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Tensor9 Cloud Adapter planning comparisons for aws::1.0.0::ecs::cluster, with backend choices shown together. Read how Tensor9 estimates service-adapter costs for price scope and capacity qualification, or return to additional services.

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ECS task execution on Kubernetes → Kubernetes Cluster

Origin API: aws::1.0.0::ecs::cluster. Target backend: kubernetes::1.0.0::cluster.

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ECS task execution on Kubernetes · Allocated task CPU-seconds per month

Feature: ECS task execution on Kubernetes. Estimated monthly service charges by Allocated task CPU-seconds per month. Adapter hosting and Tensor9 fees are excluded. Source: us-east-1; target: us-central1; currency: USD.
ECS task execution on Kubernetes · Allocated task CPU-seconds per month: monthly service charges by Allocated task CPU-seconds per month. Exact values are in the following table.ECS task execution on Kubernetes · Allocated task CPU-seconds per month: monthly service charges by Allocated task CPU-seconds per month. Exact values are in the following table.
Comparison pills describe all sampled scale points; amounts beside each service are for the named workload. Costs The Same means within 20% at every point. Costs Depend includes mixed results and unpriced samples. Sampled monthly charges in USD, rounded to cents. Difference means target minus origin; a positive difference means the target costs more. Estimated allocation, not benchmark calibrated: sized from 2 vCPU, 8 GiB memory and 100 GiB SSD at 0 vCPU-second/month to 9 nodes of 32 vCPU, 128 GiB memory and 100 GiB SSD each at 262,800,000 vCPU-second/month. Curve assumptions
  • Only this native meter varies; all other source usage and translation assumptions retain the displayed defaults. Other native meters and workload assumptions retain their explicitly displayed default quantities. Workload translation and capacity assumptions are not benchmark measurements.
  • Native monthly usage priced at the cited provider list prices; listed target allowances apply where present, excluding invoice credits, taxes and negotiated discounts. Rates as of 2026-10-22: us-east-1 → us-central1, 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.
  • Samples of explicit prices 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.
  • Rates are cited provider list prices, editable for discounts, commitments or another region. Workload translation and capacity coefficients remain editable planning assumptions, not 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.
  • Origin unit prices are cited provider list prices; capacity coefficients and translation assumptions 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.
  • Task CPU and memory independently grow worker resource-hours; task-start counts are not a capacity estimate.
  • The runtime ECS management endpoint and catalog compile-time container targets have different serving availability.
  • Self-hosted target: Kubernetes (Apache-2.0, https://github.com/kubernetes/kubernetes/blob/master/LICENSE); the host cloud’s managed control plane is a separate per-cluster-hour allocation. Selected CPU, RAM and physical disk allocation grow with workload; no per-operation price is assumed. No vendor charge: the target runs on the customer’s Kubernetes nodes, so CPU, RAM and disk bill at the Kubernetes node reference rates, Compute Engine N2 in us-central1 (USD 0.031611/vCPU-hour, 0.004237/GiB-hour) with pd-balanced disk (0.10/GiB-month) and Premium Tier egress. The cost-optimized E2 series lists 0.02181159/vCPU-hour and 0.00292353/GiB-hour; AWS m6i/r6i and Azure D2s v5/E2s v5 both decompose to 0.033/vCPU-hour and 0.00375/GiB-hour. Requested CPU and RAM are billed; node bin-packing waste, system reservations and the cluster control-plane fee are not.
  • Row-store throughput (capacityOpsPerVcpuSecond, default 1500) is measured-by-tensor9 as a lower bound: the DynamoDB adapter on Cloud SQL db-custom-2-7680 (2 vCPU, PostgreSQL 16, us-west1) served 2,974 ops/s of YCSB-A at 16 threads without recorded saturation (src/main/kotlin/t9/prime/equiv/generated/eval/CloudsqlPostgresqlYcsbAT16GoYcsbV1_0_0.kt). Published CPU-bound pgbench reaches 3,101 read-write transactions and 20,289 point reads per vCPU-second (AWS z1d.2xlarge, PostgreSQL 14.5), so actual capacity is likely higher. Reads and writes share one coefficient: at the same adapter version, read-only YCSB-C was not faster than 50%-update YCSB-A.
  • Log-broker throughput (capacityStreamMiBPerVcpuSecond 20 at 0.5 utilization, 4 GiB RAM per vCPU) is provider-documented by Google Managed Service for Apache Kafka sizing (https://docs.cloud.google.com/managed-service-for-apache-kafka/docs/plan-cluster-size): write-equivalent bytes are replicated writes plus a quarter of reads. Producer batches below 10 KB lower per-CPU throughput; that penalty is not modeled.
  • Disk utilization 0.8 is provider-documented headroom below Cloud SQL automatic storage increase, which triggers near 91-95% full (https://docs.cloud.google.com/sql/docs/postgres/instance-settings). The 20 GiB reserve exceeds PostgreSQL’s 1 GB default max_wal_size; the remainder of that reserve is unmeasured.
  • CPU tiers double from 2 vCPUs to the target’s largest node at 4 GiB per vCPU; each target’s documented largest node bounds CPU, RAM, RAM per vCPU and disk, and the durable staging database uses Cloud SQL Enterprise (96 vCPU, 6.5 GiB per vCPU, 624 GiB, 64 TiB). Targets billed per capacity unit or throughput unit are sized by their backend instead.
  • No public evidence: peak/mean work (2) and the RAM working-set fraction (0.1). Proposed measurements: the p99 one-minute rate over the monthly mean from customer CloudWatch metrics; the buffer hit ratio while stepping RAM under a fixed YCSB-B load.
  • Node bounds: Planning worker node of 32 vCPUs and 128 GiB, not a provider maximum; the cluster adds nodes up to a 1,000-node planning bound. Requested CPU and RAM bill linearly, so the node size changes only rounding.
  • Stored GiB already includes the origin family’s physical footprint assumptions; no second storage amplification is applied.
  • The workload family already selected resource-hours; the throughput coefficient is not applied again.
  • Copies and allocation fractions change cost only; they do not increase modeled primary capacity.
  • AWS Price List API, AmazonECS offer: https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonECS/current/us-east-1/index.json
  • Amazon ECS pricing: https://aws.amazon.com/ecs/pricing/
  • Compute Engine general-purpose machine pricing: https://cloud.google.com/products/compute/pricing/general-purpose
  • Disk and image pricing: https://cloud.google.com/compute/disks-image-pricing
  • Network pricing: https://cloud.google.com/vpc/network-pricing
Cost scope: Modeled target native service and explicitly modeled state allocation; hosting and Tensor9 fees only when supplied. Excluded costs and workload features:
  • Cluster control plane, worker idle floor, image pulls, persistent storage, GPU tasks, networking and ECS service lifecycle.
  • Taxes, discounts, credits and free-tier allowances not explicitly listed by this model.
  • Unmodeled dependent services, task execution and operations outside the selected workload family.
List prices read: 2026-10-22. Model: plan-351fa675b0206b0661fb0e787b5c1d6d303c1fd4 / 2026-10-22.planning.2. Curve: workload-1. Sources: AWS Price List API, AmazonECS offer, Amazon ECS pricing, Compute Engine general-purpose machine pricing, Disk and image pricing, Network pricing. See the service catalog for operation coverage, supported directions and backend limitations.