Runtime
The operational foundation that runs the BullSequana AI platform
Runtime is the foundational layer of BullSequana AI. It brings together the essential services needed to run data and AI workloads in production, with built-in support for networking, security, storage, inference, observability, and delivery automation.
It is the most basic data and AI level of the platform: the secure, reliable base that higher-level services build on to move faster and scale with confidence.
Who This Section Is For
This section is mainly useful for:
- platform engineers
- infrastructure and Kubernetes operators
- security and networking teams
- SRE and observability-oriented roles
Helpful background includes Kubernetes operations, networking, access control, storage, and production platform support.
What Runtime Is
Runtime is the shared platform layer responsible for:
- networking and service exposure
- identity, authentication, and authorization
- secret management and security controls
- model inference execution and supporting operators
- workflow orchestration and event handling
- operational data stores and artifact storage
- monitoring, logging, tracing, and debugging
- CI/CD and release automation
In practical terms, Runtime is the set of components that keeps the platform running.
How Runtime Fits in the Platform
Runtime provides the core operational capabilities used by the rest of the platform:
- CoreAI builds AI-facing services and developer capabilities on top of Runtime.
- ProAI adds enterprise data, analytics, and large-scale data operations.
- Use cases combine these layers into applications that deliver business value.
Runtime Capability Areas
The Runtime layer is organized around several operational capability domains.
| Capability area | Purpose | Example components |
|---|---|---|
| Network | Expose, route, and protect platform traffic | APISIX, MetalLB, NGINX, External DNS, cert-manager |
| Access and security | Manage identities, permissions, and secrets | Keycloak, OpenFGA, OpenBao |
| Inference | Run and support model-serving workloads | KubeAI, vLLM, FasterWhisper |
| Workflows and automation | Coordinate asynchronous and durable processes | Argo Events, Temporal |
| Data and storage | Persist operational state and artifacts | PostgreSQL, PgAdmin, MinIO |
| Monitoring and debugging | Observe health, logs, metrics, and traces | Grafana, Prometheus, Loki, Alloy, Tempo |
| Continuous integration and delivery | Build, version, publish, and deploy platform changes | Harbor, GitLab, Argo CD |
Together, these components form the execution environment used by the rest of the BullSequana AI platform.
Why Runtime Matters
Without Runtime, the platform would have no consistent way to:
- expose services to users and other systems
- secure access across users, services, and environments
- execute AI inference workloads in production
- orchestrate workflows and automations
- store artifacts, metadata, and operational state
- monitor reliability, performance, and incidents
- deliver updates safely and repeatedly
Runtime therefore acts as the base layer for platform operations. It is essential infrastructure, even when the user-visible value is delivered somewhere else in the stack.