Release #74 (2022-10-18)
- Added support for PHP8 and Magento 2.4.5. Now Wizart Magento Plugin supports for the latest version of PHP and Magento 2.4.x. Our plugin available here.
- Added a smart metadata generator. We developed and integrated some neural networks for product characteristics recognition. Now we recognise colors, styles, patterns, descriptions and other characteristic of products. It helps our clients improve their products metadata and helps their customers make choses.
- Added support for interactive murals. Now you can drag this mural across the walls to match your room decor idea (functionality enable by request).
Release #73 (2022-10-05)
- Released version 1.0.8 We added support for the latest Android 13 and the latest Android API 33.
- Added support for an interactive scene. Now you can manage carpets and drag them around your interior.
- Fixed slow and freezing sliders. Now all sliders work smoothly.
- Fixed bug with a camera works.
- Updated product type attributes. Added new properties of products. See all changes list here.
- Fixed bug with a camera works on Android 13.
Release #72 (2022-09-07)
- Fixed some bugs and stabilize PIM works.
Release #71 (2022-09-07)
- Added support for additional properties for the Paint product type.
Release #70 (2022-08-22)
- We improved the stability of our services and we fixed some issues that were causing short service interruptions.
- We improved the performance of some our highly loaded methods by 5-10 times.
We monitor the performance of our services on an constant basis. We monitor a speed and errors in the services work. We noticed that some time to time we have some problems with a speed and we have some “Time Out“ errors. The cause of that is our client database and product database which grow on an constant basis.
We profiled our code and we analized logs of our services and we noticed that we have some bottlenecks because our databases grow constantly. We recognized that we have some bottlenecks in our code and our database. We applied some solutions for our data base we optimized our SQL queries and we add new indexes. Also we optimized our code base and we minimized external requests count. Finally we found out that we have some API calls which work a long time and we applied a cache solution on Redis engine basis.
All these solutions helped us improved the performance of some our highly loaded methods by 5-10 times and currently we able to work with more parallel connections.