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The backend is where most digital products break in production. Wrong schema, missing index, brittle integration, silent failure, nine-figure scale with four-person ownership. We build backends for Southeast Asian enterprises and founders that survive all four: service topology designed for failure, data platforms that respect UU PDP and BI sovereignty rules, observability wired in before first deploy, and handover that leaves your team in control.
Indonesian production is a specific environment. Payment flows under BI-FAST and SNAP. Access rules under UU PDP. Regulated sector data under OJK, BI, BPJPH, or SATUSEHAT. Scale that moves from 'pilot' to 'a million transactions a day' in a single marketing campaign. We build backends that handle all of this: service topology with explicit failure modes, event pipelines with retry and dead-letter discipline, data platforms with access controls that pass audit, and the observability that tells you when something is wrong before your customer does.
Four phases that treat observability, failure modes, and handover as primary design inputs.
Domain and load profile. What services exist today (or need to)? Where are the scale pressures: read-heavy, write-heavy, integration-heavy, regulatory-heavy? Which downstream integrations and regulators have to be respected? Where are the current failure modes?
Service topology, data model, event schema, integration patterns, and observability decisions, together, before any code. We design for explicit failure modes: what happens when a downstream dependency is slow, down, or wrong? Idempotency, retries, dead letters, circuit breakers, decided in the design review, not discovered in production.
Senior backend engineers shipping production services with CI, testing pyramids, infrastructure-as-code, and observability from the first deploy. Incremental rollout, feature flags, and SLOs: not aspirational, measured.
Handover to your engineering and SRE teams. Runbooks, on-call playbooks, incident-response templates, cost and performance dashboards. Your team owns the backend, with our support available for upgrades, incident response, and the architectural decisions that come up six months in.
Four disciplines that together make a backend survive Indonesian production.
Microservices, modular monoliths, or hybrid, chosen per product, not per trend. Explicit service boundaries, contract-tested APIs, versioned schemas, and the failure-mode decisions built into the design review.
Event-driven integration where it fits. Kafka / NATS / SQS + SNS. Idempotent producers, retry with exponential backoff, dead-letter queues, and event replay: production-grade, not patched after the first incident.
OLTP + OLAP + CDC. Data masking and access controls for UU PDP. Warehouse modeling, semantic layer, and the governance that makes analytics trustworthy. Regulator-ready audit exports built in.
Distributed tracing, structured logging, metrics with actionable alerting, SLOs with error budgets, on-call rotations with runbooks. The operational layer that turns a shipped backend into a system your team can run.
For clients running production systems at scale, we embed senior backend engineers, DevOps leadership, and SRE talent, including fractional Head of Engineering and Head of Platform roles. Sprout already runs engineering departments for several clients on this model. Part of our augmented-teams offering.
Explore the augmented-teams model →The systems behind the products, built for regulated scale, not happy-path demos.
The backend behind Setara: spatial data pipelines, decision-intelligence services, and real-time recommendations for telecom infrastructure operations. Observable, regulated-sector-aware, built to survive carrier-grade load.
Production backend for maritime shipping logistics: cargo tracking, scheduling, document flows, multi-party integration. Built for the operational reality of Indonesian ports and regulator-aware data handling.
UU PDP (effective Oct 2024) sets legal requirements for access control, data-subject requests, and cross-border transfer on every system that touches personal data. OJK April 2025 guidance adds audit-trail requirements for AI decisioning. BI requirements govern payment flows. Indonesian backends shipped without this in the architecture create compliance findings by default.
The architectural decisions that make UU PDP compliance a property of your backend rather than a ticket on the backlog. Data-subject endpoints, access-control patterns, audit logging, cross-border controls.
The framework we use to choose between modular monolith and microservices in SEA contexts. Team size, scale profile, and compliance surface as the decision variables, not fashion.
The observability stack we wire into backends from the first deploy: traces, logs, metrics, SLOs. The difference between 'we shipped' and 'we're running.'
Tell us the state: a new production system, a legacy modernization, a platform under scale pressure, a compliance remediation. We'll scope an engagement sized to the problem, with observability and handover discipline in scope. Worst case, you get a clear no and a short memo on what to fix first. Best case, you get a backend partner who treats your production as seriously as you do, with OJK, BI, and UU PDP as design inputs, not afterthoughts.
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