> ## 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.
# Container Registry (ACR) costs
> Compare Container Registry (ACR) backend choices using explicit service-adapter planning assumptions.
Tensor9 Cloud Adapter planning comparisons for `azure::1.0.0::container-registry`, 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).
## Azure Container Registry image storage and transfer → Artifact Registry
Origin API: `azure::1.0.0::container-registry`. Target backend: `google::1.0.0::artifact-registry`.
**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.
**Designed mapping.** This cost model describes an intended adapter. Its estimated price does not establish a delivered or selectable backend.
### Azure Container Registry image storage and transfer · Retained image data
**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.
| Retained image data (GiB-month) | Origin | Target scenario | Target | Difference |
| -: | -: | - | -: | -: |
| 0 | 104.6 | Planning native backend | 90 | -14.6 |
| 10 | 105.6 | Planning native backend | 91.1 | -14.5 |
| 100 | 114.6 | Planning native backend | 101 | -13.6 |
| 1000 | 204.6 | Planning native backend | 200 | -4.6 |
| 10000 | 1104.6 | Planning native backend | 1190 | 85.4 |
| 100000 | 10104.6 | Planning native backend | 11090 | 985.4 |
**Curve assumptions**
| Target scenario | Assumption | Value | Unit |
| - | - | -: | - |
| Planning native backend | Origin price guess · Retained container image data | 0.1 | USD/GiB-month |
| Planning native backend | Origin price guess · Selected billable image transfer | 0.09 | USD/GiB |
| Planning native backend | Origin price guess · Image manifest and layer read requests | 0 | USD/Requests |
| Planning native backend | Origin price guess · Image upload and manifest write requests | 0 | USD/Requests |
| Planning native backend | Origin price guess · Allocated registry service tier | 0.02 | USD/registry-hour |
| Planning native backend | Target / origin retained image bytes | 1.1 | multiplier |
| Planning native backend | Target reads per source read | 1 | operations/read |
| Planning native backend | Target writes per source write | 1.1 | operations/write |
| Planning native backend | Target / origin billable image transfer | 1 | 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 | USD/vCPU-hour |
| Planning native backend | Target price guess · GiB-hour | 0 | USD/GiB-hour |
| Planning native backend | Target price guess · resource-hour | 0 | 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 the selected native meter varies; other usage quantities and assumptions retain their 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 exact directed mapping has a design profile. Cost modeling does not establish an implemented or deployable adapter.
* Unit prices and capacity coefficients are editable authored planning guesses, not verified provider tariffs or measured capacity.
* The origin is the exact registered azure::1.0.0::container-registry identity. Future aliases and renamed provider products require explicit registry and model updates.
* Stored image data, selected transfer bytes and read/write requests are independent source meters. Requests never create inferred image bytes or registry instances.
* Zero-rate API meters retain physical request quantities; they do not establish that all provider features are free.
* These reverse-cloud directions can be designed rather than delivered. A cost comparison does not establish an implemented adapter.
* The source registry tier is independently allocated in registry-hours. The target tariff must declare whether it has its own tier minimum.
* All target rates are editable authored planning guesses, not verified current list prices, customer discounts or benchmark evidence.
* Artifact storage and selected transferred bytes are priced independently; registry API calls are not image-pull bytes. Fixed premium registry tiers require separate allocation.
Cost scope: Modeled target native service and explicitly modeled state allocation; hosting and Tensor9 fees only when supplied.
Excluded costs and workload features:
* Image scanning, signing, build minutes, vulnerability feeds, geo-replication, regional cache services, private endpoints and network routes outside the selected scope.
* Provider free storage, included tier allowances, volume discounts, architecture-specific image inflation and one-time cross-cloud migration.
* 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-3054e044891d70f213cc5452ee12aa5351510ade` / `2026-10-18.planning.1`. Curve: `workload-1`.
