Migrating Enterprise GIS to the Cloud: Douglas County’s AWS Journey

In 2010, the GIS Department of Douglas County, Nebraska, was responsible for maintaining a distributed server environment spread across multiple facilities. At that time, the county’s internal IT division did not yet provide a virtualized infrastructure, meaning each new application or expansion required the purchase and configuration of dedicated physical hardware. As infrastructure demands grew, the department faced additional capital expenses and longer deployment cycles.

Simultaneously, Esri began highlighting the viability of operating ArcGIS Server in cloud environments, particularly on Amazon Web Services (AWS). After evaluating the AWS platform and reviewing guidance on deploying Esri software in the cloud, the department chose to pilot a cloud-based GIS architecture.

Launching ArcGIS Server on Amazon EC2

The initial step was straightforward: establish an AWS account and associate a payment method. A virtual server was then provisioned using a preconfigured Esri Amazon Machine Image (AMI), which included ArcGIS Server and ArcGIS Desktop already installed. Amazon’s Elastic Compute Cloud (EC2) provided the virtual infrastructure necessary to host these services without purchasing new hardware.

Once connected to the EC2 instance, the team registered the ArcGIS software using its developer license. Basic validation followed. An HTML file was uploaded to the web server and accessed through a browser to confirm functionality and performance. The response time was strong, confirming that the cloud-hosted web layer performed as expected.

Next, GIS datasets were transferred to the environment using Dropbox for file synchronization. Map services were published and consumed through desktop clients as well as ArcGIS Online. These workflows functioned smoothly. Encouraged by the results, the department migrated a smaller FLEX-based web mapping application to the cloud instance and reconfigured it to consume services hosted there. That test also succeeded without complications.

Expanding to Database and Enterprise Applications

With the proof of concept validated, attention shifted toward scaling the environment. A separate geodatabase server instance was created, and Cityworks—an asset and work management system built around GIS—was installed on the web server. Cityworks Server AWS operates as a browser-based, GIS-centric application layered on top of ArcGIS Server.

By late winter 2011, Douglas County had two active EC2 instances: one supporting web services and another hosting the geodatabase. Cityworks was fully operational in the cloud. Gradually, production applications and additional map services were transitioned from on-premises infrastructure to AWS.

In spring 2011, Pictometry Online was deployed within an EC2 environment running MySQL. By summer, approximately 75 percent of the county’s enterprise GIS operations were running on Amazon cloud servers.

Hybrid Workflow: Local Data Creation, Cloud-Based Services

While core services moved to AWS, geospatial data creation and editing continued locally. Updated datasets were replicated to the cloud environment, where nearly all public-facing web applications and services were hosted. This hybrid approach balanced local data control with the scalability of cloud infrastructure.

Cost management became an ongoing focus. Although AWS proved more affordable than maintaining physical servers, the department actively pursued further efficiencies. Amazon S3 was tested as a lower-cost storage platform for datasets and JavaScript-based web applications, offering both improved performance and reduced storage expenses. Automation scripts were implemented to shut down non-essential EC2 instances outside business hours, lowering operational costs for applications that did not require 24/7 uptime.

Flexibility and Organizational Benefits

From a GIS administration standpoint, elasticity emerged as the single greatest advantage. The ability to spin up new server instances or replicate existing images and pay only for actual usage transformed development and testing workflows. Software upgrades and custom application trials no longer required hardware procurement or long lead times.

At the organizational level, reliability improved and reliance on internal IT resources decreased. Infrastructure costs became more predictable, and AWS offered multiple pricing strategies for optimization. The department gained the capacity to scale resources up or down in response to operational demands.

Technical Challenges and Lessons Learned

The migration process was not without obstacles. Transitioning to a cloud-based GIS required deliberate planning, extensive testing, and persistence through trial-and-error phases. Several performance and connectivity challenges emerged.

One significant issue involved hosting a production geodatabase in the cloud while maintaining acceptable performance for desktop GIS users on the internal network. Initial attempts relied on ODBC database connctions, but latency proved problematic. Switching to web services did not fully resolve performance constraints for desktop workflows.

Ultimately, for users who could not shift to web-based tools, the department deployed small EC2 “micro” instances functioning as cloud-hosted remote desktops. Users connected directly to these instances and accessed the cloud database internally within AWS, effectively minimizing latency. This solution delivered consistent performance and reliability.

Internet bandwidth was another consideration. Some county facilities had slower connections than the main office. Before full migration, the team evaluated whether bandwidth upgrades were feasible, whether personnel could be relocated, or whether alternative remote access strategies were required.

Data replication also demanded careful attention. Maintaining synchronization between local editing environments and cloud-hosted geodatabases was essential for data integrity. Reliable replication processes became a foundational component of the cloud architecture.

Strategic Outcomes and Long-Term Impact

Throughout the transition, the DCGIS team documented challenges, performance bottlenecks, and configuration strategies. Their experience underscored three essential elements for success: comprehensive planning, rigorous testing, and openness to organizational change.

Today, Douglas County operates a predominantly cloud-based enterprise GIS infrastructure. The move to AWS has increased scalability, enhanced system reliability, and improved overall performance. Operational expenses are comparable to previous hardware-based models, but with greater flexibility and fewer capital investments.

As the department continues to expand its geospatial services and data-driven applications, cloud infrastructure provides the agility required to adapt quickly. By embracing Amazon Web Services and ArcGIS Server in the cloud, Douglas County positioned its GIS operations to be more responsive, efficient, and sustainable in the long term.