Cloud Infrastructure Energy Consumption
This dataset provides daily, cluster-level records of energy consumption, carbon emissions, and operational metrics across cloud infrastructure. It enables technology and sustainability teams to monitor efficiency, track renewable energy usage, and ensure compliance with environmental standards for ESG reporting and optimization initiatives.
Sample rows
preview · 8 of 120 rows · all 15 columns| record_idstring | cloud_providerstring | energy_cost_usdfloat | datedate | regionstring | cluster_idstring | cluster_namestring | server_countinteger | total_energy_kwhfloat | average_power_kwfloat | peak_power_kwfloat | carbon_emissions_kgfloat | renewable_energy_percentagefloat | utilization_percentagefloat | notesstring |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| REC001 | AWS | 1421.7 | 2024-06-01 | us-east-1 | CL-AWS-us-east-1-101 | Prod-Web-UsEast | 120 | 8900.2 | 372.4 | 541.2 | 3250.5 | 16.5 | 85.4 | High load, compliance period. No anomalies detected. |
| REC002 | Azure | 102.3 | 2024-06-02 | ca-central-1 | CL-AZU-ca-central-1-112 | DevOps-API-CanadaCentral | 25 | 845.6 | 32.8 | 61.3 | 210.9 | 54.6 | 66.7 | Migration underway, system performing within expected range. |
| REC003 | GCP | 81.6 | 2024-06-03 | europe-north1 | CL-GCP-europe-north1-203 | ML-Training-Nordic | 17 | 1040.1 | 43.6 | 70.2 | 58.5 | 93.7 | 97.1 | Fully renewable, high utilization for ML workloads. |
| REC004 | AWS | 1072.4 | 2024-06-04 | eu-west-2 | CL-AWS-eu-west-2-102 | Media-Streaming-London | 90 | 6102.7 | 256.8 | 401.5 | 1913.2 | 19.9 | 82.3 | Peak season, heavy streaming traffic observed. |
| REC005 | IBM | 59.7 | 2024-06-05 | us-south | CL-IBM-us-south-018 | Legacy-ERP-UsSouth | 12 | 490.3 | 16.5 | 29.1 | 105.2 | 42.9 | 31.6 | Legacy platform; scheduled for decommission later this quarter. |
| REC006 | Azure | 128.9 | 2024-06-06 | asia-east | CL-AZU-asia-east-122 | Finance-DB-AsiaEast | 28 | 987.2 | 41.8 | 63.7 | 151.5 | 57.4 | 74.1 | No anomalies. Utilization slightly above normal range. |
| REC007 | AWS | 1746.1 | 2024-06-07 | us-west-1 | CL-AWS-us-west-1-110 | Analytics-Batch-UsWest | 140 | 10920.8 | 433.9 | 688.3 | 3892.6 | 12.3 | 92.2 | Heavy processing, batch analytics for quarterly reporting. |
| REC008 | GCP | 141.2 | 2024-06-08 | us-central1 | CL-GCP-us-central1-211 | Staging-Web-UsCentral | 35 | 1472.4 | 59.1 | 98.2 | 108.4 | 82.2 | 87.6 | Staging environment, fully renewable energy usage. |
| REC009 | Oracle | 8.7 | 2024-06-09 | uk-london-1 | CL-ORA-uk-london-1-007 | HR-Payroll-London | 4 | 56.9 | 2.9 | 4.1 | 13.2 | 22.8 | 18.1 | Low utilization, prototype deployment ongoing. |
| REC010 | AWS | 1358.3 | 2024-06-10 | eu-central-1 | CL-AWS-eu-central-1-115 | Compliance-Logs-Frankfurt | 95 | 7821.6 | 316.2 | 479.6 | 2471.3 | 18.6 | 89.7 | High load, compliance reporting, stable operation. |
| REC011 | OVH | 3.4 | 2024-06-11 | fr-par-1 | CL-OVH-fr-par-1-003 | App-Dev-Paris | 2 | 23.8 | 1.1 | 2.8 | 4.3 | 38.4 | 9.2 | Boundary case, low utilization, prototype. |
| REC012 | Azure | 91.5 | 2024-06-12 | br-south-1 | CL-AZU-br-south-1-119 | DataLake-BrazilSouth | 18 | 711.4 | 28.6 | 49.3 | 170.1 | 48.6 | 69.8 | Seasonal peak, migration completed this week. |
| REC013 | GCP | 61.2 | 2024-06-13 | asia-southeast1 | CL-GCP-asia-southeast1-220 | Test-Backup-SEAsia | 11 | 520.2 | 21.4 | 38.7 | 147.4 | 63.1 | 72.4 | No anomalies, backup performed successfully. |
| REC014 | Azure | 138.9 | 2024-06-14 | eu-north-1 | CL-AZU-eu-north-1-125 | IoT-Sensors-Nordic | 22 | 1104.7 | 46.9 | 68.8 | 183.6 | 66.7 | 76.4 | Steady state, sensors reporting as expected. |
| REC015 | DigitalOcean | 5.2 | 2024-06-15 | nyc1 | CL-DO-nyc1-004 | Dev-Test-NYC | 3 | 42.5 | 1.8 | 3.5 | 10.5 | 25.2 | 12.3 | Prototype, low utilization, early-stage testing. |
| REC016 | AWS | 1039.9 | 2024-06-16 | ap-northeast-1 | CL-AWS-ap-northeast-1-135 | Ecom-Frontend-Tokyo | 82 | 5760.9 | 232.6 | 317.4 | 1587.8 | 17.4 | 88.7 | Stable operation, e-commerce traffic increasing. |
| REC017 | IBM | 22.6 | 2024-06-17 | eu-west-3 | CL-IBM-eu-west-3-021 | Legacy-Data-EUWest3 | 8 | 284.7 | 10.9 | 16.5 | 79.4 | 33.5 | 29.2 | Legacy system, scheduled for migration next month. |
