Storage
Params
name
A human readable description of the object.
storage_capacity
Storage capacity of storage in terabyte_stored.
carbon_footprint_fabrication_per_storage_capacity
Fabrication carbon footprint of storage per storage capacity in kilogram / terabyte_stored.
data_replication_factor
Data replication factor of storage in dimensionless.
data_storage_duration
Data storage duration of storage in hour.
base_storage_need
Storage initial storage need in terabyte_stored.
lifespan
Lifespan of storage in year.
fixed_nb_of_instances
User defined number of storage 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
carbon_footprint_fabrication
ExplainableQuantity in kilogram, representing the Carbon footprint of storage.
Example value: 160 kg
Depends directly on:
through the following calculations:
You can also visit the link to Carbon footprint of storage’s full calculation graph.
full_cumulative_storage_need_per_job
Dictionary with Job as keys and Cumulative storage for manually defined job in storage as values, in terabyte_stored.
Example value: {
Job Manually defined job (940432): 105192 values from 2025-01-01 00:00:00+00:00 to 2037-01-01 00:00:00+00:00 in TB stored:
first 10 vals [0.0000036, 0.000006, 0.0000114, 0.000012, 0.0000126, 0.000015, 0.0000168, 0.000321, 0.000922, 0.00183],
last 10 vals [18100, 18100, 18100, 18100, 18100, 18100, 18100, 18100, 18100, 18100],
VideoStreamingJob Video streaming job (32541b): 26298 values from 2025-01-01 00:00:00+00:00 to 2028-01-01 18:00:00+00:00 in B stored:
first 10 vals [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
last 10 vals [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
}
Depends directly on:
- Hourly Manually defined job data stored across usage patterns
- Data replication factor of storage
- Data storage duration of storage
through the following calculations:
You can also visit the link to Cumulative storage for Manually defined job in storage’s full calculation graph.
full_cumulative_storage_need
Full cumulative storage need for storage in terabyte_stored.
Example value: 105192 values from 2025-01-01 00:00:00+00:00 to 2037-01-01 00:00:00+00:00 in TB stored:
first 10 vals [0.0000036, 0.000006, 0.0000114, 0.000012, 0.0000126, 0.000015, 0.0000168, 0.000321, 0.000922, 0.00183],
last 10 vals [18100, 18100, 18100, 18100, 18100, 18100, 18100, 18100, 18100, 18100]
Depends directly on:
- Cumulative storage for Manually defined job in storage
- Cumulative storage for Video streaming job in storage
- storage initial storage need
through the following calculations:
You can also visit the link to Full cumulative storage need for storage’s full calculation graph.
raw_nb_of_instances
Hourly raw number of instances for storage in concurrent.
Example value: 105192 values from 2025-01-01 00:00:00+00:00 to 2037-01-01 00:00:00+00:00 in k:
first 10 vals [0.0000000036, 0.000000006, 0.0000000114, 0.000000012, 0.0000000126, 0.000000015, 0.0000000168, 0.000000321, 0.000000922, 0.00000183],
last 10 vals [18.1, 18.1, 18.1, 18.1, 18.1, 18.1, 18.1, 18.1, 18.1, 18.1]
Depends directly on:
through the following calculations:
You can also visit the link to Hourly raw number of instances for storage’s full calculation graph.
nb_of_instances
Hourly number of instances for storage in concurrent.
Example value: 105192 values from 2025-01-01 00:00:00+00:00 to 2037-01-01 00:00:00+00:00 in k:
first 10 vals [0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001],
last 10 vals [18.1, 18.1, 18.1, 18.1, 18.1, 18.1, 18.1, 18.1, 18.1, 18.1]
Depends directly on:
through the following calculations:
You can also visit the link to Hourly number of instances for storage’s full calculation graph.
instances_fabrication_footprint
Hourly storage instances fabrication footprint in kilogram.
Example value: 105192 values from 2025-01-01 00:00:00+00:00 to 2037-01-01 00:00:00+00:00 in kg:
first 10 vals [0.00304, 0.00304, 0.00304, 0.00304, 0.00304, 0.00304, 0.00304, 0.00304, 0.00304, 0.00304],
last 10 vals [55.1, 55.1, 55.1, 55.1, 55.1, 55.1, 55.1, 55.1, 55.1, 55.1]
Depends directly on:
through the following calculations:
You can also visit the link to Hourly storage instances fabrication footprint’s full calculation graph.
instances_energy
Example value: no value
Depends directly on:
through the following calculations:
You can also visit the link to no value’s full calculation graph.
energy_footprint
Example value: no value
Depends directly on:
through the following calculations:
You can also visit the link to Hourly storage energy footprint’s full calculation graph.
fabrication_impact_repartition_weights
Dictionary with Job as keys and Manually defined job fabrication weight in storage impact repartition as values, in terabyte_stored.
Example value: {
Job Manually defined job (940432): 105192 values from 2025-01-01 00:00:00+00:00 to 2037-01-01 00:00:00+00:00 in TB stored:
first 10 vals [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.501],
last 10 vals [18100, 18100, 18100, 18100, 18100, 18100, 18100, 18100, 18100, 18100],
VideoStreamingJob Video streaming job (32541b): 105192 values from 2025-01-01 00:00:00+00:00 to 2037-01-01 00:00:00+00:00 in GB stored:
first 10 vals [500, 500, 500, 500, 500, 500, 500, 500, 500, 499],
last 10 vals [54.7, 87.9, 121, 154, 188, 221, 254, 287, 320, 354],
}
Depends directly on:
- Cumulative storage for Manually defined job in storage
- Hourly number of instances for storage
- Storage capacity of storage
- Full cumulative storage need for storage
- storage initial storage need
through the following calculations:
You can also visit the link to Manually defined job fabrication weight in storage impact repartition’s full calculation graph.
fabrication_impact_repartition_weight_sum
Sum of storage fabrication impact repartition weights in terabyte_stored.
Example value: 105192 values from 2025-01-01 00:00:00+00:00 to 2037-01-01 00:00:00+00:00 in TB stored:
first 10 vals [1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
last 10 vals [18100, 18100, 18100, 18100, 18100, 18100, 18100, 18100, 18100, 18100]
Depends directly on:
- Manually defined job fabrication weight in storage impact repartition
- Video streaming job fabrication weight in storage impact repartition
through the following calculations:
You can also visit the link to Sum of storage fabrication impact repartition weights’s full calculation graph.
fabrication_impact_repartition
Dictionary with Job as keys and Storage fabrication impact attribution to manually defined job as values, in concurrent.
Example value: {
Job Manually defined job (940432): 105192 values from 2025-01-01 00:00:00+00:00 to 2037-01-01 00:00:00+00:00 in :
first 10 vals [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.501],
last 10 vals [1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
VideoStreamingJob Video streaming job (32541b): 105192 values from 2025-01-01 00:00:00+00:00 to 2037-01-01 00:00:00+00:00 in :
first 10 vals [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.499],
last 10 vals [0.00000302, 0.00000485, 0.00000668, 0.00000852, 0.0000103, 0.0000122, 0.000014, 0.0000159, 0.0000177, 0.0000195],
}
Depends directly on:
- Manually defined job fabrication weight in storage impact repartition
- Sum of storage fabrication impact repartition weights
through the following calculations:
You can also visit the link to storage fabrication impact attribution to Manually defined job’s full calculation graph.
usage_impact_repartition_weight_sum
Example value: no value
Depends directly on:
through the following calculations:
You can also visit the link to Sum of storage usage impact repartition weights’s full calculation graph.