Server
Params
name
A human readable description of the object.
server_type
description to be done
carbon_footprint_fabrication
carbon footprint fabrication of server in kilogram.
power
power of server in watt.
lifespan
lifespan of server in year.
idle_power
idle power of server in watt.
ram
ram of server in gigabyte.
compute
nb cpu cores of server in cpu_core.
power_usage_effectiveness
pue of server in dimensionless.
average_carbon_intensity
average carbon intensity of server electricity in gram / kilowatt_hour.
server_utilization_rate
server utilization rate in dimensionless.
base_ram_consumption
base ram consumption of server in megabyte.
base_compute_consumption
base cpu core consumption of server in cpu_core.
storage
An instance of Storage.
fixed_nb_of_instances
user defined number of server instances. Can be an EmptyExplainableObject in which case the optimum number of instances will be computed, or an ExplainableQuantity with a dimensionless value, in which case e-footprint will raise an error if the object needs more instances than available.
Backwards links
Calculated attributes
hour_by_hour_ram_need
server hour by hour ram need in gigabyte.
Example value: 26299 values from 2024-12-31 23:00:00 to 2028-01-01 17:00:00 in GB:
first 10 vals [0.15, 0.13, 0.1, 0.02, 0.08, 0.13, 0.12, 0.03, 0.12, 0.05],
last 10 vals [0.05, 0.1, 0.1, 0.05, 0.02, 0.1, 0.05, 0.03, 0.15, 0.02]
Depends directly on:
- Hourly Manually defined job average occurrences across usage patterns
- RAM needed on server server to process Manually defined job from hypothesis
- Hourly Video streaming job average occurrences across usage patterns
- Video streaming job RAM needed
through the following calculations:
You can also visit the link to server hour by hour ram need’s full calculation graph.
hour_by_hour_compute_need
server hour by hour compute need in cpu_core.
Example value: 26299 values from 2024-12-31 23:00:00 to 2028-01-01 17:00:00 in cpu_core:
first 10 vals [0.01, 0.01, 0.01, 0.0, 0.01, 0.01, 0.01, 0.0, 0.01, 0.0],
last 10 vals [0.0, 0.01, 0.01, 0.0, 0.0, 0.01, 0.0, 0.0, 0.01, 0.0]
Depends directly on:
- Hourly Manually defined job average occurrences across usage patterns
- CPU needed on server server to process Manually defined job from hypothesis
- Hourly Video streaming job average occurrences across usage patterns
- Video streaming job CPU needed
through the following calculations:
You can also visit the link to server hour by hour compute need’s full calculation graph.
occupied_ram_per_instance
ExplainableQuantity in megabyte, representing the occupied ram per server instance including services.
Example value: 2300.0 megabyte
Depends directly on:
- Base RAM consumption of server
- Video streaming service OS and streaming software base RAM consumption from hypothesis
through the following calculations:
You can also visit the link to Occupied RAM per server instance including services’s full calculation graph.
occupied_compute_per_instance
ExplainableQuantity in cpu_core, representing the occupied cpu per server instance including services.
Example value: 2 cpu_core
Depends directly on:
through the following calculations:
You can also visit the link to Occupied CPU per server instance including services’s full calculation graph.
available_ram_per_instance
ExplainableQuantity in gigabyte, representing the available ram per server instance.
Example value: 112.9 gigabyte
Depends directly on:
through the following calculations:
You can also visit the link to Available RAM per server instance’s full calculation graph.
available_compute_per_instance
ExplainableQuantity in cpu_core, representing the available cpu per server instance.
Example value: 19.6 cpu_core
Depends directly on:
through the following calculations:
You can also visit the link to Available CPU per server instance’s full calculation graph.
raw_nb_of_instances
hourly raw number of server instances in dimensionless.
Example value: 26299 values from 2024-12-31 23:00:00 to 2028-01-01 17:00:00 in dimensionless:
first 10 vals [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
last 10 vals [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
Depends directly on:
- server hour by hour ram need
- Available RAM per server instance
- server hour by hour compute need
- Available CPU per server instance
through the following calculations:
You can also visit the link to Hourly raw number of server instances’s full calculation graph.
nb_of_instances
hourly number of server instances in dimensionless.
Example value: 26299 values from 2024-12-31 23:00:00 to 2028-01-01 17:00:00 in dimensionless:
first 10 vals [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0],
last 10 vals [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
Depends directly on:
through the following calculations:
You can also visit the link to Hourly number of server instances’s full calculation graph.
instances_fabrication_footprint
hourly server instances fabrication footprint in kilogram.
Example value: 26299 values from 2024-12-31 23:00:00 to 2028-01-01 17:00:00 in kg:
first 10 vals [0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01],
last 10 vals [0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01]
Depends directly on:
through the following calculations:
You can also visit the link to Hourly server instances fabrication footprint’s full calculation graph.
instances_energy
hourly energy consumed by server instances in kilowatt_hour.
Example value: 26299 values from 2024-12-31 23:00:00 to 2028-01-01 17:00:00 in kWh:
first 10 vals [0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06],
last 10 vals [0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06]
Depends directly on:
- Hourly number of server instances
- Idle power of server
- PUE of server
- Hourly raw number of server instances
- Power of server
through the following calculations:
You can also visit the link to Hourly energy consumed by server instances’s full calculation graph.
energy_footprint
hourly server energy footprint in kilogram.
Example value: 26299 values from 2024-12-31 23:00:00 to 2028-01-01 17:00:00 in kg:
first 10 vals [0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01],
last 10 vals [0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01]
Depends directly on:
through the following calculations:
You can also visit the link to Hourly server energy footprint’s full calculation graph.