Michael Desa
Co-Founder Technical Staff at Equall
United States
Summary
🤩
Rockstar🎓
Top SchoolMichael Desa is a co-founder and technical leader with 12 years of experience building startups and scaling engineering teams at the intersection of product, business, and operations. He brings deep backend expertise in high-performance distributed systems and time-series databases, having contributed substantive improvements to InfluxData projects like Flux, Kapacitor, and InfluxDB that focused on query engine internals, observability, and concurrency fixes. As an engineering manager and former instructor, he combines hands-on systems work with people leadership and a knack for turning complex data-processing needs into robust, production-ready features. Currently leading technical efforts at Equall, he pairs a Berkeley mathematics background with pragmatic experience shipping performant data platforms and embedding error-tracking and benchmarking into core systems.
12 years of coding experience
6 years of employment as a software developer
Bachelor of Arts (BA), Mathematics, Bachelor of Arts (BA), Mathematics at University of California, Berkeley
Github Skills (17)
monitoring10
databases10
go10
query-language10
data-processing10
error-handling10
influxdb10
relational-databases10
sql-database10
database10
benchmark9
benchmarking9
query-optimization9
concurrency9
apidoc8
Programming languages (12)
Github contributions (5)
influxdata/kapacitor
Feb 2017 - May 2018
Open source framework for processing, monitoring, and alerting on time series data
Role in this project:
Backend Developer
Backend DeveloperContributions:124 commits, 70 PRs, 354 pushes in 1 year 2 months
Contributions summary:Michael made multiple commits to the `kapacitor` repository, primarily focused on enhancing the monitoring and error handling capabilities of various node types within the time series data processing framework. Their contributions involved adding error counters to multiple node types, including alert, batch, combine, where, derivative, eval, flatten, influxdb_out, influxql, and join nodes. These changes indicate a focus on improving the robustness and observability of the system, by integrating error tracking at key points in data processing pipelines.
kapacitorseries-dataalertingtime-seriesmetrics
influxdata/influxdb
Aug 2015 - Aug 2020
Scalable datastore for metrics, events, and real-time analytics
Role in this project:Back-end Developer
Back-end DeveloperContributions:1 review, 841 commits, 225 PRs in 5 years 1 month
Contributions summary:Michael's contributions focus on enhancing the performance and functionality of the InfluxDB platform. Their work includes fixing concurrency issues related to map access, adding benchmarks for various database schemas to evaluate memory usage, and integrating new features like fill(linear) to the query language. Furthermore, the user was responsible for preventing writing auth commands to influx history and improving the performance of queries.
real-time-analyticsscalablereactanalyticsevents
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