05-03, 14:30–14:55 (Asia/Jerusalem), General Track 2
CI/CD is critical for rapid software development, requiring advanced monitoring and logging infrastructure. We will present our PyTest integration with Elasticsearch, leading to significant debug reduction time and infra/product health improvements.
We will present our methods of integrating Python with the Elasticsearch database by using PyTest plugins and other advanced PyTest features. The Python + PyTest infrastructure allows us to gather useful data such as test coverage, infrastructure stability monitors, product health and debug information. We will go over the three different data levels that we are using: the CI/CD Infrastructure, test flow, and validation test coverage. In addition, we will share how this data enables us to achieve a faster, more stable CI/CD, leading to more efficient development and release cycles. Our system is based on Python PyTest and open source tools that can be run via cloud provider or local servers.
English
Target audience –Developers, Testers/QA, Integrators, DevOps, Data Scientists, R&D, Managers
Head of SW Tools, DevOps and Validation
Formed a team of software, validation and DevOps engineers, responsible for:
The design of an entire SW backend, automation, CI/CD and tools, spanning from AI frameworks, Python to low level SW (Drivers, FW)
Validation of a cutting-edge AI processor and its entire software stack (SDK, AI algorithm, FW, drivers and more) running on multiple pre-silicon and embedded platforms.
Development of business and customer tools such as building packages, Yocto distributions, benchmark tools, SDK CMD and more.
