> ## Documentation Index
> Fetch the complete documentation index at: https://docs.tensor9.com/llms.txt
> Use this file to discover all available pages before exploring further.
# azure::1.0.0::aks costs
> Compare azure::1.0.0::aks backend choices using explicit service-adapter planning assumptions.
Tensor9 Cloud Adapter planning comparisons for `azure::1.0.0::aks`, with backend choices shown together. Read [how to think about service-adapter costs](/cloud-adapter/costs/overview) for price scope and capacity qualification, or return to [additional services](/cloud-adapter/costs/additional-services).
## Managed Kubernetes and discovery → Azure AKS API on AWS EKS
Origin API: `azure::1.0.0::aks`. Target backend: `aws::1.0.0::eks::cluster`.
**Planning estimate with editable assumptions.** Unit rates, workload amplification and capacity assumptions are educated guesses awaiting verification. The displayed amounts are planning estimates, not verified provider list-price quotes or benchmark-qualified capacity. Region names identify the authored scenario assumptions.
### Managed Kubernetes and discovery · Worker CPU-hours per month
**Planning estimate with editable assumptions.** These authored unit rates and capacity assumptions require provider-price verification and representative benchmarks. They do not constitute verified list-price quotes or evidence that an adapter is available.
Estimated monthly service charges from native source usage; no calculator input is required. Adapter hosting and Tensor9 fees are excluded. Source: Explicit source planning region; target: Explicit target planning region; currency: USD.
Exact sampled model outputs in USD/month. Difference means target minus origin; a positive difference means the target costs more.
| Worker CPU-hours per month (vCPU-hour/month) | Origin | Target scenario | Target | Difference |
| -: | -: | - | -: | -: |
| 0 | 189.8 | Planning native backend | 207.32 | 17.52 |
| 1460 | 248.2 | Planning native backend | 274.48 | 26.28 |
| 5840 | 423.4 | Planning native backend | 475.96 | 52.56 |
| 23360 | 1124.2 | Planning native backend | 1281.88 | 157.68 |
| 93440 | 3927.4 | Planning native backend | 4505.56 | 578.16 |
| 373760 | 15140.2 | Planning native backend | 17400.28 | 2260.08 |
**Curve assumptions**
| Target scenario | Assumption | Value | Unit |
| - | - | -: | - |
| Planning native backend | Origin price guess · Allocated cluster control plane | 0.1 | USD/cluster-hour |
| Planning native backend | Origin price guess · Allocated worker CPU | 0.04 | USD/vCPU-hour |
| Planning native backend | Origin price guess · Allocated worker memory | 0.005 | USD/GiB-hour |
| Planning native backend | Origin price guess · Cluster management requests | 0 | USD/Requests |
| Planning native backend | Target / origin worker allocation | 1.15 | multiplier |
| Planning native backend | Target price guess · read | 0 | USD/read |
| Planning native backend | Target price guess · write | 0 | USD/write |
| Planning native backend | Target price guess · provider operation | 0 | USD/provider operation |
| Planning native backend | Target price guess · GiB-month | 0.1 | USD/GiB-month |
| Planning native backend | Target price guess · published GiB | 0 | USD/published GiB |
| Planning native backend | Target price guess · delivered GiB | 0 | USD/delivered GiB |
| Planning native backend | Target price guess · network GiB | 0.09 | USD/network GiB |
| Planning native backend | Target price guess · replica GiB-month | 0 | USD/replica GiB-month |
| Planning native backend | Target price guess · vCPU-hour | 0.04 | USD/vCPU-hour |
| Planning native backend | Target price guess · GiB-hour | 0.005 | USD/GiB-hour |
| Planning native backend | Target price guess · resource-hour | 0.1 | USD/resource-hour |
| Planning native backend | Target price guess · resource-month | 0 | USD/resource-month |
| Planning native backend | Target price guess · input token | 0 | USD/input token |
| Planning native backend | Target price guess · output token | 0 | USD/output token |
| Planning native backend | Approximate target service minimum | 0 | USD/month |
| Planning native backend | Minimum primary CPU | 2 | vCPU |
| Planning native backend | Minimum primary RAM | 8 | GiB |
| Planning native backend | Minimum primary disk | 100 | GiB |
| Planning native backend | Additional full-price standby copy | 0 | 0 or 1 |
| Planning native backend | Allocated share of provisioned cost | 1 | fraction |
| Planning native backend | Planning read/write work per vCPU-second | 1000 | operations/vCPU-second |
| Planning native backend | Planning peak / mean work | 2 | multiplier |
| Planning native backend | Planning primary CPU utilization | 0.7 | fraction |
| Planning native backend | Resident state reserved in RAM | 0.1 | fraction |
| Planning native backend | Planning disk utilization | 0.7 | fraction |
| Planning native backend | Maintenance and log disk reserve | 20 | GiB |
| Planning native backend | Staging database CPU unit-price guess | 0.0413 | USD/vCPU-hour |
| Planning native backend | Staging database RAM unit-price guess | 0.007 | USD/GiB-hour |
| Planning native backend | Staging database disk unit-price guess | 0.17 | USD/GiB-month |
| Planning native backend | Dependent object sink storage price guess | 0.023 | USD/GiB-month |
| Planning native backend | Dependent object sink write price guess | 0.000005 | USD/write |
* Only this native meter varies; all other source usage and translation assumptions retain the displayed defaults. Editable authored planning guesses, not verified provider tariffs, benchmark measurements or a commercial quote. Other native meters retain their explicitly displayed default quantities.
