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Architecture and Infra

Architecture and Infra on ThecoreGrid covers the foundations of designing and operating scalable, reliable systems at BigTech level. This category brings together system design and infrastructure practices: distributed architectures, highload patterns, cloud-native platforms, and core layers such as compute, networking, and storage. We focus on real engineering decisions — how to balance reliability, performance, cost, and long-term system evolution. Topics include Infrastructure as Code, Kubernetes, multi-region deployments, traffic management, and platform design. Content is grounded in production experience: incident post-mortems, large-scale migrations, and lessons from operating infrastructure under heavy load. Instead of abstract theory, you get practical trade-offs, proven patterns, and insights drawn from real-world systems. Architecture & Infra is built for architects, backend and platform engineers, DevOps teams, and SREs responsible for complex distributed systems and mission-critical infrastructure.

Scaling Kubernetes Without Increasing Operational Overhead: Generali’s Transition to EKS Auto Mode

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When the number of containerized services grows faster than the platform team, the bottleneck is not Kubernetes itself, but its operation. Generali faced exactly this challenge—and shifted the focus from cluster management to application management. The main limitation was not performance, but operations. The microservices portfolio was expanding, multi-tenant scenarios emerged, and with them—manual scaling, … Read more

Kubernetes and Stateful Inference: How llm-d Solves the Routing and Caching Challenge for LLM Worklo…

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As LLM production workloads grow, it becomes clear: classic Kubernetes mechanisms do not understand the nature of inference. llm-d is an attempt to bridge this gap at the platform level. The main limitation becomes apparent when inference goes beyond a “stateless HTTP service.” Requests to LLMs have different costs: prompt length, generation phase, KV-cache hits. … Read more

LLM Load Without Blind Spots: How to Bring Observability to the Routing Layer with OpenRouter and Grafe…

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When LLM becomes part of production infrastructure, traditional monitoring is no longer sufficient. The bottleneck is no longer the application code, but the routing and model selection layer — and that’s exactly where observability is needed. In LLM systems, degradation doesn’t start with HTTP endpoint failures, but with the accumulation of subtle effects: increased latency … Read more

Spring Milestone Releases: Expanding Protocols and Configuration Control in Response to Integration Complexity

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The Spring milestone release cycle shows a shift in focus: from the framework as runtime to the framework as a layer for managing protocols, data, and behavior. This is crucial where integrations and configuration become the main sources of failures. The main point of tension is not in business logic, but at the interfaces: messaging, … Read more

A Unified Global Platform as a Way to Simplify SASE and Protect AI Workloads

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Disparate security and traffic delivery services begin to break down as AI workloads and distributed users grow. The unified platform approach attempts to eliminate this class of problems through consolidation. The problem becomes apparent as the architecture grows more complex. Separate solutions for WAF, DDoS, CDN, Zero Trust, and application access create fragmentation. Each adds … Read more

Code Generation Without Control: How Agentic Systems Hit Bottlenecks in Security and Context Management

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AI agents in development have become more autonomous, but this has been accompanied by increased costs of errors and control complexity. The primary tension has shifted from model quality to system behavior management. The problem does not manifest immediately, but rather the moment the agent steps outside a simple scenario. Early approaches like “vibe coding” … Read more

QA Bottleneck: How Offloading Testing to an AI-Native Model Changes Release Velocity

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Slowdowns in QA processes often become a hidden limit for the entire engineering team. In this case, optimizing the testing pipeline has a disproportionately strong effect on delivery speed. The problem does not manifest immediately—only when the release cycle begins to depend on verification rather than development. Manual E2E (end-to-end) tests and limited parallelism create … Read more

Stateless Kafka-compatible broker: shifting durability to the storage layer

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Tansu proposes rebuilding the Kafka model: removing state from the brokers and delegating reliability to external storage. This changes the system’s behavior under load and simplifies the operational model. The problem manifests at the operational level. A classic Kafka broker is a stateful component: replication, leader elections, persistent state, long uptime. Such nodes are hard … Read more

Datadog Terraform Provider v4: Predictable Access Rights and AWS Integration Unification

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The provider update shifts the focus from convenience to predictability of behavior. This is critical when Terraform becomes the source of truth for observability configuration. The problem manifests at the state management level. In large installations, Terraform must deterministically control access and integrations. In previous versions, the behavior of monitor permissions could be non-obvious, especially … Read more

⪜ Cloud Dependency as an Architectural Risk: Multi-Cloud, Local-First, and Protocols with a “Credible Exit”

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Modern systems are designed around clouds, but reliance on a single provider is beginning to manifest as a systemic risk. The issue is not the probability of failure, but its consequences and the system’s ability to survive a loss of control. The problem becomes apparent not at the latency or throughput level, but at the … Read more

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