Here is my experience installing Exporter on Proxmox and visualizing it on Grafana.
python3 -m pip install prometheus-pve-exporter
| You are a world-class Staff Engineer in React, Typescript, Next.js and Tailwind CSS. Your role is to generate complete, | |
| functional front-end code based on the user's specifications. Adhere to these guidelines: | |
| <CleanCode> | |
| Don't Repeat Yourself (DRY) | |
| Duplication of code can make code very difficult to maintain. Any change in logic can make the code prone to bugs or can | |
| make the code change difficult. This can be fixed by doing code reuse (DRY Principle). | |
| The DRY principle is stated as "Every piece of knowledge must have a single, unambiguous, authoritative representation |
| Act as a remote junior software developer named Jacob who has been tasked with gathering requirements from a client to write up a new GitHub issue for the development team to implement. Jacob is a little bit quirky and funny, and he has a lot of respect and admiration for the client. This specific client is his favorite to work with, and he wants to make sure they have a great experience while also getting all the information needed for the GitHub issue write-up. | |
| Your job is to have a very short, concise, friendly conversation with the client to elicit all the key details needed for the GitHub issue write-up. The issue write-up should allow another developer to fully understand the scope and requirements without needing any additional information. | |
| Engage in the conversation using the following phases: | |
| Phase 1: Introduction | |
| Greet the client in a friendly manner. Explain that you will be asking them a series of questions to understand their requirements for a new software feature or bug fix. Let them know |
| #!/bin/bash | |
| set +x | |
| version="${VERSION:-1.6.1}" | |
| arch="${ARCH:-linux-amd64}" | |
| bin_dir="${BIN_DIR:-/usr/local/bin}" | |
| wget "https://github.com/prometheus/node_exporter/releases/download/v$version/node_exporter-$version.$arch.tar.gz" \ | |
| -O /tmp/node_exporter.tar.gz |
| """ | |
| Structlog example configuration with FastAPI. | |
| Features: | |
| - async bound logger | |
| - contextvars to log request-id and other meta data | |
| - custom format for default logging loggers and structlog loggers | |
| """ | |
| import asyncio | |
| import logging |
| FROM debian:latest | |
| # Install basic dev packages | |
| RUN apt-get clean && apt-get update && apt-get -y install --no-install-recommends \ | |
| apt-utils \ | |
| openssh-client \ | |
| git \ | |
| gnupg2 \ | |
| dirmngr \ | |
| iproute2 \ |
| FROM balabit/syslog-ng:3.35.1 | |
| COPY syslog-ng.conf /etc/syslog-ng/syslog-ng.conf |
| version: "3" | |
| networks: | |
| loki: | |
| services: | |
| loki: | |
| image: grafana/loki:2.4.0 | |
| volumes: | |
| - ./loki:/etc/loki |
After researching a lot on how to use PyTorch with a RTX 3060 card, specially with older versions or torch (0.4.0) and torchvision (0.2.1), I noticed that it was either impossible or very hard to do. RTX 3060 and these packages apparently doesn't have compatibility with the same versions of CUDA and cuDNN. I tried to do this by using different combinations with compiled versions available in conda, but didn't work, maybe it could work if you recompile from source these versions.
After all this, actually I was able to use RTX 3060 effectively with latest versions of all these dependencies with two methods:
conda create -n rtx_3060 python=3.6.5
conda activate rtx_3060
conda install pytorch torchvision torchaudio cudatoolkit=11.1 -c pytorch -c nvidia
| input { | |
| udp { | |
| port => 10514 | |
| type => unifi_syslog | |
| } | |
| } | |
| filter { | |
| if [type] == "unifi_syslog" { | |
| grok { |