Aggregate web server logs contain crucial information about user web behavior, system performance, and page error history. Answer the following questions about this use case: A) Id... Aggregate web server logs contain crucial information about user web behavior, system performance, and page error history. Answer the following questions about this use case: A) Identify the most suitable type of access connector for collecting and aggregating web server logs. B) List the main components of the selected access connector and describe how they interact during the data ingestion process. C) List two common types of data stores that can be utilized with the access connector identified in the first question.
Understand the Problem
The question revolves around understanding web server log data handling. It asks to identify suitable access connectors, list components and describe their interactions, and list types of data stores related to the access connector. It is primarily focused on technical aspects of data ingestion and architecture.
Answer
A) Logstash. B) Inputs, Filters, Outputs, CPU. C) Elasticsearch, Amazon S3.
A) Logstash is a suitable access connector for aggregating web server logs. It allows efficient handling and processing of log data. B) The main components are Inputs, Filters, Outputs, and the Central Processing Unit. Inputs collect data, Filters process it, Outputs send it to the data store, and the CPU coordinates these operations. C) Common data stores are Elasticsearch and Amazon S3.
Answer for screen readers
A) Logstash is a suitable access connector for aggregating web server logs. It allows efficient handling and processing of log data. B) The main components are Inputs, Filters, Outputs, and the Central Processing Unit. Inputs collect data, Filters process it, Outputs send it to the data store, and the CPU coordinates these operations. C) Common data stores are Elasticsearch and Amazon S3.
More Information
Logstash is a part of the ELK stack (Elasticsearch, Logstash, Kibana) and is widely used for log analysis due to its versatility and efficiency.
Tips
Avoid misaligning components; ensure inputs feed into filters before reaching outputs.
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