Service level agreements
Listed terms cover requests sent through this service adapter. They do not cover direct connections to the target service or replace the cloud provider’s own SLA. Each origin-to-target pair has its own terms or an explicit pending status. See the SLA tables, measurement rules, and scaling conditions.EC2 Control Plane to Virtual Machines
Adapter-added latency. A + prefix marks time added by the adapter, not the total time your application waits. Total request time includes adapter processing, backend service time and network time. The backend provider’s SLA applies independently. Only separately measured target-service wait may be subtracted, and only when your agreement permits it; internal metadata, coordination and retry processing still count. For one request, 12 ms of adapter processing plus 90 ms waiting for the backend means at least 102 ms total. This example does not add monthly p99 values.
What Tensor9 covers. These service levels cover the adapter between the origin API and target API. They do not replace the target provider’s SLA.
How latency is counted. Adapter work, including metadata and coordination, counts. Only separately measured permitted target waits are excluded.
Which terms apply. Your signed agreement names the covered operations, workload limits, remedies, and final service levels for your deployment.
What this adapter does
Local metadata and self-discovery are synthesized from the resolved deployment without a cloud round trip. Fleet reads and lifecycle mutations use the control-plane record/reconcile path for azure::1.0.0::vm. Native VM or disk creation time is reported as readiness, not hidden inside the adapter processing estimate.How the latency targets were chosen
Bounded self and fleet resource reads: +10 ms monthly p99 (adapter-added).DescribeInstanceTypes, DescribeInstances, DescribeTags, DescribeVolumes. Bounded indexed reads and page assembly.
Instance and volume lifecycle admission: +20 ms monthly p99 (adapter-added). CreateTags, DeleteTags, DescribeInstanceAttribute, ModifyInstanceAttribute, RunInstances, TerminateInstances. Validation, durable desired-state commit and reconciliation scheduling.
Your signed agreement sets the terms for your deployment. A target does not add an operation or option that the compatibility tables mark unavailable.
What counts toward latency
For a request-response row, measure from the agreed ingress boundary to dispatch of the complete response. A row that explicitly names a first response chunk ends at that chunk; its number does not cover the rest of the stream. A long-poll row names the intentional wait and when adapter delay starts. Include parsing, authorization, admission, translation, serialization, adapter-owned storage and coordination, retries and response handling. Subtract only separately measured target-workload waits and external network segments allowed by the measurement rules. The adapter’s own response handling and dispatch remain covered. A database used for adapter metadata is still adapter work, even if a cloud provider hosts it. For concurrent calls, exclude the union of permitted wait intervals, not the sum of overlapping spans. Calculate each request’s adapter duration first, then the monthly p99. Do not subtract one service’s p99 from another’s. Known adapter timeouts are over-budget samples; failed or incomplete requests cannot disappear to improve the percentile. Missing measurements do not become zero latency. An SDK call span alone does not prove how much of its duration can be excluded.Endpoint reachability and request failures
The endpoint-reachability target measures adapter health checks. Correctly forwarding a target quota or permission error is different from producing that error because the adapter sent the wrong request. Adapter-caused failures remain Tensor9’s responsibility even when the target is healthy. Correctness and data-integrity requirements apply to every supported request. Endpoint reachability does not measure request correctness or grant an allowance for incorrect results.Scaling and target-service capacity
Self-discovery scales per host and should remain independent of fleet size. Fleet lists are bounded pages; lifecycle writes serialize per resource identity while unrelated instances and volumes reconcile concurrently. Qualification fixes filter count, returned resources, tag count and mutation fan-out. Tell Tensor9 the expected steady rate, bursts, concurrency, payload sizes and operation mix. Tensor9 sizes and scales the adapter for the agreed load; you choose and monitor the target service’s capacity with Tensor9’s help. A latency budget is not a requests-per-second rating. Larger requests and higher rates need explicit terms, not silent inheritance of a small-request SLA.Data and behavior guarantees
IMDS and describe responses identify the same instance, network and attached resources. Lifecycle success means desired state is durably recorded, IDs are stable, foreign resources are not exposed, and unsupported mutation forms fail before partial target changes.Example and diagnosis
DescribeInstances for the calling VM is a local identity read. RunInstances records one bounded launch request and returns an adapter identity; the target VM becoming ready is a separate state transition. A later DescribeInstances must report that same identity and observed readiness. Usetensor9 explain and the documented explain headers to understand the selected adapter and its behavior. Correlate available request diagnostics with the target provider’s latency, throttling and capacity metrics. An explain report helps diagnose a request; it is not by itself a qualified SLA timing measurement. Share the operation, request shape, timestamps and request identifiers with support, with credentials and customer payloads removed.
