Adaltas is a team of consultants with a focus on Open Source, Big Data and distributed systems based in France, Canada and Morocco.
- Architecture, audit and digital transformation
- Cloud and on-premise operation
- Complex application and ingestion pipelines
- Efficient and reliable solutions delivery
Latest articles
Find your way into data related Microsoft Azure certifications
Categories: Cloud Computing, Data Engineering | Tags: Data Governance, Data Science, Azure
Microsoft Azure has certification paths for many technical job roles such as developer, Data Engineer, Data Scientist and solution architect among others. Each of these certifications consists of…
Apr 14, 2021
Bridging the DBnomics Swagger/OpenAPI schema with GraphQL
Categories: DevOps & SRE, Front End | Tags: Data Engineering, GraphQL, JAMstack, JavaScript, REST, Node.js, Schema
While redacting a long and fastidious document today, I came across DBnomics, an open platform federating economic datasets. Browsing its website and APIs, I found their OpenAPI schema (aka Swagger…
By David WORMS
Apr 8, 2021
Apache Liminal: when MLOps meets GitOps
Categories: Big Data, Containers Orchestration, Data Engineering, Data Science, Tech Radar | Tags: Data Engineering, Deep Learning, CI/CD, Data Science, Deployment, Docker, GitOps, Kubernetes, Machine Learning, MLOps, Open source, Python, TensorFlow
Apache Liminal is an open-source software which proposes a solution to deploy end-to-end Machine Learning pipelines. Indeed it permits to centralize all the steps needed to construct Machine Learning…
Mar 31, 2021
Storage size and generation time in popular file formats
Categories: Data Engineering, Data Science | Tags: Avro, HDFS, Hive, ORC, Big Data, JSON, Parquet, Data Lake, File Format
Choosing an appropriate file format is essential, whether your data transits on the wire or is stored at rest. Each file format comes with its own advantages and disadvantages. We covered them in a…
Mar 22, 2021
TensorFlow Extended (TFX): the components and their functionalities
Categories: Big Data, Data Engineering, Data Science, Learning | Tags: Beam, Data Engineering, Deep Learning, Pipeline, CI/CD, Data Science, Deployment, Machine Learning, MLOps, Open source, Python, TensorFlow
Putting Machine Learning (ML) and Deep Learning (DL) models in production certainly is a difficult task. It has been recognized as more failure-prone and time consuming than the modeling itself, yet…
Mar 5, 2021
JS monorepos in prod 4: unit testing with Mocha and Should.js
Categories: DevOps & SRE, Front End | Tags: Monorepo, Node.js
Unit testing is essential for every long-term project and allows you to pull down functionalities of your code into isolated testable units. Indeed the main goal of a unit test is to verify if an…
By David WORMS
Feb 25, 2021
JS monorepos in prod 3: commit enforcement and changelog generation
Categories: DevOps & SRE, Front End | Tags: Git, JavaScript, Unit tests, CI/CD, Monorepo, Node.js, Release and features
Conventional Commits introduces a structured format for commit messages. It standardizes the messages among all the contributors. This makes them more readable and easy to automate. It simplifies the…
By David WORMS
Feb 2, 2021
JS monorepos in prod 2: project versioning and publishing
Categories: DevOps & SRE, Front End | Tags: Git, JavaScript, Unit tests, CI/CD, GitOps, Monorepo, Node.js, Release and features
One great advantage of a monorepo is to maintain coherent versions between packages and to automatize the version creation and the publication of packages. This article covers the versioning and…
By David WORMS
Jan 11, 2021
JS monorepos in prod 1: project initialization
Categories: DevOps & SRE, Front End | Tags: Git, JavaScript, GitOps, Monorepo, Node.js, Release and features
Every project journey begins with the step of initialization. When your overall project is composed of multiple projects, it is tempting to create one Git repository per project. In Node.js, a project…
By David WORMS
Jan 5, 2021
Build your open source Big Data distribution with Hadoop, HBase, Spark, Hive & Zeppelin
Categories: Big Data, Infrastructure | Tags: Hive, Maven, Git, Unit tests, Hadoop, HBase, Spark, Release and features
The Hadoop ecosystem gave birth to many popular projects including HBase, Spark and Hive. While technologies like Kubernetes and S3 compatible object storages are growing in popularity, HDFS and YARN…
Dec 18, 2020
Faster model development with H2O AutoML and Flow
Categories: Data Science, Learning | Tags: Automation, Cloud, H2O, Machine Learning, MLOps, On-premises, Open source, Python
Building Machine Learning (ML) models is a time-consuming process. It requires expertise in statistics, ML algorithms, and programming. On top of that, it also requires the ability to translate a…
Dec 10, 2020
OAuth2 and OpenID Connect for microservices and public applications (Part 2)
Categories: Containers Orchestration, Cyber Security | Tags: CNCF, JSON, LDAP, Micro Services, OAuth2, OpenID Connect
Using OAuth2 and OpenID Connect, it is important to understand how the authorization flow is taking place, who shall call the Authorization Server, how to store the tokens. Moreover, microservices and…
By David WORMS
Nov 20, 2020
OAuth2 and OpenID Connect, a gentle and working introduction (Part 1)
Categories: Containers Orchestration, Cyber Security | Tags: CNCF, Go Lang, JAMstack, LDAP, Kubernetes, OpenID Connect
Understanding OAuth2, OpenID and OpenID Connect (OIDC), how they relate, how the communications are established, and how to architecture your application with the given access, refresh and id tokens…
By David WORMS
Nov 17, 2020
Connecting to ADLS Gen2 from Hadoop (HDP) and Nifi (HDF)
Categories: Big Data, Cloud Computing, Data Engineering | Tags: HDFS, NiFi, Authorization, Hadoop, Authentication, Azure Data Lake Storage (ADLS), Azure, OAuth2
As data projects built in the Cloud are becoming more and more frequent, a common use case is to interact with Cloud storage from an existing on premise Big Data platform. Microsoft Azure recently…
Nov 5, 2020
Rebuilding HDP Hive: patch, test and build
Categories: Big Data, Infrastructure | Tags: Hive, Maven, Git, GitHub, Java, Unit tests, Release and features
The Hortonworks HDP distribution will soon be deprecated in favor of Cloudera’s CDP. One of our clients wanted a new Apache Hive feature backported into HDP 2.6.0. We thought it was a good opportunity…
Oct 6, 2020
Data versioning and reproducible ML with DVC and MLflow
Categories: Data Science, DevOps & SRE, Events | Tags: Data Engineering, Git, Databricks, Delta Lake, Machine Learning, MLflow, Storage
Our talk on data versioning and reproducible Machine Learning proposed to the Data + AI Summit (formerly known as Spark+AI) is accepted. The summit will take place online the 17-19th November…
Sep 30, 2020
Experiment tracking with MLflow on Databricks Community Edition
Categories: Data Engineering, Data Science, Learning | Tags: Deep Learning, Spark, Databricks, Delta Lake, Machine Learning, MLflow, Notebook, Python, Scikit-learn
Introduction to Databricks Community Edition and MLflow Every day the number of tools helping Data Scientists to build models faster increases. Consequently, the need to manage the results and the…
Sep 10, 2020
Version your datasets with Data Version Control (DVC) and Git
Categories: Data Science, DevOps & SRE | Tags: DevOps, Git, Infrastructure, Operation, GitOps, SCM
Using a Version Control System such as Git for source code is a good practice and an industry standard. Considering that projects focus more and more on data, shouldn’t we have a similar approach such…
By Grégor JOUET
Sep 3, 2020