend (auth, key management, rate-limit config) and ClickHouse-backed
analytics endpoints (dashboards, logs explorer).
Quickstart
Docker (fastest)
git clone https://github.com/Heet852003/SentryFlow.git
cd SentryFlow
docker compose up -d
From source
# Backendcd backend
python -m venv venv &&source venv/bin/activate # Windows: venv\Scripts\activate
pip install -r requirements.txt
cp .env.example .env
uvicorn main:app --reload
# Aggregator (separate terminal)cd aggregator
pip install -r requirements.txt
cp .env.example .env
python batch_consumer.py
# Frontend (separate terminal)cd frontend
npm install
npm start
Prerequisites: Python 3.9+, Node 16+, PostgreSQL, Redis, Kafka, ClickHouse
(or just use docker compose up -d, which brings up all of them).
Usage
  1. Register/log in, then create an API key from the API Keys page. It's
shown once, store it client-side.
  2. Configure per-endpoint rate limits from the Rate Limit Monitor: pick
sliding-window or token-bucket, set the limit and window.
  3. Watch traffic land in the Dashboard, drill into a specific user from
User View, or inspect raw requests in the Logs Explorer.
Repository layout
backend/ FastAPI gateway: auth, rate limiting, request logging
aggregator/ Kafka consumer that batches request logs into ClickHouse
frontend/ React dashboard
docs/ API, deployment, and rate-limiting docs
scripts/ dev/docker startup and mock-data helpers

See docs/api.md, docs/deployment.md,
and docs/rate-limiting.md for details.
Testing
cd backend
pytest
Contributing
Contributions are welcome. Fork the repo, create a feature branch, and open
a pull request. See CONTRIBUTING.md.
License
MIT. See LICENSE for details.
About
A comprehensive API monitoring and management system
Resources
Readme
MIT license
Contributing
Contributing
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
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var style = document.createElement('style');
style.textContent = '
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})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
GitHub - Heet852003/SentryFlow: A comprehensive API monitoring and management system · GitHub
Skip to content
BranchesTags
Repository files navigation
SentryFlow logo
SentryFlow
A self-hosted API gateway with rate limiting, request logging, and usage analytics.
BackendFrontendAnalyticsLicense
SentryFlow sits in front of your APIs as a gateway: it authenticates requests
by API key, enforces per-endpoint rate limits, and streams every request
through Kafka into ClickHouse so usage patterns, error rates, and latency
are queryable after the fact instead of only visible in scattered logs.
Features
  • API key management: issue, scope, and revoke keys per user.
  • Rate limiting: sliding-window and token-bucket algorithms, configurable
per endpoint.
  • Request logging: every request is logged with timing, status, and
caller identity for auditing and debugging.
  • Streaming analytics: request logs are published to Kafka and batch-
consumed into ClickHouse, so the dashboard queries pre-aggregated metrics
instead of scanning raw logs.
  • Dashboard: usage charts, a per-user view, a live rate-limit monitor,
and a logs explorer, all in one React app.
Architecture
flowchart LR
CLIENT[API caller] -->|API key| BACKEND
subgraph BACKEND["Backend (FastAPI)"]
AUTH[Auth middleware]
RATE[Rate limiter\nsliding window / token bucket]
LOG[Logging middleware]
end
BACKEND --> UPSTREAM[Your API]
BACKEND -->|request events| KAFKA[(Kafka)]
KAFKA --> AGG[Aggregator\nbatch consumer]
AGG --> CH[(ClickHouse)]
DASH[React Dashboard] -->|metrics queries| CH
DASH -->|key mgmt, config| BACKEND

