A candidate runtime for validation, authorization, and forwarding at the regional boundary.
Design constraint. Keep CPU-heavy inference and transcoding on suitable compute. Runtime limits and dependency compatibility require workload tests.
Platform / Engineering approach
Clear boundaries.
Connected systems.
Engineering the infrastructure behind intelligent applications. A modular platform direction with explicit responsibilities, observable decisions, and deliberate deployment choices.
Architecture preview
One request path. Complementary layers.
- 01
Application
Request and user context
- 02
Edge
Regional policy boundary
- 03
Gateway
Model routing and adapters
- 04
Provider
Inference execution
Telemetry branch
Pulse
Request spans → Redaction & sampling → Storage → Analytics
Execution branch
Flow
Event acceptance → Queue → Workers → State → Callback
Gateway and Media continue existing development projects. Pulse and Flow are concepts; Edge is research. This diagram is a proposed architecture, not a deployed service map.
Responsibility model
Each layer has a job.
Separate responsibilities keep the request path clear: the application owns the experience, while each infrastructure layer handles a specific concern.
- Your applicationApplication boundary
- Own the user experience and define the workload. Keep credentials, execution deadlines, and sensitive data handling explicit.
- ASTER EdgeRequest policy
- Research into lightweight regional validation and policy evaluation. Global state remains with an explicit owner.
- ASTER GatewayModel access
- The core development project: consistent request contracts, configurable routing, and provider isolation.
- ASTER PulseRequest intelligence
- A proposed telemetry path for traces, usage attribution, and explanations of routing and failure behavior.
- ASTER FlowAsynchronous execution
- A proposed event and job path for bounded steps, persisted state, and recoverable callbacks.
- Asteria MediaApplication workloads
- A development project exploring library experience, storage ownership, and media delivery.
Deployment research
Choose the runtime for the responsibility.
Cloudflare offers useful building blocks for parts of this architecture. These are integration candidates, not existing deployments or a partnership. The current website runs on Next.js and Vercel.
A candidate object store for source assets, thumbnails, and experiment artifacts, accessed through a storage adapter.
Design constraint. Define access policy, lifecycle rules, and recovery separately. Validate range requests and cache behavior for media delivery.
A candidate SQL store for a small library index, job references, or configuration records where workload limits fit.
Design constraint. Avoid treating it as an unlimited telemetry warehouse. Query patterns, database limits, and migration strategy need evaluation.
A candidate transport between event acceptance and background consumers, with retries and dead-letter handling.
Design constraint. Delivery is at least once and ordering is not guaranteed. Consumers need idempotency and an explicit state model.
A candidate for per-workflow coordination or a narrowly scoped quota authority with consistent attached storage.
Design constraint. Model the coordination key carefully. A single hot key can concentrate work; state location affects the request path.
A potential source of runtime diagnostics alongside application-level, OpenTelemetry-compatible request instrumentation.
Design constraint. Define sampling, retention, redaction, and export requirements. Platform diagnostics alone cannot explain every product-level decision.
Reference documentation reviewed October 2026. Service limits and workload fit must be checked during implementation.
Operational design
Reliability is more than a runtime.
Own the state
Define where configuration, workflow checkpoints, and source assets live. Document consistency requirements, backups, and restore paths.
Design the failure path
Set deadlines, classify retryable errors, and isolate side effects. Test duplicate events and uncertain provider outcomes before increasing scale.
Measure the actual workload
Compare deployment patterns with controlled tests. Regional proximity, caching, and serverless execution are choices to evaluate, not automatic performance guarantees.
Engineering principles
A shared way of building.
API-first boundaries
Define contracts and failure behavior before adding integrations. A clear interface makes a system easier to change.
Modular by responsibility
Separate routing, telemetry, execution, and storage so each layer can be understood and tested independently.
Observable decisions
Record why a route or retry was chosen. Metrics are useful when they explain a request, not just decorate a dashboard.
Deployment ownership
Keep operational tradeoffs visible: configuration, backups, secrets, and recovery belong in the design.
Reproducible evidence
Use explicit configurations and controlled experiments. Distinguish a proposal from a measured result.
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