Early detection and warning for system bottlenecks in an on-demand environment
In accordance with embodiments, there are provided mechanisms and methods for facilitating early detection and warning for system bottlenecks in an on-demand services environment according to one embodiment. In one embodiment and by way of example, a method includes detecting waits during processing of a query within a processing pipeline, wherein the waits include one or more of application-specific waits and database-specific waits; diagnosing the waits to identify a wait that has turned into a bottleneck; classifying one or more types of issues causing the wait to turn into the bottleneck; generating an alert having associated information detailing the issues based on the one or more types and a location of the wait within the processing pipeline; and transmitting the alert to facilitate correction activities.
1. A computer-implemented method comprising:
detecting waits as application-specific waits or database-specific waits during processing of a query within a processing pipeline;
obtaining one or more of 1) application metrics associated with the application-specific weights or 2) database metrics associated with the database-specific waits;
identifying, based on the application metrics or the database metrics, a wait that has turned into a bottleneck;
classifying one or more issues causing the wait to turn into the bottleneck;
generating an alert regarding the bottleneck based on the one or more issues and a location of the wait within the processing pipeline, wherein the alert is associated with information detailing the one or more issues based on the wait being an application-specific wait or a database-specific wait; and
transmitting the alert to facilitate correction activities based on the information.
2. The method of claim 1 , further comprising gathering the application metrics relating to one or more applications associated with the application-specific waits, wherein the application metrics include processing data relating to the one or more applications associated with the application-specific waits.
3. The method of claim 1 , further comprising gathering the database metrics relating to one or more databases associated with the database-specific waits, wherein the database metrics include processing data relating to one or more databases associated with the database-specific waits.
4. The method of claim 1 , further comprising detecting correlation between the application metrics and the database metrics,
wherein an application metric correlating with a database metric indicates the bottleneck is caused by the database-specific wait, and
wherein an absence of the correlation between the application metrics and the database metrics indicates the bottleneck is caused by the application-specific wait.
5. The method of claim 1 , wherein the one or more issues are classified, and the alert is generated and transmitted if the bottleneck is caused by the database-specific wait, and
wherein the one or more issues are not classified, and the alert is not generated or transmitted if the bottleneck is caused by the application-specific wait.
6. The method of claim 5 , wherein classifying of the one or more issues comprises obtaining background data relating to the bottleneck and one or more databases associated with the bottleneck, wherein the information associated with the alert further includes the background data, wherein the query includes one or more of a query request and a query response, wherein the query response is generated in response to the query request.
7. The method of claim 1 , wherein the alert is transmitted to a computing device offering access to the alert via a user interface including one or more of a graphical user interface (GUI), a web browser, or an application-based interface, and an application programming interface (API).
8. A database system comprising:
a server computer having one or more processors coupled to memory having thereon instructions, the one or more processors to execute the instructions to perform operations comprising:
detecting waits as application-specific waits or database-specific waits during processing of a query within a processing pipeline;
obtaining one or more of 1) application metrics associated with the application-specific weights or 2) database metrics associated with the database-specific waits;
identifying, based on the application metrics or the database metrics, a wait that has turned into a bottleneck;
classifying one or more issues causing the wait to turn into the bottleneck;
generating an alert regarding the bottleneck based on the one or more issues and a location of the wait within the processing pipeline, wherein the alert is associated with information detailing the one or more issues based on the wait being an application-specific wait or a database-specific wait; and
transmitting the alert to facilitate correction activities based on the information.
9. The database system of claim 8 , wherein the operations further comprise gathering the application metrics relating to one or more applications associated with the application-specific waits, wherein the application metrics include processing data relating to the one or more applications associated with the application-specific waits.
10. The database system of claim 8 , wherein the operations further comprise gathering the database metrics relating to one or more databases associated with the database-specific waits, wherein the database metrics include processing data relating to one or more databases associated with the database-specific waits.
11. The database system of claim 8 , wherein the operations further comprise detecting correlation between the application metrics and the database metrics,
wherein an application metric correlating with a database metric indicates the bottleneck is caused by the database-specific wait, and
wherein an absence of the correlation between the application metrics and the database metrics indicates the bottleneck is caused by the application-specific wait.
12. The database system of claim 8 , wherein the one or more issues are classified, and the alert is generated and transmitted if the bottleneck is caused by the database-specific wait, and
wherein the one or more issues are not classified, and the alert is not generated or transmitted if the bottleneck is caused by the application-specific wait.
13. The database system of claim 12 , wherein classifying of the one or more issues comprises obtaining background data relating to the bottleneck and one or more databases associated with the bottleneck, wherein the information associated with the alert further includes the background data, wherein the query includes one or more of a query request and a query response, wherein the query response is generated in response to the query request.
14. The database system of claim 8 , wherein the alert is transmitted to a computing device offering access to the alert via a user interface including one or more of a graphical user interface (GUI), a web browser, or an application-based interface, and an application programming interface (API).
15. A computer-readable medium having stored thereon instructions which, when executed, cause a computing device to perform operations comprising:
detecting waits as application-specific waits or database-specific waits during processing of a query within a processing pipeline;
obtaining one or more of 1) application metrics associated with the application-specific weights or 2) database metrics associated with the database-specific waits;
identifying, based on the application metrics or the database metrics, a wait that has turned into a bottleneck;
classifying one or more issues causing the wait to turn into the bottleneck;
generating an alert regarding the bottleneck based on the one or more issues and a location of the wait within the processing pipeline, wherein the alert is associated with information detailing the one or more issues based on the wait being an application-specific wait or a database-specific wait; and
transmitting the alert to facilitate correction activities based on the information.
16. The computer-readable medium of claim 15 , wherein the operations further comprise gathering the application metrics relating to one or more applications associated with the application-specific waits, wherein the application metrics include processing data relating to the one or more applications associated with the application-specific waits.
17. The computer-readable medium of claim 15 , wherein the operations further comprise gathering the database metrics relating to one or more databases associated with the database-specific waits, wherein the database metrics include processing data relating to one or more databases associated with the database-specific waits.
18. The computer-readable medium of claim 15 , wherein the operations further comprise detecting correlation between the application metrics and the database metrics,
wherein an application metric correlating with a database metric indicates the bottleneck is caused by the database-specific wait, and
wherein an absence of the correlation between the application metrics and the database metrics indicates the bottleneck is caused by the application-specific wait.
19. The computer-readable medium of claim 15 , wherein the one or more issues are classified, and the alert is generated and transmitted if the bottleneck is caused by the database-specific wait, and
wherein the one or more issues are not classified, and the alert is not generated or transmitted if the bottleneck is caused by the application-specific wait.
20. The computer-readable medium of claim 19 , wherein classifying of the one or more issues comprises obtaining background data relating to the bottleneck and one or more databases associated with the bottleneck, wherein the information associated with the alert further includes the background data, wherein the query includes one or more of a query request and a query response, wherein the query response is generated in response to the query request.
21. The computer-readable medium of claim 15 , wherein the alert is transmitted to a computing device offering access to the alert via a user interface including one or more of a graphical user interface (GUI), a web browser, or an application-based interface, and an application programming interface (API).