Bench Reports can be customized using many items (charts, tables, ...). Each one of these items can be configured using performance metrics.
This section list all the metrics available in OctoPerf.
Hit Metrics List¶
All the following metrics are available in OctoPerf. To know which report item car display this metrics, please report to the hit metrics availability table.
These metrics comes in various types (Minimum, average, count, rate, etc.). Refer to the performance metrics types table to know them.
|UserLoad||Number of active users.||Many other metrics should not changed as the user load increase.|
|Response time||Time between the request and the end of the response, in milliseconds. The response time includes both the latency and the connect time.||The lower the better. Should be less than 4 seconds.|
|Connect time||Time between the request and the server connection, in milliseconds.||The lower the better. If you get high connect times your servers may be running out of available sockets, or your database may be overloaded.|
|Latency (Server time)||Time between the request and the first response byte, in milliseconds.||The lower the better. If you get high response times and low latencies your servers may be running out of bandwidth. Check the throughput to confirm this.|
|Network time||Response time - Latency||The lower the better. If you get high network times your servers may be running out of bandwidth. Check the throughput to confirm this.|
|Throughput||Bit rate in Bytes per second. Amount of data exchanged between the clients and the servers.||Must grow along the user load. If it reaches an unexpected plateau, you may be running out of bandwidth.|
|Errors||Count or rate of errors that occurred.||Errors may happen if you did not validate your virtual user. Otherwise, errors may be the sign that your servers or database are overloaded.|
|Hits||Count or rate of hits (requests) that occurred.||Should increase as the user load goes up.|
|Assertions||Count of assertions in error, failed, or successful.||Assertions in error or failed lets your know that your servers did not answer as you expected.|
Hit Metrics Types¶
Each metric comes in various types. The table below list all of them.
|Minimum||Minimum value of a metric.|
|Average||Average value of a metric.|
|Maximum||Maximum value of a metric.|
|Variance||The variance quantifies the dispersion of the metric. A variance close to 0 indicates that the metric values tend to be very close to the mean, while a high variance indicates that the values are spread out over a wider range. Its unit is the square of the metric unit.|
|Standard deviation||Simply the square root of the variance. It's easier to compare to other metric types using a common unit.|
|Percentile 90||A percentile indicates the value below which a given percentage of observations in a group of observations fall. For example, the 90th percentile is the value below which 90 percent of the observations may be found.|
|Percentile 95||A percentile indicates the value below which a given percentage of observations in a group of observations fall. For example, the 95th percentile is the value below which 95 percent of the observations may be found.|
|Percentile 99||A percentile indicates the value below which a given percentage of observations in a group of observations fall. For example, the 99th percentile is the value below which 99 percent of the observations may be found.|
|Median||Simply a 50th percentile: the value below which 50 percent of all the values may be found.|
|Total||Count of a metric. Number of occurrences of an event.|
|Rate||Count of a metric per second.|
|Apdex||Apdex (Application Performance Index) defines a standard method for reporting the performance of software applications, by specifying a way to analyze the degree to which measured performance meets user expectations. Score is between 0 and 1, at 1 all users are satisfied.|
The following table defines the metrics and their associated statistics:
|Metric||Min. Avg. and Max.||Std Dev. and Variance||Med. Percentile||Total||Rate||Apdex|
Hit Metrics Availability¶
The table below displays all performance metrics per type and which report items can display them.
|Metric||Type||Line Chart||Summary||Top Chart||Percentiles Chart||Results Table/Tree|
|Response time||Standard deviation||X||X||X||X|
|Response time||Percentile 90||X||X|
|Response time||Percentile 95||X||X|
|Response time||Percentile 99||X||X|
|Connect time||Standard deviation||X||X||X||X|
|Assertions in error||Total||X||X||X||X|
Monitoring Metrics List¶
The following monitoring metrics are collected for each load generator involved during the load tests. Note that there is a page dedicated to load generators monitoring where you can find more details.
|% CPU Usage||Percentage of CPU usage||The lower the better. Excessive CPU usage can lead to increased response times or random failures.|
|Load avg per CPU (1 min)||Number of threads queued per CPU averaged for the last minute||Load average represents the number of threads waiting to be processed by the CPU. Ideally this value should not be more than 1. Otherwise it can indicate a high CPU activity, disk usage or network bottleneck.|
|% Used memory||Percentage of memory usage||The lower the better. As our agent's JVM makes use of all the memory it can, this value should not change much during the test, if at all.|
|Sent MB/Sec||Outbound network usage in megabytes||Must grow along the user load. If it reaches a plateau before maximum load is achieved, you may be running out of bandwidth.|
|Received MB/Sec||InBound network usage in megabytes||Must grow along the user load. If it reaches a plateau before maximum load is achieved, you may be running out of bandwidth.|
|Established connections||Number of established TCP connections||Must grow along with the user load. If it reaches a plateau before maximum load is achieved, your server network capacity may be exceeded.|
|% Segments retransmitted||Percentage of TCP segments retransmitted||The lower the better. A very small percentage can have a huge impact on response times.|
Java Virtual Machine¶
|Memory / % heap memory used||Percentage of heap memory in use||The lower the better. High heap memory usage can cause the load generator to fail.|
|G1 Young / collectionCount||Number of garbage collections in the young generation.||These collections have little impact on the JVM performance and can often be disregarded.|
|G1 Young / collectionTime||Amount of time spent in collections||Time spent in garbage collection of G1 young.|
|G1 Old / collectionCount||Number of garbage collections in the old generation.||These collection have a large impact on the JVM performance, it is important to keep track of them if you suspect a performance issue on the load generators.|
|G1 Old / collectionTime||Amount of time spent in collections||Time spent in garbage collection of G1 old.|
More details are available in the page dedicated to load generators monitoring.
Monitoring Metrics Availability¶
Monitoring metrics are only available in line charts.
Donut chart metrics¶
|HTTP methods||HTTP methods (GET, POST, DELETE, ...) distribution|
|HTTP response codes||HTTP response codes (2xx, 3xx, 4xx, 5xx, ...) distribution. You should avoid error codes such as 4xx and 5xx.|