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The primary challenge undertaken was to fetch the data from SQL databases containing billions of records in a matter of seconds. Another challenge was delivering a fail safe system so the requests are not lost because of services being unavailable.
We had to integrate a traffic analyzer with a legacy designed database system of ACL. Another hurdle was to provide filtering at a highly atomic level in a dataset with billions of records and a complex database designed architecture. Heavy download queries had to be handled without putting too much load on the servers.
We used a GPU based database SQREAM for faster retrieval of records and created an indexed database and performed DB query optimization exercises.
Highly optimized use of SQL for fast data retrieval from the database.
To enhance the queries and reporting, SQream Big Data database was used to query billions of records.
To enhance the experience, detailed reports are displayed in the SPA for better user experience and faster loading.
Latency reports for any failure and reporting of messages are also sent to the user to analyze the usage.
Data distributed across databases of different types (MySQL, SQream) based on the age of data for extremely fast query performance.
Ability to have in depth filter, intra-data item filtering supported for enhanced user experience and refined data.
The Traffic Analyzer administrator can manage other admins and their project clients. The client is added to the website through App ID and granted access to different features by the admin.
Administrators have different levels of permissions that they can provide to the users.
Features available to users are Dashboard, Detailed Reports, Summary Reports, Delivery Latency Reports, Short URL Reports, User Management, Download History, and Alert Notifications.
We used queue-based microservices architecture to make for the development of a high fail-safe system.Read Articles