GIL ZILBERFELD - Agile Testing Consultant, TestinGil

DIRTY TESTS AND HOW TO CLEAN THEM

We write tests and code for other people. Tests are code too, and both should be clean.

As a clean code fanatic, I see it as a personal mission to go around preaching how powerful clean code is. But unfortunately, it seems that test code is not considered "real code", and therefore is not considered "dirty".

In this session, we'll talk about concrete examples of anti-patterns in tests, and how to clean them up. We'll see how clean code principles apply directly to tests. And that's true for all tests - from unit to end-to-end, and regardless of who writes them - developers and testers. We'll see those in action.

"Clean code looks like it was written by someone who cares.", said Michael Feathers. Test code may even be more important to write cleanly for that reason.

EYAL COHEN - Automation Infrastructure Tech Lead, Taboola

SCALEABLE ANDROID AUTOMATION TESTING USING APPIUM ON KUBERNETES

How did we build entire eco-system to test android application on emulators fast, reliable and stable with open source libs only.

From local test writing to entire life cycle of the application under test (AUT) the Automation QA can all use the emulators we building on Kubernetes and using just few clicks in Jenkins to execute hundreds of test include network calls validation using internal proxy.

DANNY TOURGEMAN - VP of Quality, AppsFlyer

TESTING & MONITORING IN PRODUCTION @ SCALE

Testing and monitoring in production. Why are we doing it and How?

In this session, we will discuss how AppsFlyer's customers operate their business in reality, in real-time, all the time.
Why we run functional testing and validation periodically on our real production environment, and the testing challenges we face.
We will show examples of how are we doing testing in production along with monitoring and collection results up to alerts.

RAKEFET SHIMONY - Quality director, Finastra

DIGITAL TRANSFORMATION IN QUALITY ASSURANCE – FOLLOWING THE CHANGE IN QA

1. What is the meaning TODAY what is quality V.S while working in WF.
2. The change in the concept that QA is not testers v.s developers BUT it’s the engineering/R&D department responsibility
3. How to do it , how to execute it
4. At the same time how to preserve testers guild and expertise

ORIT GOLOWINSKI - Group Product Manager - Manage, GitLab

MEASURING DEVOPS IMPLEMENTATION

DevOps is a process, it is not something tangible. How can you measure the value of a change in process? Without measurements there is no clear way to know if an organization is improving overtime and if their DevOps investments is worthwhile.

In this talk we will present several ways to measure DevOps success, among them DORA4 metrics which have become the industry standard metrics that indicate the performance of a software development team.

ORLY SHECHTMAN - Senior Product Manager, Testim.io

AUTOMATION USING ARTIFICIAL INTELLIGENCE(AI) AND MACHINE LEARNING(ML)

Creating end-to-end functional tests is hard work. Automation frameworks require coding skills and platform-specific knowledge. Each test can take hours, creating a bottleneck that hinders fast releases. Once written, the flakey tests often fail on each minor code change, sucking up time for test maintenance.

Do AI-based solutions effectively solve these problems? This presentation will talk about different AI and machine learning approaches and how they enable test automation. We will also look to the future and discuss how AI might fundamentally change UI testing.

ELI BATTAT - Senior Software Engineer, Red Hat

HOW TO EASILY AUTOMATE PERFORMANCE TESTING IN OPENSHIFT AND KUBERNETES

Today, more and more organizations are using OpenShift/Kubernetes as part of their development pipeline. It is a big challenge to run scale testing on this complex container orchestration system. For that, we have developed the benchmark-runner automation framework.

Benchmark-runner is a containerized open-source Python-based project, secured and using cutting-edge technologies like GitHub actions, Docker, Ansible, Elasticsearch, Grafana, Prometheus, OpenShift visualizations (CNV - Kubevirt), and it is fully integrated with public clouds: AWS, Azure, and IBM Clouds.

This framework can connect easily to any OpenShift/Kubernetes cluster anywhere, run pod or Kubert virtual machines benchmarks against one node or more, fetch data results, and generate automatic reports.