Social network for finding, storing and sharing music

Development challenges:

1. There was a huge bulk of data with the relational structure represented as text-files in the system. The Customer wanted to arrange fast ways of searching for data items.
2. We had to scale and route the high load Stateful Service. The classical approach to balancing the load could not be used for this service.
3. The data processing algorithm was implemented as SQL scripts. The implementation took more than 24 hours. The Customer wanted to speed up this process.

QA challenges:

This is a big data and high load application. It’s featured by micro service architecture, it has integrations with music providers and social networks. The primary challenge was to create test data, which included musical contents and users. The application has to work on all iPhone devices, starting from iPhone 5s to the newest ones, running under different iOS versions. The project is developed under the Agile methodology with the short iteration period, so to conduct testing on so many devices took a lot of effort. The QA team was distributed between two remote offices, so it required the development and establishment of the QA process in a way that the two teams could collaborate efficiently.

1. We have used ETL algorithm based on the framework ReactiveX. The search index is created in ElasticSearch.
2. We have implemented a self-balancing method for the cluster. An individual address is sent to a client, the client can be served at this address.
3. We have migrated the data processing algorithm to Apache Spark.

QA activities:

Functional testing, API testing, performance testing, usability testing, configurational testing, compatibility testing, security testing, iOS mobile automation, Android mobile automation, QA process establishment and management.