Exporter for Storage Area Network (SAN)

Related tags

Deep Learningsan_exporter
Overview

SAN Exporter

license CI Docker Pulls Code size

Prometheus exporter for Storage Area Network (SAN).

We all know that each SAN Storage vendor has their own glossary of terms, health/performance metrics and monitoring tool.

But from operator view,

  • We normally focus on some main metrics which are similar on different storage platform.
  • We are not only monitoring SAN storage but also other devices and services at multi-layer (application, virtual Machine, hypervisor, operating system and physical).

That's why we build this to have an unified monitoring/alerting solution with Prometheus and Alermanager.

Architecture overview

SAN exporter architecture

Features

There are some main features you might want to know, for others, please see example configuration.

  • Enable/disable optinal metrics for each backend
  • Enable/disable backend
  • Backend will automatically stop collecting data from SAN system after timeout seconds from last request of client. With this feature, we can deploy two instances as Active/Passive mode for high availability.

Note: Backend may not respond metrics in the first interval while collecting, calculating and caching metrics.

Quick start

  • Start a dummy driver with Docker
$ git clone [email protected]:vCloud-DFTBA/san_exporter.git
$ cd san_exporter/
$ cp examples/dummy_config.yml config.yml
# docker run --rm -p 8888:8888 -v $(pwd)/config.yml:/san-exporter/config.yml --name san-exporter daikk115/san-exporter:0.1.0

See the result at http://localhost:8888/dummy_backend

  • Start a dummy driver manually
$ git clone [email protected]:vCloud-DFTBA/san_exporter.git
$ cd san_exporter/
$ cp examples/dummy_config.yml config.yml
$ sudo apt-get install libxml2-dev libxslt1-dev python3.7-dev
$ pip3 install -r requirements.txt
$ python3.7 manage.py

See the result at http://localhost:8888/dummy_backend

Deployment

Create configuration file

# mkdir /root/san-exporter
# cp /path/to/san_exporter/examples/config.yml.sample /root/san-exporter/config.yml

Update /root/san-exporter/config.yml for corresponding to SAN storage

Run new container

# docker volume create san-exporter
# docker run -d -p 8888:8888 -v san-exporter:/var/log/ -v /root/san-exporter/config.yml:/san-exporter/config.yml --name san-exporter daikk115/san-exporter:latest

Supported Drivers

  • Matrix of driver's generic metrics
Capacity all Capacity pool IOPS/Throuhgput pool Latency pool IOPS/Throughput node Latency node CPU node RAM node IOPS/Throughput LUN Latency LUN IOPS/Throughput disk Latency disk IOPS/Throughput port Latency port Alert
HPMSA X X X X X X X X
DellUnity X X X X X X X X X X
HitachiG700 X X X
HPE3Par X X X X X X X X
NetApp X X X X X X
SC8000 X X X X X X X X X X X
V7k X X X X X X
  • Connection port requirements
    • For some SAN system, we collect metrics over SP API but some others, we collect metrics dirrectly from controller API.
    • In some special cases, we collect alerts over SSH.
SAN System Service Processor Connection Port
HPMSA NO 443
Dell Unity NO 443
Hitachi G700 YES 23451
IBM V7000 NO #TODO
IBM V5000 NO #TODO
HPE 3PAR YES #TODO
NetApp ONTAP NO 443
SC8000 NO 3033

Metrics

All metrics are prefixed with "san_" and has at least 2 labels: backend_name and san_ip

Info metrics:

Metrics name Type Help
san_storage_info gauge Basic information: serial, version, ...

