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Agenda
Coming Soon!
- Day 1
- Day 2
For many of us, 1st of January 2021 cannot come soon enough. 2020 will be the year that will hit the books as “the year of disruption” or for some “the year of the new normal”. But one thing is sure, life will never be the same again and Digital has become the new norm. But how can we use the developments of 2020 to build a new society, new organisations, new careers. In this presentation I will deepdive in the new norm and come with inspiring cases of people and companies that changed perspective and used the crises as a way to re-invent themselves. Are you up for a new normal, and ready to change your perspective. Then make sure you listen in to this keynote
For many of us, 1st of January 2021 cannot come soon enough. 2020 will be the year that will hit the books as “the year of disruption” or for some “the year of the new normal”. But one thing is sure, life will never be the same again and Digital has become the new norm. But how can we use the developments of 2020 to build a new society, new organisations, new careers. In this presentation I will deepdive in the new norm and come with inspiring cases of people and companies that changed perspective and used the crises as a way to re-invent themselves. Are you up for a new normal, and ready to change your perspective. Then make sure you listen in to this keynote
Musala Soft develops a new Declaration Management System for the Dutch Customs. As an independent Test Automation Engineer, I helped the Dutch government with testing the delivered products. We implemented a Test Automation framework using Robot Framework and applied the principles of the Test Automation Pyramid, enabling us to test the system very efficient. Also the testers of Musala Soft were involved.
In this talk I want to emphasize on the importance of the test automation pyramid and the possibilities to use the REST interface of applications with Robot Framework.
ps. The Terms and Conditions are in Bulgarian, so I am not sure what I agreed with 😉
In this topic we are going to share how to build an automation framework which can be used by everyone. Main technologies behind it are java / cucumber / testNG. ISTA participants will see main principles building an automation framework in a way any QA will be able to learn / use and contribute. On top of that any non technical person will be able to consume and write UI tests. There will be examples from a client we have been working with since 2016 – adidas HQ. Part of our presentation will be devoted to the automation growth knowledge within the project – scaling from 3 automation engineers to 50+ for the period of 6 months.
Blazor is a technology which allows you to build a web application using only C#.
Soon after Blazor WASM was officially released it started gaining quite a lot of popularity.
In this talk, we will start with a general overview of the Blazor WASM framework and continue with more specifics about the framework such as authentication, performance optimizations, unit tests, error handling, etc. We will showcase these things in a demo application build specifically for this presentation.
Cypress is a relatively new JavaScript testing framework that seems to be targeting a lot of the typical pain points when it comes to all types of web related testing, especially end-to-end. In this talk you will receive a general overview of the technology with its quirks and strong suits.
How can you make your app a success? How can you maintain it easily during its lifetime? Which are the things to focus on and where can you use shortcuts? When to use startup developers and when to avoid them? All these questions are answered in this talk so that you too can develop your mobile app successfully.
Imagine “to run”. You probably see in your mind yourself running, or an athlete crossing the finish line, or a cheetah chasing a gazelle. We are object oriented – we perceive and consume the world through the objects in it. We need an object to show an action. Our perception of the world is built on objects that we can interact with – touch, see, export,… and that have properties – large, blue, nice,… . We are so object-oriented, that we objectify even abstract notions – liberty is a woman waving a flag or holding a torch, and democracy can be built or ruined.
Three basic needs form the backbone of this objectivity: orientation, consistency and organization. It is beneficial to understand the principle of object-orientedness and the basic needs and apply them in your work. This object-oriented approach to analysis and design breaks down the problem space into objects, their attributes, the relations among the objects and the actions that can be performed with these objects.
You will:
Understand the concept of object-orientedness, which is successfully used by programming, design, and documentation;
Take a different look at the way you think about content and places;
See various examples that illustrate the three basic human needs in a place;
Change the way you design, test, and deliver.
Ideally, there would be a single unified Data Science Platform,
that everyone would use, for all Data Science use cases.
There are more challenges towards that ideal point.
The Data Science Process has more phases each further branching out into many tasks,
and each task can potentially have different hardware requirements (CPUs, GPUs, etc.),
and software requirements (programming languages, libraries, frameworks, etc.).
The software tools that can be used for one task are usually more,
and overall the software tools landscape is very fragmented and has high variance.
During development, there is constant change in data, code, and ML models.
Our end-to-end Data Science Workflows need to be reliable, portable, scalable, and reusable.
We should also be able to iterate fast and work Agile-like.
It is not just about training ML models and prediction,
there is a lot more to operationalization and lifecycle management of ML products.
The modern approach for addressing all these challenges is to use containerized components,
connected in a microservices architecture, to orchestrate the entire system from one main control point,
and to apply DevOps principles for continuous development, integration, deployment, and monitoring.
In other words, we need MLOps.
After this talk, you will be able to start experimenting towards making your own Data Science Platform.
Have you ever worked with a large and complex codebase, limited automated test coverage, lengthening release cycles, and the danger of accumulating technical debt? It can be difficult to know where to begin, particularly when you have competing demands to spend time delivering new functionality. Two years ago our team realised we needed to modernize the architecture of one of our products, which would eventually involving refactoring the several hundred-thousand line codebase from a monolithic architecture to a distributed micro-service based deployment. In this talk I’ll share how we used test automation techniques to drive this transformation, and share lessons learnt as we redesigned both our software architecture and our development processes – allowing us to move from quarterly release cycles to a continuous delivery model.
Modern cloud architectures often rely on storing and analyzing “big data” where common recurring problems are cost, scale and searchability. This has been traditionally solved with proven No-Sql technologies such as ElasticSearch, Cassandra, Hadoop, data lake, etc. Our team within Vmware CarbonBlack explored these technologies and found limitations with respect to the data ingress volume, latency, data privacy, cost, scale and search flexibility. In this talk we explore the alternative solution built: a novel way to leverage existing Lucene search technology in conjunction with data lake approach to store, index and search many petabytes of real-time streaming data in a cost-efficient way.
“Modern software development methodologies and approaches help to increase delivery speed while still caring about software quality. However, if we think about manual regression tests, they are not only time consuming and repeatable, but also feedback time is quite high. These are the reasons why regression tests are often automated.
Automated tests can provide results faster and it’s possible to execute them more frequently than manual ones. They can decrease the overall time needed for tests, but what’s probably even more important, they allow to test and receive feedback earlier in the development process. It’s essential if we want to release and deliver business value faster and more frequently.
But what if we have more and more tests and even automated execution of them takes too much time – 10 minutes… 30 minutes… maybe even hours? Should we consider the ability to execute full tests set just a few times a day as something normal? Is adding more compute resources the only option to reduce the execution time? Or maybe there are too many high-level tests and some of them should be replaced by low-level ones according to the Test Pyramid? Is the Test Pyramid still valid in the cloud world?
During the presentation, you will see how the serverless cloud services like AWS Lambda may be used to run tests in the highly parallelized environment that can speed up test execution even hundreds of times.”
Speakers
Coming Soon!
*UNTIL 20/07
*UNTIL 30/09
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