Application to store 3D models

Type Web application
AREAS OF EXPERTISE Full-text search with Solr, AWS
QA TOOLS Selenium, Browser DevTools, Postman, Apache JMeter, MySQL Workbench, Putty, Fiddler, JIRA, Zephyre, Blazemeter, Datadog, OWASP ZAP, Burp, John the ripper, SSL scan, Nessus scanner
TEAM 15 employees

The project is a web-application to store and access 3D models. The application allows users to have a 3D models storage where they can view models by categories and download chosen ones. 3D models viewing without specialized software installation makes it possible to reduce management time considerably – designers’ work results can be viewed with minimal labor costs.


Development challenges:

  1. The customer wanted to migrate data of SketchUp models to his own server. The volume of data and files was large (about 4-6 TB). The migration of files and data in Solr had to be performed within a short period of time.
  2. The customer wanted to include full text search by different parameters. The number of queries was to be from 80 to 150 queries per second.
  3. A large amount of static content (about 100 000 images and files) had to be cached.

QA challenges:

  1. This is the high load and the big data application. Development of the test data for API testing, determining performance intensive use cases, organization and conduction of performance testing were the main challenges in QA for this project. The primary goal of the performance testing was the determining environment configuration capable to meet performance criteria of the project.
  2. The development and QA teams of the project were distributed between 3 offices, located in the different time zones, so the QA processes we developed took this fact into account.
  1. We parallelized the download of data and the download of files. Some data have been migrated consistently.
  2. Our specialists decided to use Solr for implementing full text search instead of MySQL. Solr is able to process a great number of queries faster.
  3. We used Amazon Cloud Front that allowed us to cache images and files. The customer’s servers did not receive queries, they were addressed to Amazon server where they were processed.

QA activities:

Functional testing, API testing, performance testing, configurational testing, security testing, web Automation QA process establishment and management.

  1. Our developers successfully performed migration of data and files to the server within 24 hours.
  2. Our specialists implemented full text search. The number of queries is up to 150 queries per second.
  3. We optimized the application and decreased the server load by 10 times.
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