Stack analysis to unlock performance, decrease costs and help future planning. Bring long-term vision.
Develop your cloud application/platform using Python, Java, or Scala. Deploy using serverless primitives like AWS Lambda or container based solutions like Kubernetes. Wide expertise going from numerical optimization and datascience to storage technologies, DevOps and Cloud Native key enablers. Deep dive into your stack code and infrastructure most inner layers to uncover the primary lever to boost performances.
Help starting projects and teams to prepare their large scale success. Capacity planning for large projects. Perform system design on large distributed system to improve reliability, eliminate bottlenecks and optimize resources utilization.
“Julien has been involved throughout 2019 in our department for a consulting mission on Apache Cassandra (a NoSQL database management system) and its use in the implementation of the Axway API Management suite.His expertise and skills have helped improve the performance and behavior of our platforms. He also did not hesitate to go beyond the scope of his mission to provide support and analysis on production incidents. Bravo and thanks again!”
“Two excellent missions from Julien based on his technical skills, his expertise and a very good relationship.”
“I had the great pleasure to work with Julien Laurenceau on our autonomous vehicle and platooning car project on 5G and 6G networks. Julien designed and developed our first data layer prototype on a 5G Edge cloud platform with high availability, scalability and low latency constraints. The project is currently in beta but we are very optimistic for future iterations and physical testing and experimentation. Julien is a good architect on stream data systems, Iot platforms like #Pulsar and #Warp10 TSDB.”
Note: This article was inspired by a LinkedIn post by Can Sinan A. on the hidden operational cost of an Iceberg migration, especially when governance moves from one access-control plane to several layers: catalog, storage Read more
When Tesla published patent WO2024073080 describing a new file format internally called “.smol”, the headline was simple: 4x reduction in IOPS for AI training. Most people read this as a hardware story. It isn’t. It’s Read more
If you are running Ceph Squid with a mix of managed and unmanaged OSDs, there is one thing worth stating clearly upfront: There is no in-place adoption mechanism in Squid. You cannot “import” an existing Read more