Deploying OpenLab in the Cloud

Significance of the Topic

Adopting cloud infrastructure for analytical data systems transforms capital-intensive on-premises operations into flexible, operational-expense services. This shift enables laboratories to centralize IT management, outsource routine maintenance, scale resources on demand and optimize total cost of ownership.

Aims and Overview of the Article

This technical overview outlines how to deploy Agilent OpenLab Server and ECM XT in a hybrid private cloud using Amazon Web Services (AWS) and Microsoft Azure. It summarizes supported configurations, network requirements and performance considerations to guide informed planning and implementation.

Methodology and Instrumentation

The deployment model separates acquisition instruments on-premises from server and storage in the cloud. Supported cloud services include AWS Relational Database Service (PostgreSQL), EC2 virtual machines, S3 object storage and Azure D-Series VMs. Connectivity options are site-to-site VPN or cloud-specific private links. Network performance targets are 1 Gbps bandwidth, ~45 Mbps throughput and latency under 10 ms between cloud instances.

Used Instrumentation

• OpenLab ECM XT v2.6 or higher
• AWS RDS for PostgreSQL
• AWS EC2 (e.g. m7a.2xlarge for all-in-one configurations)
• AWS S3 storage
• Microsoft Azure D-Series virtual machines
• Virtual Private Cloud (VPC) with Elastic Network Adapter (ENA) for low latency

Main Findings and Discussion

Testing confirms full support for AWS RDS, EC2 and S3 as well as Azure VMs in hybrid architectures. Utilizing AWS ENA optimizes throughput and reduces CPU load on instances. On-premises to cloud links exhibit 30–80 ms latency, while intra-cloud latency remains below 10 ms. China-region clouds are not supported.

Benefits and Practical Applications

• Shifts IT costs from capital expenditure to operational expense
• Scales storage and compute dynamically to match workload demands
• Reduces in-house data center maintenance and hardware refresh cycles
• Allows centralized management of analytical data systems across multiple sites

Future Trends and Applications

As cloud services evolve, improved network fabrics, automated deployment pipelines and containerization will further streamline analytical workflows. Integration with AI-driven analytics and edge computing will enable real-time data processing and deeper insights directly at the instrument level.

Conclusion

Deploying OpenLab in a hybrid private cloud offers significant agility, cost savings and centralized control. Success depends on careful network design, selection of appropriate IaaS configurations and partnership with a vendor that provides detailed installation guidance. Agilent’s standard services and support agreements help ensure a smooth transition to cloud-based analytical infrastructures.