Workflows & DAG
Modeling sequences and dependencies. Visibility on the critical path and contention points.
En clair : We see the graph, not a list of cron jobs.
In plain terms
Coordinate without rigidifying.
We orchestrate sequences across services, processing, controls, and decisions. Workflows handle priorities, retries, delays, conditions, dependencies, and alternate paths.
Centralized monitoring and execution indicators keep control in production: what ran, what failed, what to replay, in which order.
Tool choice (Airflow, n8n, event-driven engines, custom) follows criticality, volume and the existing ecosystem. We avoid stacking competing orchestrators.
Orchestration is not a factory of opaque workflows: every path is documented, testable and observable, with runbooks for operations.
DAGModeled journeys
RetryStructured recoveries
SLAMeasured execution
RunbookStandardized response
What we do
Bring order to complexity.
Coordination mechanisms so each step lands at the right time, with the right guardrails.
Event-driven
Reactive orchestration on an event bus. Useful when the pace is driven by the field or by systems.
En clair : The workflow starts when the event arrives.
Microservices
Distributed service coordination: contracts, timeouts, circuit breakers, and execution correlation.
En clair : Services stay decoupled; the journey stays under control.
Recoveries & fallback
Alternate paths and post-incident recovery. Retries, compensations, and dead-letter queues are part of the design.
En clair : A partial failure does not stop the whole system.
Monitoring
Execution indicators, alerts and runbooks. Technical and business SLAs are tracked in the same views.
En clair : Operations know what to do without waiting for the developer.
API management
Controlled exposure of orchestrated results and services. AuthN/Z, quotas and call auditing.
En clair : What is orchestrated can be consumed safely.
Frequently asked questions
Orchestration — questions.
Do you use Airflow, n8n or custom engines?
We choose the tool based on criticality, volume, and existing ecosystem — including custom engines when needed. What matters is operational coherence.
How do you manage partial failures?
Through retries, dead-letter queues, compensations, and alternative paths documented in the workflow. Each strategy is tested—not improvised in a crisis.
Can we mix batch and event-driven?
Yes. Many platforms combine scheduled triggers and events. We clarify boundaries to avoid double execution.
How do you avoid the “black box” effect?
Graph visibility, correlated logs, per-step metrics and living documentation. An opaque workflow is an operational risk.
Who operates the workflows day to day?
Depending on the model: RDMC teams for keep-in-operational-condition (MCO), client teams with knowledge transfer, or co-operation. Runbooks and alerts are adapted to the chosen mode.
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