{'fraction_non_alphanumeric': 0.029224904701397714, 'fraction_numerical': 0.0021177467174925877, 'mean_word_length': 4.979746835443038, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Impact of Running Dynamic/Static Scans on the Performance of an App Running in a GKE Clusters

The IT world we live in today, are prone to ransomware attacks or hijacking of applications due to vulnerability and stealing vital data has become a norm, so to say our IT resources are vulnerable. The scanning of the applications, data, the IT infrastructure which houses them is become paramount. Data and/or Applications stored/running in a dormant/active state in a GitHub repository, centralized version control system (CVCS), or whether it is running as a service such as Website, Representational State Transfer (REST) [1], having an API Gateway accessing the critical data [2]…, etc are more vulnerable to attacks than before. Modern techniques of a CI/CD process where data is pulled, compiled and brings the application/data alive has to be continuously monitored and checked for vulnerabilities without compromising the responsiveness of the application. This study is an effort to show that the static/dynamic scanning of applications/data in both dormant/running state of an application does not affect the performance of the application or access of critical data using the REST/Web Service Definition Language, or WUSDL (Web Services Description Language). In this study, the applications/data were deployed in a GKE (Google Cloud Kubernetes environment ) and were scanned using an industry-standard scanning tool viz Prisma Compute®. The performance of the application/data access using REST and or WUSDL was computed using the TCP/IP handshake delta time. These delta time were statistically analyzed by using Test of Hypothesis/Analysis of variance (ANOVA) [3] and K-Means [4] to determine if the delta in TCP/IP 3-way handshake is significantly different when the application is in an idle state ( no user traffic being processed), and in a static/dynamic scan mode using the Prisma Compute® tool when the user traffic is introduced. Based on the tests conducted, we found that there is not a significant difference in running dynamic or static scans on the application or the data and its impact is not statistically significant to the performance. This paper presents the case study which details the application/data test setup in the GKE environment, tests ran, statistical analysis conducted on the data obtained and the preliminary results.