Theoretical optimizations can backfire in practice. We learned this the hard way at DoorDash when a “smart” HashMap change made latency worse. After years optimizing 50M+ monthly requests, here’s what actually works: measure tail latencies not averages, layer your caching with jittered TTLs, profile real workloads instead of trusting Big O, and treat performance as a practice not a project. Your intuition about what’s slow might probably be wrong.

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Retries aren’t a safety net—they’re a load multiplier. In distributed systems, naive retries across layers can trigger retry storms, amplify latency, and cause cascading failures. The fix isn’t more retries but smarter ones: use exponential backoff with jitter, enforce retry budgets, implement circuit breakers, and ensure idempotency. Combine these with timeouts, bulkheads, and observability to build truly resilient systems.

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arXiv:2604.01441v1 Announce Type: cross Abstract: Modern real-time systems require accurate characterization of task timing behavior to ensure predictable performance, particularly on complex hardware architectures. Existing methods, such as worst-case execution time analysis, often fail to capture the fine-grained timing behaviors of a task under varying resource contexts (e.g., an allocation of cache, memory bandwidth, and CPU frequency), which is necessary to achieve efficient resource utilization. In this paper, we introduce a novel generative profiling approach that synthesizes context-dependent, […]

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Feedback-rich neural architectures can regenerate earlier representations and inject temporal context, making them a natural setting for strictly local synaptic plasticity. We ask whether a minimal, backpropagation-free feedback–Hebbian system can already express interpretable continual-learning–relevant behaviors under controlled training schedules. We introduce a compact prediction–reconstruction architecture with two feedforward layers for supervised association learning and two dedicated feedback layers trained to reconstruct earlier activity and re-inject it as additive temporal context. All synapses are updated by a unified local […]

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The app sec community was happy to see that OWASP is considering making a move in their Top 10 update: “Security Logging and Alerting Failures” from position #10 to position #9, and highlighted in the 2025 release with a new name emphasizing a critical component that was often overlooked—alerting. “Security Logging & Alerting Failures” represents more than a simple reordering of priorities. It signals a shift in how organizations will approach application security in an era of increasingly […]

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We’ve come across announcement of multiple robot vacuums from the CES 2026 event, but there was one that immediately caught the attention of many. Here, I’m talking about the Roborock’s Saros Rover. It is a robot vacuum designed for multi-storey homes. Unlike regular robot vacuums that crawl across floors to get it cleaned, the Saros Rover uses a wheel-leg mechanism that enables it to climb stairs. Interestingly, there’s even more; it can also maintain stability on uneven surfaces […]

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Introduction Today’s global digital platforms are powered by hundreds of microservices that run behind the frontend that users are exposed to. These services all have to operate at scale in conjunction with each other. Hence, the ultimate user experience is determined by the composite availability of these systems, engineered so that the final service continues to operate even if subsystems experience outages. Talking about availability standards of 5 9s, systems that are available 99.999% of the time are […]

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arXiv:2602.06085v1 Announce Type: new Abstract: FPGAs offer high performance, low latency, and energy efficiency for accelerated computing, yet adoption in scientific and edge settings is limited by the specialized hardware expertise required. High-level synthesis (HLS) boosts productivity over HDLs, but competitive designs still demand hardware-aware optimizations and careful dataflow design. We introduce LAAFD, an agentic workflow that uses large language models to translate general-purpose C++ into optimized Vitis HLS kernels. LAAFD automates key transfor mations: deep pipelining, vectorization, […]

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