Loading
Backend: FastAPI, SQLAlchemy, Redis (rate-limit counters), Kafka producer.
Aggregator: a standalone Kafka consumer that batches request events into
ClickHouse. Frontend: React + Chart.js + Tailwind, talking to both the
backend (auth, key management, rate-limit config) and ClickHouse-backed
analytics endpoints (dashboards, logs explorer).
Quickstart
Docker (fastest)
git clone https://github.com/Heet852003/SentryFlow.git
cd SentryFlow
docker compose up -d
From source
# Backendcd backend
python -m venv venv &&source venv/bin/activate # Windows: venv\Scripts\activate
pip install -r requirements.txt
cp .env.example .env
uvicorn main:app --reload
# Aggregator (separate terminal)cd aggregator
pip install -r requirements.txt
cp .env.example .env
python batch_consumer.py
# Frontend (separate terminal)cd frontend
npm install
npm start
Prerequisites: Python 3.9+, Node 16+, PostgreSQL, Redis, Kafka, ClickHouse
(or just use docker compose up -d, which brings up all of them).
Usage
  1. Register/log in, then create an API key from the API Keys page. It's
shown once, store it client-side.
  2. Configure per-endpoint rate limits from the Rate Limit Monitor: pick
sliding-window or token-bucket, set the limit and window.
  3. Watch traffic land in the Dashboard, drill into a specific user from
User View, or inspect raw requests in the Logs Explorer.
Repository layout
backend/ FastAPI gateway: auth, rate limiting, request logging
aggregator/ Kafka consumer that batches request logs into ClickHouse
frontend/ React dashboard
docs/ API, deployment, and rate-limiting docs
scripts/ dev/docker startup and mock-data helpers

See docs/api.md, docs/deployment.md,
and docs/rate-limiting.md for details.
Testing
cd backend
pytest
Contributing
Contributions are welcome. Fork the repo, create a feature branch, and open
a pull request. See CONTRIBUTING.md.
License
MIT. See LICENSE for details.
About
A comprehensive API monitoring and management system
Resources
Readme
MIT license
Contributing
Contributing
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Highlight search terms from Google/DuckDuckGo/Bing referrer
(function() {
var ref = document.referrer;
var terms = [];
if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {
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var found = false;
terms.forEach(function(term) {
var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\]\\]/g, '\\') + ')', 'gi');
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observer.observe(document.body, { childList: true, subtree: true });
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} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
GitHub - Heet852003/SentryFlow: A comprehensive API monitoring and management system · GitHub
Skip to content
BranchesTags
Repository files navigation
SentryFlow logo
SentryFlow
A self-hosted API gateway with rate limiting, request logging, and usage analytics.
BackendFrontendAnalyticsLicense
SentryFlow sits in front of your APIs as a gateway: it authenticates requests
by API key, enforces per-endpoint rate limits, and streams every request
through Kafka into ClickHouse so usage patterns, error rates, and latency
are queryable after the fact instead of only visible in scattered logs.
Features
  • API key management: issue, scope, and revoke keys per user.
  • Rate limiting: sliding-window and token-bucket algorithms, configurable
per endpoint.
  • Request logging: every request is logged with timing, status, and
caller identity for auditing and debugging.
  • Streaming analytics: request logs are published to Kafka and batch-
consumed into ClickHouse, so the dashboard queries pre-aggregated metrics
instead of scanning raw logs.
  • Dashboard: usage charts, a per-user view, a live rate-limit monitor,
and a logs explorer, all in one React app.
Architecture
flowchart LR
CLIENT[API caller] -->|API key| BACKEND
subgraph BACKEND["Backend (FastAPI)"]
AUTH[Auth middleware]
RATE[Rate limiter\nsliding window / token bucket]
LOG[Logging middleware]
end
BACKEND --> UPSTREAM[Your API]
BACKEND -->|request events| KAFKA[(Kafka)]
KAFKA --> AGG[Aggregator\nbatch consumer]
AGG --> CH[(ClickHouse)]
DASH[React Dashboard] -->|metrics queries| CH
DASH -->|key mgmt, config| BACKEND

