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Databricks scales monitoring with Hydra; nOps rebuilds on Lakebase

作者 PulseAugur 编辑部 · [16 个来源] ·

Databricks has developed a new monitoring platform called Hydra, built on its Lakehouse architecture, to handle the massive scale of its operations, ingesting over 10 trillion samples daily and managing 5 billion active timeseries. This platform addresses challenges with high-cardinality metrics and aims for a more hands-off, self-healing infrastructure. Meanwhile, nOps has rebuilt its cloud optimization platform using Databricks Lakebase, integrating its application and analytics for a simpler, faster architecture. Additionally, several companies are launching tools and platforms aimed at simplifying cloud infrastructure management and AI application deployment across AWS, GCP, and Azure, with a focus on security and developer experience. AI

影响 New infrastructure and tools are emerging to support large-scale AI deployments and multi-cloud management, indicating a maturing ecosystem for AI operations.

排序理由 Multiple companies announce significant advancements in cloud infrastructure, monitoring, and AI deployment tools, including major platform updates from Databricks and nOps.

在 dev.to — LLM tag 阅读 →

AI 生成摘要 · Google Gemini · 来自 16 个来源。 我们如何撰写摘要 →

Databricks scales monitoring with Hydra; nOps rebuilds on Lakebase

报道来源 [16]

  1. Databricks Blog TIER_1 English(EN) ·

    10 trillion samples a day: Scaling beyond traditional monitoring infra at Databricks

    Databricks’ monitoring infrastructure has more than tripled in size over the last year, ...

  2. Databricks Blog TIER_1 English(EN) ·

    How nOps Rebuilt Their Cloud Optimization Platform on Databricks Lakebase, and Why Other ISVs Should Too

    nOps, a Databricks Built On partner managing over $4 billion in annual cloud spend,...

  3. HN — AI infrastructure stories TIER_1 English(EN) · TankeJosh ·

    Launch HN: Infra.new (YC W23) – DevOps copilot with guardrails built in

  4. HN — AI infrastructure stories TIER_1 English(EN) · suryao ·

    Launch HN: Argonaut (YC S21) – Easily Deploy Apps and Infra to AWS and GCP

  5. MarkTechPost TIER_1 English(EN) · Michal Sutter ·

    Best Vector Databases in 2026: Pricing, Scale Limits, and Architecture Tradeoffs Across Nine Leading Systems

    <p>Vector databases are now core retrieval infrastructure for RAG and agentic AI. This guide compares nine production options on architecture, pricing, and scale.</p> <p>The post <a href="https://www.marktechpost.com/2026/05/10/best-vector-databases-in-2026-pricing-scale-limits-a…

  6. Mastodon — sigmoid.social TIER_1 日本語(JA) · [email protected] ·

    AI and Cloud Infrastructure (AWS, GCP, Azure) Comparison: Reasons Companies Choose Them Explaining the differences between AWS, GCP, and Azure for AI and cloud infrastructure. Introducing reasons why companies choose cloud infrastructure and AI use cases. https:// ai-blog-seven-wine.vercel.app/ ja/posts/2026-05

    AIとクラウドインフラ（AWS・GCP・Azure）比較：企業が選ぶ理由 AIとクラウドインフラの比較。AWS・GCP・Azureの違いを解説。企業がクラウドインフラを選ぶ理由と、AIの活用事例を紹介する。 https:// ai-blog-seven-wine.vercel.app/ ja/posts/2026-05-21-am-8vpqs # AI # クラウドインフラ # AWS

  7. Towards AI TIER_1 English(EN) · Sunilkumar Reddy Eraganeni ·

    Building Multi-Cloud Architectures

    <figure><img alt="" src="https://cdn-images-1.medium.com/max/870/1*wbu6jmZmIu3BiUZat3x8KA.png" /></figure><p><strong>1. Introduction: Why Multi-Cloud Became Inevitable</strong></p><p>The enterprise data platform supported multiple regions and distinct business units. Data workloa…

  8. dev.to — MCP tag TIER_1 English(EN) · Michael "Mike" K. Saleme ·

    May 2026: The MCP Attack Surface Tripled — Three Disclosures and a Bank's SEC Filing Tell You What to Test

    <p>In the past two weeks, four publicly-documented events made the AI agent attack surface concrete in a way vendor marketing usually obscures. They share a single structural property: the agent's trust model is wrong, and the consequences are now measurable.</p> <h2> The exposur…

