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.MySQL Flexible Server to RDS MySQL
Deployment availability. These targets describe this adapter design. Confirm that your deployment supports the listed operations; a numerical target does not establish runtime availability.
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
Foraws::1.0.0::rds::mysql, Azure Flexible Server management requests create and configure the corresponding managed PostgreSQL or MySQL service. Native SQL traffic goes to the target engine; these numbers apply to management acceptance and configuration handling. High-availability selection can map to the target’s HA option without making the target’s failover duration part of the adapter request budget. These targets describe this adapter design; confirm that your deployment supports the listed operations. A numerical target does not establish runtime availability.
How the latency targets were chosen
Flexible Server changes: 30 ms monthly p99.Servers_Create, Servers_Delete, Servers_Update. Validate the origin request, retain its resource identity and requested configuration, and construct the target change. Adapter-owned metadata and coordination waits remain included.
Database and server configuration: 20 ms monthly p99. Configurations_Update, Databases_Create, Databases_Delete, FirewallRules_CreateOrUpdate, FirewallRules_Delete. Bounded configuration validation, durable adapter metadata and response encoding; native provisioning completion and propagation are separate.
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.Availability and failures
The 99.9% request target measures correct adapter handling, not the percentage of application calls that return success. Correctly forwarding a target quota or permission error is different from producing that error because the adapter sent the wrong request. Adapter-caused failures count even when the target is healthy. With 1,000,000 eligible calls in a month, a 99.9% target permits at most 1,000 adapter-attributable failures. Endpoint probes have their own denominator. Correctness defects remain actionable even when the monthly availability percentage is met.Scaling and target-service capacity
Scale API handlers and background workers separately. The agreement bounds resource count, concurrent changes, status polling, configuration size and burst growth. More replicas do not remove a shared metadata-store bottleneck or a target API quota. Tensor9 is responsible for adapter capacity within that envelope; the customer supplies target capacity and permissions. Native resource readiness is monitored separately from request acceptance. Keep native SQL connection and storage sizing separate from control-plane request rate. A deployment burst that creates many databases stresses provider quotas and adapter reconciliation differently from a busy existing database. 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
Return truthful accepted/pending/failed status and enforce the target’s allowed flags, versions and extension set. Azure-specific identity mechanisms outside the profile must not be presented as working logins. Database creation does not transfer source data or backup history. Configuration requests must apply to the intended server even after retries or name reuse.Example and diagnosis
Update an allowed setting onorders-db and create one database. The configuration row covers validation and recorded changes, while a required restart completes later. Test the application’s connection and extension-dependent queries separately; their native execution latency is not measured by this management SLA.
Use tensor9 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.
MySQL Flexible Server to Cloud SQL for MySQL
Deployment availability. These targets describe this adapter design. Confirm that your deployment supports the listed operations; a numerical target does not establish runtime availability.
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
Forgoogle::1.0.0::cloudsql::mysql, Azure Flexible Server management requests create and configure the corresponding managed PostgreSQL or MySQL service. Native SQL traffic goes to the target engine; these numbers apply to management acceptance and configuration handling. High-availability selection can map to the target’s HA option without making the target’s failover duration part of the adapter request budget. These targets describe this adapter design; confirm that your deployment supports the listed operations. A numerical target does not establish runtime availability.
How the latency targets were chosen
Flexible Server changes: 30 ms monthly p99.Servers_Create, Servers_Delete, Servers_Update. Validate the origin request, retain its resource identity and requested configuration, and construct the target change. Adapter-owned metadata and coordination waits remain included.
Database and server configuration: 20 ms monthly p99. Configurations_Update, Databases_Create, Databases_Delete, FirewallRules_CreateOrUpdate, FirewallRules_Delete. Bounded configuration validation, durable adapter metadata and response encoding; native provisioning completion and propagation are separate.
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.Availability and failures
The 99.9% request target measures correct adapter handling, not the percentage of application calls that return success. Correctly forwarding a target quota or permission error is different from producing that error because the adapter sent the wrong request. Adapter-caused failures count even when the target is healthy. With 1,000,000 eligible calls in a month, a 99.9% target permits at most 1,000 adapter-attributable failures. Endpoint probes have their own denominator. Correctness defects remain actionable even when the monthly availability percentage is met.Scaling and target-service capacity
Scale API handlers and background workers separately. The agreement bounds resource count, concurrent changes, status polling, configuration size and burst growth. More replicas do not remove a shared metadata-store bottleneck or a target API quota. Tensor9 is responsible for adapter capacity within that envelope; the customer supplies target capacity and permissions. Native resource readiness is monitored separately from request acceptance. Keep native SQL connection and storage sizing separate from control-plane request rate. A deployment burst that creates many databases stresses provider quotas and adapter reconciliation differently from a busy existing database. 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
Return truthful accepted/pending/failed status and enforce the target’s allowed flags, versions and extension set. Azure-specific identity mechanisms outside the profile must not be presented as working logins. Database creation does not transfer source data or backup history. Configuration requests must apply to the intended server even after retries or name reuse.Example and diagnosis
Update an allowed setting onorders-db and create one database. The configuration row covers validation and recorded changes, while a required restart completes later. Test the application’s connection and extension-dependent queries separately; their native execution latency is not measured by this management SLA.
Use tensor9 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.