Last updated：2022-01-11 13:43:23
KES applies to a variety of business scenarios, such as search service, real-time log analysis, time series data analysis, and business intelligence analysis.
KES is widely applied to application, website, and enterprise-class searches. In daily work and life, people perform searches to quickly find required information, such as products, locations, videos, documents, hotels, and flights. KES provides a low-latency search service that is highly available and supports a large number of concurrent requests. It helps you find required information in PBs of data within milliseconds.
KES applies to real-time log analysis scenarios. It can be used to analyze business logs such as user behavior logs, status logs such as exception logs and slow logs, system logs, and audit logs. Logs can help you locate exceptions but they are scattered, diversified, and large in scale. KES provides a comprehensive solution for log analysis. KES uses Beats and Logstash to connect to various data sources, stores logs in a centralized storage, and uses Kibana dashboards to display analysis results. KES supports full-text search and responds to your searches in seconds. This allows you to interactively analyze massive amounts of logs and to efficiently utilize logs.
KES can be used to monitor infrastructure metrics, containers, application performance, and IoT devices. You can write tens of millions of time series data records to KES per second. KES provides multi-dimensional, flexible, and scalable statistical analysis capabilities and responds within seconds. This allows you to be notified of system events in real time. You can also observe historical trends, regularities, and abnormalities, and make predictions and warnings accordingly.
Under the trend of data-driven decision-making, more and more companies rely on data analysis and mining to make business decisions. For example, the owner of a large shopping mall can make business decisions based on the reports about the trend of user consumption and the composition of user groups in a specific region in the past three years. With the growth in the volume of data and increased demand for efficiency in analysis, KES can assist in business decision-making by providing structured queries, complex filtering, and aggregate statistics.