Controller metrics:

Metrics name Type Help
san_totalNodes gauge Total nodes
san_masterNodes gauge Master nodes
san_onlineNodes gauge Online nodes
san_compress_support gauge Compress support, 1 = Yes, 0 = No
san_thin_provision_support gauge Thin provision support, 1 = Yes, 0 = No
san_system_reporter_support gauge System reporter support, 1 = Yes, 0 = No
san_qos_support gauge QoS support, 1 = Yes, 0 = No
san_totalCapacityMiB gauge Total system capacity in MiB
san_allocatedCapacityMiB gauge Total allocated capacity in MiB
san_freeCapacityMiB gauge Total free capacity in MiB
san_cpu_system_utilization gauge The average percentage of time that the processors on nodes are busy doing system I/O tasks
san_cpu_compression_utilization gauge The approximate percentage of time that the processor core was busy with data compression tasks
san_cpu_total gauge The cpus spent in each mode

Pool metrics:

Metrics name Type Help
san_pool_totalLUNs gauge Total LUNs (or Volumes)
san_pool_total_capacity_mib gauge Total capacity of pool in MiB
san_pool_free_capacity_mib gauge Free of pool in MiB
san_pool_provisioned_capacity_mib gauge Provisioned of pool in MiB
san_pool_number_read_io gauge Read I/O Rate - ops/s
san_pool_number_write_io gauge Write I/O Rate - ops/s
san_pool_read_cache_hit gauge Read Cache Hits - %
san_pool_write_cache_hit gauge Write Cache Hits - %
san_pool_read_kb gauge gauge Read Data Rate - KiB/s
san_pool_write_kb gauge Write Data Rate - KiB/s
san_pool_read_service_time_ms gauge Read Response Time - ms/op
san_pool_write_service_time_ms gauge Write Response Time - ms/op
san_pool_read_IOSize_kb gauge Read Transfer Size - KiB/op
san_pool_write_IOSize_kb gauge Write Transfer Size - KiB/op
san_pool_queue_length gauge Queue length of pool

Port metrics:

Metrics name Type Help
san_port_number_read_io gauge Port Read I/O Rate - ops/s
san_port_number_write_io gauge Port Write I/O Rate - ops/s
san_port_write_kb gauge Port Write Data Rate - KiB/s
san_port_read_kb gauge Port Read Data Rate - KiB/s
san_port_write_IOSize_kb gauge Port Write Transfer Size - KiB/op
san_port_read_IOSize_kb gauge Port Read Transfer Size - KiB/op
san_port_queue_length gauge Queue length of port

For more information about specific metrics of SANs, see Specific SAN Metrics

Integrate with Prometheus, Alertmanager and Grafana

Some grafana images:

SAN exporter dashboard overview

SAN exporter dashboard pool

SAN exporter dashboard port

You might also like...
Web mining module for Python, with tools for scraping, natural language processing, machine learning, network analysis and visualization.
Web mining module for Python, with tools for scraping, natural language processing, machine learning, network analysis and visualization.

Pattern Pattern is a web mining module for Python. It has tools for: Data Mining: web services (Google, Twitter, Wikipedia), web crawler, HTML DOM par

Computational Linguistics Research Group 8.4k Jan 3, 2023
Neurolab is a simple and powerful Neural Network Library for Python

Neurolab Neurolab is a simple and powerful Neural Network Library for Python. Contains based neural networks, train algorithms and flexible framework

null 152 Dec 6, 2022
A scikit-learn compatible neural network library that wraps PyTorch

A scikit-learn compatible neural network library that wraps PyTorch. Resources Documentation Source Code Examples To see more elaborate examples, look

null 4.9k Dec 31, 2022
Visualizer for neural network, deep learning, and machine learning models
Visualizer for neural network, deep learning, and machine learning models

Netron is a viewer for neural network, deep learning and machine learning models. Netron supports ONNX (.onnx, .pb, .pbtxt), Keras (.h5, .keras), Tens

Lutz Roeder 21k Jan 6, 2023
Graph neural network message passing reframed as a Transformer with local attention

Adjacent Attention Network An implementation of a simple transformer that is equivalent to graph neural network where the message passing is done with

Phil Wang 49 Dec 28, 2022
data/code repository of "C2F-FWN: Coarse-to-Fine Flow Warping Network for Spatial-Temporal Consistent Motion Transfer"

C2F-FWN data/code repository of "C2F-FWN: Coarse-to-Fine Flow Warping Network for Spatial-Temporal Consistent Motion Transfer" (https://arxiv.org/abs/

