{
    "info": {
        "author": "NAGY, Attila",
        "author_email": "nagy.attila@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "License :: OSI Approved :: MIT License",
            "Operating System :: OS Independent",
            "Programming Language :: Python"
        ],
        "description": "# cloudperf\n## Measuring the relative performance of cloud resources\n\nCloudperf is a python helper for running benchmarks on cloud providers'\ninfrastructure (currently Amazon AWS/EC2 is supported) and getting/comparing\nthe results along with their price.\n\nFeatures include:\n* fetch and upload EC2 instance prices (both on-demand and spot) from/to S3\n* run defined benchmarks on all EC2 node types in docker images\n** ability to run more sophisticated benchmark setups (on one node), like launching a multi-instance distributed DB server and a benchmark client\n** any docker image can be used for the benchmarks, the only requirement is to be able to produce a benchmark score\n* CLI for updating/getting the gathered data\n\n## Getting started\n\nYou can install the application with a simple `pip install cloudperf`.\nThen you'll have the `cloudperf` executable, which is the main entry point to the\napplication.\n\n### Cloudperf data\n\nCloudperf works with tabular data, stored in S3 (world readable published) in\ncompressed JSON files.\nThe three files are:\n1. Prices: https://cloudperf-data.s3-us-west-2.amazonaws.com/prices.json.gz\n1. Performance: https://cloudperf-data.s3-us-west-2.amazonaws.com/performance.json.gz\n1. Combined: https://cloudperf-data.s3-us-west-2.amazonaws.com/combined.json.gz\n\nPrices are constantly updated for many reasons:\n1. new instance types come and old ones go\n1. the prices can change\n1. the spot prices change dynamically, very similarly to a stock exchange\n\nThe Performance data is updated in a much less frequent manner.\nThe Combined file is updated approximately daily and it's mainly for embedded\nweb, not for general use.\n\n### Using the CLI\n\nThe CLI has two modes of operation:\n1. get/show mode\n1. update mode\n\nThe first is when you use the already compiled data, which contains the current\nprices and benchmark results.\nThe second can be used to update either the price list or (re)run the benchmarks\nand store the data. You can use this internally as well to run your own benchmarks.\n\nThe get mode has some common arguments:\n* `--cols` for the columns you want to see. There are many columns in the data tables,\nmany of them are hidden by default, to make the output easier to read.\n* `--sort` the column(s) to sort on\n* `--filter` you can filter on the given column's data. You can use basic operators,\nlike `>`, `<`, `>=`, `<=` and `=`\n\n#### Getting the prices\n\nIf you execute `cloudperf prices`, it will fetch actual pricing data from S3 and\nshow it to you, like:\n```\n$ cloudperf prices\ninstanceType          region          spot-az  vcpu    memory     price\n      t3.nano      eu-north-1      eu-north-1c     2     0.500   0.00160\n      t3.nano       us-east-2       us-east-2c     2     0.500   0.00160\n      t3.nano       us-east-1       us-east-1a     2     0.500   0.00160\n      t3.nano       us-east-1       us-east-1f     2     0.500   0.00160\n      t3.nano       us-east-1       us-east-1d     2     0.500   0.00160\n      t3.nano       us-east-1       us-east-1c     2     0.500   0.00160\n      t3.nano       us-east-1       us-east-1b     2     0.500   0.00160\n      t3.nano      eu-north-1      eu-north-1a     2     0.500   0.00160\n      t3.nano       us-west-2       us-west-2a     2     0.500   0.00160\n      t3.nano       us-east-2       us-east-2b     2     0.500   0.00160\n      t3.nano      eu-north-1      eu-north-1b     2     0.500   0.00160\n      t3.nano       us-east-2       us-east-2a     2     0.500   0.00160\n      t3.nano       eu-west-1       eu-west-1a     2     0.500   0.00170\n      t3.nano       eu-west-1       eu-west-1c     2     0.500   0.00170\n      t3.nano    ca-central-1    ca-central-1b     2     0.500   0.00170\n      t3.nano      