flask-profiler
kube-opex-analytics
| flask-profiler | kube-opex-analytics | |
|---|---|---|
| 1 | 3 | |
| 744 | 443 | |
| - | - | |
| 0.0 | 5.8 | |
| over 1 year ago | about 1 month ago | |
| Python | Python | |
| MIT License | Apache License 2.0 |
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.
flask-profiler
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Profiling Flask application to improve performance
There are a lot of profiling tools for Python code, and most of them are built-in โ like profile or cProfile. Since Iโm speaking about Flask application, letโs see what the world has especially for it. There is a beautiful lib called flask-profiler, which has a web interface with some cool features such as route or date filters. But Flask also has a built-in in werkzeug's profiler. It looked awesomely easy in use, so it was the first โ and the last โ one I tried. To use the built-in profiler youโll need to add only two lines of code to your project:
kube-opex-analytics
- GitHub - rchakode/kube-opex-analytics: ๐จ Kubernetes Usage Analytics and Accounting for Cost Allocation and Capacity Planning - Hourly Trends, Daily and Monthly Accounting - Prometheus Exporter - Built-in & Grafana Dashboards.
- Kubernetes Opex Analytics
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Tracking the efficiency of resource requests on Kubernetes
Thanks to kube-opex-analytics, an open source Kubernetes usage analytics and accounting tool (read more about it at the end of this story), we address the problem of assessing the efficiency of resource requests set on Kubernetes workloads. The release v22.02.0 introduces a new indicator called ๐๐ฌ๐๐ ๐/๐๐๐ช๐ฎ๐๐ฌ๐ญ ๐๐๐๐ข๐๐ข๐๐ง๐๐ฒ. Conceptually, this indicator is defined as the ratio between the actual usage and the resource requests. The indicator is provided by namespace and, as all other kube-opex-analytics indicators, it's computed based on hourly-consolidated Kubernetes metrics.
What are some alternatives?
scalene - Scalene: a high-performance, high-precision CPU, GPU, and memory profiler for Python with AI-powered optimization proposals
prometheus-nftables-exporter - Prometheus Exporter for Linux Nftables Firewall Stats
Shynet - Modern, privacy-friendly, and detailed web analytics that works without cookies or JS.
Redash - Make Your Company Data Driven. Connect to any data source, easily visualize, dashboard and share your data.
gprof2dot - Converts profiling output to a dot graph.
prometheus-switchbot-exporter - A Prometheus exporter for SwitchBot Meter devices.
django-leaflet-admin-list - The Django Leaflet Admin List package provides an admin list view featured by the map and bounding box filter for the geo-based data of the GeoDjango.
Centreon - Centreon is a network, system and application monitoring tool. Centreon is the only AIOps Platform Providing Holistic Visibility to Complex IT Workflows from Cloud to Edge.
rqmonitor - Flask based more dynamic and actionable frontend dashboard for monitoring Redis Queue ๐ฉ๐ฟโ๐ป http://python-rq.org
Apache Superset - Apache Superset is a Data Visualization and Data Exploration Platform [Moved to: https://github.com/apache/superset]