Loading
Backend: FastAPI, SQLAlchemy, Redis (rate-limit counters), Kafka producer.
Aggregator: a standalone Kafka consumer that batches request events into
ClickHouse. Frontend: React + Chart.js + Tailwind, talking to both the
backend (auth, key management, rate-limit config) and ClickHouse-backed
analytics endpoints (dashboards, logs explorer).
Quickstart
Docker (fastest)
git clone https://github.com/Heet852003/SentryFlow.git
cd SentryFlow
docker compose up -d
From source
# Backendcd backend
python -m venv venv &&source venv/bin/activate # Windows: venv\Scripts\activate
pip install -r requirements.txt
cp .env.example .env
uvicorn main:app --reload
# Aggregator (separate terminal)cd aggregator
pip install -r requirements.txt
cp .env.example .env
python batch_consumer.py
# Frontend (separate terminal)cd frontend
npm install
npm start
Prerequisites: Python 3.9+, Node 16+, PostgreSQL, Redis, Kafka, ClickHouse
(or just use docker compose up -d, which brings up all of them).
Usage
  1. Register/log in, then create an API key from the API Keys page. It's
shown once, store it client-side.
  2. Configure per-endpoint rate limits from the Rate Limit Monitor: pick
sliding-window or token-bucket, set the limit and window.
  3. Watch traffic land in the Dashboard, drill into a specific user from
User View, or inspect raw requests in the Logs Explorer.
Repository layout
backend/ FastAPI gateway: auth, rate limiting, request logging
aggregator/ Kafka consumer that batches request logs into ClickHouse
frontend/ React dashboard
docs/ API, deployment, and rate-limiting docs
scripts/ dev/docker startup and mock-data helpers

See docs/api.md, docs/deployment.md,
and docs/rate-limiting.md for details.
Testing
cd backend
pytest
Contributing
Contributions are welcome. Fork the repo, create a feature branch, and open
a pull request. See CONTRIBUTING.md.
License
MIT. See LICENSE for details.
About
A comprehensive API monitoring and management system
Resources
Readme
MIT license
Contributing
Contributing
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Strip utm_, fbclid, gclid, etc. from all links on page
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var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',
'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',
'ref', 'ref_src', 'source', 'medium', 'campaign'];
function cleanUrl(url) {
try {
var u = new URL(url, window.location.origin);
var changed = false;
trackingParams.forEach(function(p) {
if (u.searchParams.has(p)) {
u.searchParams.delete(p);
changed = true;
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document.querySelectorAll('a[href]').forEach(function(a) {
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if (clean !== a.href) a.href = clean;
});
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observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '
GitHub - Heet852003/SentryFlow: A comprehensive API monitoring and management system · GitHub
Skip to content
BranchesTags
Repository files navigation
SentryFlow logo
SentryFlow
A self-hosted API gateway with rate limiting, request logging, and usage analytics.
BackendFrontendAnalyticsLicense
SentryFlow sits in front of your APIs as a gateway: it authenticates requests
by API key, enforces per-endpoint rate limits, and streams every request
through Kafka into ClickHouse so usage patterns, error rates, and latency
are queryable after the fact instead of only visible in scattered logs.
Features
  • API key management: issue, scope, and revoke keys per user.
  • Rate limiting: sliding-window and token-bucket algorithms, configurable
per endpoint.
  • Request logging: every request is logged with timing, status, and
caller identity for auditing and debugging.
  • Streaming analytics: request logs are published to Kafka and batch-
consumed into ClickHouse, so the dashboard queries pre-aggregated metrics
instead of scanning raw logs.
  • Dashboard: usage charts, a per-user view, a live rate-limit monitor,
and a logs explorer, all in one React app.
Architecture
flowchart LR
CLIENT[API caller] -->|API key| BACKEND
subgraph BACKEND["Backend (FastAPI)"]
AUTH[Auth middleware]
RATE[Rate limiter\nsliding window / token bucket]
LOG[Logging middleware]
end
BACKEND --> UPSTREAM[Your API]
BACKEND -->|request events| KAFKA[(Kafka)]
KAFKA --> AGG[Aggregator\nbatch consumer]
AGG --> CH[(ClickHouse)]
DASH[React Dashboard] -->|metrics queries| CH
DASH -->|key mgmt, config| BACKEND

