Qlik Cloud resource limits
QV2QS builds apps directly in Qlik Cloud. The build process, reload, and automatic binary upload are all subject to the resource limits of the Qlik Cloud tenant. These limits vary by subscription tier and space configuration.
App upload size
Automatic binary load uploads the original QVW file to Qlik Cloud as a temporary app. Large QVW files may exceed the upload limit for the tenant. If the upload fails, the conversion still succeeds (the app is built without data), but the automatic data load does not complete. To work around this limitation, deploy the app to a space with large app support enabled. Alternatively, use --binaryAppId to reference an existing app already in the tenant, or reload the app manually after configuring data connections.
App reload memory
Reloading the converted app requires sufficient memory allocation in the Qlik Cloud engine. Large QlikView applications with many tables, fields, or high row counts may exceed the default memory allocation for the space. Deploy large apps to a space with large app support enabled to provide higher memory and compute resources for the reload.
Space configuration
By default, QV2QS creates apps in the personal space. Personal spaces have standard resource limits. For large applications, deploy to a shared space configured for large app support using --spaceId on the command line.
Data connections and load script
QV2QS converts the UI but does not create data connections in Qlik Cloud. If the load script references local file paths, ODBC connections, or QVD files, those data sources must be available in the Qlik Cloud environment before the app can reload successfully. QV2QS applies basic path normalization (backslash to forward slash in lib:// paths), but connection names and file paths typically require manual adjustment or migration through QAMT.
Reload concurrency
Qlik Cloud limits the number of concurrent reloads per tenant. When QV2QS batch deployment runs with many workers, reload requests that exceed the tenant limit queue server-side. The cloud deployment phase speedup plateaus once the concurrent reload limit is reached, regardless of local CPU and thread resources.
For the full specification of Qlik Cloud resource limits, capacity guardrails, and subscription tier details, see Qlik Cloud specifications and capacity guardrails.