As organizations increasingly adopt multi-cloud architectures, they face growing challenges in managing data pipelines, enforcing governance, and maintaining performance across hybrid environments. Recently a global industrial technology company transitioned from Pentaho Data Integration Community Edition (CE) to our Enterprise Edition (EE) to address the scalability, governance, and operational efficiency challenges in their multi-cloud data integration framework.

Scaling Beyond Pentaho Data Integration Community Edition 

For years, the organization had relied on Pentaho CE 8.3 to orchestrate ETL processes. However, as data volumes surged and operational demands grew, the limitations of the open-source edition became all too apparent.

• Fragmented repository management made version control and artifact promotion difficult.
• Limited orchestration capabilities led to inefficiencies and bottlenecks in data movement.
• A lack of high-availability execution increased the risk of failures in a distributed environment.
• Inefficient hybrid cloud processing required better integration between on-premise servers and cloud storage solutions like Azure Blob Storage.

The company initiated an upgrade plan to move from Pentaho Data Integration CE to EE for enhanced scalability, governance, and hybrid-cloud performance.

More Than Just an Upgrade

The migration process was more than a software upgrade – it was a complete architectural transformation that would propel the company forward. The transition focused on three key initiatives: scalable execution, stronger governance, and improved operational visibility.

1. Establishing a Scalable Execution Framework

A major concern was job execution efficiency, especially with large-scale batch processing. The old system lacked dynamic workload balancing, causing resource contention and failures.

The new execution model uses Tray Server as a load balancer, to monitor server availability and assign jobs dynamically to the best Carte server. This improved workload distribution and ensured high availability. Performance was further improved by:

• Implementing a slot-based scheduling system for larger jobs to request more resources.
• Using a hybrid execution strategy to map Azure Blob Storage directly to Carte servers, reducing data movement.
• Streamlining Snowflake integration for better ingestion and data processing efficiency.

2. Strengthening Governance and Security

Governance played a pivotal role in the migration journey. Previously, the company’s file-based repository lacked centralized control, posing challenges in enforcing security policies and maintaining version control standards.

With the new system, governance was enhanced through several key measures:

• LDAP Authentication replaced the old manual user management system, allowing for centralized identity management.
• Role-Based Access Control (RBAC) provided granular permissions tailored for different user roles and job executions, enhancing security and compliance.
• Git-backed CI/CD workflows ensured a structured artifact promotion across development, testing, and production environments, bringing consistency and reliability to deployments.

The new deployment pipeline followed a structured approach, eliminating inconsistencies and facilitating faster issue resolutions in:

• Development: Code was maintained in local Git repositories with file-based storage.
• Testing: Artifacts were pushed to a Pentaho EE repository for thorough validation.
• Production: Deployments were orchestrated using the Pentaho job scheduler, with Tray overseeing execution to ensure smooth operations.

This structured approach streamlined governance and significantly enhanced the reliability and efficiency of job executions.

3. Improving Operational Efficiency and Observability

Before the migration, the company struggled with limited visibility into job performance and failures. The upgrade delivered key improvements, including:

• With the Pentaho Scheduler for centralized job management all job executions were orchestrated, which also means they came equipped with monitoring and retry mechanisms to ensure smooth and consistent operations.
• A dedicated logging database was deployed alongside Pentaho EE, meticulously capturing job execution metrics. From these custom dashboards were created, providing real-time visibility into the status of each job, making it easier to identify bottlenecks and performance issues swiftly.
• An OpsMart framework was introduced for performance monitoring. This framework offered pre-built reports and dashboards that detailed ETL execution performance, providing invaluable insights into the system’s operations.

Achieving A Robust, Scalable Multi-Cloud Data Integration Framework

The transition to Pentaho Data Integration Enterprise Edition yielded multiple measurable improvements in performance and governance.

• Job execution became 30% faster, thanks to parallelized workloads and optimized execution nodes.
• Governance and security improved dramatically, ensuring corporate compliance with role-based access controls.
• Automated workload balancing through Tray and Carte significantly reduced job failures.
• Enhanced monitoring and logging provided real-time insights into system performance and job execution health.

The structured transition to Pentaho Data Integration Enterprise Edition not only enhanced execution efficiency but also fortified the company’s governance framework. For any enterprise facing scalability and governance challenges in a multi-cloud environment, Pentaho Data Integration Enterprise Edition presents a robust solution for achieving greater efficiency, reliability, and security.

For enterprises facing scalability or governance challenges in multi-cloud environments, contact Pentaho Services to learn more about building your own path to greater efficiency, reliability, and security.