Category: Blog Post

  • Exploratory Notebooks for Deep Learning, AI, and Data Tools: A Beginner’s Guide

    Exploratory Notebooks for Deep Learning, AI, and Data Tools: A Beginner’s Guide

    Exploratory Notebooks for Deep Learning, AI, and Data Tools: A Beginner’s Guide Are you looking at some resources to get you up to speed with popular Deep Learning and Data processing frameworks? This blog entry provides a curated collection of notebooks that will help you kickstart your journey. You can find the notebooks at this

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  • CPU Load Testing Exercises: Tools and Analysis for Oracle Database Servers

    CPU Load Testing Exercises: Tools and Analysis for Oracle Database Servers

    CPU Load Testing Exercises: Tools and Analysis for Oracle Database Servers This document describes some basic CPU load testing exercises on three different types of database servers used by the Oracle Service at CERN. It reports on the tests performed, tools used for data gathering, data analysis, findings, and lessons learned. Motivations CPU usage is

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  • Introduction to Apache Spark APIs for Data Processing

    Introduction to Apache Spark APIs for Data Processing

    Introduction to Apache Spark APIs for Data Processing Welcome to the website of the course on Apache Spark by CERN IT. The course is self-paced and open, it is a short introduction to the architecture and key abstractions used by Spark. Theory and demos cover the main Spark APIs: DataFrame API, Spark SQL, Streaming, Machine

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  • Can High Energy Physics Analysis Profit from Apache Spark APIs?

    Can High Energy Physics Analysis Profit from Apache Spark APIs?

    Can High Energy Physics Analysis Profit from Apache Spark APIs? We are in a golden age for distributed data processing, with an abundance of tools and solutions emerging from industry and open source. High Energy Physics (HEP) experiments at the LHC stand to profit from all this progress, as they are data-intensive operations with several

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  • Integrating ORDS with 3rd-party SSO

    Integrating ORDS with 3rd-party SSO

    Integrating ORDS with 3rd-party SSO In today’s post I will describe the process of integrating OIDC implicit flow with ORDS running on Tomcat against Keycloak service. May sound complicated, but we’ll break it down into individual components so we know what we’re talking about. OIDC implicit flow OIDC or OpenID Connect is an extension of

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  • Hardening Apache ZooKeeper security using zkpolicy

    Hardening Apache ZooKeeper security using zkpolicy

    Hardening Apache ZooKeeper security using zkpolicy Apache ZooKeeper is an open-source server which enables highly reliable distributed coordination. Distributed applications can use it to maintain configuration information, implement naming, provide synchronization and group services. There are numerous applications using ZooKeeper such as Hbase, Kafka, YARN, HDFS and Spark. Metadata is stored in data objects named

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  • ORDS – Managing APEX static images

    ORDS – Managing APEX static images

    ORDS – Managing APEX static images In today’s post, we’ll be talking about the possible ways to manage the static images/CSS/JS that come shipped with APEX, when running on ORDS. They are separate resources (not contained in the DB like some other APEX images) necessary for your APEX applications look and behave the way they’re

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  • Creating PDFs in APEX after ORDS 19.1

    Creating PDFs in APEX after ORDS 19.1

    Creating PDFs in APEX after ORDS 19.1 Creating PDFs in APEX after ORDS 19.1 Until 19.1 ORDS provided a built-in printing engine based on Apache FOP which allowed you to download a PDF version of your reports and XLS-FO templates in a very easy manner. However in ORDS 18.4.0 release notes we could find information

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  • Distributed Deep Learning for Physics with TensorFlow and Kubernetes

    Distributed Deep Learning for Physics with TensorFlow and Kubernetes

    Distributed Deep Learning for Physics with TensorFlow and Kubernetes Summary: This post details a solution for distributed deep learning training for a High Energy Physics use case, deployed using cloud resources and Kubernetes. You will find the results for training using CPU and GPU nodes. This post also describes an experimental tool that we developed,

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