Silverlake Axis has a core banking and loan product called SILK, used by most banks in Southeast Asia, like in Malaysia, Singapore, and Thailand. The new product I'm working on, Mobius, is a replacement for SILK, which runs on a mainframe. Mobius uses TiDB, along with Java and other frameworks.
We use an open-source tool called Prometheus. It is an available offering with extensive documentation. The primary purpose of using a time series database like Prometheus is to collect metrics of various activities. These activities can be on the user side, infrastructure side, or behind the scenes where the software is running. There is a wide variety of use cases for time series databases, mainly focused on collecting and analyzing metrics. For example, you might want to track how many active users log into your product over different periods—minutes, hours, days, weeks, or months. This data can help you understand user behavior and activity trends. Time series databases record data points over time, allowing you to recall past data or visualize current activity. This is useful for monitoring user engagement, understanding the geographic distribution of your user base, and many other metrics. We use Prometheus for collecting metrics and Grafana for visualizing them. Grafana allows us to create real-time charts and graphs that display how data changes over time. For example, if you are running an e-commerce site, you might see increased user activity in the evenings when people are more likely to shop. By combining Prometheus with Grafana, we can track events such as payment initiations on an e-commerce site. Prometheus records the events, and Grafana visualizes them, showing trends and spikes in user activity
DBaaS offers scalable database management hosted in the cloud, eliminating the need for physical infrastructure. It is tailored for efficient data handling, providing flexibility and cost-effectiveness for businesses seeking streamlined data operations. Database as a Service provides organizations with managed database solutions, effectively reducing the complexity associated with traditional database management. Companies opting for DBaaS benefit from its scalability, automated backups,...
Silverlake Axis has a core banking and loan product called SILK, used by most banks in Southeast Asia, like in Malaysia, Singapore, and Thailand. The new product I'm working on, Mobius, is a replacement for SILK, which runs on a mainframe. Mobius uses TiDB, along with Java and other frameworks.
We use an open-source tool called Prometheus. It is an available offering with extensive documentation. The primary purpose of using a time series database like Prometheus is to collect metrics of various activities. These activities can be on the user side, infrastructure side, or behind the scenes where the software is running. There is a wide variety of use cases for time series databases, mainly focused on collecting and analyzing metrics. For example, you might want to track how many active users log into your product over different periods—minutes, hours, days, weeks, or months. This data can help you understand user behavior and activity trends. Time series databases record data points over time, allowing you to recall past data or visualize current activity. This is useful for monitoring user engagement, understanding the geographic distribution of your user base, and many other metrics. We use Prometheus for collecting metrics and Grafana for visualizing them. Grafana allows us to create real-time charts and graphs that display how data changes over time. For example, if you are running an e-commerce site, you might see increased user activity in the evenings when people are more likely to shop. By combining Prometheus with Grafana, we can track events such as payment initiations on an e-commerce site. Prometheus records the events, and Grafana visualizes them, showing trends and spikes in user activity