### Azure Container Registry image storage and transfer · Selected image transfer 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.
| Selected image transfer per month (GiB/month) | Origin | Target scenario | Target | Difference |
| -: | -: | - | -: | -: |
| 0 | 24.6 | Planning native backend | 11 | -13.6 |
| 100 | 33.6 | Planning native backend | 20 | -13.6 |
| 1000 | 114.6 | Planning native backend | 101 | -13.6 |
| 10000 | 924.6 | Planning native backend | 911 | -13.6 |
| 100000 | 9024.6 | Planning native backend | 9011 | -13.6 |
| 1000000 | 90024.6 | Planning native backend | 90011 | -13.6 |
**Curve assumptions**
| Target scenario | Assumption | Value | Unit |
| - | - | -: | - |
| Planning native backend | Origin price guess · Retained container image data | 0.1 | USD/GiB-month |
| Planning native backend | Origin price guess · Selected billable image transfer | 0.09 | USD/GiB |
| Planning native backend | Origin price guess · Image manifest and layer read requests | 0 | USD/Requests |
| Planning native backend | Origin price guess · Image upload and manifest write requests | 0 | USD/Requests |
| Planning native backend | Origin price guess · Allocated registry service tier | 0.02 | USD/registry-hour |
| Planning native backend | Target / origin retained image bytes | 1.1 | multiplier |
| Planning native backend | Target reads per source read | 1 | operations/read |
| Planning native backend | Target writes per source write | 1.1 | operations/write |
| Planning native backend | Target / origin billable image transfer | 1 | 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 | USD/vCPU-hour |
| Planning native backend | Target price guess · GiB-hour | 0 | USD/GiB-hour |
| Planning native backend | Target price guess · resource-hour | 0 | 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 the selected native meter varies; other usage quantities and assumptions retain their 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 exact directed mapping has a design profile. Cost modeling does not establish an implemented or deployable adapter.
* Unit prices and capacity coefficients are editable authored planning guesses, not verified provider tariffs or measured capacity.
* The origin is the exact registered azure::1.0.0::container-registry identity. Future aliases and renamed provider products require explicit registry and model updates.
* Stored image data, selected transfer bytes and read/write requests are independent source meters. Requests never create inferred image bytes or registry instances.
* Zero-rate API meters retain physical request quantities; they do not establish that all provider features are free.
* These reverse-cloud directions can be designed rather than delivered. A cost comparison does not establish an implemented adapter.
* The source registry tier is independently allocated in registry-hours. The target tariff must declare whether it has its own tier minimum.
* All target rates are editable authored planning guesses, not verified current list prices, customer discounts or benchmark evidence.
* Artifact storage and selected transferred bytes are priced independently; registry API calls are not image-pull bytes. Fixed premium registry tiers require separate allocation.
Cost scope: Modeled target native service and explicitly modeled state allocation; hosting and Tensor9 fees only when supplied.
Excluded costs and workload features:
* Image scanning, signing, build minutes, vulnerability feeds, geo-replication, regional cache services, private endpoints and network routes outside the selected scope.
* Provider free storage, included tier allowances, volume discounts, architecture-specific image inflation and one-time cross-cloud migration.
* 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-3054e044891d70f213cc5452ee12aa5351510ade` / `2026-10-18.planning.1`. Curve: `workload-2`.
### Azure Container Registry image storage and transfer · Image read requests per second
**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.
| Image read requests per second (requests/s) | Origin | Target scenario | Target | Difference |
| -: | -: | - | -: | -: |
| 0 | 114.6 | Planning native backend | 101 | -13.6 |
| 1 | 114.6 | Planning native backend | 101 | -13.6 |
| 10 | 114.6 | Planning native backend | 101 | -13.6 |
| 100 | 114.6 | Planning native backend | 101 | -13.6 |
| 1000 | 114.6 | Planning native backend | 101 | -13.6 |
| 10000 | 114.6 | Planning native backend | 101 | -13.6 |
**Curve assumptions**
| Target scenario | Assumption | Value | Unit |
| - | - | -: | - |
| Planning native backend | Origin price guess · Retained container image data | 0.1 | USD/GiB-month |
| Planning native backend | Origin price guess · Selected billable image transfer | 0.09 | USD/GiB |
| Planning native backend | Origin price guess · Image manifest and layer read requests | 0 | USD/Requests |
| Planning native backend | Origin price guess · Image upload and manifest write requests | 0 | USD/Requests |
| Planning native backend | Origin price guess · Allocated registry service tier | 0.02 | USD/registry-hour |
| Planning native backend | Target / origin retained image bytes | 1.1 | multiplier |
| Planning native backend | Target reads per source read | 1 | operations/read |
| Planning native backend | Target writes per source write | 1.1 | operations/write |
| Planning native backend | Target / origin billable image transfer | 1 | 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 | USD/vCPU-hour |
| Planning native backend | Target price guess · GiB-hour | 0 | USD/GiB-hour |
| Planning native backend | Target price guess · resource-hour | 0 | 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 the selected native meter varies; other usage quantities and assumptions retain their 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 exact directed mapping has a design profile. Cost modeling does not establish an implemented or deployable adapter.
