Systems | Development | Analytics | API | Testing

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Using shift-left and shift-right in video games

There’s a new way to approach quality. In game testing, "shift-left" is all about catching issues earlier in the development process rather than waiting until production. @Mac Clark from Sauce Labs explains how game engines like Unity and Unreal allow for a shift-left approach using AI agents to automate testing before a game reaches players. This proactive method can help identify potential crashes and errors at the engine level, ensuring a more stable product launch.

How to Fix Android's Resources. NotFoundException

The Resources.NotFoundException is Android's way of saying "Hey, you told me to grab something, but it's not where you said it would be!" This error typically shows up when you're trying to access strings, layouts, drawables, or other resources that Android can't locate in your app's resource files. Maybe they were renamed, deleted, or never existed in the first place. Or perhaps they're hiding in the wrong folder.

The Perks of Using Astera at Your Logistics Company

Logistics industry has to deal with data from multiple sources including bills of lading, customs declaration forms, proofs of delivery, and others. Then they have to ensure the data is prepped, extracted, parsed, converted to the right format and then analyzed. Given how important logistics is in today’s market, it is no wonder that McKinsey Global Supply Chain Leader Survey 2024 reported 74% of respondents were interested in advanced digital and AI-based tools for planning and scheduling.

Distributed Phoenix: Deployment and Scaling

In part one of this series, we managed distributed state using GenServers. This provided a foundation for understanding some core concepts in distributed Phoenix applications. Now, we turn our focus to deployment and scaling strategies. As your application evolves to meet growing demands, knowing how to scale horizontally, maintain high availability, and monitor distributed components becomes crucial.

New with Confluent Platform 7.8: Confluent Platform for Apache Flink (GA), mTLS Identity for RBAC Authorization, and More

At Confluent, we’re committed to building the world's leading data streaming platform that gives you the ability to stream, connect, process, and govern all your data, and makes it available wherever it’s needed, however it’s needed, in real time. Today, we're excited to announce the release of Confluent Platform 7.8. This release builds upon Apache Kafka 3.8, reinforcing our core capabilities as a data streaming platform.

What is Staff Augmentation, and How Does It Benefit Your Business?

We are seeing businesses across industries engage with large-scale projects needing a talent pool experienced in AI, cloud, IoT, or other emerging technologies. However, the fluctuating nature of these projects requires a flexible workforce, which can only naturally comprise part-time hires. This is why we see a steady investment in the staff augmentation market. The 2023 evaluation for the IT staff augmentation market was approximately USD 300 billion in the recent market reports.

Kubernetes vs Docker: 7 Key Differences

It’s impossible to learn about containerization without hearing about Docker and Kubernetes. These two tools together dominate the world of containers, both being the de facto standard in what they each do. When you’re first getting started learning about containers, it can be quite a challenge to figure out the differences between these two tools.

Building a FinOps Ethos

In today’s data-driven enterprises, the intersection of fiscal responsibility and technical innovation has never been more critical. As data processing costs continue to scale with business growth, building a FinOps culture within your Data Engineering team isn’t just about cost control, it’s about creating a mindset that views cost optimization as an integral part of technical excellence.

Gen AI in Action: Customers Use Cortex AI to Garner New Insights and Accelerate Innovation

For years, companies have operated under the prevailing notion that AI is reserved only for the corporate giants — the ones with the resources to make it work for them. But as technology speeds forward, organizations of all sizes are realizing that generative AI isn’t just aspirational; it’s accessible and applicable now.