EC2 Control Plane to Compute Engine
Adapter-added latency. A + prefix marks time added by the adapter, not the total time your application waits. Total request time includes adapter processing, backend service time and network time. The backend provider’s SLA applies independently. Only separately measured target-service wait may be subtracted, and only when your agreement permits it; internal metadata, coordination and retry processing still count. For one request, 12 ms of adapter processing plus 90 ms waiting for the backend means at least 102 ms total. This example does not add monthly p99 values.
What Tensor9 covers. These service levels cover the adapter between the origin API and target API. They do not replace the target provider’s SLA.
How latency is counted. Adapter work, including metadata and coordination, counts. Only separately measured permitted target waits are excluded.
Which terms apply. Your signed agreement names the covered operations, workload limits, remedies, and final service levels for your deployment.
What this adapter does
Local metadata and self-discovery are synthesized from the resolved deployment without a cloud round trip. Fleet reads and lifecycle mutations use the control-plane record/reconcile path for google::1.0.0::compute::instance. Native VM or disk creation time is reported as readiness, not hidden inside the adapter processing estimate.How the latency targets were chosen
Bounded self and fleet resource reads: +10 ms monthly p99 (adapter-added).DescribeInstanceTypes, DescribeInstances, DescribeTags, DescribeVolumes. Bounded indexed reads and page assembly.
Instance and volume lifecycle admission: +20 ms monthly p99 (adapter-added). CreateTags, DeleteTags, DescribeInstanceAttribute, ModifyInstanceAttribute, RunInstances, TerminateInstances. Validation, durable desired-state commit and reconciliation scheduling.
Your signed agreement sets the terms for your deployment. A target does not add an operation or option that the compatibility tables mark unavailable.
What counts toward latency
For a request-response row, measure from the agreed ingress boundary to dispatch of the complete response. A row that explicitly names a first response chunk ends at that chunk; its number does not cover the rest of the stream. A long-poll row names the intentional wait and when adapter delay starts. Include parsing, authorization, admission, translation, serialization, adapter-owned storage and coordination, retries and response handling. Subtract only separately measured target-workload waits and external network segments allowed by the measurement rules. The adapter’s own response handling and dispatch remain covered. A database used for adapter metadata is still adapter work, even if a cloud provider hosts it. For concurrent calls, exclude the union of permitted wait intervals, not the sum of overlapping spans. Calculate each request’s adapter duration first, then the monthly p99. Do not subtract one service’s p99 from another’s. Known adapter timeouts are over-budget samples; failed or incomplete requests cannot disappear to improve the percentile. Missing measurements do not become zero latency. An SDK call span alone does not prove how much of its duration can be excluded.Endpoint reachability and request failures
The endpoint-reachability target measures adapter health checks. Correctly forwarding a target quota or permission error is different from producing that error because the adapter sent the wrong request. Adapter-caused failures remain Tensor9’s responsibility even when the target is healthy. Correctness and data-integrity requirements apply to every supported request. Endpoint reachability does not measure request correctness or grant an allowance for incorrect results.Scaling and target-service capacity
Self-discovery scales per host and should remain independent of fleet size. Fleet lists are bounded pages; lifecycle writes serialize per resource identity while unrelated instances and volumes reconcile concurrently. Qualification fixes filter count, returned resources, tag count and mutation fan-out. Tell Tensor9 the expected steady rate, bursts, concurrency, payload sizes and operation mix. Tensor9 sizes and scales the adapter for the agreed load; you choose and monitor the target service’s capacity with Tensor9’s help. A latency budget is not a requests-per-second rating. Larger requests and higher rates need explicit terms, not silent inheritance of a small-request SLA.Data and behavior guarantees
IMDS and describe responses identify the same instance, network and attached resources. Lifecycle success means desired state is durably recorded, IDs are stable, foreign resources are not exposed, and unsupported mutation forms fail before partial target changes.Example and diagnosis
DescribeInstances for the calling VM is a local identity read. RunInstances records one bounded launch request and returns an adapter identity; the target VM becoming ready is a separate state transition. A later DescribeInstances must report that same identity and observed readiness. Usetensor9 explain and the documented explain headers to understand the selected adapter and its behavior. Correlate available request diagnostics with the target provider’s latency, throttling and capacity metrics. An explain report helps diagnose a request; it is not by itself a qualified SLA timing measurement. Share the operation, request shape, timestamps and request identifiers with support, with credentials and customer payloads removed.