* Planning estimate · editable authored rates and sizing assumptions dated 2026-10-18; not verified provider prices. Explicit source planning region → Explicit target planning region, USD/month.
* Source prices are reference charges, not an invoice. Target lines cover selected service usage/configuration only; adapter hosting and Tensor9 fees are excluded.
* Explicit tariff samples are not performance measurements or capacity qualification. No interpolation or break-even guarantee is implied.
* Variant assumptions show the first axis sample; any axis-dependent configuration is described by this curve's workload note.
* Editable authored planning guesses, not verified provider tariffs, benchmark measurements or a commercial quote.
* Default-zero rates are explicit assumptions, not evidence that the deployed service or resource is free.
* Provisioned-unit minimums use an editable approximate allocation floor. Modeled target service cost is max(usage/allocation, minimum), with billable network, durable staging and dependent sinks added separately; actual RU/TU sizing, scaling increments and throughput remain unqualified.
* Durable staging is priced once: provisioned targets include adapter state in their selected allocation; native targets add a separate staging allocation when required. Adapter hosting is a separate allocation and must exclude resources already priced as staging, workers or target capacity.
* A declared adapter mapping and cost model do not establish implementation availability or service equivalence.
* This is a declared directed mapping; a planning estimate does not establish deployment or request-serving support.
* All default unit prices and capacity coefficients are editable authored planning guesses, not measured capacity or a provider quote.
* Management requests do not reveal resource allocation or workload traffic. Provisioned resources and traffic are independent inputs.
* The discovery adapter does not itself own or provision the cluster. Allocate existing cluster capacity once across adapters.
* All target rates are editable authored planning guesses, not verified current list prices, customer discounts or benchmark evidence.
* Cluster control-plane hours and worker CPU/RAM are separately allocated. Allocate shared cluster costs once across adapters.
Cost scope: Modeled target native service and explicitly modeled state allocation; hosting and Tensor9 fees only when supplied.
Excluded costs and workload features:
* Worker disks, GPUs, ingress, network traffic, extended support and observability.
* Taxes, discounts, credits and free-tier allowances unless explicitly reflected in edited rates.
* Unmodeled dependent services, task execution and operations outside the selected workload family.
Planning assumptions authored: 2026-10-18. Model: `plan-81f875cc8106220f4746382cc25d5d85811e9637` / `2026-10-18.planning.1`. Curve: `workload-1`.
### Managed Kubernetes and discovery · Cluster-hours per month
**Planning estimate with editable assumptions.** These authored unit rates and capacity assumptions require provider-price verification and representative benchmarks. They do not constitute verified list-price quotes or evidence that an adapter is available.
Estimated monthly service charges from native source usage; no calculator input is required. Adapter hosting and Tensor9 fees are excluded. Source: Explicit source planning region; target: Explicit target planning region; currency: USD.
Exact sampled model outputs in USD/month. Difference means target minus origin; a positive difference means the target costs more.
