Modern performance monitoring with Speedgain for Databases
Posted: Mon Jan 27, 2025 10:29 am
Today's IT landscapes are becoming increasingly heterogeneous. Many services are purchased as SaaS or PaaS, parts of the infrastructure may already be hosted in a cloud, and new applications are provided as a collection of microservices. It can therefore be difficult for conventional monolithic monitoring systems to keep up with the rapid development. Every new source system requires new plugins, every new metric requires an adjustment.
Speedgain for Databases follows an open and modern architectural concept that is scalable and expandable, either by the manufacturer ITGAIN or the customer themselves.
A modern monitoring tool should not only alert but also provide information for condition analyses
Traditional monitoring is afghanistan telegram screening limited to collecting predefined metrics for which corresponding limits and alarms can be derived. Ultimately, the aim of monitoring is to obtain a quick overview of the system landscape in order to identify any problems or failures as quickly as possible. Classic monitoring reaches its limits in today's hybrid system landscape and the requirements for maximum availability. On the one hand, it only reacts to a previously defined error state and, on the other hand, detailed data for a detailed root cause analysis is often missing because it was not collected in the defined selection of metrics.
In recent years, the concept of observability of systems or services has become established. Observability is a property of a (distributed) system that describes how well the execution of programs, the status of modules and the communication between components can be deduced from the output data. Metrics, logs and traces are typically provided by the system for this purpose [1] .
Speedgain for Databases follows an open and modern architectural concept that is scalable and expandable, either by the manufacturer ITGAIN or the customer themselves.
A modern monitoring tool should not only alert but also provide information for condition analyses
Traditional monitoring is afghanistan telegram screening limited to collecting predefined metrics for which corresponding limits and alarms can be derived. Ultimately, the aim of monitoring is to obtain a quick overview of the system landscape in order to identify any problems or failures as quickly as possible. Classic monitoring reaches its limits in today's hybrid system landscape and the requirements for maximum availability. On the one hand, it only reacts to a previously defined error state and, on the other hand, detailed data for a detailed root cause analysis is often missing because it was not collected in the defined selection of metrics.
In recent years, the concept of observability of systems or services has become established. Observability is a property of a (distributed) system that describes how well the execution of programs, the status of modules and the communication between components can be deduced from the output data. Metrics, logs and traces are typically provided by the system for this purpose [1] .