  9. Mastodon — sigmoid.social TIER_1 English(EN) · [email protected] ·

    I wrote new posts on the Pluralsight blog covering: • AI Agents for Kubernetes • Agentic CLI for AKS • Multicloud cost management A look at where AI, Kubernetes

    I wrote new posts on the Pluralsight blog covering: • AI Agents for Kubernetes • Agentic CLI for AKS • Multicloud cost management A look at where AI, Kubernetes, and cloud operations are heading. Read more: https://www. buchatech.com/2026/05/explorin g-ai-kubernetes-and-multiclou…

    链接 buchatech.com/…/exploring-ai-kubernetes-a…
  10. Mastodon — sigmoid.social TIER_1 English(EN) · [email protected] ·

    Running AI applications shouldn't mean building and securing infrastructure from scratch. Our AI Hosting: managed Kubernetes, data sovereignty, flexible deploym

    Running AI applications shouldn't mean building and securing infrastructure from scratch. Our AI Hosting: managed Kubernetes, data sovereignty, flexible deployment (AWS / Azure / GCP / on-premise), and a team with deep application hosting expertise. Focus on your # AI models. We'…

    链接 amazee.io/ai-hosting
  11. The Register — AI TIER_1 English(EN) · Jessica Lyons ·

    The never-ending supply chain attacks worm into SAP npm packages, other dev tools

    <h4>Mini Shai-Hulud caught spreading credential-stealing malware</h4> <p>The wave of supply chain attacks aimed at security and developer tools has washed up more victims, namely SAP and Intercom npm packages, plus the lightning PyPI package.…</p>

  12. The Register — AI TIER_1 English(EN) · Jessica Lyons ·

    Ongoing supply-chain attack 'explicitly targeting' security, dev tools

    <h4>Vendor confirms repo data exposure after Lapsus$ claims source code, secrets dump</h4> <p>Software security testing outfit Checkmarx has become the latest organization caught up in an ongoing attack on security-tool providers. The biz said data posted online appears to have c…

  13. dev.to — LLM tag TIER_1 English(EN) · keeper ·

    When Models Eat the World: Supply Chain Quality for AI-Dependent Systems

    <blockquote> <p>When your code quality is decided by a third party's model whose behavior can change without notice, where does your quality system stand?</p> </blockquote> <h2> A Quality Risk You're Probably Ignoring </h2> <p>In February 2026, a SaaS company's customer satisfact…

  14. dev.to — LLM tag TIER_1 English(EN) · Guy Kobrinsky ·

    You WON'T Get Realtime LLM Cost From Your Public Cloud

    <p>As an engineering manager who has spent years grappling with infrastructure costs across all public cloud environments, I've seen firsthand how quickly expenses can spiral without proper visibility. When it comes to Generative AI, specifically LLMs, there's a common misconcept…

  15. Mastodon — fosstodon.org TIER_1 English(EN) · [email protected] ·

    🚨 Hiring Alert | Senior Technical Architect – AI & Digital Engineering 🚨 📍 Location: Hyderabad 👨‍💻 Experience: 12–14 Years 💼 Employment Type: Permanent 💰 CTC: U

    🚨 Hiring Alert | Senior Technical Architect – AI & Digital Engineering 🚨 📍 Location: Hyderabad 👨‍💻 Experience: 12–14 Years 💼 Employment Type: Permanent 💰 CTC: Up to 40 LPA 📩 Apply here: - https:// zurl.co/8FVNz # Hiring # TechnicalArchitect # AI # GenAI # CloudArchitecture # Java…

  16. Mastodon — fosstodon.org TIER_1 한국어(KO) · [email protected] ·

    Burn – Analyze K8s cost waste by namespace and pod. Just kubectl, no deploy

    Burn – K8s cost waste by namespace and pod. Just kubectl, no deploy Burn은 Kubernetes 클러스터의 네임스페이스와 파드 단위 비용 낭비를 분석하는 CLI 도구로, 별도의 에이전트 배포 없이 kubectl 명령어만으로 실행할 수 있습니다. AWS, Azure, GCP 클라우드 및 온프레미스 환경을 지원하며, 실제 사용량 기반 비용 분석과 AI 추천 기능을 통해 비용 절감 방안을 제시합니다. Slack 통합도 제공하여 실시간 비용 보고서와…

    链接 github.com/…/burn

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