Abstract: Computerized techniques are described for detecting performance degradation during features ramp up. A first version of web content is sent to first client devices. The first version of the web content lacks a particular feature. First performance data that indicates performance of each first client device with respect to processing the web content is received. A second version of the web content is sent to second client devices. The second version of the web content has the particular feature. Second performance data that indicates performance of each second client device with respect to processing the web content is received. The first performance data is compared with the second performance data to determine a difference between a processing metric associated with the first version of the web content and a processing metric associated with the second version of the web content.

Abstract: Techniques are provided for assigning application instances to different machines. Resource usage of a particular resource by multiple application instances over a period of time is determined. Two or more application instances may be assigned to the same machine if the combined resource usage of the application instances does not exceed the resource capacity of the machine. One or more different types of resources may be considered for machine assignment, such as CPU, memory, network I/O, and disk I/O.

Abstract: Techniques for generating, storing, and using service call graphs are provided. In one technique, trace data items generated by different services are correlated to generate a service call graph. Trace data indicates when certain services are called and their respective latencies as a result of a client request. A service call graph may reflect a single trace or multiple traces over a particular period of time. A service call graph may be analyzed to inform administrators of a web site how a web application and the services it relies on are performing. A service call graph may be used to determine whether there are sufficient resources to support a projected increase in traffic to a web application. A service call graph may be used to estimate a cost of a web application. Multiple service call graphs may be compared to determine one or more root causes of a performance problem.

Abstract: Techniques for generating and using service call graphs are provided. In one technique, trace data items generated by different services are correlated to generate a service call graph. Trace data indicates when certain services are called and their respective latencies as a result of a client request. A service call graph may reflect a single trace or multiple traces over a particular period of time. A service call graph may be analyzed to inform administrators of a web site how a web application and the services it relies on are performing. A service call graph may be used to determine whether there are sufficient resources to support a projected increase in traffic to a web application. A service call graph may be used to estimate a cost of a web application. Multiple service call graphs may be compared to determine one or more root causes of a performance problem.

Abstract: Computerized techniques are described for detecting performance degradation during features ramp up. A first version of web content is sent to first client devices. The first version of the web content lacks a particular feature. First performance data that indicates performance of each first client device with respect to processing the web content is received. A second version of the web content is sent to second client devices. The second version of the web content has the particular feature. Second performance data that indicates performance of each second client device with respect to processing the web content is received. The first performance data is compared with the second performance data to determine a difference between a processing metric associated with the first version of the web content and a processing metric associated with the second version of the web content.

Abstract: Techniques for generating and using service call graphs are provided. In one technique, trace data items generated by different services are correlated to generate a service call graph. Trace data indicates when certain services are called and their respective latencies as a result of a client request. A service call graph may reflect a single trace or multiple traces over a particular period of time. A service call graph may be analyzed to inform administrators of a web site how a web application and the services it relies on are performing. A service call graph may be used to determine whether there are sufficient resources to support a projected increase in traffic to a web application. A service call graph may be used to estimate a cost of a web application. Multiple service call graphs may be compared to determine one or more root causes of a performance problem.

Abstract: Computerized techniques are described for detecting performance degradation during features ramp up. A first version of web content is sent to first client devices. The first version of the web content lacks a particular feature. First performance data that indicates performance of each first client device with respect to processing the web content is received. A second version of the web content is sent to second client devices. The second version of the web content has the particular feature. Second performance data that indicates performance of each second client device with respect to processing the web content is received. The first performance data is compared with the second performance data to determine a difference between a processing metric associated with the first version of the web content and a processing metric associated with the second version of the web content.

Abstract: Computerized techniques are described for detecting performance degradation during features ramp up. A first version of web content is sent to first client devices. The first version of the web content lacks a particular feature. First performance data that indicates performance of each first client device with respect to processing the web content is received. A second version of the web content is sent to second client devices. The second version of the web content has the particular feature. Second performance data that indicates performance of each second client device with respect to processing the web content is received. The first performance data is compared with the second performance data to determine a difference between a processing metric associated with the first version of the web content and a processing metric associated with the second version of the web content.

Abstract: Techniques for reassigning client devices to different POP centers are provided. Client devices execute code that causes the client devices to request data from one or more POP centers. The client device record how much time it takes to receive the requested data. The download time is reported and aggregated to determine POP center-to-client device assignments. If it is determined that a client device should be reassigned to a particular POP center, then a DNS provider is configured to update the appropriate hostname-to-IP address mapping to an IP address of the particular POP center. A change in performance based on a POP reassignment may then be determined.

Abstract: Techniques for generating and using service call graphs are provided. In one technique, trace data items generated by different services are correlated to generate a service call graph. Trace data indicates when certain services are called and their respective latencies as a result of a client request. A service call graph may reflect a single trace or multiple traces over a particular period of time. A service call graph may be analyzed to inform administrators of a web site how a web application and the services it relies on are performing. A service call graph may be used to determine whether there are sufficient resources to support a projected increase in traffic to a web application. A service call graph may be used to estimate a cost of a web application. Multiple service call graphs may be compared to determine one or more root causes of a performance problem.

Abstract: Techniques for generating and using service call graphs are provided. In one technique, trace data items generated by different services are correlated to generate a service call graph. Trace data indicates when certain services are called and their respective latencies as a result of a client request. A service call graph may reflect a single trace or multiple traces over a particular period of time. A service call graph may be analyzed to inform administrators of a web site how a web application and the services it relies on are performing. A service call graph may be used to determine whether there are sufficient resources to support a projected increase in traffic to a web application. A service call graph may be used to estimate a cost of a web application. Multiple service call graphs may be compared to determine one or more root causes of a performance problem.

Abstract: Techniques for generating and using service call graphs are provided. In one technique, trace data items generated by different services are correlated to generate a service call graph. Trace data indicates when certain services are called and their respective latencies as a result of a client request. A service call graph may reflect a single trace or multiple traces over a particular period of time. A service call graph may be analyzed to inform administrators of a web site how a web application and the services it relies on are performing. A service call graph may be used to determine whether there are sufficient resources to support a projected increase in traffic to a web application. A service call graph may be used to estimate a cost of a web application. Multiple service call graphs may be compared to determine one or more root causes of a performance problem.

Abstract: Techniques for generating, storing, and using service call graphs are provided. In one technique, trace data items generated by different services are correlated to generate a service call graph. Trace data indicates when certain services are called and their respective latencies as a result of a client request. A service call graph may reflect a single trace or multiple traces over a particular period of time. A service call graph may be analyzed to inform administrators of a web site how a web application and the services it relies on are performing. A service call graph may be used to determine whether there are sufficient resources to support a projected increase in traffic to a web application. A service call graph may be used to estimate a cost of a web application. Multiple service call graphs may be compared to determine one or more root causes of a performance problem.

Abstract: Computerized techniques are described for detecting performance degradation during features ramp up. A first version of web content is sent to first client devices. The first version of the web content lacks a particular feature. First performance data that indicates performance of each first client device with respect to processing the web content is received. A second version of the web content is sent to second client devices. The second version of the web content has the particular feature. Second performance data that indicates performance of each second client device with respect to processing the web content is received. The first performance data is compared with the second performance data to determine a difference between a processing metric associated with the first version of the web content and a processing metric associated with the second version of the web content.