What are Throughput Performance, Latency Performance, and Memory Footprint in Java Programming?

1.Throughput Performance

There are more inquiries to make once you have a throughput performance objective for the application or feature being developed. These inquiries are intended to fine-tune the throughput requirement and will increase the likelihood that the application java Programming will meet or surpass its performance goals. Additional inquiries to think about posing include:

Is the performance Java Programming objective to be regarded as the peak performance objective?
Or is the throughput objective a performance goal that the application must always meet?
What is the highest load that the application is anticipated to handle? For instance, how many concurrent or active users, concurrent or active transactions are anticipated?
Can the throughput drop below the performance objective if the application’s load exceeds the projected load?
How long can it stay below the performance objective if it is possible to do so? Alternatively, for how long should the application continue to operate at its maximum capacity or under conditions of increased load?
Is there a maximum amount of CPU that can be consumed by the application at different load levels, or is there an expected amount of CPU?
If there is a cap on CPU usage, how much more CPU can be used beyond that limit, and for how long is it allowed?
How will the application’s throughput be assessed?
Where will the computation of throughput be done?

The final question is vitally significant. To achieve the throughput performance goal, it can be essential to have a clear understanding of how and where throughput will be assessed. Those with an interest in the performance may have different ideas about how and where throughput is assessed. The additional issues listed below may likewise generate differing viewpoints.

What are Throughput Performance, Latency Performance, and Memory Footprint in Java Programming?

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2.Latency or Response Time Performance

Performance goals for latency or response time should be well-documented and understood, much like the throughput performance target. The first stage is to specify a response time requirement or target, as previously said. A decent place to start is with a target that simply measures an anticipated response time for requests. After establishing that first performance Java Programming goal, more in-depth inquiries can be used to further define the response time and latency expectations. Additional inquiries are as follows:

Is the response time objective an absolute minimum that should never be surpassed?
Is the target for response time an average goal? Is it expressed as a percentile, such as a response time in the 90th, 95th, or 99th percentile?
Is it possible to go above the reaction time objective?
If so, how much can be added to it?
How long can it be exceeded, too?
How will response time be assessed?
Where will response time measurements be taken?

The last two should be thoroughly investigated as they are crucial issues. If an external load driver program is involved, for instance, it might include built-in features to assess reaction time latency. If you have access to the source code and wish to use those built-in features, look at how the response time is calculated and reported. Be wary of reaction times that provide averages and standard deviations, as was previously stated. Response times are not evenly spaced out. So, attempting to use statistical methods that assume normally distributed data will lead to improper conclusions.

In a perfect world, you would record the response times for every request and response. Plot the data after that and arrange it so that you can see reaction time percentiles, including the worst-case response time.

If you are trying to report response times as viewed by someone who utilises the application metrics provided by the server program and not the system-wide or client-side metrics, you should be instantly suspicious if response times are tracked internally in the server application. Let’s explore this further. Just imagine that you are communicating with the server application right now. You send the application a request. However, let’s say a garbage collection event occurs before the server program has had a chance to read the request completely (which takes two seconds). The program hasn’t computed the incoming request timestamp since it hasn’t finished reading the request you just sent. This caused a two-second delay in the request you just sent, which will not be included in the response time latency.

Therefore, you should not use the data to reflect response time latency as experienced by a client application engaging with a server application when response time latency is measured within a server. The server’s response time calculation may not account for queuing that takes place between the client and server. When a server’s response time is assessed, it actually measures the latency starting from the arrival timestamp (after the incoming request has been read) all the way through until the response timestamp is taken (typically after the transaction completes and a response to the request is written).

Much of what is written in this section regarding how response time latency should be assessed applies to measuring throughput as well, even if it was not mentioned earlier when discussing throughput.

3.Memory Footprint or Memory Usage

Memory footprint requirements, or the amount of memory the application can consume, should also be well-documented and understood, much like the throughput and latency requirements that need to be fine-tuned. As with throughput and latency, defining a memory footprint goal is the first step. How much memory is anticipated to be consumed or used, in other words? A decent place to start is with a goal that simply measures expected Java heap use. Once that basic objective has been set, you can continue to probe for further information to make clearer what is anticipated. These extra questions may cover the following topics:

Does the amount of memory that is anticipated to be used in the application simply comprise the Java heap size? Or does that sum also account for native RAM consumed by the JVM or the application?
Is it possible that the anticipated memory consumption will never be exceeded?
How much might the expected memory consumption be surpassed, if at all?
How long can it be exceeded, too?
How will the amount of RAM used be calculated?
Will the statistic take into account the JVM process’s resident memory size as reported by the operating system?
Will the quantity of current data on the Java heap also be included?
When will memory usage be assessed?
Will the application’s idle time be measured?
when the program is operating in a steady state?
when the load is at its peak?

By proactively asking these kinds of questions, you can prevent some potential misunderstandings from people with different stakes in the application.