Loading
Backend: FastAPI, SQLAlchemy, Redis (rate-limit counters), Kafka producer.
Aggregator: a standalone Kafka consumer that batches request events into
ClickHouse. Frontend: React + Chart.js + Tailwind, talking to both the
backend (auth, key management, rate-limit config) and ClickHouse-backed
analytics endpoints (dashboards, logs explorer).
Quickstart
Docker (fastest)
git clone https://github.com/Heet852003/SentryFlow.git
cd SentryFlow
docker compose up -d
From source
# Backendcd backend
python -m venv venv &&source venv/bin/activate # Windows: venv\Scripts\activate
pip install -r requirements.txt
cp .env.example .env
uvicorn main:app --reload
# Aggregator (separate terminal)cd aggregator
pip install -r requirements.txt
cp .env.example .env
python batch_consumer.py
# Frontend (separate terminal)cd frontend
npm install
npm start
Prerequisites: Python 3.9+, Node 16+, PostgreSQL, Redis, Kafka, ClickHouse
(or just use docker compose up -d, which brings up all of them).
Usage
  1. Register/log in, then create an API key from the API Keys page. It's
shown once, store it client-side.
  2. Configure per-endpoint rate limits from the Rate Limit Monitor: pick
sliding-window or token-bucket, set the limit and window.
  3. Watch traffic land in the Dashboard, drill into a specific user from
User View, or inspect raw requests in the Logs Explorer.
Repository layout
backend/ FastAPI gateway: auth, rate limiting, request logging
aggregator/ Kafka consumer that batches request logs into ClickHouse
frontend/ React dashboard
docs/ API, deployment, and rate-limiting docs
scripts/ dev/docker startup and mock-data helpers

See docs/api.md, docs/deployment.md,
and docs/rate-limiting.md for details.
Testing
cd backend
pytest
Contributing
Contributions are welcome. Fork the repo, create a feature branch, and open
a pull request. See CONTRIBUTING.md.
License
MIT. See LICENSE for details.
About
A comprehensive API monitoring and management system
Resources
Readme
MIT license
Contributing
Contributing
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Auto-enable theater mode on YouTube
(function() {
function tryTheater() {
var btn = document.querySelector('button[aria-label="Theater mode"], ytd-player #player button[title="Theater mode"]');
if (btn && !btn.classList.contains('activated')) {
btn.click();
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}
// Try immediately
tryTheater();
// Try after navigation (SPA)
var lastUrl = location.href;
setInterval(function() {
if (location.href !== lastUrl) {
lastUrl = location.href;
setTimeout(tryTheater, 500);
}
}, 1000);
// Also try on player load
var observer = new MutationObserver(tryTheater);
observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
GitHub - Heet852003/SentryFlow: A comprehensive API monitoring and management system · GitHub
Skip to content
BranchesTags
Repository files navigation
SentryFlow logo
SentryFlow
A self-hosted API gateway with rate limiting, request logging, and usage analytics.
BackendFrontendAnalyticsLicense
SentryFlow sits in front of your APIs as a gateway: it authenticates requests
by API key, enforces per-endpoint rate limits, and streams every request
through Kafka into ClickHouse so usage patterns, error rates, and latency
are queryable after the fact instead of only visible in scattered logs.
Features
  • API key management: issue, scope, and revoke keys per user.
  • Rate limiting: sliding-window and token-bucket algorithms, configurable
per endpoint.
  • Request logging: every request is logged with timing, status, and
caller identity for auditing and debugging.
  • Streaming analytics: request logs are published to Kafka and batch-
consumed into ClickHouse, so the dashboard queries pre-aggregated metrics
instead of scanning raw logs.
  • Dashboard: usage charts, a per-user view, a live rate-limit monitor,
and a logs explorer, all in one React app.
Architecture
flowchart LR
CLIENT[API caller] -->|API key| BACKEND
subgraph BACKEND["Backend (FastAPI)"]
AUTH[Auth middleware]
RATE[Rate limiter\nsliding window / token bucket]
LOG[Logging middleware]
end
BACKEND --> UPSTREAM[Your API]
BACKEND -->|request events| KAFKA[(Kafka)]
KAFKA --> AGG[Aggregator\nbatch consumer]
AGG --> CH[(ClickHouse)]
DASH[React Dashboard] -->|metrics queries| CH
DASH -->|key mgmt, config| BACKEND

