AlejandroFX
Digital ecosystem and tech platform for a trading community: product, infrastructure and 24/7 operations.
→ kubectl apply -k ./trading✓ deployment/copy-engine synced✓ deployment/signals-api healthy↻ hpa scaling 3 → 5 pods✓ grafana: latency p95 0.42s✓ rollout complete · 0 downtimeBusiness → Product → Infrastructure → Operations.
AlejandroFX is the platform and digital ecosystem of a trading brand with a community of more than 1,500 traders. The project spans the website and product experience, the copy trading system and all the cloud infrastructure that keeps it running around the clock.
A growing community running on manual hosting.
Trading real-time signals demands that nothing goes down. With manual deployments and no observability, every change was a risk and every incident a blind investigation.
Declarative infrastructure and observable operations.
We moved everything to Kubernetes with GitOps: every change is versioned in Git and deployed automatically. On top of that, a low-latency copy trading system and a full observability stack.
The architecture, top to bottom.
Each layer has a clear responsibility and is deployed independently.
Replicating a trade before the market moves.
Copy trading is a timing problem: if the copy arrives late, the price has already changed. The system listens to the lead trader's order and replicates it across subscribed accounts with minimal latency, keeping state consistent.
- Ingestion of the lead trader's signal
- Per-account validation and risk control
- Concurrent replication across subscribed accounts
- State confirmation and reconciliation
- Tracking interface for the user
Every change, versioned and reversible.
The repository describes the system's desired state. ArgoCD applies it and keeps it in sync.
See the system, don't guess it.
Metrics, logs and alerts wired into dashboards the team reviews every day.
From manual hosting to an operable platform.
The migration couldn't interrupt service: the community trades real-time signals. We went layer by layer, validating each one before moving on to the next.
- Inventory of services and dependencies
- Identification of single points of failure
- Definition of availability targets
- Users → App → Services → K8s architecture
- Environment separation
- Copy trading engine model
- Kubernetes: deployments, HPA, resources
- GitOps with ArgoCD and CI/CD pipelines
- Low-latency copy trading engine
- Metrics, logs and alerts wired up
- System health dashboards
- Actionable thresholds and alerts
What the platform looks like in operation.
Ecosystem interfaces, cluster status and monitoring dashboards.
What IDEASCOL built on this project.
A primarily engineering project: architecture, infrastructure, continuous delivery and operations.
- Layered platform architecture design
- Environment definition and deployment strategy
- Modeling of the copy trading system flow
- Infrastructure setup on Kubernetes
- Configuration of deployments, autoscaling and resources
- Secrets management and environment separation
- GitOps implementation with ArgoCD
- CI/CD pipelines and deployment automation
- Rollback strategy and zero-downtime deployments
- Observability stack: metrics, logs and alerts
- System health dashboards
- Definition of thresholds and actionable alerts
What it's built with.
What changed once it went live.
- Reproducible, zero-downtime deployments.
- Instant rollback for any incident.
- The team sees system health in real time.
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