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Cloud-Z gathers information and perform benchmarks on cloud instances in multiple cloud providers.

Cloud-Z Cloud-Z gathers information and perform benchmarks on cloud instances in multiple cloud providers. Cloud type, instance id, and type CPU infor
Information
Category: Golang / Networking
Watchers: 0
Star: 4
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Last update: Jan 6, 2022
Resource links
https://github.com/CloudSnorkel/cloud-z

Cloud-Z

Cloud-Z gathers information and perform benchmarks on cloud instances in multiple cloud providers.

  • Cloud type, instance id, and type
  • CPU information including type, number of available cores, and cache sizes
  • RAM information
  • Benchmark CPU
  • Storage devices information
  • Benchmark storage
  • Network devices information
  • Benchmark network

Supported clouds:

  • Amazon Web Services (AWS)
  • Google Cloud Platform (GCP)
  • Microsoft Azure

Supported platforms:

  • Windows
    • x86_64
    • arm64
  • Linux
    • x86_64
    • arm64

CI

Usage

Cloud-Z is provided as a single binary that can be downloaded from the releases page.

$ ./cloud-z
+---------------+-----------------------+
| Cloud         | AWS                   |
| AMI           | ami-0712c70d31ba14f8a |
| Instance ID   | i-12345678900112344   |
| Instance type | t4g.nano              |
+---------------+-----------------------+
+-----------------+--------------------------------+
| CPU             | Intel(R) Xeon(R) CPU @ 2.20GHz |
| Vendor          | GenuineIntel                   |
| Vendor ID       | Intel                          |
| Family          |                              6 |
| MHz             |                           2200 |
| Logical cores   |                              2 |
| Physical cores  |                              1 |
| Thread per core |                              2 |
| Boost frequency |                              0 |
| L1 Cache        | 32.00KB instruction, 32.00KB   |
|                 | data                           |
| L2 Cache        | 256.00KB                       |
| L2 Cache        | 256.00KB                       |
| L3 Cache        | 55.00MB                        |
| Cache line      |                             64 |
| Features        | ADX, AESNI, AVX, AVX2, BMI1,   |
|                 | BMI2, CLMUL, CMOV, CX16,       |
|                 | ERMS, F16C, FMA3, HLE, HTT,    |
|                 | HYPERVISOR, IBPB, LZCNT, MMX,  |
|                 | MMXEXT, NX, POPCNT, RDRAND,    |
|                 | RDSEED, RDTSCP, RTM, SSE,      |
|                 | SSE2, SSE3, SSE4, SSE42,       |
|                 | SSSE3, STIBP                   |
+-----------------+--------------------------------+
+-----------------------+----------+
| Total RAM             | 1.0GB    |
| Stick #1: location    | DIMM 0   |
| Stick #1: type        | RAM DIMM |
| Stick #1: size        | 1024MB   |
| Stick #1: data width  | 64-bit   |
| Stick #1: total width | 64-bit   |
| Stick #1: speed       | 0 MHz    |
+-----------------------+----------+

Contents

    octodns Tools for managing DNS across multiple providers
    IanTayler Some benchmarks for functions with a static base function written in C concurrently wrapped in Go.
    nccgroup Multi-Cloud Security Auditing Tool
    joedicastro A comparison between some VPS providers. It uses Ansible to perform a series of automated benchmark tests over the VPS servers that you specify. It allows the reproducibility of those tests by anyone that wanted to compare these results to their own. All the tests results are available in order to provide independence and transparency.
    huseinzol05 Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations
    huseinzol05 Gathers scalable tensorflow and infrastructure deployment
    huseinzol05 Gathers machine learning and Tensorflow deep learning models for NLP problems, 1.13 < Tensorflow < 2.0
    GoogleCloudPlatform PerfKit Benchmarker (PKB) contains a set of benchmarks to measure and compare cloud offerings. The benchmarks use default settings to reflect what most users will see. PerfKit Benchmarker is licensed under the Apache 2 license terms. Please make sure to read, understand and agree to the terms of the LICENSE and CONTRIBUTING files before proceeding.
    georgian-io A cloud-agnostic ML Platform that will enable Data Scientists to run multiple experiments, perform hyper parameter optimization, evaluate results and serve models (batch/realtime) while still maintaining a uniform development UX across cloud environments
    vantage-sh The Cloud Cost Handbook is a free, open-source, community-supported set of guides meant to help explain often-times complex pricing of public cloud infrastructure and service providers in plain english.
    bisohns Rust library for performing basic cloud storage actions across major cloud providers e.g aws
    dionhaefner A suite of benchmarks to test the sequential CPU and GPU performance of most popular high-performance libraries for Python.
    djkoloski Benchmarks for rust serialization frameworks
    amscanne Tiny collection of micro benchmarks.
    haskell-perf Benchmarks for dictionary data structures: hash tables, maps, tries, etc.
    dingjiansw101 Benchmarks for Object Detection in Aerial Images
    espocrm Implementations for different SMS providers for EspoCRM. Can be used for 2-factor authentication or automatic SMS sending via Workflow and BPM tools.
    miyavsu-limited Supercharge the data of your refine app! Get data from anywhere. Customize your data provider by mixing it with different data providers/data methods.
    vv9k bin+lib rustop-rs - Linux system information parser
    idealo Workflow that shows how to train neural networks on EC2 instances with GPU support and compares training times to CPUs
    andrewchambers SFTP <-> Cloud service bridge.
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