Julien Balestra
Director Of Engineering at Datadog
Paris, Ile-de-France
Summary
🤩
Rockstar🎓
Top SchoolJulien Balestra is a Director of Engineering based in Paris with 11 years of experience building and operating cloud-native infrastructure and observability platforms. He has grown through hands-on SRE and engineering roles into leadership at Datadog, where he has driven backend, DevOps and testing improvements across the Datadog Agent and core integrations. A frequent open-source contributor, Julien has worked on high-impact projects like Kubernetes autoscaler and containerd, adding TLS streaming, compression support, autoscaling metrics and stronger test coverage for Docker and Kubelet workflows. Known for blending pragmatic engineering with operational rigor, he focuses on measurable observability improvements and resilient systems at scale. An early technologist trained at 42 Paris, he brings a practical SRE mindset to product engineering and platform reliability.
11 years of coding experience
11 years of employment as a software developer
Certification en technologie numérique Programmation informatique, Certification en technologie numérique Programmation informatique at 42 Paris
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (27)
autoscaling10
kubernetes10
docker10
observability10
tls1210
python10
testing10
cloud-infrastructure10
tls1310
dockers10
mtls10
containerd10
go10
prometheus10
kubernetes-pods10
Programming languages (8)
Github contributions (5)
DataDog/datadog-agent
Nov 2017 - Mar 2019
Main repository for Datadog Agent
Role in this project:
Back-end & DevOps Engineer
Back-end & DevOps EngineerContributions:4 reviews, 70 commits, 106 PRs in 1 year 3 months
Contributions summary:Julien focused on enhancing the Datadog Agent's testing infrastructure, particularly for Docker-related features. Their contributions included adding tests for service checks and event handling within the Docker environment, alongside creating unit tests for mocksender. They also improved the agent's Docker entrypoint script and implemented checks for container image stats and global metrics. Furthermore, the user worked on enhancements for the agent's Kubernetes integration, specifically the service mapper.
golangdatadog-agentagentobservabilitypmm
kubernetes/autoscaler
Aug 2019 - Jul 2020
Autoscaling components for Kubernetes
Role in this project:Back-end & DevOps Engineer
Back-end & DevOps EngineerContributions:15 commits, 9 PRs, 22 comments in 11 months
Contributions summary:Julien primarily contributed to the metrics and core logic of the Kubernetes autoscaler. They implemented new metrics for scale-down cooldown, and function duration summaries, enhancing the observability of the autoscaler's operations. The user also addressed an issue related to the handling of instances with unknown MIGs and implemented improvements to the AWS launch configuration cache, demonstrating their proficiency in both back-end and cloud infrastructure aspects. They also modified the taints logic to better manage existing nodes.
k8skubernetesautoscaling
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.