Loading
Backend: FastAPI, SQLAlchemy, Redis (rate-limit counters), Kafka producer.
Aggregator: a standalone Kafka consumer that batches request events into
ClickHouse. Frontend: React + Chart.js + Tailwind, talking to both the
backend (auth, key management, rate-limit config) and ClickHouse-backed
analytics endpoints (dashboards, logs explorer).
Quickstart
Docker (fastest)
git clone https://github.com/Heet852003/SentryFlow.git
cd SentryFlow
docker compose up -d
From source
# Backendcd backend
python -m venv venv &&source venv/bin/activate # Windows: venv\Scripts\activate
pip install -r requirements.txt
cp .env.example .env
uvicorn main:app --reload
# Aggregator (separate terminal)cd aggregator
pip install -r requirements.txt
cp .env.example .env
python batch_consumer.py
# Frontend (separate terminal)cd frontend
npm install
npm start
Prerequisites: Python 3.9+, Node 16+, PostgreSQL, Redis, Kafka, ClickHouse
(or just use docker compose up -d, which brings up all of them).
Usage
  1. Register/log in, then create an API key from the API Keys page. It's
shown once, store it client-side.
  2. Configure per-endpoint rate limits from the Rate Limit Monitor: pick
sliding-window or token-bucket, set the limit and window.
  3. Watch traffic land in the Dashboard, drill into a specific user from
User View, or inspect raw requests in the Logs Explorer.
Repository layout
backend/ FastAPI gateway: auth, rate limiting, request logging
aggregator/ Kafka consumer that batches request logs into ClickHouse
frontend/ React dashboard
docs/ API, deployment, and rate-limiting docs
scripts/ dev/docker startup and mock-data helpers

See docs/api.md, docs/deployment.md,
and docs/rate-limiting.md for details.
Testing
cd backend
pytest
Contributing
Contributions are welcome. Fork the repo, create a feature branch, and open
a pull request. See CONTRIBUTING.md.
License
MIT. See LICENSE for details.
About
A comprehensive API monitoring and management system
Resources
Readme
MIT license
Contributing
Contributing
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
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})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
GitHub - Heet852003/SentryFlow: A comprehensive API monitoring and management system · GitHub
Skip to content
BranchesTags
Repository files navigation
SentryFlow logo
SentryFlow
A self-hosted API gateway with rate limiting, request logging, and usage analytics.
BackendFrontendAnalyticsLicense
SentryFlow sits in front of your APIs as a gateway: it authenticates requests
by API key, enforces per-endpoint rate limits, and streams every request
through Kafka into ClickHouse so usage patterns, error rates, and latency
are queryable after the fact instead of only visible in scattered logs.
Features
  • API key management: issue, scope, and revoke keys per user.
  • Rate limiting: sliding-window and token-bucket algorithms, configurable
per endpoint.
  • Request logging: every request is logged with timing, status, and
caller identity for auditing and debugging.
  • Streaming analytics: request logs are published to Kafka and batch-
consumed into ClickHouse, so the dashboard queries pre-aggregated metrics
instead of scanning raw logs.
  • Dashboard: usage charts, a per-user view, a live rate-limit monitor,
and a logs explorer, all in one React app.
Architecture
flowchart LR
CLIENT[API caller] -->|API key| BACKEND
subgraph BACKEND["Backend (FastAPI)"]
AUTH[Auth middleware]
RATE[Rate limiter\nsliding window / token bucket]
LOG[Logging middleware]
end
BACKEND --> UPSTREAM[Your API]
BACKEND -->|request events| KAFKA[(Kafka)]
KAFKA --> AGG[Aggregator\nbatch consumer]
AGG --> CH[(ClickHouse)]
DASH[React Dashboard] -->|metrics queries| CH
DASH -->|key mgmt, config| BACKEND

