Monitored pilot deployment
What evidence should you gather before authorising a pilot deployment, and how do you detect and then address degradation?
- Lovable
- Claude Code
- Codex
3500 € per session, excl. VAT
In short
Over two days, totalling 14 hours excluding breaks, you build a pilot deployment dossier for an application developed with AI assistance. You prepare configurations, check secrets, test critical user journeys and implement monitoring instrumentation. An incident simulation enables you to verify alerts, rollback and responsibilities.
Why this training?
An application that works in a demonstration can fail at deployment: inconsistent configuration, an unavailable dependency, an incompatible migration or an exposed secret. Preparation must produce verifiable evidence, not just a list of intentions. Monitoring connects technical signals to user journeys. By linking each alert to an action, an owner and a rollback procedure, the team makes simulated incidents diagnosable. Running case study: The fictional organisation Avelune Consignes is preparing a locker booking portal. In an isolated environment, the team must detect failed bookings, prevent unauthorised access and return to a stable version after a faulty change. Transfer to the workplace: Before any internal pilot, have the dossier reviewed by technical and security leads, adapt thresholds to expected usage and rehearse rollback in an authorised environment.
Objectives of this training
- Map deployment dependencies and risks.
- Build a configuration that separates environments and secrets.
- Run blocking tests on critical user journeys.
- Instrument errors, latency and availability.
- Demonstrate a rollback and document a launch decision.
Who is it for and what are the prerequisites?
Roles and tasks concerned
- Developers and technical leads for applications created with AI assistance.
- Technical product managers preparing a supervised experiment.
Prior skills
- Be able to read, modify and version-control a web application.
- Be able to run tests and interpret application logs.
- Have practical experience of assisted code generation with human review.
What you will work on
Define the pilot scope
Objective: Define launch conditions. Architecture, dependencies, critical user journeys and responsibilities.
Separate configurations
Objective: Avoid mixing environments. Variables, secrets, minimum permissions and parameters.
Review assisted changes
Objective: Maintain control over proposed code. Generation and modification based on instructions, human review, dependencies.
Build blocking tests
Objective: Verify essential user journeys. Booking, authorisation, unavailability and regression prevention.
Rehearse a release
Objective: Reproduce an isolated installation. Identifiable version, build, migrations and post-installation checks.
Instrument without exposing data
Objective: Produce actionable signals. Structured logs, correlation, errors, latency and minimisation.
Define alerts
Objective: Link degradation to intervention. Training thresholds, time windows, noise and escalation.
Simulate a failure
Objective: Assess detection and diagnosis. Controlled injection, timeline and evidence.
Test rollback
Objective: Restore a consistent version. Data compatibility, backup and limitations of reverse migrations.
Hold the launch review
Objective: Justify a conditional decision. Evidence, blocking anomalies and residual risks.
What you take away
- Instrumented prototype and documented configuration.
- Test dossier with results and anomalies.
- Monitoring dashboard with thresholds and recipients.
- Pilot deployment procedure, rollback and reasoned decision.
Method and assessment
- Short explanations followed by immediate practice on the running case study.
- Individual work followed by work in pairs, with peer review of outputs.
- Guided group discussion: what works, what needs correcting and what remains a human decision.
- Preparation: Prepare a runnable training repository, fictional or anonymised data and an isolated environment. Check access to the authorised tools: Lovable, Claude Code or Codex; consult their official documentation for available capabilities.
Observable criteria: No secret appears in the repository, AI instructions or inspected logs. ; Critical tests have a reproducible result and a blocking rule. ; An injected failure triggers the expected alert with actionable context. ; Rollback restores the reference user journey and preserves data consistency. ; The final decision distinguishes evidence obtained, residual risks and prerequisite actions..
Frequently asked questions
Do we actually deploy to production?
No, the practical work remains on an isolated prototype and prepares for a pilot.
Do we need to use all three tools?
No, one authorised tool is sufficient; its capabilities depend on its official documentation.
Can we send secrets to the assistant?
No. Use dummy values and keep secrets out of exchanges.
How is monitoring assessed?
Through a controlled failure, an observed alert and a verified restoration.
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