Microservices and Kubernetes help our architecture to scale and to be independent at the price of running many more applications. Golang provides a powerful profiling tool called pprof, it is useful to collect information from a running binary for future investigation. The problem is that you are not always there to take a profile when needed, sometimes you do not even know when you need to one, that’s how a continuous profiling strategy helps.
There’s no better way to understand container security than seeing some live hacking! This session introduces the state of docker security by reviewing vulnerabilities in docker images and their impact on applications, and demonstrates via hands-on live hacking. This session further provides the audience with security best practices when building docker container images, and each successful hack will help you better understand the mistakes you can make, their implications, and how you can avoid them.
DevOps works and made all our lives easier, but it can do so much more for so many more people! In this talk we step into the shoes of someone who does Business Process Management (BPM), see DevOps from that perspective, and learn how DevOps practises apply to making BPM more efficient!
Does your organization have hundreds or thousands of existing applications? Need to decide which to maintain and which to modernize? Is your current strategy “everything goes into a container”?
Come join this session to learn processes and practices that helped organizations adopt cloud native development practices to go beyond “just containerization”.
Organisations build software all the time, from developer machines to CI, even public pull requests.
There are security risks associated with these actions! Come discover what they are and how to mitigate them.
The build tool is about execution of modifications and thus inherently insecure.
This presentation describes the most common test smells and some methods used to prevent them. These methods are applied in the test of a big project and results are presented.
It starts by pointing out the importance of test automation and costs resulted by the ignorance of QA. It is also described that automation is needed but has several difficulties like inconsistent results. This is followed by reasons of those results, definition of test smells and taxonomy of test smell types with a description of each smell.
The second part briefly investigates a real system, providing examples of conditions. For this work; SUT is a cloud-based open IoT operating system, which consists of microservices. The product has been developed by more than 600 people in 10 globally distributed countries.
Many enterprises that want to become a data-driven organisation start a separate data team in isolation. For first exploration of data science and understanding its potential, that is fine. However, to become successful with data and deliver the promises of a data-driven organisation, data science needs to be integrated in the organisation and data scientists (and analysts) need to be able to use a mature self-service platform to develop their models.
Increasing requirements in code quality and availability can only be tackled by adopting a CI/CD process. Starting with a simple application, we will implement a basic build chain that compiles, tests, and deploys our solution using NUKE. In the next step, we will use TeamCity to make our build an actual CI build that gets triggered with every new change. How do you change things?
It is crucial to understand how we can automate everything in data platforms to make it stable and enable real time data streaming analysis. There are some the most important details how it can be provided. Monitoring, Infrastructure-as-Code, automation, preventing issues – how it works in practice and which services are the most useful?
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