Loading
Backend: FastAPI, SQLAlchemy, Redis (rate-limit counters), Kafka producer.
Aggregator: a standalone Kafka consumer that batches request events into
ClickHouse. Frontend: React + Chart.js + Tailwind, talking to both the
backend (auth, key management, rate-limit config) and ClickHouse-backed
analytics endpoints (dashboards, logs explorer).
Quickstart
Docker (fastest)
git clone https://github.com/Heet852003/SentryFlow.git
cd SentryFlow
docker compose up -d
From source
# Backendcd backend
python -m venv venv &&source venv/bin/activate # Windows: venv\Scripts\activate
pip install -r requirements.txt
cp .env.example .env
uvicorn main:app --reload
# Aggregator (separate terminal)cd aggregator
pip install -r requirements.txt
cp .env.example .env
python batch_consumer.py
# Frontend (separate terminal)cd frontend
npm install
npm start
Prerequisites: Python 3.9+, Node 16+, PostgreSQL, Redis, Kafka, ClickHouse
(or just use docker compose up -d, which brings up all of them).
Usage
  1. Register/log in, then create an API key from the API Keys page. It's
shown once, store it client-side.
  2. Configure per-endpoint rate limits from the Rate Limit Monitor: pick
sliding-window or token-bucket, set the limit and window.
  3. Watch traffic land in the Dashboard, drill into a specific user from
User View, or inspect raw requests in the Logs Explorer.
Repository layout
backend/ FastAPI gateway: auth, rate limiting, request logging
aggregator/ Kafka consumer that batches request logs into ClickHouse
frontend/ React dashboard
docs/ API, deployment, and rate-limiting docs
scripts/ dev/docker startup and mock-data helpers

See docs/api.md, docs/deployment.md,
and docs/rate-limiting.md for details.
Testing
cd backend
pytest
Contributing
Contributions are welcome. Fork the repo, create a feature branch, and open
a pull request. See CONTRIBUTING.md.
License
MIT. See LICENSE for details.
About
A comprehensive API monitoring and management system
Resources
Readme
MIT license
Contributing
Contributing
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Universal Dark Mode - works on any site
(function() {
var enabled = true;
function applyDarkMode() {
if (!enabled) return;
// Create style element if it doesn't exist
var style = document.getElementById('universal-dark-mode-style');
if (!style) {
style = document.createElement('style');
style.id = 'universal-dark-mode-style';
document.head.appendChild(style);
}
// Dark mode CSS - inverts colors but preserves images/video
style.textContent = '
/* Invert everything except media */
html {
filter: invert(1) hue-rotate(180deg) !important;
background: #1a1a2e !important;
}
/* Restore images, videos, iframes, canvas */
img, video, iframe, canvas, svg, picture, [style*="background-image"] {
filter: invert(1) hue-rotate(180deg) !important;
}
/* Preserve specific elements that should not be inverted */
.no-dark-mode, .no-dark-mode *,
[data-theme="light"], [data-theme="light"],
.ace_editor, .ace_editor *,
.CodeMirror, .CodeMirror *,
.monaco-editor, .monaco-editor *,
.markdown-body pre, .markdown-body pre *,
.highlight, .highlight *,
pre code, pre code * {
filter: none !important;
}
/* Fix common UI elements */
.modal, .popup, .dropdown-menu, .tooltip, .popover {
filter: invert(1) hue-rotate(180deg) !important;
background: #2d2d44 !important;
border-color: #444 !important;
}
/* Scrollbars */
::-webkit-scrollbar { background: #1a1a2e !important; }
::-webkit-scrollbar-thumb { background: #444 !important; }
::-webkit-scrollbar-thumb:hover { background: #555 !important; }
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::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }
::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }
';
}
function removeDarkMode() {
var style = document.getElementById('universal-dark-mode-style');
if (style) style.remove();
}
// Toggle with Alt+Shift+D
document.addEventListener('keydown', function(e) {
if (e.altKey && e.shiftKey && e.key === 'D') {
e.preventDefault();
enabled = !enabled;
if (enabled) {
applyDarkMode();
console.log('[Universal Dark Mode] Enabled');
} else {
removeDarkMode();
console.log('[Universal Dark Mode] Disabled');
}
}
});
// Apply on load
applyDarkMode();
// Re-apply on dynamic content
var observer = new MutationObserver(function(mutations) {
if (enabled && !document.getElementById('universal-dark-mode-style')) {
applyDarkMode();
}
});
observer.observe(document.head, { childList: true });
console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');
})();
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();
GitHub - Heet852003/SentryFlow: A comprehensive API monitoring and management system · GitHub
Skip to content
BranchesTags
Repository files navigation
SentryFlow logo
SentryFlow
A self-hosted API gateway with rate limiting, request logging, and usage analytics.
BackendFrontendAnalyticsLicense
SentryFlow sits in front of your APIs as a gateway: it authenticates requests
by API key, enforces per-endpoint rate limits, and streams every request
through Kafka into ClickHouse so usage patterns, error rates, and latency
are queryable after the fact instead of only visible in scattered logs.
Features
  • API key management: issue, scope, and revoke keys per user.
  • Rate limiting: sliding-window and token-bucket algorithms, configurable
per endpoint.
  • Request logging: every request is logged with timing, status, and
caller identity for auditing and debugging.
  • Streaming analytics: request logs are published to Kafka and batch-
consumed into ClickHouse, so the dashboard queries pre-aggregated metrics
instead of scanning raw logs.
  • Dashboard: usage charts, a per-user view, a live rate-limit monitor,
and a logs explorer, all in one React app.
Architecture
flowchart LR
CLIENT[API caller] -->|API key| BACKEND
subgraph BACKEND["Backend (FastAPI)"]
AUTH[Auth middleware]
RATE[Rate limiter\nsliding window / token bucket]
LOG[Logging middleware]
end
BACKEND --> UPSTREAM[Your API]
BACKEND -->|request events| KAFKA[(Kafka)]
KAFKA --> AGG[Aggregator\nbatch consumer]
AGG --> CH[(ClickHouse)]
DASH[React Dashboard] -->|metrics queries| CH
DASH -->|key mgmt, config| BACKEND

