Paul-Adrien CORDONNIER

DevOps and Data Engineer

Published articles

GitOps in practice, deploy Kubernetes applications with ArgoCD

GitOps in practice, deploy Kubernetes applications with ArgoCD

Categories: Containers Orchestration, DevOps & SRE, Adaltas Summit 2021 | Tags: Argo CD, CI/CD, Git, GitOps, IaC, Kubernetes

GitOps is a set of practices to deploy applications using Git. Application definitions, configurations, and connectivity are to be stored in a version control software such as Git. Git then serves as…

Paul-Adrien CORDONNIER

By Paul-Adrien CORDONNIER

Dec 16, 2021

Logstash pipelines remote configuration and self-indexing

Logstash pipelines remote configuration and self-indexing

Categories: Data Engineering, Infrastructure | Tags: Docker, Elasticsearch, Kibana, Logstash, Log4j

Logstash is a powerful data collection engine that integrates in the Elastic Stack (Elasticsearch - Logstash - Kibana). The goal of this article is to show you how to deploy a fully managed Logstash…

Paul-Adrien CORDONNIER

By Paul-Adrien CORDONNIER

Dec 13, 2019

Hadoop Ozone part 2: tutorial and getting started of its features

Hadoop Ozone part 2: tutorial and getting started of its features

Categories: Infrastructure | Tags: CLI, Learning and tutorial, REST, HDFS, Ozone, Amazon S3, Cluster

The releases of Hadoop Ozone come with a handy docker-compose file to try out Ozone. The below instructions provide details on how to use it. You can also use the Katacoda training sandbox which…

Hadoop Ozone part 3: advanced replication strategy with Copyset

Hadoop Ozone part 3: advanced replication strategy with Copyset

Categories: Infrastructure | Tags: HDFS, Ozone, Cluster, Kubernetes, Node

Hadoop Ozone provide a way of setting a ReplicationType for every write you make on the cluster. Right now is supported HDFS and Ratis but more advanced replication strategies can be achieved. In this…

Hadoop Ozone part 1: an introduction of the new filesystem

Hadoop Ozone part 1: an introduction of the new filesystem

Categories: Infrastructure | Tags: HDFS, Ozone, Cluster, Kubernetes

Hadoop Ozone is an object store for Hadoop. It is designed to scale to billions of objects of varying sizes. It is currently in development. The roadmap is available on the project wiki. This article…

Monitoring a production Hadoop cluster with Kubernetes

Monitoring a production Hadoop cluster with Kubernetes

Categories: DevOps & SRE | Tags: Thrift, Grafana, Shinken, Hadoop, Knox, Cluster, Docker, Elasticsearch, Kubernetes, Node, Node.js, Prometheus, Python

Monitoring a production grade Hadoop cluster is a real challenge and needs to be constantly evolving. The software we use today is based on Nagios. Very efficient when it comes to the simplest…

Paul-Adrien CORDONNIER

By Paul-Adrien CORDONNIER

Dec 21, 2018

Accelerating query processing with materialized views in Apache Hive

Accelerating query processing with materialized views in Apache Hive

Categories: Business Intelligence, DataWorks Summit 2018 | Tags: Calcite, Druid, OLAP, Hive, Release and features, SQL

The new materialized view feature is coming in Apache Hive 3.0. Jesus Camacho Rodriguez from Hortonworks held a talk ”Accelerating query processing with materialized views in Apache Hive” about it…

Paul-Adrien CORDONNIER

By Paul-Adrien CORDONNIER

May 31, 2018

Nobody* puts Java in a Container

Nobody* puts Java in a Container

Categories: Containers Orchestration, Open Source Summit Europe 2017, Infrastructure | Tags: cgroups, Java, JRE, JVM, Namespaces, Docker

This talk was about the issues of putting Java in a container and how, in its latest version, the JDK is now more aware of the container it is running in. The presentation is led by Joerg Schad…

Paul-Adrien CORDONNIER

By Paul-Adrien CORDONNIER

Oct 28, 2017

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We are a team of Open Source enthusiasts doing consulting in Big Data, Cloud, DevOps, Data Engineering, Data Science…

We provide our customers with accurate insights on how to leverage technologies to convert their use cases to projects in production, how to reduce their costs and increase the time to market.

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