Cost-Optimal Dynamic Provisioning of Ephemeral Microservice Environments in Distributed Continuous Integration Pipelines
Keywords:
Blast Radius Provisioning, Continuous Integration, Directed Acyclic Graph, Ephemeral Environments, Kubernetes Operator, Microservices, Spot InstancesAbstract
Integration testing within distributed microservice CI pipelines presents a persistent infrastructure dilemma: shared static staging environments serialize developer workflows and generate cross-team contamination, while statically replicated parallel environments consume cloud resources linearly with team growth. Neither approach scales economically or operationally at enterprise scale. This paper presents an automated framework that resolves this trade-off by provisioning per-pull-request ephemeral environments constrained to a blast radius sub-graph derived from a statically analyzed service dependency Directed Acyclic Graph (DAG). A custom Kubernetes Operator maps each incoming code mutation to the minimal set of affected services, provisions them onto serverless spot-instance backends, and replaces out-of-scope dependencies with dynamically generated mock interfaces, achieving near-zero idle infrastructure cost. Evaluation against the DeathStarBench Social Network workload — 420 pull requests simulated over 24 hours across a 27-service polyglot topology — demonstrates 74.02% infrastructure cost savings against static staging and consistent provisioning latency below four minutes regardless of total service catalog size. Total infrastructure spend under the proposed framework was $73.80, compared to $284.10 for the static baseline and $198.50 for a naive ephemeral model. These results establish that dependency-aware orchestration eliminates the staging dichotomy without reintroducing the scheduling bottlenecks characteristic of naive full-environment ephemeral strategies.
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