EKILI 46 Dec 14, 2022
Simple command line tool for text to image generation using OpenAI's CLIP and Siren (Implicit neural representation network)
Simple command line tool for text to image generation using OpenAI's CLIP and Siren (Implicit neural representation network)

Deep Daze mist over green hills shattered plates on the grass cosmic love and attention a time traveler in the crowd life during the plague meditative

Phil Wang 4.4k Jan 3, 2023
End-to-End Object Detection with Fully Convolutional Network
End-to-End Object Detection with Fully Convolutional Network

This project provides an implementation for "End-to-End Object Detection with Fully Convolutional Network" on PyTorch.

null 472 Dec 22, 2022
TensorFlow-based neural network library
TensorFlow-based neural network library

Sonnet Documentation | Examples Sonnet is a library built on top of TensorFlow 2 designed to provide simple, composable abstractions for machine learn

DeepMind 9.5k Jan 7, 2023
Comments
  • Support purestorage please!

    Support purestorage please!

    Is your feature request related to a problem? Please describe. A clear and concise description of what the problem is. Ex. I'm always frustrated when [...]

    Describe the solution you'd like A clear and concise description of what you want to happen.

    Describe alternatives you've considered A clear and concise description of any alternative solutions or features you've considered.

    Additional context Add any other context or screenshots about the feature request here. Can you support purestorage?

    opened by wanbeepeto 0
Releases(v0.8.0)

  • v0.8.0(Aug 17, 2021)

    • Release notes:
      • Add Dell Unnity driver
      • Add Hitachi G700 driver
      • Add HPE 3PAR driver
      • Add HPMSA driver
      • Add NetApp ONTAP driver
      • Add Dell SC800 driver
      • Add IBM V7000 driver
    • Docker image: daikk115/san-exporter:0.8.0
    Source code(tar.gz)
    Source code(zip)

  • v0.1.0(Aug 15, 2021)

Owner
vCloud
Not Only vCloud - Don’t Forget To Be Awesome
vCloud
GitHub Repository
An unofficial personal implementation of UM-Adapt, specifically to tackle joint estimation of panoptic segmentation and depth prediction for autonomous driving datasets.

Semisupervised Multitask Learning This repository is an unofficial and slightly modified implementation of UM-Adapt[1] using PyTorch. This code primar

Abhinav Atrishi 11 Nov 25, 2022
StarGANv2-VC: A Diverse, Unsupervised, Non-parallel Framework for Natural-Sounding Voice Conversion

StarGANv2-VC: A Diverse, Unsupervised, Non-parallel Framework for Natural-Sounding Voice Conversion Yinghao Aaron Li, Ali Zare, Nima Mesgarani We pres

Aaron (Yinghao) Li 282 Jan 01, 2023
"Projelerle Yapay Zeka Ve Bilgisayarlı Görü" Kitabımın projeleri

"Projelerle Yapay Zeka Ve Bilgisayarlı Görü" Kitabımın projeleri Bu Github Reposundaki tüm projeler; kaleme almış olduğum "Projelerle Yapay Zekâ ve Bi

Ümit Aksoylu 4 Aug 03, 2022
U-Net: Convolutional Networks for Biomedical Image Segmentation

Deep Learning Tutorial for Kaggle Ultrasound Nerve Segmentation competition, using Keras This tutorial shows how to use Keras library to build deep ne

Yihui He 401 Nov 21, 2022
Repository for MDPGT

MD-PGT Repository for implementing and reproducing the results for the paper MDPGT: Momentum-based Decentralized Policy Gradient Tracking. Available E

Xian Yeow Lee 2 Dec 30, 2021
Implementation for Homogeneous Unbalanced Regularized Optimal Transport

HUROT: An Homogeneous formulation of Unbalanced Regularized Optimal Transport. This repository provides code related to this preprint. This is an alph

Théo Lacombe 1 Feb 17, 2022
NLG evaluation via Statistical Measures of Similarity: BaryScore, DepthScore, InfoLM

NLG evaluation via Statistical Measures of Similarity: BaryScore, DepthScore, InfoLM Automatic Evaluation Metric described in the papers BaryScore (EM

Pierre Colombo 28 Dec 28, 2022
Rethinking Transformer-based Set Prediction for Object Detection

Rethinking Transformer-based Set Prediction for Object Detection Here are the code for the ICCV paper. The code is adapted from Detectron2 and AdelaiD

Zhiqing Sun 62 Dec 03, 2022
Download from Onlyfans.com.