* Unit prices and capacity coefficients are editable authored planning guesses, not verified provider tariffs or measured capacity.
* The origin is the exact registered azure::1.0.0::container-registry identity. Future aliases and renamed provider products require explicit registry and model updates.
* Stored image data, selected transfer bytes and read/write requests are independent source meters. Requests never create inferred image bytes or registry instances.
* Zero-rate API meters retain physical request quantities; they do not establish that all provider features are free.
* These reverse-cloud directions can be designed rather than delivered. A cost comparison does not establish an implemented adapter.
* The source registry tier is independently allocated in registry-hours. The target tariff must declare whether it has its own tier minimum.
* All target rates are editable authored planning guesses, not verified current list prices, customer discounts or benchmark evidence.
* Artifact storage and selected transferred bytes are priced independently; registry API calls are not image-pull bytes. Fixed premium registry tiers require separate allocation.
Cost scope: Modeled target native service and explicitly modeled state allocation; hosting and Tensor9 fees only when supplied.
Excluded costs and workload features:
* Image scanning, signing, build minutes, vulnerability feeds, geo-replication, regional cache services, private endpoints and network routes outside the selected scope.
* Provider free storage, included tier allowances, volume discounts, architecture-specific image inflation and one-time cross-cloud migration.
* 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-3054e044891d70f213cc5452ee12aa5351510ade` / `2026-10-18.planning.1`. Curve: `workload-3`.
## Azure Container Registry image storage and transfer → ECR (Elastic Container Registry)
Origin API: `azure::1.0.0::container-registry`. Target backend: `aws::1.0.0::ecr`.
**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.
**Designed mapping.** This cost model describes an intended adapter. Its estimated price does not establish a delivered or selectable backend.
### Azure Container Registry image storage and transfer · Retained image data
**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.
| Retained image data (GiB-month) | Origin | Target scenario | Target | Difference |
| -: | -: | - | -: | -: |
| 0 | 104.6 | Planning native backend | 90 | -14.6 |
| 10 | 105.6 | Planning native backend | 91.1 | -14.5 |
| 100 | 114.6 | Planning native backend | 101 | -13.6 |
| 1000 | 204.6 | Planning native backend | 200 | -4.6 |
| 10000 | 1104.6 | Planning native backend | 1190 | 85.4 |
| 100000 | 10104.6 | Planning native backend | 11090 | 985.4 |
**Curve assumptions**
| Target scenario | Assumption | Value | Unit |
| - | - | -: | - |
| Planning native backend | Origin price guess · Retained container image data | 0.1 | USD/GiB-month |
| Planning native backend | Origin price guess · Selected billable image transfer | 0.09 | USD/GiB |
| Planning native backend | Origin price guess · Image manifest and layer read requests | 0 | USD/Requests |
| Planning native backend | Origin price guess · Image upload and manifest write requests | 0 | USD/Requests |
| Planning native backend | Origin price guess · Allocated registry service tier | 0.02 | USD/registry-hour |
| Planning native backend | Target / origin retained image bytes | 1.1 | multiplier |
| Planning native backend | Target reads per source read | 1 | operations/read |
| Planning native backend | Target writes per source write | 1.1 | operations/write |
| Planning native backend | Target / origin billable image transfer | 1 | 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 | USD/vCPU-hour |
| Planning native backend | Target price guess · GiB-hour | 0 | USD/GiB-hour |
| Planning native backend | Target price guess · resource-hour | 0 | 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 the selected native meter varies; other usage quantities and assumptions retain their 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 exact directed mapping has a design profile. Cost modeling does not establish an implemented or deployable adapter.
