{'fraction_non_alphanumeric': 0.01678445229681979, 'fraction_numerical': 0.0, 'mean_word_length': 5.5491329479768785, '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}}
Exploring Cloud Monitoring Data Using Search Cluster and Semantic Media Wiki

Cloud monitoring data are produced from traces of infrastructures, platforms and custom metrics to help ensure that workloads are operating at optimum levels. Analysis of cloud monitoring data delivers knowledge of the system's workload, usage pattern and enables prediction for future capacity planning. The operations involve data query and extraction, data analysis and result visualization. Since the volume of monitoring data is large, these operations require a cloud architecture to support extracting and aggregating data in an arbitrary range of granularity. Furthermore, the cloud architecture should be integrated with a Web-based interface for structured query and result visualization. This paper presents our software tool, called Trace Analyzer that explores a cloud-based search engine for data indexing and query, displays the processing results in the form of Semantic Media Wiki (SMW) pages. This cloud architecture is empirically assessed to evaluate its responsiveness when processing a large set of data records under node failures.