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Jupyter Agents: training LLMs to reason with notebooks

Hugging Face dropped an open pipeline and dataset for training small models—think **Qwen3-4B**—into sharp **Jupyter-native data science agents**. They pulled curated Kaggle notebooks, whipped up synthetic QA pairs, added lightweight **scaffolding**, and went full fine-tune. Net result? A **36% jump .. read more  

Jupyter Agents: training LLMs to reason with notebooks
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Becoming a Research Engineer at a Big LLM Lab - 18 Months of Strategic Career Development

To land a big career role like Mistral, mix efficient **tactical** moves (like LeetCode practice) with **strategic** ups, like building a powerful portfolio and a solid network. Balance is key; aim to impress and prepare well without overlooking the power of strategy in shaping a successful career... read more  

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Shai-Hulud npm Supply Chain Attack

Malicious npm packages just leveled up: this one dropped a self-spreading worm that hijacks repos and leaks secrets the moment it lands. It abuses `postinstall` scripts to run TruffleHog and swipe tokens straight from your codebase. Then it uses GitHub Actions to exfiltrate the loot and auto-publis.. read more  

Shai-Hulud npm Supply Chain Attack
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Top 30 Argo CD Anti-Patterns to Avoid When Adopting Gitops

A teardown of Argo CD anti-patterns calls out 28 common misfires—stuff like skipping Git for Application CRDs or stuffing Helm/Kustomize config right into Argo CD manifests. Yikes. It pushes for a cleaner setup: use **ApplicationSets** instead of rolling your own YAML, turn on **auto-sync/self-heal.. read more  

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How FinOps Drives Value for Every Engineering Dollar

Duolingo’s FinOps crew didn’t just track cloud costs—they wired up sharp, automated observability across 100+ microservices. Real-time alerts now catch AI and infra spend spikes before they torch the budget. They sliced TTS costs by 40% with in-memory caching. Dumped pricey CloudWatch metrics for P.. read more  

How FinOps Drives Value for Every Engineering Dollar
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Introducing DigitalOcean Organizations, a new and comprehensive account layer

DigitalOcean just dropped **Organizations**—a real upgrade for anyone juggling multiple Teams. Think one top-level account to rule them all: centralized user control, one invoice to track, and org-wide settings for taxes, credits, and permissions... read more  

Introducing DigitalOcean Organizations, a new and comprehensive account layer
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Observability for the Invisible: Tracing Message Drops in Kafka Pipelines

When an event drops silently in a distributed system, it is not a bug, it is an architectural blind spot. Detect, debug, and prevent message loss in Kafka-based streaming pipelines using tools like OpenTelemetry, Fluent Bit, Jaeger, and dead-letter queues. Make sure observability gaps in event strea.. read more  

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Demystifying Log Retention in Azure

Azure logs come in three flavors: **Activity Logs**, **Diagnostic Logs**, and **Log Analytics**. Each with its own rules for retention and billing. The catch? Those differences aren’t quirks—they’re baked in... read more  

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What are Error Budgets? A Guide to Managing Reliability

OneUptime shows how to put **error budgets** to work—keeping feature velocity in check without tanking reliability. The goal: ship fast, stay within SLOs. They do it by tracking **burn rates**, syncing across teams, and tuning SLOs to match how users actually use the product. Less guesswork, more s.. read more  

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Intelligent Kubernetes Load Balancing at Databricks

Databricks replaced default Kubernetes load balancing for a **proxyless, client-side gRPC setup**, wired up through a custom control plane. No more **CoreDNS**. No more **kube-proxy**. Clients now get live endpoint discovery through **xDS**, plus smarter routing tricks like **Power of Two Choices** .. read more  

Intelligent Kubernetes Load Balancing at Databricks
Kata Containers is a Cloud Native Computing Foundation (CNCF) project designed to close the security gap between traditional Linux containers and virtual machines. Instead of sharing a single host kernel like standard containers, Kata Containers launches each pod or container inside its own lightweight virtual machine using hardware virtualization.

This approach dramatically reduces the attack surface and prevents container escape vulnerabilities, making Kata ideal for multi-tenant, untrusted, or sensitive workloads. Despite using VMs under the hood, Kata is optimized for fast startup times and integrates seamlessly with Kubernetes through the Container Runtime Interface (CRI), allowing it to be used alongside runtimes like containerd and CRI-O.

Kata Containers is commonly used in scenarios such as multi-tenant Kubernetes clusters, confidential computing, sandboxed AI workloads, serverless platforms, and agent execution environments where strong isolation is mandatory. It supports multiple hypervisors, including QEMU, Firecracker, and Cloud Hypervisor, and continues to evolve toward faster boot times, lower memory overhead, and better hardware acceleration support.