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Ultimate Guide to Citus Con: An Event for Postgres, 2023 edition

The Citus Data

Americas livestream, Citus open source user, real-time analytics, JSONB) Lessons learned: Migrating from AWS-Hosted PostgreSQL RDS to Self-Hosted Citus , by Matt Klein & Delaney Mackenzie of Jellyfish.co. (on-demand Checkpoint and WAL configs , by Samay Sharma on the Postgres open source team at Microsoft.

Azure 84
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AI Chihuahua! Part I: Why Machine Learning is Dogged by Failure and Delays

d2iq

Components that are unique to data engineering and machine learning (red) surround the model, with more common elements (gray) in support of the entire infrastructure on the periphery. Before you can build a model, you need to ingest and verify data, after which you can extract features that power the model.

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Kubernetes for Big Data Workloads

Abhishek Tiwari

Kubernetes has emerged as go to container orchestration platform for data engineering teams. In 2018, a widespread adaptation of Kubernetes for big data processing is anitcipated. Organisations are already using Kubernetes for a variety of workloads [1] [2] and data workloads are up next. Native frameworks.

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Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

AWS Machine Learning - AI

Organizational resiliency draws on and extends the definition of resiliency in the AWS Well-Architected Framework to include and prepare for the ability of an organization to recover from disruptions. Ram Vittal is a Principal ML Solutions Architect at AWS.

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Orchestrating Data/ML Workflows at Scale With Netflix Maestro

Netflix Tech

As Big data and ML became more prevalent and impactful, the scalability, reliability, and usability of the orchestrating ecosystem have increasingly become more important for our data scientists and the company. Another dimension of scalability to consider is the size of the workflow.

Data 84
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The Good and the Bad of Docker Containers

Altexsoft

Docker is an open-source containerization software platform: It is used to create, deploy and manage applications in virtualized containers. Launched in 2013 as an open-source project, the Docker technology made use of existing computing concepts around containers, specifically the Linux kernel with its features.

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The Good and the Bad of Hadoop Big Data Framework

Altexsoft

Apache Hadoop is an open-source Java-based framework that relies on parallel processing and distributed storage for analyzing massive datasets. Developed in 2006 by Doug Cutting and Mike Cafarella to run the web crawler Apache Nutch, it has become a standard for Big Data analytics. Scalability. What is Hadoop?