On this site, there is only displayed the English speaking sessions of the OOP 2022 Digital. You can find all conference sessions, including the German speaking ones, here.
The times given in the conference program of OOP 2022 Digital correspond to Central European Time (CET).
By clicking on "EVENT MERKEN" within the lecture descriptions you can arrange your own schedule. You can view your schedule at any time using the icon in the upper right corner.
- Artificial Intelligence Now!
- C++ and Programming of Embedded Systems
- DevOps & Automation Now!
- Diversity & Inclusion
- From Projects to Products/Services: Aligning Architecture and Organization for Sustainable Speed
- Full Day Tutorial
- Fusion: IT-Future-Society
- Half Day Tutorial
- Modern Software Architecture
- Product Development in Times of Digitalization
- Signature Track: The Time is Now!
- Social Integration
- Software Architecture Communication & Assessment
- Testing & Quality
- Trends & Techniques
- Use Domain-Driven Design Now!
- Artificial Intelligence
- Domain-Driven Design
- Product Development
- Programming Languages
- Requirements Engineering
- Soft Skills/Social Skills
- Software Engineering
- Talks with Limited Attendance
- Testing & Quality
- Virtual Reality
Today we must deal with shorter time-to-market, increasing complexity and more agility while keeping quality and other key system properties high.
To address these challenges the right timing in testing is critical but often not explicitly tackled. Therefore, in this interactive tutorial we reflect on our current approach on timing in testing, investigate and discuss needed strategies, tactics, and practices in different areas, and share experiences and lessons learned to improve timing in testing – because it is time to act now!
Maximum number of participants: 50
Target Audience: Test Architects, Test Engineers, Product Owners, Quality Managers, Software Architects, Developers
Prerequisites: Basic knowledge about testing and quality engineering
Today we must deal with shorter time-to-market, increasing complexity and more agility while keeping quality and other key system properties high. Our test systems increase in size, volume, flexibility, velocity, complexity, and unpredictability. Additionally, digitalization requires more than just a face lift in testing.
To address these challenges the right timing in testing (“when to do what kind of testing and how?”) is critical, but often not explicitly tackled. Therefore, in this interactive tutorial we reflect on our current approach on timing in testing, investigate and discuss needed strategies, tactics, and practices in different areas, and share experiences and lessons learned to improve timing in testing – because it is time to act now!
Some of the areas in testing that are covered in the tutorial are:
- When to do what kind of testing in the lifecycle – agile, lean, DevOps, and beyond
- Testing too early vs. too late – risks and opportunities
- Test automation and the test pyramid – shift-left, shift-right
- When to stop testing – test exit criteria
- Repetition in testing – regression testing
Chaos engineering, popularised by Netflix, is an approach to building scalable, resilient systems through destructive experiments, but what other impacts does it have? How can adopting chaos engineering change organisational culture? This talk explores the parallels between modern distributed architectures and the unpredictable challenges of the modern world, and how approaches like chaos engineering help organisations deal with both.
We will deep dive into the practices needed to make chaos engineering a success in your organisation and uncover how they help beyond just chaos engineering experiments. We will also explore the nature of complex, socio-technical systems and why new approaches are needed to deal with them.
Target Audience: Anyone in a team or organisation considering adopting chaos engineering
Digitalization has been changing existing industry B2B businesses, digitalization business models arrived and the Digitalization solutions need to be developed to support this. The sudden enforcement of social distancing has given the digital transformation a significant push forward. How do we develop innovative Digitalization offerings in the future? We will show how to seize these opportunities and forge new paths toward the new normal for Software Engineering.
Target Audience: Software Engineers, System and Software Architects, Software Managers
Prerequisites: Knowledge in Software Engineering Practice
To continuously deliver IT systems at speed with a focus on business value, high-performance IT delivery teams integrate quality engineering in their way of working.
