Framework-aware query orchestration for Angular micro-frontends: a type-safe approach to GraphQL deduplication and performance optimization

Graph-based micro-frontend architectures often face redundant data fetching, inconsistent schema enforcement, and delayed load times in modular applications. A framework-aware query orchestration system addresses these challenges through compile-time and runtime optimizations. During compilation, Angular component dependencies are mapped to GraphQL schema fields, enabling type-safe access, preventing over-fetching, and validating schema compliance before execution. At runtime, cryptographic query fingerprinting, route-based prefetching, and lifecycle- aware caching consolidate identical requests, reducing application programming interface (API) calls from 8.2 to 3.1 per session (−62%) and improving cache hit rates from 12% to 89%. Evaluations on synthetic benchmarks and a production-grade healthcare dashboard demonstrate reductions in redundant queries (−67%), bundle size (−24%), and Time to Interactive from 3.5 to 1.8 s (−49%), while eliminating Total Blocking Time. Type-safe integration further minimizes runtime errors (−92%) and accelerates schema migrations (−85%), while centralized query management reduces boilerplate code by 67%, improving developer productivity. Resource audits indicate potential payload savings of over 5 MB through compression, minification, and removal of unused assets. In a realistic Angular micro-frontend case study, the orchestrator reduced redundant GraphQL requests and manual query coordination by up to 87% relative to a production-calibrated Apollo Client baseline, with statistically significant improvements in Time-to-Interactive (TTI) under diverse network conditions.

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Publication Details

Journal
PeerJ Computer Science
Published
2026-02-24
DOI
https://doi.org/10.7717/peerj-cs.3650
Primary Topic
Scientific Computing and Data Management
Type
article
Field-Weighted Citation Impact
0.00
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article

Framework-aware query orchestration for Angular micro-frontends: a type-safe approach to GraphQL deduplication and performance optimization

Shrinivass A. Balasubramanian
PeerJ Computer Science
Scientific Computing and Data Management
article

Framework-aware query orchestration for Angular micro-frontends: a type-safe approach to GraphQL deduplication and performance optimization

Shrinivass A. Balasubramanian
article en

Abstract

Graph-based micro-frontend architectures often face redundant data fetching, inconsistent schema enforcement, and delayed load times in modular applications. A framework-aware query orchestration system addresses these challenges through compile-time and runtime optimizations. During compilation, Angular component dependencies are mapped to GraphQL schema fields, enabling type-safe access, preventing over-fetching, and validating schema compliance before execution. At runtime, cryptographic query fingerprinting, route-based prefetching, and lifecycle- aware caching consolidate identical requests, reducing application programming interface (API) calls from 8.2 to 3.1 per session (−62%) and improving cache hit rates from 12% to 89%. Evaluations on synthetic benchmarks and a production-grade healthcare dashboard demonstrate reductions in redundant queries (−67%), bundle size (−24%), and Time to Interactive from 3.5 to 1.8 s (−49%), while eliminating Total Blocking Time. Type-safe integration further minimizes runtime errors (−92%) and accelerates schema migrations (−85%), while centralized query management reduces boilerplate code by 67%, improving developer productivity. Resource audits indicate potential payload savings of over 5 MB through compression, minification, and removal of unused assets. In a realistic Angular micro-frontend case study, the orchestrator reduced redundant GraphQL requests and manual query coordination by up to 87% relative to a production-calibrated Apollo Client baseline, with statistically significant improvements in Time-to-Interactive (TTI) under diverse network conditions.

PeerJ Computer ScienceVol. 12
Shrewsbury College (GB)
Decent work and economic growth
Openalex Percentile: Top 48%
Scientific Computing and Data Management
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