Developing custom CLIs for different types of devices is costly and time consuming, requiring custom parser, formatter and validation software. NOCVue CLI is an XML-based solution, allowing developers to define CLI commands and actions that generate customized code. Typically, a complete CLI command set for a complex device can be developed in less than three months.
NOCVue CLI allows equipment manufacturers to easily create and support commands for devices.
- Cisco-like CLI with value-added features
- Password-based user management
- File-based log management
- Session management and default support for Telnet and SSH.
- Multi-session support
- Command syntax validation and command termination
- System configuration changes supported at runtime.
- XML schema validation
- Automated build scripts
- Customized banner for CLI
- Configuration of hierarchical commands and it’s supporting options
- Extendable to support TL1 and SNMP protocols
- Rapid time to market–basic code is generated, only the data validation functions need to written and integrated with database
- Supports multiple operating systems–-Linux, VxWorks, Windows
NOCVue CLI Features
- XML-based input and schema validation: CLI commands are displayed in an XML file, making it easy to edit and regenerate code.
- Cisco-like CLI features: Features supported include partial command completion, help, global commands and interactive command handling.
- Database: CLI code is database agnostic; any database can be integrated using backend APIs.
- Built-in user management commands: Support for user-management commands are built in, further reducing development time.
- Built-in system commands: Product is packaged with basic system commands. Only device-specific commands need to be added.
- GUI: Friendly user interface provided for generating configuration files.
- Small footprint: Code size is very small, requiring only a few kilobytes.
- Portable to any RTOS: Code is generic and portable.
NOCVue NMS/EMS can be deployed as a standalone NMS/EMS application server or scaled using a distributed sever model.