krr
django-prometheus
| krr | django-prometheus | |
|---|---|---|
| 5 | 5 | |
| 2,311 | 1,385 | |
| 13.8% | - | |
| 9.2 | 7.0 | |
| 7 days ago | 5 months 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.
krr
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What is the role of QoS for Pods?
Thanks buddy. I have seen a tool recently by robusta but not sure if helpful or not. Haven't tried it yet. https://github.com/robusta-dev/krr
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Preventing wasted resources
To calculate the optimal values you will need to have some historical metrics from a timeframe with representative load flowing through the pods. Then you can check the CPU/Memory usage metrics to see typical/max usage. There are also various tools that can help you with recommendations, but they will most likely require metrics history too, e.g. https://github.com/robusta-dev/krr
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Who is using VerticalPodAutoscaler?
VPA is ok. I thought this project, https://github.com/robusta-dev/krr, from Robusta looked promising (for sizing containers). I'd also look at continuous profiling solutions like Prodfiler or Parca.
- KRR - accurate resource recommendations based on historical Prometheus data
- Show HN: Prometheus-based resource recommendations for Kubernetes
django-prometheus
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Question: Django Graphene / GQL Monitoring via Prometheus?
We have a Django Graphene app working, and are gather Prometheus telemetry to monitor our end points. We are leveraging the Django Prometheus Middle Ware and are able to get telemetry and view it via Grafana. This all works and is awesome.
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Ask HN: What SaaS would you recommend to monitor business data of a Django app?
Thank you in advance.
[0] - https://github.com/korfuri/django-prometheus
- Best practices for setting up monitoring for a Dockerized Django app on Ubuntu 20.04?
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Monitoring Django apps
Prometheus stores data in a custom format and provides it's own metrics SDK's. Uriel Corfa has done the heavy lifting for us by writing an app which hooks into the Django middleware, ORM and cache layer and automatically exposes metrics generalized metrics. All you need to do is to install and configure django-prometheus.
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Ask HN: Prometheus vs. StatsD / Telegraf
[2] https://github.com/korfuri/django-prometheus/blob/master/doc...
What are some alternatives?
kptop - CLI tool for Kubernetes that provides pretty monitoring for Nodes, Pods, Containers, and PVCs resources on the terminal through Prometheus metrics
celery-exporter - A Prometheus exporter for Celery metrics
optscale - FinOps and MLOps platform to run ML/AI and regular cloud workloads with optimal performance and cost.
django-health-check - a pluggable app that runs a full check on the deployment, using a number of plugins to check e.g. database, queue server, celery processes, etc.
prometheus-enhanced-snmp-exporter - Enhanced prometheus SNMP exporter with multithreading support and variable SNMP pooling interval
pushgateway - Push acceptor for ephemeral and batch jobs.
prom2teams - prom2teams is an HTTP server built with Python that receives alert notifications from a previously configured Prometheus Alertmanager instance and forwards it to Microsoft Teams using defined connectors
netbox-plugin-prometheus-sd - Provide Prometheus url_sd compatible API Endpoint with data from Netbox
hitron-exporter - Hitron CGN series Prometheus exporter
client_python - Prometheus instrumentation library for Python applications
kube-state-metrics - Add-on agent to generate and expose cluster-level metrics.
blackbox_exporter - Blackbox prober exporter