ap-south-1      ap-south-1b     2     0.500   0.00170\n      t3.nano      ap-south-1      ap-south-1a     2     0.500   0.00170\n      t3.nano       us-west-2       us-west-2c     2     0.500   0.00170\n      t3.nano    ca-central-1    ca-central-1a     2     0.500   0.00170\n      t3.nano       eu-west-1       eu-west-1b     2     0.500   0.00170\n      t3.nano       eu-west-2       eu-west-2b     2     0.500   0.00180\n      t3.nano    eu-central-1    eu-central-1c     2     0.500   0.00180\n      t3.nano       us-west-2       us-west-2b     2     0.500   0.00180\n      t3.nano       eu-west-2       eu-west-2a     2     0.500   0.00180\n      t3.nano       eu-west-2       eu-west-2c     2     0.500   0.00180\n      t3.nano    eu-central-1    eu-central-1a     2     0.500   0.00180\n      t3.nano    eu-central-1    eu-central-1b     2     0.500   0.00180\n      t3.nano       us-west-1       us-west-1b     2     0.500   0.00190\n      t3.nano       us-west-1       us-west-1a     2     0.500   0.00190\n      t3.nano  ap-northeast-1  ap-northeast-1a     2     0.500   0.00200\n     t1.micro       eu-west-1       eu-west-1b     1     0.613   0.00200\n      t3.nano  ap-southeast-2  ap-southeast-2b     2     0.500   0.00200\n      t3.nano  ap-southeast-2  ap-southeast-2c     2     0.500   0.00200\n      t3.nano  ap-southeast-2  ap-southeast-2a     2     0.500   0.00200\n      t3.nano  ap-southeast-1  ap-southeast-1c     2     0.500   0.00200\n     t1.micro       us-east-1       us-east-1b     1     0.613   0.00200\n     t1.micro       us-east-1       us-east-1c     1     0.613   0.00200\n```\n\nYou can filter for any columns, like for a given region:\n```\n$ cloudperf prices --filter region=us-west-2 | head -10\ninstanceType     region     spot-az  vcpu    memory    price\n      t3.nano  us-west-2  us-west-2a     2     0.500   0.0016\n      t3.nano  us-west-2  us-west-2c     2     0.500   0.0017\n      t3.nano  us-west-2  us-west-2b     2     0.500   0.0018\n     t1.micro  us-west-2  us-west-2a     1     0.613   0.0020\n     t1.micro  us-west-2  us-west-2b     1     0.613   0.0020\n     t1.micro  us-west-2  us-west-2c     1     0.613   0.0020\n     t3.micro  us-west-2  us-west-2c     2     1.000   0.0031\n     t3.micro  us-west-2  us-west-2a     2     1.000   0.0031\n     t3.micro  us-west-2  us-west-2b     2     1.000   0.0031\n```\n\nYou can have multiple filters:\n```\n$ cloudperf prices --filter 'vcpu>=128' --filter region=us-west-2\ninstanceType     region     spot-az  vcpu  memory    price\n x1.32xlarge  us-west-2  us-west-2c   128  1952.0   4.0014\n x1.32xlarge  us-west-2  us-west-2b   128  1952.0   4.0014\n x1.32xlarge  us-west-2        None   128  1952.0  13.3380\n x1.32xlarge  us-west-2  us-west-2a   128  1952.0  13.3380\nx1e.32xlarge  us-west-2        None   128  3904.0  26.6880\nx1e.32xlarge  us-west-2  us-west-2b   128  3904.0  26.6880\nx1e.32xlarge  us-west-2  us-west-2a   128  3904.0  26.6880\n```\n\nThe spot-az column contains the Availability Zone (AZ) and the last known spot\nprice if available. spot-az None marks the on-demand price for the instance in\nthat region.\n\n#### Getting the benchmark results\nYou can issue `cloudperf performance --no-combined` to get the latest benchmark\nresults. This will include all the benchmarks for the benchmarked instances and\ntheir latest score.\nBy default, this will only show the benchmark results with the vCPU-numbered\nconcurrency (meaning the benchmark program ran with vCPU parallelism).