International Journal of Science, Engineering and TechnologyAuthors: Srujana Parepalli
Abstract: Enterprises operating large-scale data integration platforms increasingly face the challenge of migrating legacy Extract-Transform-Load (ETL) workloads to cloud environments without disrupting mission-critical data pipelines that underpin analytics, regulatory reporting, and operational decision-making. Traditional ETL systems such as Informatica PowerCenter were architected around centralized, on-premise execution engines, tightly coupled metadata repositories, and fixed infrastructure assumptions, making direct cloud migration non-trivial due to concerns around data gravity, security, latency, and governance. As cloud computing matured and Integration Platform as a Service (iPaaS) offerings emerged, organizations began adopting hybrid and cloud-native integration patterns that decouple control and execution, allowing scalability and operational flexibility while preserving data locality and compliance. This article examines cloud migration patterns for legacy ETL workloads using Informatica technologies, with a particular focus on the architectural evolution from on-premise PowerCenter deployments to Informatica Cloud and early Informatica Intelligent Cloud Services (IICS). Drawing on industry documentation, publicly available architectural diagrams, and foundational cloud migration and data integration studies published between 2000 and 2017, the paper categorizes common migration strategies, evaluates their architectural trade-offs in terms of performance, security, and maintainability, and presents practical patterns for phased, hybrid, and incremental cloud adoption in enterprise data integration landscapes.
DOI: https://doi.org/10.5281/zenodo.18081146
