Jordan Storms
Software Engineer II at Datadog
Bloomingdale, New Jersey, United States
Summary
🤩
Rockstar🎓
Top SchoolJordan Storms is a Software Engineer II at Datadog with a decade of experience building back-end and full-stack web solutions from New Jersey. After pivoting from a path toward a PhD in Computational Neuroscience, he taught himself Python in grad school and translated that analytical mindset into production-grade engineering. At Datadog he has moved up from Solutions Engineer to developer, contributing to high-profile open-source projects such as Datadog’s serverless functions and agent—adding Lambda metrics, expanding inferred-span support for multiple AWS event sources, and improving testing and adaptive flush strategies. He combines DevOps pragmatism with strong backend skills across Go, Java, and scripting, and has hands-on experience parsing complex log data and adding telemetry for serverless environments. Known for bridging research-driven curiosity with operational rigor, he brings a practical focus on observability and resilient cloud integrations.
10 years of coding experience
6 years of employment as a software developer
Computational Neuroscience, Computational Neuroscience at New Jersey Institute of TechnologyFlatiron SchoolBachelor of Science - BS, Biology, Bachelor of Science - BS, Biology at William Paterson University of New Jersey
Github Skills (31)
tracer10
python10
testing10
distributed-tracing10
aws-lambda10
regular-expression10
go10
aws10
apm-agent10
serverless10
trace10
scripting9
cicd9
java9
opentelemetry-go9
Programming languages (12)
Github contributions (5)
DataDog/datadog-agent
Dec 2021 - Nov 2022
Main repository for Datadog Agent
Role in this project:
Back-end Developer & DevOps Engineer
Back-end Developer & DevOps EngineerContributions:82 reviews, 42 commits, 50 PRs in 11 months
Contributions summary:Jordan primarily contributed to the serverless components of the Datadog agent, focusing on integration testing for Java-based serverless functions and adding support for new event types (SNS, SQS, Kinesis, DynamoDB, EventBridge) within the inferred span functionality. They also made improvements to the agent's adaptive flush strategy and added a feature to include Azure App Service metadata. Their work involved modifying Go code, shell scripts, and Java code, and managing environment variables related to integration testing and race detection.
golangdatadog-agentagentobservabilitypmm
DataDog/datadog-serverless-functions
Jun 2020 - Jun 2020
Repo of AWS Lambda and Azure Functions functions that process streams and send data to Datadog
Role in this project:Back-end Developer
Back-end DeveloperContributions:4 reviews, 39 commits, 14 PRs in 9 days
Contributions summary:Jordan primarily contributed to the `aws/logs_monitoring/enhanced_lambda_metrics.py` file, focusing on enhancing the metrics extracted from AWS Lambda function logs. They added functionality to capture and report initialization duration and timeout metrics. They also implemented improvements to the existing metric extraction logic, including tag management, formatting, and unit tests. The user's work involved modifying regular expressions for parsing log data.
azure-functionsserverlessaws-lambdastreamsaws
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