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Updates and recent posts about BigQuery..

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@kala shared a link, 3 months, 2 weeks ago

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The 2026 Data Engineering Roadmap: Building Data Systems for the Agentic AI Era

Data engineering’s getting flipped.AI agentsandLLMsaren’t just tagging along anymore - they’re the main users now. That means engineers need to buildcontext-aware, machine-readable data systemsthat don’t just store info but actually make sense of it. Think:vector databases,knowledge graphs,semantic .. read more

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@kala shared a link, 3 months, 2 weeks ago

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Streamlining Security Investigations with Agents

Slack broke down how it's threading AI into its product without torching user trust.Slack AIleans hard ontenant-specific data isolationandzero data retention- no leftover crumbs from LLM interactions. Instead of piping user data through someone else’s APIs, Slack runs LLMs onits own infrawhere it ca.. read more

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@kala shared a link, 3 months, 2 weeks ago

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2025: The year in LLMs

2025 was the year LLMs stopped just answering questions and started building things.Reasoning modelslike OpenAI’s o-series and Claude Code took over tool-driven workflows. Asynchronous coding agentsbroke out. These models didn’t just write code - they ran it, debugged it, then did it again. That loo.. read more

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@kala shared a link, 3 months, 2 weeks ago

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The Architects of AI Are TIME's 2025 Person of the Year

The Architects of AI drove the economy, shaped geopolitics, and changed the way we interact with the world... read more

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@kala shared a link, 3 months, 2 weeks ago

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Meet the ‘Mad Max’-Loving CEO Challenging Nvidia With a Renegade Chip

June Paik spurned a takeover offer from Meta Platforms last year. Now his South Korean company, FuriosaAI, has an AI chip entering mass production... read more

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@kala shared a link, 3 months, 2 weeks ago

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My LLM coding workflow going into 2026

Anthropic saysClaude Code writes about 90% of its own code now. Why? Because devs are getting smart with AI. They're slicing problems into tight, testable chunks and running structured workflows that keep LLMs on a short leash. It's not just prompts anymore. Think context packaging, multi-agent setu.. read more

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@devopslinks shared a link, 3 months, 2 weeks ago

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Race Condition in DynamoDB DNS System: Analyzing the AWS US-EAST-1 Outage

A long AWS smackdown in US-EAST-1 traced back to a ticking time bomb inDynamoDB’s automated DNS system. The flaw torpedoed EC2 networking, hobbled Lambda and Fargate, and dragged down theNetwork Load Balancer. Endpoints ghosted. Configs stalled. Everything snowballed. AWS says they’ll upgrade EC2 th.. read more

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@devopslinks shared a link, 3 months, 2 weeks ago

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You don’t need NAT gateway to deploy Lambda into VPC

AWS just made a big dent in NAT gateway bills. You can now runLambda in VPCs with IPv6 and an egress-only Internet gateway- no more always-on NAT draining your wallet. Keep the private subnets locked down. Still get outbound Internet access. IPv6 handles the traffic, slicing out the NAT middleman... read more

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@devopslinks shared a link, 3 months, 2 weeks ago

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Datacenters in space are a terrible, horrible, no good idea.

A former NASA engineer - now a Google Cloud AI infra alum - rips apart the idea of building GPU datacenters in orbit. His verdict: space is a terrible server rack. Power delivery? A nightmare. Heat dissipation? Worse in a vacuum. Radiation? Frying time. Even a 200kW solar rig (think ISS-sized) could.. read more

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@devopslinks shared a link, 3 months, 2 weeks ago

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ArgoCD diffs at scale

Monday.com ditched ArgoCD's built-in manifest diffing. Instead, they wired up a custom CI renderer that pre-renders Helm charts using real cluster data. Then it compares the desired states across Git branches. The kicker: diffs go to a UI with custom grouping support. Reviews get easier. New devs ge.. read more

BigQuery is a cloud-native, serverless analytics platform designed to store, query, and analyze massive volumes of structured and semi-structured data using standard SQL. It separates storage from compute, automatically scales resources, and eliminates the need for infrastructure management, indexing, or capacity planning.

BigQuery is optimized for analytical workloads such as business intelligence, log analysis, data science, and machine learning. It supports real-time data ingestion via streaming, batch loading from cloud storage, and federated queries across external data sources like Cloud Storage, Bigtable, and Google Drive.

Query execution is distributed and highly parallel, enabling interactive performance even on petabyte-scale datasets. The platform integrates deeply with the Google Cloud ecosystem, including Looker for BI, Vertex AI for ML workflows, Dataflow for streaming pipelines, and BigQuery ML, which allows users to train and run machine learning models directly using SQL.

Built-in security features include fine-grained IAM controls, column- and row-level security, encryption by default, and audit logging. BigQuery follows a consumption-based pricing model, charging for storage and queries (on-demand or reserved capacity).