Robin Use Cases
See the Robin value in your environment
The Robin platform empowers your developers, DBAs, and data scientists to deploy and manage any application pipeline anywhere, on-prem or in the cloud, by providing an “as-a-service” experience. Let’s examine a few scenarios of how this would work for you.
Mistakes happen in the real world when managing complex applications, so the ability to go back to a point in time before the mistake is critical. If you are depending on storage-level snapshots, you may be able to restore your data, but not the entire application state. With Robin, you can seamlessly travel between different application states (backward and forward), even if the application’s topology and configuration have changed over time. With Robin’s application time-travel, your developers are free to run what-if analyses and to quickly and freely collaborate with other teams with the push of a button.
Scaling Up Applications
Many data-centric applications will run into scenarios when you need to add more resources to maintain or improve performance. Normally, you would need to bring down your application cluster in order to reconfigure it for better performance – and in the process, slow down your developers. With Robin, increasing performance is as easy as adjusting the brightness on your smartphone. You can adjust a slider to increase or decrease CPU, memory, and storage IOPS resources to any container with one-click simplicity, while your developers have continuous access to the applications they need.
Scaling Out Applications
For new application deployments, most developers like to start small and add resources as needed over time. However, it can be a complex process to ensure that both the performance and availability of the application are maintained through this process. With Robin, you can simply add more resources with one click. Because Robin understands your application, it will learn the data locality, affinity, and anti-affinity constraints and automatically bring up the new resources in compliance with those policies.
Running multiple data-intensive applications on shared infrastructure saves you significant cost, but also creates a few challenges, as some applications are more important than others. You can suffer from noisy neighbors and your performance cannot be guaranteed. Because Kubernetes can’t guarantee storage IOPS isolation, there is no way to work around this. With Robin, solving the noisy neighbor problem is as easy as setting consumption quotas for each application or user by establishing minimum and/or maximum IOPs, all while the application is running. No application downtime is needed to dial up or down the performance of your application.