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The Mythical Technical Debt (Brooke, please, forgive me.) <This talk is designed for a technical audience> In software-intensive systems development, we often face trade-offs between speed and long-term maintainability. These trade-offs accumulate as technical debt, the hidden cost of short-term decisions that can impact future development. Technical debt goes beyond the initial choices made when creating software. It encompasses design decisions, coding practices, or anything that might hinder future development efforts. By effectively identifying and managing this debt, we can build robust and scalable software systems. In this talk, we'll explore different types of technical debt and their impact on projects. We'll delve into practical methods to identify, measure, and reduce it. Finally, we'll see how to turn technical debt into an advantage, using it as a springboard for innovation with real-world examples.

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This presentation covers the following topics: What is logging? The purpose of logging: Debugging The purpose of logging: Security The purpose of logging: Stats & analytics Traditional logging Traditional logging: Advantages Traditional logging: Disadvantages The solution: Large-scale logging Large-scale logging: Core principles Large-scale logging: Solution types Large-scale logging: Cloud vs on-prem Large-scale logging: Operational complexity Large-scale logging: Security Large-scale logging: Costs Large-scale logging: On-prem comparison - Elasticsearch - Grafana Loki - VictoriaLogs On-prem comparison: Setup and operation On-prem comparison: Costs On-prem comparison: Full-text search support On-prem comparison: How to efficiently query 100TB of logs? On-prem comparison: Integration with CLI tools VictoriaLogs for large-scale logging VictoriaLogs demo instance - Ingestion rate: 3600 messages / minute - The number of log messages: 1.1 billion - Uncompressed log messages’ size: 1.5TB - Compressed log messages’ size: 23GB - Compression ratio: 47x - Memory usage: 150MB VictoriaLogs CLI integration demo - Which errors have occurred in all the apps during the last hour? - How many errors have occurred during the last hour? - Which apps generated the most of errors during the last hour? - The number of per-minute errors for the last 10 minutes - Status codes for the last hour - Non-200 status codes for the last week - Top client IPs for the last 4 weeks with 404 and 500 response status codes - Per-month stats for the given IP across all the logs Large-scale logging solution MUST provide excellent CLI integration VictoriaLogs: (temporary) drawbacks VictoriaLogs: Recap - Easy to setup and operate - The lowest RAM usage and disk space usage (up to 30x less than Elasticsearch and Grafana Loki) - Fast full-text search - Excellent integration with traditional command-line tools for log analysis - Accepts logs from popular log shippers (Filebeat, Fluentbit, Logstash, Vector, Promtail, Grafana Agent) - Open source and free to use!

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Unlock the full potential of your software development lifecycle with SpiraPlan's powerful REST APIs. Led by experts from Inflectra and our partner, MVerve, this webinar offers a practical guide to leveraging the API's power for automation, integration, and data-driven insights. Whether you're an API expert or beginner, our recap blog is packed with valuable information to enhance your SpiraPlan experience. The webinar emphasized how SpiraPlan's REST API allows you to: • Automate Workflows: Streamline your processes by automating repetitive tasks. • Integrate with Existing Tools: Seamlessly connect SpiraPlan with your existing software ecosystem. • Build Custom Solutions: Tailor SpiraPlan to your unique needs by developing custom applications and integrations. • Gain Deeper Insights: Extract valuable data from SpiraPlan for advanced reporting and analysis.

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Talk given at NewCrafts Paris Conference 2024 Abstract: Have you ever observed quality problems with what your team is delivering? Have you ever felt your team is learning about the actual status quo late, too late to include these insights in your next steps? Have you ever wondered how to influence change when you’re “just” a specialist on the team, maybe even felt powerless? I’ve mostly worked with people who never experienced effective collaboration across roles and specialties. How to get such a team to move toward testing throughout the delivery workflow from idea to production, on all kinds of levels, for all parts of the product, by the whole team? How to consider quality from the start and have it continuously inform our decision-making? Over the years, I’ve built a repertoire of tactics to help teams transform toward holistic testing and quality. They range from meeting people where they are to creating guidelines, pairing and many others. It’s a toolbox of approaches to try out and find the sweet spot where people start moving toward better directions together. These tactics are fallible, not all of them work in all contexts, and yet they have helped my teams get to a better place. Join this talk to get inspired to take things into your hands. Learn what you can try yourself in your context to help your team make the first steps on your journey towards holistic testing and quality. Key learnings: - Learn how you can influence team culture, no matter your role or experience level - Add team transformation tactics to your toolbox of approaches to try - Understand the many ways we can move towards holistic testing and quality

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Computation is increasingly constrained by power. With each advancement in the manufacturing process, a decreasing percentage of the CPU can operate at full capacity, leading to the emergence of the term 'dark silicon'. This trend necessitates techniques that utilize chip area to optimize power efficiency through specialized accelerators. The presentation will outline key concepts that led to the dark silicon such as Moore’s law and breakdown of Dennard scaling, followed by an overview of current and upcoming CPU accelerators. The focus will then shift to vector units and the specifics of vector programming. Attendees will be introduced to registers, a range of vector operations, and methods to develop branchless algorithms such as sorting networks. The session will conclude with an overview of the new Java Vector API and how it was already picked up by projects to do AI inference (Llama 2) and vector search (AstraDB and Cassandra).

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