Distributed Model Counting without Bottlenecks
Distributed model counting with work-stealing: how gDMC reduces overhead and solves the load balancing problem in #SAT systems
Highload
Highload on ThecoreGrid focuses on designing and operating systems that handle massive scale, traffic, and data under strict reliability requirements.
We explore architectures and patterns for horizontal scaling, load distribution, fault tolerance, and performance optimization in distributed environments. Topics include sharding, replication, caching strategies, queueing systems, backpressure handling, and latency reduction under peak load. We analyze real-world trade-offs between consistency, availability, and cost, along with failure scenarios and recovery strategies. Content is grounded in BigTech practices, including incident post-mortems and lessons from operating systems at global scale. You’ll find deep dives into infrastructure behavior, traffic management, autoscaling, and resilience engineering. Instead of simplified guides, the Highload tag delivers practical engineering insights for backend engineers, architects, platform teams, and SREs responsible for building and maintaining systems that must perform reliably under extreme demand.
MEV in DAG BFT Breaks Honest Ordering
MEV in DAG BFT: how Mysticeti creates transaction ordering bias and why DAG linearization becomes a critical architectural bottleneck
DNS routing for gRPC eliminates thundering herd
DNS routing for gRPC: how changing the Route 53 policy eliminated the thundering herd and distributed the load across 121 million connections without errors
Kubernetes sharded watch reduces API load
Server-side sharded list and watch in Kubernetes changes the behavior of controllers. This is an attempt to eliminate the system ceiling when working with high-cardinality resources. When Kubernetes clusters grow to tens of thousands of nodes, controllers hit scalability limits not where one would typically expect. The problem arises at the list/watch interaction level with … Read more
DocDB architecture for zero-downtime scaling
DocDB architecture: how Stripe scales databases to 5 million QPS through zero-downtime data movement and strict data control.
MRC Protocol for Resilient GPU Networks
The MRC protocol is explained in practice: how GPU networks avoid congestion, withstand failures, and scale to 100k+ GPUs without loss of efficiency.
Redis proxy for highload caching and failure control
Redis proxy becomes a key layer for cache management as load and complexity increase. Let’s explore how an architectural proxy eliminates degradation and stabilizes highload systems. The problem does not manifest immediately — until the moment Redis stops being a “transparent” component and starts dictating system behavior. In the described case, degradation began with an … Read more
WebRTC routing reduces latency in voice AI
WebRTC routing is becoming critical for voice AI, where audio stream continuity and minimal latency are essential. We analyze how the reworking of routing changes system behavior under load. The problem does not manifest immediately — until the moment the system scales to global real-time traffic. In the classic WebRTC model of “one port per … Read more
AI compute infrastructure Stargate how to scale 10GW
AI compute infrastructure as the foundation for scaling models. An analysis of Stargate, architecture, partnerships, and growth constraints.
CDN error handling under edge failure pressure
CDN error handling: why edge errors lose context and how to architecturally prepare for failures at the CDN level.