* Unit prices and capacity coefficients are editable authored planning guesses, not verified provider tariffs or measured capacity.
* The origin is the exact registered azure::1.0.0::container-registry identity. Future aliases and renamed provider products require explicit registry and model updates.
* Stored image data, selected transfer bytes and read/write requests are independent source meters. Requests never create inferred image bytes or registry instances.
* Zero-rate API meters retain physical request quantities; they do not establish that all provider features are free.
* These reverse-cloud directions can be designed rather than delivered. A cost comparison does not establish an implemented adapter.
* The source registry tier is independently allocated in registry-hours. The target tariff must declare whether it has its own tier minimum.
* All target rates are editable authored planning guesses, not verified current list prices, customer discounts or benchmark evidence.
* Artifact storage and selected transferred bytes are priced independently; registry API calls are not image-pull bytes. Fixed premium registry tiers require separate allocation.
Cost scope: Modeled target native service and explicitly modeled state allocation; hosting and Tensor9 fees only when supplied.
Excluded costs and workload features:
* Image scanning, signing, build minutes, vulnerability feeds, geo-replication, regional cache services, private endpoints and network routes outside the selected scope.
* Provider free storage, included tier allowances, volume discounts, architecture-specific image inflation and one-time cross-cloud migration.
* 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-467139ccc3b7867e112f92665e29e6fc37f11022` / `2026-10-18.planning.1`. Curve: `workload-1`.
### Azure Container Registry image storage and transfer · Selected image transfer 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.
| Selected image transfer per month (GiB/month) | Origin | Target scenario | Target | Difference |
| -: | -: | - | -: | -: |
| 0 | 24.6 | Planning native backend | 11 | -13.6 |
| 100 | 33.6 | Planning native backend | 20 | -13.6 |
| 1000 | 114.6 | Planning native backend | 101 | -13.6 |
| 10000 | 924.6 | Planning native backend | 911 | -13.6 |
| 100000 | 9024.6 | Planning native backend | 9011 | -13.6 |
| 1000000 | 90024.6 | Planning native backend | 90011 | -13.6 |
**Curve assumptions**
| Target scenario | Assumption | Value | Unit |
| - | - | -: | - |
| Planning native backend | Origin price guess · Retained container image data | 0.1 | USD/GiB-month |
| Planning native backend | Origin price guess · Selected billable image transfer | 0.09 | USD/GiB |
| Planning native backend | Origin price guess · Image manifest and layer read requests | 0 | USD/Requests |
| Planning native backend | Origin price guess · Image upload and manifest write requests | 0 | USD/Requests |
| Planning native backend | Origin price guess · Allocated registry service tier | 0.02 | USD/registry-hour |
| Planning native backend | Target / origin retained image bytes | 1.1 | multiplier |
| Planning native backend | Target reads per source read | 1 | operations/read |
| Planning native backend | Target writes per source write | 1.1 | operations/write |
| Planning native backend | Target / origin billable image transfer | 1 | 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 | USD/vCPU-hour |
| Planning native backend | Target price guess · GiB-hour | 0 | USD/GiB-hour |
| Planning native backend | Target price guess · resource-hour | 0 | 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 the selected native meter varies; other usage quantities and assumptions retain their 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 exact directed mapping has a design profile. Cost modeling does not establish an implemented or deployable adapter.
* Unit prices and capacity coefficients are editable authored planning guesses, not verified provider tariffs or measured capacity.
* The origin is the exact registered azure::1.0.0::container-registry identity. Future aliases and renamed provider products require explicit registry and model updates.
* Stored image data, selected transfer bytes and read/write requests are independent source meters. Requests never create inferred image bytes or registry instances.
* Zero-rate API meters retain physical request quantities; they do not establish that all provider features are free.
* These reverse-cloud directions can be designed rather than delivered. A cost comparison does not establish an implemented adapter.
* The source registry tier is independently allocated in registry-hours. The target tariff must declare whether it has its own tier minimum.