\nIf you want to see benchmark results for each number of vCPUs, you can use for\nexample:\n```\n$ cloudperf performance --no-combined --no-maxcpu --filter instanceType=m5.24xlarge --filter benchmark_id=stress-ng:crc16\ninstanceType     benchmark_id  benchmark_cpus  benchmark_score\nm5.24xlarge  stress-ng:crc16               1         153.4700\nm5.24xlarge  stress-ng:crc16               2         305.4200\nm5.24xlarge  stress-ng:crc16               3         457.2700\nm5.24xlarge  stress-ng:crc16               4         607.5400\nm5.24xlarge  stress-ng:crc16               5         750.4900\nm5.24xlarge  stress-ng:crc16               6         897.9900\nm5.24xlarge  stress-ng:crc16               7        1042.1200\nm5.24xlarge  stress-ng:crc16               8        1186.4000\nm5.24xlarge  stress-ng:crc16               9        1333.7000\nm5.24xlarge  stress-ng:crc16              10        1480.6400\nm5.24xlarge  stress-ng:crc16              11        1624.5700\nm5.24xlarge  stress-ng:crc16              12        1773.9300\nm5.24xlarge  stress-ng:crc16              13        1921.5400\nm5.24xlarge  stress-ng:crc16              14        2066.2900\nm5.24xlarge  stress-ng:crc16              15        2213.0600\nm5.24xlarge  stress-ng:crc16              16        2359.9000\nm5.24xlarge  stress-ng:crc16              17        2507.6800\nm5.24xlarge  stress-ng:crc16              18        2653.8500\nm5.24xlarge  stress-ng:crc16              19        2800.1600\nm5.24xlarge  stress-ng:crc16              20        2945.6200\nm5.24xlarge  stress-ng:crc16              21        3092.3500\nm5.24xlarge  stress-ng:crc16              22        3238.4400\nm5.24xlarge  stress-ng:crc16              23        3383.5900\nm5.24xlarge  stress-ng:crc16              24        3528.6500\nm5.24xlarge  stress-ng:crc16              25        3673.7700\nm5.24xlarge  stress-ng:crc16              26        3821.0200\nm5.24xlarge  stress-ng:crc16              27        3963.2900\nm5.24xlarge  stress-ng:crc16              28        4109.5900\nm5.24xlarge  stress-ng:crc16              29        4253.9200\nm5.24xlarge  stress-ng:crc16              30        4400.6100\nm5.24xlarge  stress-ng:crc16              31        4543.7900\nm5.24xlarge  stress-ng:crc16              32        4690.0000\nm5.24xlarge  stress-ng:crc16              33        4826.8500\nm5.24xlarge  stress-ng:crc16              34        4938.4700\nm5.24xlarge  stress-ng:crc16              35        5114.5600\nm5.24xlarge  stress-ng:crc16              36        5256.2100\nm5.24xlarge  stress-ng:crc16              37        5391.5700\nm5.24xlarge  stress-ng:crc16              38        5532.8000\nm5.24xlarge  stress-ng:crc16              39        5641.4900\nm5.24xlarge  stress-ng:crc16              40        5797.2500\nm5.24xlarge  stress-ng:crc16              41        5941.1000\nm5.24xlarge  stress-ng:crc16              42        6072.0700\nm5.24xlarge  stress-ng:crc16              45        6207.2000\nm5.24xlarge  stress-ng:crc16              43        6208.1700\nm5.24xlarge  stress-ng:crc16              44        6333.4600\nm5.24xlarge  stress-ng:crc16              46        6508.2700\nm5.24xlarge  stress-ng:crc16              47        6709.0500\nm5.24xlarge  stress-ng:crc16              48        6869.4300\nm5.24xlarge  stress-ng:crc16              50        6973.1700\nm5.24xlarge  stress-ng:crc16              49        6973.2600\nm5.24xlarge  stress-ng:crc16              51        7127.6400\nm5.24xlarge  stress-ng:crc16              52        7327.4600\nm5.24xlarge  stress-ng:crc16              53        7444.9100\nm5.24xlarge  stress-ng:crc16              54        7546.5700\nm5.24xlarge  stress-ng:crc16              55        7658.1300\nm5.24xlarge  stress-ng:crc16              56        7708.0800\nm5.24xlarge  stress-ng:crc16              57        7885.0400\nm5.24xlarge  stress-ng:crc16              58        7994.7500\nm5.24xlarge  stress-ng:crc16              59        8099.9600\nm5.24xlarge  stress-ng:crc16              60        8211.5600\nm5.24xlarge  stress-ng:crc16              61        8314.0200\nm5.24xlarge  stress-ng:crc16              62        8434.1600\nm5.24xlarge  stress-ng:crc16              63        8543.7900\nm5.24xlarge  stress-ng:crc16              64        8650.0700\nm5.24xlarge  stress-ng:crc16              65        8751.9500\nm5.24xlarge  stress-ng:crc16              66        8861.1900\nm5.24xlarge  stress-ng:crc16              67        8974.5600\nm5.24xlarge  stress-ng:crc16              68        9083.7900\nm5.24xlarge  stress-ng:crc16              69        9194.9700\nm5.24xlarge  stress-ng:crc16              70        