{'fraction_non_alphanumeric': 0.01650485436893204, 'fraction_numerical': 0.0, 'mean_word_length': 5.286585365853658, '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}}
Models@runtime for Monitoring Cloud Services in Google App Engine

A number of monitoring approaches for cloud services have been proposed in the last years. However, they suffer from several limitations mainly due to changes in the monitoring requirements or because of the complexity in dealing with raw data from services at runtime. To address these problems, in a previous work, we proposed a platform-independent monitoring middleware for cloud services using models@runtime. This middleware was implemented in Microsoft Azure to monitor the quality of cloud services. To provide further evidence about the generalizability of our approach, in this work, we introduce the implementation of the monitoring middleware in the Google App Engine. The middleware gather raw data from the running cloud services to perform measurements that assess the compliance to the quality requirements established in a SLA. The use of models@runtime allowed us to provide a high-level of flexibility to change quality requirements at runtime.