* All target rates are editable authored planning guesses, not verified current list prices, customer discounts or benchmark evidence.
* Artifact storage and selected transferred bytes are priced independently; registry API calls are not image-pull bytes. Fixed premium registry tiers require separate allocation.
Cost scope: Modeled target native service and explicitly modeled state allocation; hosting and Tensor9 fees only when supplied.
Excluded costs and workload features:
* Image scanning, signing, build minutes, vulnerability feeds, geo-replication, regional cache services, private endpoints and network routes outside the selected scope.
* Provider free storage, included tier allowances, volume discounts, architecture-specific image inflation and one-time cross-cloud migration.
* 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-467139ccc3b7867e112f92665e29e6fc37f11022` / `2026-10-18.planning.1`. Curve: `workload-2`.
### Azure Container Registry image storage and transfer · Image read requests per second
**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.
| Image read requests per second (requests/s) | Origin | Target scenario | Target | Difference |
| -: | -: | - | -: | -: |
| 0 | 114.6 | Planning native backend | 101 | -13.6 |
| 1 | 114.6 | Planning native backend | 101 | -13.6 |
| 10 | 114.6 | Planning native backend | 101 | -13.6 |
| 100 | 114.6 | Planning native backend | 101 | -13.6 |
| 1000 | 114.6 | Planning native backend | 101 | -13.6 |
| 10000 | 114.6 | Planning native backend | 101 | -13.6 |
**Curve assumptions**
| Target scenario | Assumption | Value | Unit |
| - | - | -: | - |
| Planning native backend | Origin price guess · Retained container image data | 0.1 | USD/GiB-month |
| Planning native backend | Origin price guess · Selected billable image transfer | 0.09 | USD/GiB |
| Planning native backend | Origin price guess · Image manifest and layer read requests | 0 | USD/Requests |
| Planning native backend | Origin price guess · Image upload and manifest write requests | 0 | USD/Requests |
| Planning native backend | Origin price guess · Allocated registry service tier | 0.02 | USD/registry-hour |
| Planning native backend | Target / origin retained image bytes | 1.1 | multiplier |
| Planning native backend | Target reads per source read | 1 | operations/read |
| Planning native backend | Target writes per source write | 1.1 | operations/write |
| Planning native backend | Target / origin billable image transfer | 1 | 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 | USD/vCPU-hour |
| Planning native backend | Target price guess · GiB-hour | 0 | USD/GiB-hour |
| Planning native backend | Target price guess · resource-hour | 0 | 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 the selected native meter varies; other usage quantities and assumptions retain their 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 exact directed mapping has a design profile. Cost modeling does not establish an implemented or deployable adapter.
* Unit prices and capacity coefficients are editable authored planning guesses, not verified provider tariffs or measured capacity.
* The origin is the exact registered azure::1.0.0::container-registry identity. Future aliases and renamed provider products require explicit registry and model updates.
* Stored image data, selected transfer bytes and read/write requests are independent source meters. Requests never create inferred image bytes or registry instances.
* Zero-rate API meters retain physical request quantities; they do not establish that all provider features are free.
* These reverse-cloud directions can be designed rather than delivered. A cost comparison does not establish an implemented adapter.
* The source registry tier is independently allocated in registry-hours. The target tariff must declare whether it has its own tier minimum.
* All target rates are editable authored planning guesses, not verified current list prices, customer discounts or benchmark evidence.
* Artifact storage and selected transferred bytes are priced independently; registry API calls are not image-pull bytes. Fixed premium registry tiers require separate allocation.
Cost scope: Modeled target native service and explicitly modeled state allocation; hosting and Tensor9 fees only when supplied.
Excluded costs and workload features:
* Image scanning, signing, build minutes, vulnerability feeds, geo-replication, regional cache services, private endpoints and network routes outside the selected scope.
* Provider free storage, included tier allowances, volume discounts, architecture-specific image inflation and one-time cross-cloud migration.
* 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-467139ccc3b7867e112f92665e29e6fc37f11022` / `2026-10-18.planning.1`. Curve: `workload-3`.
See the [service catalog](/cloud-adapter/service-catalog/aws/catalog) for operation coverage, supported directions and backend limitations.
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