AWS-based Web Log Analysis System Architecture

AWS-based Web Log Analysis System Architecture

AWS provides services and infrastructure to build reliable, fault tolerant, and highly available Web applications in the cloud environment. In a production environment, these applications generate a large amount of log information. This data is an important source of knowledge for any company to operate web applications. Analysis logs can reveal information, such as traffic patterns, user behavior, and market information.

However, as Web applications grow and the number of visitors increases, it is increasingly challenging to store and analyze network logs. Demonstrate how to use AWS to build a scalable and reliable large-scale log analysis platform. The core component of this architecture is AmazonElastic MapReduce, A Hadoop framework that enables analysts to process big data economically and conveniently.

1. The Web Front-End Server runs on an Amazon ElasticCompute Cloud (Amazon EC2) instance.

2. Amazon CloudFront is a CDN service that distributes static files to users. It also produces valuable log information, featuring low latency and high transmission rate.

3. Data is sent through multiple web servers or edge nodes in parallel. log files are periodically uploaded to AmazonSimple Storage Service (Amazon S3 ).

4. Amazon ElasticMapReduce clusters are used to process datasets. AmazonElastic MapReduce uses the Hadoop framework to process data in parallel job streams.

5. When Amazon EC2 has unused capacity, you can cut costs through SpotPrice, which is based on availability and real-world requests. If the workload is exhausted or needs to be expanded within a period of time, you can use SpotInstances to dynamically expand the cluster capacity, significantly reducing the cost of running the job flow.

6. Using tools like Apache Hive, the data processing result is pushed to a relational Database, which can be an AmazonRelational Database Service (Amazon RDS) instance. AmazonRDS is easy to install, operate, and expand in the cloud environment.

7. Like many services, AmazonRDS instances are priced based on the pay-as-you-go model. After analysis, the database is backed up to Amazon S3 as a snapshot, and the service is terminated. The database can be re-created whenever necessary.

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