| REC018 | AWS | 2121.5 | 2024-06-18 | us-west-2 | CL-AWS-us-west-2-108 | Batch-Processing-UsWest2 | 175 | 13120 | 550.8 | 799.2 | 4912.5 | 9.2 | 97.8 | Peak load, end of quarter batch jobs. |
| REC019 | Azure | 87.9 | 2024-06-19 | ap-south-1 | CL-AZU-ap-south-1-130 | App-Dev-IndiaSouth | 16 | 672.8 | 28.9 | 48.7 | 138.5 | 45.8 | 64.2 | No anomalies, steady utilization. |
| REC020 | GCP | 221.7 | 2024-06-20 | us-west1 | CL-GCP-us-west1-212 | AI-Research-USWest | 38 | 1582.3 | 64.5 | 99.7 | 51.8 | 98.4 | 98.3 | Fully renewable, high utilization for AI research. |
What the 120 rows show
from the 120-row sampleAWS (cloud provider) stands out: mean energy_
- 89.8median energy_
cost_ usd - 19median server_
count - 810.7median total_
energy_ kwh - 33.3median average_
power_ kw - 57.3median peak_
power_ kw - 141.8median carbon_
emissions_ kg
Median 89.8, from 0.0 to 2,122.
- string 6
- integer 1
- float 7
- date 1
Columns
15 columns in three groups| column | type | description | example |
|---|---|---|---|
| Text 6 columns | |||
record_id | string | Unique identifier for each daily energy consumption record.unique | REC001 |
cloud_provider | string | Name of the cloud service provider (e.g., AWS, Azure, GCP).7 providers | AWS |
region | string | Geographical region or data center location of the server cluster. | us-east-1 |
cluster_id | string | Unique identifier for the server cluster. | CL-AWS-us-east-1-101 |
cluster_name | string | Descriptive name of the server cluster.optional | Prod-Web-UsEast |
notes | string | Additional notes or comments regarding the day's operations or anomalies.optional | High load, compliance per… |
| Numbers 8 columns | |||
server_count | integer | Number of servers in the cluster.1 or more | 120 |
total_energy_kwh | float | Total energy consumed by the cluster for the day, measured in kilowatt-hours (kWh).0 or more | 8900.2 |
average_power_kw | float | Average power draw of the cluster during the day, measured in kilowatts (kW).0 or more · optional | 372.4 |
peak_power_kw | float | Peak power draw of the cluster during the day, measured in kilowatts (kW).0 or more · optional | 541.2 |
carbon_emissions_kg | float | Total carbon emissions produced by the cluster for the day, measured in kilograms (kg) CO2-equivalent.0 or more | 3250.5 |
renewable_energy_percentage | float | Percentage of energy consumption sourced from renewable energy (0-100).0 to 100 · optional | 16.5 |
energy_cost_usd | float | Total cost of energy consumed by the cluster for the day, in US dollars.0 or more · optional | 1421.7 |
utilization_percentage | float | Average utilization of the cluster as a percentage (0-100).0 to 100 · optional | 85.4 |
| Dates and times 1 column | |||
date | date | Date of the energy consumption and emissions measurement. | 2024-06-01 |
Use it for
An energy dashboard
Energy_
cost_ usd by cloud_ provider. Excel, Power BI or Tableau. Why do the 31 AWS rows have a mean energy_
cost_ usd of 1,423? A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
- Records120REC0011421.7AWSREC002102.3AzureREC00381.6GCP
A software demo
Believable records with date, cloud_
provider and region to fill a screen in front of a buyer.
This dataset120 rows15 columns
Yours10,000 rows15 columnsregion: UK only
blueprint · cloud-infrastructure-energy-consumption
Behind this dataset
Same schema. As many rows as you need.
These 120 rows came out of a blueprint — 15 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.
Rules it was built with
- Each row represents energy usage for one server cluster per day
- Carbon emissions calculated using local energy grid coefficients
- Include separate fields for renewable vs. non-renewable energy sources
- Tag anomalous consumption spikes (above 25% daily average)
- Map clusters to business application tags for impact analysis
- Data must include compliance status with internal ESG benchmarks
Open the blueprint in Data Factory
1 credit per row. New accounts start with 25 free credits.
- Exports
- CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
- Licence
- yours to use, including commercially
- API slug
- cloud-infrastructure-energy-consumption