Loading
Backend: FastAPI, SQLAlchemy, Redis (rate-limit counters), Kafka producer.
Aggregator: a standalone Kafka consumer that batches request events into
ClickHouse. Frontend: React + Chart.js + Tailwind, talking to both the
backend (auth, key management, rate-limit config) and ClickHouse-backed
analytics endpoints (dashboards, logs explorer).
Quickstart
Docker (fastest)
git clone https://github.com/Heet852003/SentryFlow.git
cd SentryFlow
docker compose up -d
From source
# Backendcd backend
python -m venv venv &&source venv/bin/activate # Windows: venv\Scripts\activate
pip install -r requirements.txt
cp .env.example .env
uvicorn main:app --reload
# Aggregator (separate terminal)cd aggregator
pip install -r requirements.txt
cp .env.example .env
python batch_consumer.py
# Frontend (separate terminal)cd frontend
npm install
npm start
Prerequisites: Python 3.9+, Node 16+, PostgreSQL, Redis, Kafka, ClickHouse
(or just use docker compose up -d, which brings up all of them).
Usage
  1. Register/log in, then create an API key from the API Keys page. It's
shown once, store it client-side.
  2. Configure per-endpoint rate limits from the Rate Limit Monitor: pick
sliding-window or token-bucket, set the limit and window.
  3. Watch traffic land in the Dashboard, drill into a specific user from
User View, or inspect raw requests in the Logs Explorer.
Repository layout
backend/ FastAPI gateway: auth, rate limiting, request logging
aggregator/ Kafka consumer that batches request logs into ClickHouse
frontend/ React dashboard
docs/ API, deployment, and rate-limiting docs
scripts/ dev/docker startup and mock-data helpers

See docs/api.md, docs/deployment.md,
and docs/rate-limiting.md for details.
Testing
cd backend
pytest
Contributing
Contributions are welcome. Fork the repo, create a feature branch, and open
a pull request. See CONTRIBUTING.md.
License
MIT. See LICENSE for details.
About
A comprehensive API monitoring and management system
Resources
Readme
MIT license
Contributing
Contributing
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages