InfoQ Homepage Culture & Methods Content on InfoQ
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Transforming Software Product Teams into Tech Investors
The key responsibility of an organisation lies in balancing user value with profitability. In a product organisation, software product teams invest their own time. According to Fabrice des Mazery, software developers are much more than stakeholders; they are the main investors as they are part of the product teams.
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Java in Education Initiative Aims to Empower the Next Generation of Developers
The Java in Education, launched by the Java Community Process (JCP) Executive Committee, is making significant strides in promoting Java technology within educational institutions. This program seeks to bridge the gap between academia and industry, ensuring that Java remains a foundational skill for aspiring developers.
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Enabling Developer Productivity: Intentional Evolution of the Platform at InfoQ Dev Summit Boston
At the InfoQ Dev Summit in Boston, Jennifer Davis, an engineering manager at Google and author of "Effective DevOps" and "Modern System Administration," discussed strategies for enhancing developer productivity through intentional evolution of platforms. She emphasized the importance of effective documentation and code samples in fostering a thriving developer community.
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How Data Mesh Platforms Connect Data Producers and Consumers
A challenge that companies often face when exploiting their data in data warehouses or data lakes is that ownership of analytical data is weak or non-existent, and quality can suffer as a result. A data mesh is an organizational paradigm shift in how companies create value from data where responsibilities go back into the hands of producers and consumers.
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Transitioning from a Software Engineering Role into a Management Role
Software engineers who want to become good at leading engineers can use everyday opportunities to practice management. Peter Gillard-Moss gave a talk at QCon London where he shared his experience with becoming a manager, and provided tips and ideas for engineers aiming to become a manager.
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WDL 1.2.0: Enhancing Workflow Description Language for Bioinformatics
The Workflow Description Language (WDL) team has announced the release of WDL 1.2.0, a significant update to improve workflow descriptions' flexibility and usability in bioinformatics. This new version introduces several key features and enhancements that promise to streamline workflow management and execution, making it easier for developers and researchers to implement and manage workflows.
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Improving Mobile Test Automation with Continuous Integration, Central Logging, and Metrics Analysis
Continuous integration can enhance automated mobile testing. Test data from multiple mobile devices running parallel tests can be consolidated to support monitoring. Jira tickets from manual testing can trigger the build process to ensure that testers will have the correct software version to do the manual testing.
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Fostering Healthy Tech Teams in a DevOps World
Building healthy DevOps tech teams that are responsible for a broad area can be challenging. To measure the success of your team, several frameworks provide metrics indicating team health. Psychological safety matters for healthy teams to ensure each software engineer brings their own lived experiences to build better products and that they feel safe to do so.
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Combatting Alert Fatigue at Cloudflare
In a detailed blog post, Monika Singh at Cloudflare explores the stressful environment on-call personnel face. On-call staff frequently deal with numerous alerts, leading to alert fatigue—a state of exhaustion caused by responding to non-prioritised or unclear alerts. To combat this, Cloudflare teams conduct periodic alert analyses to enhance the accuracy and actionability of alerts.
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How to Scale Agile Software Development with Technology and Lean
Agile software development can be done at scale with the use of technology like self-service APIs, infrastructure provisioning, real-time collaboration software, and distributed versioning systems. Lean can complement and scale an agile culture with techniques like obeyas, systematic problem-solving, one-piece-flow and takt time, and kaizen.
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Making Agile Software Development Work for Multicultural Teams
While equality provides team members with the same opportunities and allowances, equity is about creating an environment where individual and unique needs can be met. According to ElMohanned Mohamed, communication in multicultural teams should be precise and clear with low dependence on the context.
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QCon London: a Tale of Team Topologies at m3ter
At QCon London 2024, Ricardo Nuno Almeida spoke about adapting Team Topologies at m3ter. Almeida, senior software engineering manager at m3ter, spoke about how adaptability proved crucial to success and ran through m3ter's journey of evolving team topologies to meet growth demands and changing priorities.
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How to Build Large Scale Cyber-Physical Systems
To build large-scale safety-critical systems, we need to decompose the system into smaller solvable problems, resolve what is known, and resolve unknowns through experiments, Robin Yeman argued. She suggested investing in test environments for both software and hardware early to enable being test-driven early to increase the safety, security, reliability, and availability of the systems.
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QCon London: Curating a Developer Experience
In a talk at QCon London 2024 titled "Curating the Developer Experience," Andy Burgin discussed embracing Developer Experience (DevEx) as an operational philosophy at the betting company Flutter. Recognising the potential of DevEx to enhance productivity and foster collaboration and empathy between teams, Burgin explained how Flutter implemented and evolved their Developer Experience.
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Challenges and Solutions for Building Machine Learning Systems
According to Camilla Montonen, the challenges of building machine learning systems are mostly creating and maintaining the model. MLOps platforms and solutions contain components needed to build machine systems. MLOps is not about the tools; it is a culture and a set of practices. Montonen suggests that we should bridge the divide between practices of data science and machine learning engineering.