OnlySave: Onlyfans downloader Getting Started: Download the setup executable from the latest release. Install and run. Only works on Windows currently

4 May 30, 2022
GDR-Net: Geometry-Guided Direct Regression Network for Monocular 6D Object Pose Estimation. (CVPR 2021)

GDR-Net This repo provides the PyTorch implementation of the work: Gu Wang, Fabian Manhardt, Federico Tombari, Xiangyang Ji. GDR-Net: Geometry-Guided

169 Jan 07, 2023
Real-time analysis of intracranial neurophysiology recordings.

py_neuromodulation Click this button to run the "Tutorial ML with py_neuro" notebooks: The py_neuromodulation toolbox allows for real time capable pro

Interventional Cognitive Neuromodulation - Neumann Lab Berlin 15 Nov 03, 2022
A repository built on the Flow software package to explore cyber-security attacks on intelligent transportation systems.

A repository built on the Flow software package to explore cyber-security attacks on intelligent transportation systems.

George Gunter 4 Nov 14, 2022
Data Engineering ZoomCamp

Data Engineering ZoomCamp I'm partaking in a Data Engineering Bootcamp / Zoomcamp and will be tracking my progress here. I can't promise these notes w

Aaron 61 Jan 06, 2023
A collection of Jupyter notebooks to play with NVIDIA's StyleGAN3 and OpenAI's CLIP for a text-based guided image generation.

StyleGAN3 CLIP-based guidance StyleGAN3 + CLIP StyleGAN3 + inversion + CLIP This repo is a collection of Jupyter notebooks made to easily play with St

Eugenio Herrera 176 Dec 30, 2022
Official PyTorch implementation of "Synthesis of Screentone Patterns of Manga Characters"

Manga Character Screentone Synthesis Official PyTorch implementation of "Synthesis of Screentone Patterns of Manga Characters" presented in IEEE ISM 2

Tsubota 2 Nov 20, 2021
A PyTorch implementation of the architecture of Mask RCNN

EDIT (AS OF 4th NOVEMBER 2019): This implementation has multiple errors and as of the date 4th, November 2019 is insufficient to be utilized as a reso

Sai Himal Allu 975 Dec 30, 2022
Data and code for the paper "Importance of Kernel Bandwidth in Quantum Machine Learning"

Reproducibility materials for "Importance of Kernel Bandwidth in Quantum Machine Learning" Repo structure: code contains Python scripts used to genera

Ruslan Shaydulin 3 Oct 23, 2022
[CVPR 2021] Semi-Supervised Semantic Segmentation with Cross Pseudo Supervision

TorchSemiSeg [CVPR 2021] Semi-Supervised Semantic Segmentation with Cross Pseudo Supervision by Xiaokang Chen1, Yuhui Yuan2, Gang Zeng1, Jingdong Wang

Chen XiaoKang 387 Jan 08, 2023
An atmospheric growth and evolution model based on the EVo degassing model and FastChem 2.0

EVolve Linking planetary mantles to atmospheric chemistry through volcanism using EVo and FastChem. Overview EVolve is a linked mantle degassing and a

Pip Liggins 2 Jan 17, 2022
The official code repo of "HTS-AT: A Hierarchical Token-Semantic Audio Transformer for Sound Classification and Detection"

Hierarchical Token Semantic Audio Transformer Introduction The Code Repository for "HTS-AT: A Hierarchical Token-Semantic Audio Transformer for Sound

Knut(Ke) Chen 134 Jan 01, 2023