Quality engineering is the new concept in achieving the right quality of IT systems. Testing only after an IT product was developed is an outdated approach. Built-in quality from the start is needed to guarantee business value in today’s IT delivery models. Quality engineering is about changes in skills, organization, automation and quality measures.
Target Audience: All people involved in high-performance IT delivery teams
Prerequisites: General knowledge of IT delivery
To continuously deliver IT systems at speed with a focus on business value, high-performance cross-functional IT delivery teams integrate quality engineering in their way of working.
Quality engineering is the new concept in achieving the right quality of IT systems. Testing an application only after the digital product has been fully developed has long been a thing of the past. More is needed to guarantee the quality of applications that are delivered faster and more frequently in today’s high-performance IT delivery models. It is about achieving built-in quality. The road to quality engineering means changes in terms of starting points, skills, organization, automation and quality measures.
Our new VOICE model guides teams to align their activities with the business value that is pursued, and by measuring indicators, teams give the right information to stakeholders to establish their confidence that the IT delivery will actually result in business value for the customers.
Teams benefit from the clear definition of QA&Testing topics that are a useful grouping of all activities relevant to quality engineering. Organizing topics are relevant to align activities between teams and performing topics have a focus on the operational activities within a team.
Also, to be able to deliver quality at speed, for today’s teams it is crucial to benefit from automating activities, for example in a CI/CD pipeline, whereby people must remember that automation is not the goal but just a way to increase quality and speed.
In this presentation the audience will learn why a broad view on quality engineering is important and how quality engineering can be implemented to achieve the right quality of IT products, the IT delivery process and the people involved.
This presentation is based on our new book "Quality for DevOps teams" (ISBN 978-90-75414-89-9) which supports high-performance cross-functional teams in implementing quality in their DevOps culture, with practical examples, useful knowledge and some theoretical background.
Rik is a trainer for test design techniques for over 15 years.
In large software projects the assessment of the impact of a code change can be a cumbersome task. If the software has grown and shows an evolutionary design there are always unwanted side effects.
Change control boards are established. But on what data do they judge what can happen with the changes? Very often there is the HIPPO syndrome which means it is the highest paid person's opinion.
In this talk we will show you ways to come to a deterministic prediction of the impact, what data you need and what you can do with it.
Target Audience: Architects, Test Managers, Developers, Testers
Prerequisites: Basic knowledge of collected data in software projects
On-Call is an increasing reality for developers, especially when a site has strict uptime requirements. And sadly, the experience often sucks. It's easy to mandate 24x7 support, it's much harder to set it up in a way that doesn't make the life of the people in the rotation miserable.
I want to talk about improving alerting. I'm focusing on creating high-quality alerts that trigger when they should and don't trigger when nothing is happening. Continuous tuning, automation, and using the right metrics are core parts of this process.
Target Audience: Developers, Architects, DevOps, Operators
Prerequisites: Monitoring, operating production software
Do you believe in “you build it, you run it”? What if you have on-call rotations, where you are responsible 24x7 for the health of a system? Nothing is quite so infuriating as a collection of poorly structured alerts that trigger randomly.
So, let’s do better! I want to talk about how to improve your monitoring capabilities. There are a few topics I want to touch:
- Reduce the noise
- Automate as much as possible
- Build actionable triggers
- Tune your monitoring constantly
After this talk, you’ll have concrete actions to make your engineers’ life easier when on-call.
He is a full-stack engineer with infrastructure skills. He has led multiple agile delivery teams, being an individual contributor, driving architecture topics, and coaching and supporting other team members.
He believes in high-quality software and advocates for Continuous Delivery, Tes- Driven Development, and quick iteration. He writes and speaks about his experience regularly.
Our world accelerates, innovation cycles get shorter, causing innovation pressure for software companies to deliver their software faster and with high quality. DevOps shows us that delivery speed and quality are no trade-offs. You can have both!
