## 5 Validation of Results
### Evaluations and Results  
To evaluate these experiments in SPIDEP, a total of 800,000 queries were sent for a period of 80 min (approximately 200,000 queries every 20 min). It should be noted that these values are obtained from the experiments performed between the two variants of SPIDEP, for more details please refer to Table 3. Another factor to consider is that 50 users are simulated requesting a set of random data simultaneously. Now, the response times of the instances are acceptable and are sufficient for this number of users; however, it must be kept in mind that this quality degrades as the number of users increases, if not foreseen with an adequate scalability of the infrastructure vs the demand [21]. The results were collected through a tabular output report generated after each load test, corresponding to its environment, as shown in Table 3. For the tables, the following labels are used: SPIDEP-SOA-K8s-T1 is a K8 environment that hosts all the services of the SPIDEP-SOA platform, this test will run multiple HTTP queries to a single service (service E); SPIDEP-MSA-K8s-T1 is a K8s environment that hosts all the services of the SPIDEP-MSA platform, this test will run multiple HTTP queries to a single service (service E); SPIDEP-SOA-K8s-T2 is a K8 environment that hosts all the services of the SPIDEP-SOA platform, this test will run multiple HTTP queries to two services simultaneously (services E and G); and SPIDEP-MSA-K8s-T2 is a K8 environment that hosts all the services of the SPIDEP-MSA platform, this test will run multiple HTTP queries to two services simultaneously (services E and G). The report contains several important values divided into four labels reflecting the type of environment executed, including the type of HTTP method executed, the number of samples, average response time, number of requests that are processed (i.e., hits per seconds), 90 th percentile, 95 th percentile, 99 th percentile, number and percentage of failed requests, the average latency time and the data consumption transferred between the user and the service. Additionally, several stress simulation tests in the infrastructure that host both variants of SPIDEP were performed, whose functions are to detect any problems that may arise in the platform. Reviewing CPU performance, memory, network I/O and connections (e.g., engine health to BlazeMeter) indicates whether the SPIDEP infrastructure itself is capable of supporting the demand-related bottlenecks or errors that appear [21; 53], as shown in Figures 4-7, with one figure for each environment. \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \multirow{2}{*}{**Labels**} & \multicolumn{3}{c}{**Avg.**} & \multicolumn{3}{c}{**Error Count**} & \multirow{2}{*}{**Avg. Bytes**} \\  & & & **Response** & & **Avg. Hitss** & \multicolumn{1}{c}{**90\% Line \({}^{*}\)**} & \multicolumn{1}{c}{**95\% Line \({}^{*}\)**} & \multicolumn{1}{c}{**99\% Line \({}^{*}\)**} & \multicolumn{1}{c}{**and**} & \multicolumn{1}{c}{**Accuracy**} \\  & & & **Time \({}^{*}\)** & & & & & & & & \\  & & & & & & & & & & & \\  & & & & & & & & & & & \\  & & & & & & & & & & & \\  & & & & & & & & & & & \\ \end{tabular}
\end{table} 
Table 3: General results of the simultaneous queries made to the RESTful methods of the SPIDEF application, under the SOA and MSA architectural styles, invoking single and dual services (i.e., medical data management (service E) and intervention management (service G). Figure 4: Engine Health Report SPIDEP-SOA-K8s-T1. The colored lines represent various parameters as follows: the blue line is the bandwidth traffic; the purple line is the memory load generated by the users; the green line is the CPU load generated by the users; and the red line is the active connections within the test. Figure 5: Engine Health Report SPIDEP-MSA-K8s-T1.