Pros and Cons
- Automation engine - easy to take scripted action on specific device events.
- Automation action open source - the platform allows you to custom build snippet actions with Python to remediate any unhealthy event detected on devices.
- Manager of managers - the platform has several ways of receiving inbound alerts and alarms not only from directly monitored devices but from 3rd-party solutions in the form of traps, emails and REST API connections.
- Built-in Reporting - the reporting engine that comes with the platform is woefully inadequate to perform most of any report request that is not a very simple and basic output of data.
- Continuous Integration/Continuous Deployment support - the platform is bound by Power-Packs for deployment of monitoring solutions for specific device types. These are great when first starting out using the platform as they allow you to on-board several types of device support, but when you mature and start building your own actions and monitoring solutions, they are cumbersome to work with.
- Current Platform Architecture - the main CDB design requires lots of memory and CPU to handle the load of all the threaded processing of even a few thousand monitored devices. To scale up to several thousand or tens of thousands if devices becomes a pricing hurdle. Also, in a cloud deployment strategy, this processing power comes at a hefty price for cloud resources, not including the pricey SL1 license costs as well.
- Custom development support - when you start developing your own snippet actions for monitoring custom devices or solutions, ScienceLogic only provides a pay-for Professional Services resource to assist you in even the smallest of development questions. The product customer support desk will not spend time discussing development solutions and providing development support. This has been an issue for SL from the beginning and the company needs to put together a development support arm.