| Cluster-hours per month (cluster-hour/month) | Origin | Target scenario | Target | Difference |
| -: | -: | - | -: | -: |
| 0 | 350.4 | Planning native backend | 402.96 | 52.56 |
| 730 | 423.4 | Planning native backend | 475.96 | 52.56 |
| 3650 | 715.4 | Planning native backend | 767.96 | 52.56 |
| 7300 | 1080.4 | Planning native backend | 1132.96 | 52.56 |
| 36500 | 4000.4 | Planning native backend | 4052.96 | 52.56 |
**Curve assumptions**
| Target scenario | Assumption | Value | Unit |
| - | - | -: | - |
| Planning native backend | Origin price guess · Allocated cluster control plane | 0.1 | USD/cluster-hour |
| Planning native backend | Origin price guess · Allocated worker CPU | 0.04 | USD/vCPU-hour |
| Planning native backend | Origin price guess · Allocated worker memory | 0.005 | USD/GiB-hour |
| Planning native backend | Origin price guess · Cluster management requests | 0 | USD/Requests |
| Planning native backend | Target / origin worker allocation | 1.15 | multiplier |
| Planning native backend | Target price guess · read | 0 | USD/read |
| Planning native backend | Target price guess · write | 0 | USD/write |
| Planning native backend | Target price guess · provider operation | 0 | USD/provider operation |
| Planning native backend | Target price guess · GiB-month | 0.1 | USD/GiB-month |
| Planning native backend | Target price guess · published GiB | 0 | USD/published GiB |
| Planning native backend | Target price guess · delivered GiB | 0 | USD/delivered GiB |
| Planning native backend | Target price guess · network GiB | 0.09 | USD/network GiB |
| Planning native backend | Target price guess · replica GiB-month | 0 | USD/replica GiB-month |
| Planning native backend | Target price guess · vCPU-hour | 0.04 | USD/vCPU-hour |
| Planning native backend | Target price guess · GiB-hour | 0.005 | USD/GiB-hour |
| Planning native backend | Target price guess · resource-hour | 0.1 | USD/resource-hour |
| Planning native backend | Target price guess · resource-month | 0 | USD/resource-month |
| Planning native backend | Target price guess · input token | 0 | USD/input token |
| Planning native backend | Target price guess · output token | 0 | USD/output token |
| Planning native backend | Approximate target service minimum | 0 | USD/month |
| Planning native backend | Minimum primary CPU | 2 | vCPU |
| Planning native backend | Minimum primary RAM | 8 | GiB |
| Planning native backend | Minimum primary disk | 100 | GiB |
| Planning native backend | Additional full-price standby copy | 0 | 0 or 1 |
| Planning native backend | Allocated share of provisioned cost | 1 | fraction |
| Planning native backend | Planning read/write work per vCPU-second | 1000 | operations/vCPU-second |
| Planning native backend | Planning peak / mean work | 2 | multiplier |
| Planning native backend | Planning primary CPU utilization | 0.7 | fraction |
| Planning native backend | Resident state reserved in RAM | 0.1 | fraction |
| Planning native backend | Planning disk utilization | 0.7 | fraction |
| Planning native backend | Maintenance and log disk reserve | 20 | GiB |
| Planning native backend | Staging database CPU unit-price guess | 0.0413 | USD/vCPU-hour |
| Planning native backend | Staging database RAM unit-price guess | 0.007 | USD/GiB-hour |
| Planning native backend | Staging database disk unit-price guess | 0.17 | USD/GiB-month |
| Planning native backend | Dependent object sink storage price guess | 0.023 | USD/GiB-month |
| Planning native backend | Dependent object sink write price guess | 0.000005 | USD/write |
* Only this native meter varies; all other source usage and translation assumptions retain the displayed defaults. Editable authored planning guesses, not verified provider tariffs, benchmark measurements or a commercial quote. Other native meters retain their explicitly displayed default quantities.
* Planning estimate · editable authored rates and sizing assumptions dated 2026-10-18; not verified provider prices. Explicit source planning region → Explicit target planning region, USD/month.
* Source prices are reference charges, not an invoice. Target lines cover selected service usage/configuration only; adapter hosting and Tensor9 fees are excluded.
* Explicit tariff samples are not performance measurements or capacity qualification. No interpolation or break-even guarantee is implied.
* Variant assumptions show the first axis sample; any axis-dependent configuration is described by this curve's workload note.
* Editable authored planning guesses, not verified provider tariffs, benchmark measurements or a commercial quote.
* Default-zero rates are explicit assumptions, not evidence that the deployed service or resource is free.
* Provisioned-unit minimums use an editable approximate allocation floor. Modeled target service cost is max(usage/allocation, minimum), with billable network, durable staging and dependent sinks added separately; actual RU/TU sizing, scaling increments and throughput remain unqualified.
* Durable staging is priced once: provisioned targets include adapter state in their selected allocation; native targets add a separate staging allocation when required. Adapter hosting is a separate allocation and must exclude resources already priced as staging, workers or target capacity.
* A declared adapter mapping and cost model do not establish implementation availability or service equivalence.
* This is a declared directed mapping; a planning estimate does not establish deployment or request-serving support.
* All default unit prices and capacity coefficients are editable authored planning guesses, not measured capacity or a provider quote.
* Management requests do not reveal resource allocation or workload traffic. Provisioned resources and traffic are independent inputs.
* The discovery adapter does not itself own or provision the cluster. Allocate existing cluster capacity once across adapters.
* All target rates are editable authored planning guesses, not verified current list prices, customer discounts or benchmark evidence.
* Cluster control-plane hours and worker CPU/RAM are separately allocated. Allocate shared cluster costs once across adapters.
Cost scope: Modeled target native service and explicitly modeled state allocation; hosting and Tensor9 fees only when supplied.
Excluded costs and workload features:
* Worker disks, GPUs, ingress, network traffic, extended support and observability.
* Taxes, discounts, credits and free-tier allowances unless explicitly reflected in edited rates.
* Unmodeled dependent services, task execution and operations outside the selected workload family.
Planning assumptions authored: 2026-10-18. Model: `plan-81f875cc8106220f4746382cc25d5d85811e9637` / `2026-10-18.planning.1`. Curve: `workload-2`.
See the [service catalog](/cloud-adapter/service-catalog/aws/catalog) for operation coverage, supported directions and backend limitations.
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