Deployment Architecture
- Jiffy bots can run across multiple regions or in multiple clusters from a centralized server. Each cluster could have bots running across geographically separate machines.
- Bots are scalable across multiple ports or across multiple client desktops and can run out of one or more Windows servers instead of separate Windows desktops.
- Jiffy core components (Alice, Orchestration Engine (ORENG), Jiffy web application) and the webserver can be scaled horizontally outside the application server as well.
- Bot Manager will assess the capability of bots running across the clusters and assigns the task to the appropriate bot.
- JDI studio is a designer module used to design the JDI Screens for business.
- Jiffy Data Interface is a portal solution for operations resources to monitor and provide data inputs for the bot.
- Jiffy Admin Module is for the bot administrators to track and control the bots across the clusters/regions.
- The Jiffy/JDI DB could be Oracle or Postgres.
Windows Server Based Deployment Architecture
In the deployment diagram above the bots are all installed on a single windows server. This enables us to scale bot up and down on a need basis without additional infrastructure cost. Also, the applications patches are very well controlled when the automations are on the windows servers. Any tasks which downloads large amount data also gets significant benefits as the bots are running on the same data centre as the applications under automation.
PROS:
- Load Sharing between resources is better managed and automatically controlled.
- Better management of patch updates and application upgrades.
- The application that has to be automated should be compatible with the Windows server.
VDI Server Based Deployment Architecture
Multiple Jiffy Bots running on different virtual desktops. Each virtual desktop hosting a bot.
This is another sample deployment model. Here the bots are deployed in VDI. This simulates an employee as-is. Typically challenges of getting the client applications installed on the server is mitigated with this approach.
PROS:
- Simulates an Employee as-is.
- Better security control- unlock, execute and lock the machine after the bot usage.
- Automated application upgrades and security patches can impact bot execution.
- More expensive to manage when running bots at scale.
Scalability
Both, the core servers and cognitive servers can be scaled horizontally as well a vertically. For example, a typical server configuration of 8 core 32GB is good enough to run at least 20 bots. The infrastructure could be scaled to 8 Core 64 GB for a 50 bot implementation or the same load could be manged with 2 servers of 8 core 32 GB each. The later will enable failover and load balancing as well.
The same applies to the cognitive server, which are typically deployed in clusters to balance load and data back.
The bot machines are generally horizontally scaled unless you are using a windows server as bot machine. In case of VDI’s another desktop is added to the cluster, the load is automatically balanced.