Managed applications
Deploy services with an appropriate scaling model.
aiqorxBackend & data / Google Cloud
Google Cloud provides managed application, data, networking, and infrastructure services.
Talk through your project
A connected engineering approach
People, tasks, accessibility
Components, logic, integrations
Data, operations, maintenance
The architecture follows your product requirements.
01 / Where it fits
Deploy services with an appropriate scaling model.
Organize analytical and application workloads.
Integrate identity and service communication.
02 / Architecture
Separate projects and permissions, plan data location, and define deployment and rollback behavior. Make service quotas visible.
Managed scaling and data services have cost and limit tradeoffs that should be tested against expected usage.
03 / Delivery & care
Test authorization, schema changes, concurrency, timeouts, and recovery. Inspect operational logs and rehearse restoring data and rolling back a release.
Review the users, existing systems, constraints, and definition of success.
Document the architecture, interfaces, risks, and delivery scope.
Review working increments against real use cases and failure conditions.
Prepare operating guidance, ownership, and a practical maintenance plan.
04 / A few useful questions
Managed scaling and data services have cost and limit tradeoffs that should be tested against expected usage.
Start with a code and architecture review. The useful outcome is a clear decision about what to keep, improve, or replace, with the dependencies and delivery risks made explicit.
The estimate depends on the workflows, integrations, platform requirements, and quality expectations. A focused discovery phase can reduce uncertainty before committing to the full build.
Agree on source ownership, documentation, monitoring, support responsibilities, and a maintenance plan as part of the engagement.
Something in mind?
Let's build