9305.0300\nm5.24xlarge  stress-ng:crc16              71        9408.9300\nm5.24xlarge  stress-ng:crc16              72        9504.9400\nm5.24xlarge  stress-ng:crc16              73        9630.7000\nm5.24xlarge  stress-ng:crc16              74        9739.4700\nm5.24xlarge  stress-ng:crc16              75        9849.7800\nm5.24xlarge  stress-ng:crc16              76        9955.6900\nm5.24xlarge  stress-ng:crc16              77       10067.6800\nm5.24xlarge  stress-ng:crc16              78       10163.1200\nm5.24xlarge  stress-ng:crc16              79       10284.8700\nm5.24xlarge  stress-ng:crc16              80       10392.3300\nm5.24xlarge  stress-ng:crc16              81       10489.5500\nm5.24xlarge  stress-ng:crc16              82       10609.9500\nm5.24xlarge  stress-ng:crc16              83       10660.9400\nm5.24xlarge  stress-ng:crc16              84       10819.9800\nm5.24xlarge  stress-ng:crc16              85       10931.2500\nm5.24xlarge  stress-ng:crc16              86       11042.3300\nm5.24xlarge  stress-ng:crc16              87       11142.7500\nm5.24xlarge  stress-ng:crc16              88       11259.1200\nm5.24xlarge  stress-ng:crc16              89       11366.6500\nm5.24xlarge  stress-ng:crc16              90       11432.5700\nm5.24xlarge  stress-ng:crc16              91       11569.4600\nm5.24xlarge  stress-ng:crc16              92       11680.7600\nm5.24xlarge  stress-ng:crc16              93       11787.9300\nm5.24xlarge  stress-ng:crc16              94       11902.5500\nm5.24xlarge  stress-ng:crc16              95       11995.5200\nm5.24xlarge  stress-ng:crc16              96       12102.4500\n```\nHere you can see how scalable is that instance (mainly the hypervisor/CPU and of\ncourse the OS).\n\n#### Getting performance/price results\n\nThe main reason for this program to exist is to conduct a performance/price ratio\nfor the benchmarked instances in order to know which instances should we use for\nexecuting large batch jobs.\n\nYou can list the instances' relative performance/price results with a command\nsimilar to this:\n\n```\n$ cloudperf performance  --filter benchmark_id=stress-ng:crc16 --filter region=us-west-2\ninstanceType     benchmark_id  benchmark_cpus  perf/price   price  benchmark_score     region     spot-az\n[...]\n  t2.2xlarge  stress-ng:crc16               8   8765.0808  0.1114         976.4300  us-west-2  us-west-2b\n  t2.2xlarge  stress-ng:crc16               8   8765.0808  0.1114         976.4300  us-west-2  us-west-2a\n   t2.xlarge  stress-ng:crc16               4   8862.2980  0.0557         493.6300  us-west-2  us-west-2a\n   t2.xlarge  stress-ng:crc16               4   8862.2980  0.0557         493.6300  us-west-2  us-west-2b\n   t2.xlarge  stress-ng:crc16               4   8862.2980  0.0557         493.6300  us-west-2  us-west-2c\n   t3.xlarge  stress-ng:crc16               4   9067.4651  0.0501         454.2800  us-west-2  us-west-2b\n  c4.8xlarge  stress-ng:crc16              36   9370.8534  0.4992        4677.9300  us-west-2  us-west-2c\n  c4.8xlarge  stress-ng:crc16              36   9529.2931  0.4909        4677.9300  us-west-2  us-west-2b\n  c4.8xlarge  stress-ng:crc16              36   9535.1203  0.4906        4677.9300  us-west-2  us-west-2a\n  t3.2xlarge  stress-ng:crc16               8   9742.1769  0.1029        1002.4700  us-west-2  us-west-2a\n  t3.2xlarge  stress-ng:crc16               8  10004.6906  0.1002        1002.4700  us-west-2  us-west-2b\n    t3.small  stress-ng:crc16               2  12400.0000  0.0209         259.1600  us-west-2  us-west-2d\n    t3.small  stress-ng:crc16               2  12459.6154  0.0208         259.1600  us-west-2        None\n   t2.medium  stress-ng:crc16               2  17940.2878  0.0139         249.3700  us-west-2  us-west-2c\n   t2.medium  stress-ng:crc16               2  17940.2878  0.0139         249.3700  us-west-2  us-west-2b\n   t2.medium  stress-ng:crc16               2  17940.2878  0.0139         249.3700  us-west-2  us-west-2a\n    t3.small  stress-ng:crc16               2  41136.5079  0.0063         259.1600  us-west-2  us-west-2a\n    t3.small  stress-ng:crc16               2  41136.5079  0.0063         259.1600  us-west-2  us-west-2b\n    t3.small  stress-ng:crc16               2  41136.5079  0.0063         259.1600  us-west-2  us-west-2c\n```\n\nHere you can see if nothing more is important to you than to get decent performance\nfor your money, t3.small would be the best.