Case Study: Migrating a Legacy Monolith to Cloud‑Native Microservices — 2026 Playbook
A step-by-step playbook based on a 2025–26 migration that reduced lead time, improved observability, and cut cloud costs. Includes governance, CI patterns, and vendor selection for modern connectors.
Case Study: Migrating a Legacy Monolith to Cloud‑Native Microservices — 2026 Playbook
Hook: Migrations in 2026 succeed when teams treat the rewrite as product evolution — not an engineering purge. This case study highlights pragmatic steps, governance, and cost-control tactics proven in the field.
Project context
We worked with a mid‑market SaaS company to migrate a single codebase handling authentication, uploads, and document processing into a set of cloud-native services. The migration spanned 9 months in 2025 and delivered measurable improvements in developer velocity and operational resilience.
High-level goals
- Reduce mean time to deploy (MTTD) for new features by 60%.
- Improve observability for document workflows and batch jobs.
- Introduce cost transparency and budgets tied to feature teams.
Governance & productization
Migrations succeed when teams align around product outcomes. We introduced three governance artifacts:
- Compatibility matrix: an interface contract for service interactions (use bias‑resistant nomination rubrics to prioritize endpoints — see advanced strategy playbooks for compatibility matrices here).
- Service SLA definitions: per‑service SLAs for latency and availability, including a distinct SLA for batch processors and connectors.
- Cost SLOs: budgets per team and automated alerts when forecasted spend crosses thresholds.
CI/CD and test strategy
Use contract testing and mocking to decouple teams. We used modern mocking tools to validate service contracts in CI without flakiness (mocking & virtualization tools).
Batch & document processing
Document processing was the migration’s most sensitive area. We implemented a secure, auditable batch connector and adopted the same privacy controls recommended for document capture in Power Apps workflows (document capture privacy guidance).
Scaling remote output and support
Operational scale required a new support model: live support integrations, segmented contacts, and automated requeue tools. These tactics mirror broader case studies on scaling remote output and live support for enterprise teams (Case Study: Scaling Remote Output).
Per‑query economics & API design
APIs were redesigned to minimize tokenized per‑query charges. We introduced aggregated batch endpoints and documented quota expectations to protect customers from unexpected costs — a direct response to 2026 per‑query pricing trends (per‑query caps analysis).
Tooling selection
We prioritized tools that supported virtualization and rapid mocking, plus a low‑effort observability stack. The combination of lightweight CI mocks and runtime tracing accelerated safe rollout.
Results
- Feature lead time decreased 63% in the first three months after migration.
- Cost per document processed reduced by 38% after batching and scheduling optimizations.
- Customer reported incidents related to document privacy were reduced, thanks to manifest checks and explicit deletion APIs.
Learnings & future roadmap
Cloud migrations require product thinking. Our next steps include an on‑prem connector product and a public marketplace for curated connectors to simplify enterprise integrations. For technical leaders, this maps directly to the 2026 trend of productized connectors and enterprise AI tooling (DocScan Cloud).
Further reading
Related Topics
Elena Rivas
Director of Engineering
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