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5 Best Platforms for Managing Cloud Costs Through Architecture Design

Cloud cost control often starts too late. By the time a team reviews a monthly bill, the decisions shaping that bill are usually already locked in. Workloads have been placed. Redundancy has been designed in. Regions have been chosen. Services have been duplicated. Data transfer paths have been created. What looks like a finance problem later is often an architecture problem much earlier.
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From Loose Threads to Tightly Woven - The AI Shift in Software Design

AI is advancing at breakneck speed-from basic rule-based systems to autonomous agents. Over 240,000 AI papers are published annually, with 1.8M+ projects on GitHub and 80+ large language models released in 2024 alone. Forecast AI spend is expected to top $632B by 2028. Amid the hype, the focus must be on delivering real value and preparing for what's next.

The (not so) hidden cost of custom logging

Custom logging can technically capture everything, but in practice, it rarely does. Coverage degrades over time, external APIs get forgotten, and during incidents, you're left asking "did anyone log this?" instead of debugging. Automatic capture solves this. If you're a technical leader, there's a good chance your team is spending significant time on custom logging… and you might not even realize how much it's costing you in productivity and incomplete debugging data.

Why observability tools are missing critical debugging data (no matter how you sample)

There's a common belief in the observability space: if you just collect more data, you'll have what you need to debug any issue. The reality is more frustrating: even with 100% unsampled observability, you're still missing critical debugging data. There's a common belief in the observability space: if you just collect more data, you'll have what you need to debug any issue. The reality is more frustrating: even with 100% unsampled observability, you're still missing critical debugging data.

Architectural Visualization with Unreal Engine: Trends, Challenges, and Workflows

Architectural visualization, or archviz, has shifted rapidly from static 2D renders to immersive 3D experiences that have transformed how architects, designers, and developers communicate their vision. Using this technology, a development team can “walk” clients through hyper-realistic replicas of an office headquarters or residential complex well before ground is ever broken.

Multiplayer 2025: year in review

In 2025 we focused on a simple but ambitious goal: making debugging faster, less fragmented and less manual. Check out all our releases to make that possible. 2025 was a defining year for Multiplayer. We focused on a simple but ambitious goal: making debugging faster, less fragmented and less manual. That meant meeting developers where they were already working and capturing the right context at the right time.

Multiplayer sketches: annotating session recordings for better collaboration

Annotations are a way to draw, write, and comment directly on top of full-stack session recordings. Now, instead of sketching ideas in isolation, teams can mark up actual user sessions, highlighting specific UI elements, API calls, and backend traces that need attention. Whiteboarding tools are indispensable in system design for visually conveying concepts, ideas, and rough plans. They tap into our natural preference for visual learning.

Six best practices for backend design in distributed system

Most modern software systems are distributed systems, but designing a distributed system isn’t easy. Here are six best practices to get you started. Most modern software systems are distributed systems. Designing and maintaining a distributed system, however, isn't easy. There are so many areas to master: communication, security, reliability, concurrency, and, crucially, observability and debugging.

High user satisfaction scores aren't worth a burned-out team

Multiplayer transforms the chaos of support tickets, eliminating manual work, sloppy hand-offs, and grepping through log files. End-user support has always been messy. Manual steps, tool-switching, and scattered communication turn what should be a simple fix into a marathon of frustration. Tickets feel like scavenger hunts: everyone’s searching for details, logs, screenshots, or that missing repro step. Developers are left waiting on context that never arrives.