\n_WARNING! The benchmarks are executed with unlimited CPU credits (where applicable),\nbut this is not reflected in the prices!_\n\nExcluding burstable instances from the list gives:\n```\nc5d.18xlarge  stress-ng:crc16              72  14177.0380  0.7029        9965.0400       us-east-2       us-east-2b\n c5.18xlarge  stress-ng:crc16              72  14339.3896  0.6946        9960.1400       us-east-2       us-east-2c\n c5.18xlarge  stress-ng:crc16              72  14368.3497  0.6932        9960.1400       us-east-2       us-east-2b\n c5d.2xlarge  stress-ng:crc16               8  14375.2618  0.0764        1098.2700       us-east-2       us-east-2b\n  c4.4xlarge  stress-ng:crc16              16  14386.1878  0.1448        2083.1200       us-east-2       us-east-2c\n  c4.4xlarge  stress-ng:crc16              16  14386.1878  0.1448        2083.1200       us-east-2       us-east-2b\n  c4.4xlarge  stress-ng:crc16              16  14386.1878  0.1448        2083.1200       us-east-2       us-east-2a\n c5d.2xlarge  stress-ng:crc16               8  14450.9211  0.0760        1098.2700       us-east-2       us-east-2c\n  c5.4xlarge  stress-ng:crc16              16  14595.0690  0.1521        2219.9100       us-east-2       us-east-2a\n  c5.4xlarge  stress-ng:crc16              16  14595.0690  0.1521        2219.9100       us-east-2       us-east-2c\n  c5.4xlarge  stress-ng:crc16              16  14604.6711  0.1520        2219.9100       us-east-2       us-east-2b\n c5d.9xlarge  stress-ng:crc16              36  14605.6416  0.3421        4996.5900       us-east-2       us-east-2a\n c5d.9xlarge  stress-ng:crc16              36  14605.6416  0.3421        4996.5900       us-east-2       us-east-2b\n c5d.9xlarge  stress-ng:crc16              36  14605.6416  0.3421        4996.5900       us-east-2       us-east-2c\n   a1.xlarge  stress-ng:crc16               4  15625.8883  0.0197         307.8300       us-east-2       us-east-2b\n   a1.xlarge  stress-ng:crc16               4  15625.8883  0.0197         307.8300       us-east-2       us-east-2a\n  c4.8xlarge  stress-ng:crc16              36  16153.0732  0.2896        4677.9300       us-east-2       us-east-2b\n  c4.8xlarge  stress-ng:crc16              36  16153.0732  0.2896        4677.9300       us-east-2       us-east-2a\n  c4.8xlarge  stress-ng:crc16              36  16153.0732  0.2896        4677.9300       us-east-2       us-east-2c\n```\nWhich means at the time of writing, a spot c4.8xlarge instance is the winner\nof the price/performance contest in the us-east-2 region.\n\n## Currently available benchmarks\n\nBecause running benchmarks cost money, the range of them is quite limited ATM.\nWe use [stress-ng](https://kernel.ubuntu.com/~cking/stress-ng/) to do multiprocess\nbenchmarking. We don't really care about the absolute numbers just the relation\nbetween them.\n\n* `stress-ng:hdd_rndwr_512`: this writes 512 byte blocks with O_DIRECT, O_DSYNC flags\n* `stress-ng:hdd_rndwr_4k`: this writes 4k byte blocks with O_DIRECT, O_DSYNC flags\n* `stress-ng:crc16`: this computes 1024 rounds of CCITT CRC16 on random data\n* `stress-ng:matrixprod`: matrix product of two 128 x 128 matrices of double floats\n\n## Motivation\n\nThis script and running the benchmarks is sponsored by [System1](http://system1.com/).\nSystem1 uses Amazon's infrastructure to run its business and has a lot of batch jobs,\nwhich should be executed in the most cost effective manner.\nCloudperf helps to achieve that: it shows which is the most performing instance\nfor a given price at the time of the execution.\n\n## Realtime data\n\nThe actual prices can be browsed here:\nhttps://bra-fsn.github.io/cloudperf/prices.html",
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