client_python
wakaq
| client_python | wakaq | |
|---|---|---|
| 15 | 3 | |
| 3,785 | 565 | |
| 1.3% | 0.5% | |
| 7.2 | 8.7 | |
| 8 days ago | 2 months ago | |
| Python | Python | |
| Apache License 2.0 | BSD 3-clause "New" or "Revised" License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
client_python
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Show HN: Hatchet – Open-source distributed task queue
Here you go: https://stackoverflow.com/questions/75652326/celery-spawn-si...
Plus some adjacent discussion on GitHub: https://github.com/prometheus/client_python/issues/902
Hope that helps!
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How to monitor Python application performance
Prometheus, which is also a CNCF open source project, collects metrics data by scraping HTTP endpoints and then stores that data in a time series database that uses a multidimensional model. It’s a powerful tool for gathering metrics about your application and it also includes alerting functionality that you can use to notify your teams when issues come up. Prometheus includes a client library for Python.
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Kafka-Python metric reporters
We have a java one but the principle is the same. Install the Prometheus client ( https://github.com/prometheus/client_python) ,create the metrics you want, then push jmx settings to Prometheus.
- Observabilidade com Prometheus
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Setup Grafana with Prometheus for Python projects using Docker
The code above is copied from the official documentation of prometheus_client which simply creates a new metric named request_processing_seconds that measures the time spent on that particular request. We'll cover other types of metrics later in this post.
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Prometheus histogram with python
Just use the client? https://github.com/prometheus/client_python
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Monitoring Latency with Python
I've experimented with the official Prometheus python client, i really really like the way they use decorators to instrument. I've tried to measure latency with multiple types of metrics (histogram, & summary), i see the value in both of them, but the one that between fits my objective is the histogram metric type. Great!
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Best way to handle several python script plugins for a service? Create an image + container for each one? Create one for them all? Running them as microservices?
Now is a good time to expand your event loop by adding metrics collection of the event handler functions and also use that endpoint as a liveness probe. E.g. https://github.com/prometheus/client_python just add the event handled, success/error and the duration as a histogram (look for examples of tracking http requests served)
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Why is Prometheus generating duplicate data (while using python client)?
I've spent along time trying to figure out a bug that I'm facing while using Prometheus from its python client.
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Python node exporter *Help
The official Prometheus Python client library makes this easy, no need to worry about the export file format.
wakaq
- Show HN: Hatchet – Open-source distributed task queue
- Ask HN: What apps have you created for your own use?
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Building a distributed task queue in Python
https://github.com/wakatime/wakaq/blob/main/wakaq/__init__.p...
and
https://github.com/wakatime/wakaq/blob/main/wakaq/worker.py
is the meat of it. The blog post talks about the Redis data structures used, and there's not much to it beyond that.
What are some alternatives?
prometheus-fastapi-instrumentator - Instrument your FastAPI with Prometheus metrics.
rqmonitor - Flask based more dynamic and actionable frontend dashboard for monitoring Redis Queue 👩🏿💻 http://python-rq.org
django-prometheus - Export Django monitoring metrics for Prometheus.io
wakaq-ts - Background task queue for TypeScript backed by Redis, a super minimal Celery
netbox-plugin-prometheus-sd - Provide Prometheus url_sd compatible API Endpoint with data from Netbox
SSDB - SSDB - A fast NoSQL database, an alternative to Redis
pushgateway - Push acceptor for ephemeral and batch jobs.
conductor - Conductor is an event driven orchestration platform
node_exporter - Exporter for machine metrics
arq - Fast job queuing and RPC in python with asyncio and redis.
statsd_exporter - StatsD to Prometheus metrics exporter
Conveyor MQ - A fast, robust and extensible distributed task/job queue for Node.js, powered by Redis.