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Migrating Airbnb’s JVM Monorepo to Bazel

Airbnb yanked tens of millions of lines of Java, Kotlin, and Scala out of Gradle and dropped them intoBazel. Why? Faster builds, reproducible results, and smoother dev workflows. They didn’t just swap tools—they rewired the whole thing. A customautomated build file generatornow slices up targets fi.. read more  

Migrating Airbnb’s JVM Monorepo to Bazel
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Using DuckDB in AWS Lambda

DuckDB is an open-source in-process SQL OLAP database management system optimized for analytical queries. It can efficiently handle large datasets in a memory-efficient manner, making it suitable for serverless architectures. A DuckDB Lambda layer can be used to run performant queries on remote data.. read more  

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Best Linux distro for developers of 2025

TechRadar rounds up the best Linux distros for devs.Manjarodelivers Arch power without the pain.DebianandUbuntu LTShold steady for those who put uptime over edge.Fedorakeeps the new stuff flowing. Solusrolls with a tight curation hand—smooth updates, no chaos.Mocaccinoaims at Gentoo lovers who want.. read more  

Best Linux distro for developers of 2025
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Can LLMs replace on call SREs today?

ClickHouse ran five LLMs through an autonomous root cause gauntlet using OpenTelemetry data. None nailed it solo. OpenAI’s o3 and Claude Sonnet 4 came closest. GPT-4.1 was the cheapest brain on the block. Things got weird under the hood. Token usage spiked unpredictably. Queries slammed observabili.. read more  

Can LLMs replace on call SREs today?
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Hunting Living Secrets: Secret Validity Checks Arrive in GitHub Advanced Security for Azure DevOps

GitHub Advanced Security for Azure DevOps just got sharper: it now checks if leaked secrets are actuallyvalid. Secrets are flagged asActiveorUnknownby pinging providers in real time. No setup needed. It auto-kicks in for supported secret types. Why care?Because not every secret leak is an emergenc.. read more  

Hunting Living Secrets: Secret Validity Checks Arrive in GitHub Advanced Security for Azure DevOps
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Dynamo, DynamoDB, and Aurora DSQL

Marc Brooker breaks down the jump fromAmazon DynamotoDynamoDBandAurora DSQL, tracing how the guts of cloud databases have changed. It’s a story about dropping old trade-offs and picking up stronger guarantees. DynamoDB ditches the old hash-ring replication for multi-AZ replica sets backed by Paxos... read more  

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Kubernetes costs keep rising. Can AI bring relief?

88% of Kubernetes users say their total costs keep climbing—thanks to overprovisioned clusters, messy architectures, and hands-on ops. So now, 92% are bringing inAI-driven cost toolsto automate rightsizing and squeeze waste from sprawling workloads. System shift:AI isn't just sneaking into cluster .. read more  

Kubernetes costs keep rising. Can AI bring relief?
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Kubernetes v1.34 Sneak Peek: A Game-Changer for the Kubernetes Expert’s Lifecycle

Kubernetes v1.34 lands August 2025 with a clear agenda: smarter scheduling, tighter control, fewer surprises. Dynamic Resource Allocationgoes stable, letting clusters actually reason about GPUs, FPGAs, and NICs. AI/ML and HPC jobs stop guessing and start requesting what they need. ServiceAccount t.. read more  

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Kubernetes Learning Roadmap

The Kubernetes Learning Roadmap covers key concepts such as understanding Kubernetes use cases, installing Kubernetes locally, interacting with Kubernetes using YAML and kubectl, managing deployments and replica sets, and networking in Kubernetes. Additionally, it includes topics like managing envir.. read more  

Kubernetes Learning Roadmap
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Elon Musk's xAI Offers Up To $440K For Infrastructure Engineers, Calls It 'Adventure Of A Lifetime'

xAI wants infrastructure engineers to help scale itssupercomputing stack—and they're not playing small. They're after folks who knowKubernetes, can wrangleL4/L7 proxies, and speak fluentcloud networking. The goal: pushmulti-cluster production inferenceacross the Memphis supercluster (yeah, the one .. read more  

Elon Musk's xAI Offers Up To $440K For Infrastructure Engineers, Calls It 'Adventure Of A Lifetime'
Vertex AI is Google Cloud’s end-to-end machine learning and generative AI platform, designed to help teams build, deploy, and operate AI systems reliably at scale. It unifies data preparation, model training, evaluation, deployment, and monitoring into a single managed environment, reducing operational complexity while supporting advanced AI workloads.

Vertex AI supports both custom models and foundation models, including Google’s Gemini model family. It enables organizations to fine-tune models, run large-scale inference, orchestrate agentic workflows, and integrate AI into production systems with strong security, governance, and observability controls.

The platform includes tools for AutoML, custom training with TensorFlow and PyTorch, managed pipelines, feature stores, vector search, and online and batch prediction. For generative AI use cases, Vertex AI provides APIs for text, image, code, multimodal generation, embeddings, and agent-based systems, including support for Model Context Protocol (MCP) integrations.

Built for enterprise environments, Vertex AI integrates deeply with Google Cloud services such as BigQuery, Cloud Storage, IAM, and VPC, enabling secure data access and compliance. It is widely used across industries like finance, healthcare, retail, and science for applications ranging from recommendation systems and forecasting to autonomous research agents and AI-powered products.