In this talk, we will go on a journey from the beginnings of DevOps to today. We discuss findings of the famous DevOps study, detailed out in the Accelerate book. I make a case, why every company should measure the Four Key Metrics of DevOps and show you different ways to approach this.
Target Audience: Architects, Engineering Managers, Project Leaders, Developers
Prerequisites: You should have worked on at least one IT project or product.
Due to the capabilities of Kubernetes, the usage of patterns rises to solve complex questions, but causing often confusion and unnecessary implementations. This talk intends to show what are the right scenarios for and for which cases another pattern is more suitable.
In this talk, Max will introduce you to various patterns, often misused by running applications and services within Kubernetes. The focus will be on structural patterns like Sidecars and Ambassadors as well as more advanced patterns like Controller and Operator.
Target Audience: Architects, DevOps Engineers, Platform Teams
Prerequisites: Good Understanding of Kubernetes
From this talk, you should take away in which scenario a pattern will suit most likely and how you can implement it. We will also look critically at the usage of these patterns.
Max ist Kubernetes und Cloud Native Advocate bei Liquid Reply mit Sitz in München. In den vergangenen Jahren hat er Cloud-native Lösungen auf/mit Kubernetes gebaut. In letzter Zeit treibt er das Thema Plattform-Engineering bei verschiedenen Kunden voran, um die aktuellen Herausforderungen mit komplexen Zielumgebungen zu vereinfachen. Nachts arbeitet er mit dem Kubernetes-Release-Team zusammen, um neue Kubernetes-Versionen zur Verfügung zu veröffentlichen.
The clean code principles are well-known in modern, agile software development. But what has become the default for our business code, unfortunately by no means applies to our infrastructure code. Instead, we find badly crafted, complicated and highly tangled code that is manually tested using a trial and error approach. However, for modern cloud based systems the infrastructure code plays a crucial role. So it's about time we begin to treat it as a 1st class citizen! This hands-on session shows how to craft clean infrastructure as code.
Target Audience: Architects, Developers, DevOps Engineers, SREs
Prerequisites: Basic knowledge of infrastructure as code practices and tools
I will introduce two AWS services: CodeGuru and DevOps Guru.
CodeGuru Reviewer uses ML and automated reasoning to automatically identify critical issues, security vulnerabilities, and hard-to-find bugs during application development.
DevOps Guru analyzes data like application metrics, logs, events, and traces to establish baseline operational behavior and then uses ML to detect anomalies. It does this by having the ability to correlate and group metrics together to understand the relationships between those metrics, so it knows when to alert.
Target Audience: Developers, Architects, Decision Makers
Prerequisites: Basic understanding of the code quality metrics and observability
In this talk I will introduce two AWS services: CodeGuru and DevOps Guru.
Code reviews are one example and are important to improve software quality, software security, and increase knowledge transfer in the teams working with critical code bases. Amazon CodeGuru Reviewer uses ML and automated reasoning to automatically identify critical issues, security vulnerabilities, and hard-to-find bugs during application development. CodeGuru Reviewer also provides recommendations to developers on how to fix issues to improve code quality and dramatically reduce the time it takes to fix bugs before they reach customer-facing applications and result in a bad experience
Amazon DevOps Guru analyzes data like application metrics, logs, events, and traces to establish baseline operational behavior and then uses ML to detect anomalies. The service uses pre-trained ML models that are able to identify spikes in application requests. It does this by having the ability to correlate and group metrics together to understand the relationships between those metrics, so it knows when to alert and when not to.
This talk describes how to build and run a successful product development organization that delivers business value, not just features. I will cover what makes effective product development teams, how to structure, loosely couple, align and choreograph them, especially in larger organisations with up to 100 teams. Methods I will talk about include OKRs and Kanban Flight Levels. In this context I will also show when and how decentralised product teams can benefit from centralised platforms.
Target Audience: CTO, Manager, Decision Makers
Prerequisites: Experience with software development at scale