Shreyas Srivatsan
Distinguished Engineer at Palo Alto Networks
Seattle, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolShreyas Srivatsan is a Distinguished Engineer based in Seattle with 17+ years of experience building virtualization, operating systems, and distributed backend systems. He has deep kernel and OS expertise from work on Microsoft's Hyper‑V and has since focused on cloud-native observability and resilient orchestration at Uber, Chronosphere, and now Palo Alto Networks. Shreyas contributes to prominent open-source projects like Cadence and M3, improving Prometheus-style metrics, context propagation, and time-series ingestion—work that directly boosts observability and operational debugging at scale. He combines low-level systems rigor with pragmatic backend engineering, shipping features that make large distributed workflows and TSDBs more measurable and reliable. Notably, his contributions include refining metric semantics and workflow history handling, a pattern that reflects attention to subtle correctness and production readiness. He holds an MS in Computer Science from Columbia Engineering and a B.Tech from NIT Karnataka.
7 years of coding experience
15 years of employment as a software developer
MS Computer Science, MS Computer Science at Columbia EngineeringB. Tech Computer Engineering, B. Tech Computer Engineering at National Institute of Technology Karnataka
Github Skills (19)
propagation10
timeseries-database10
cadence10
distributed-systems10
tsd10
go10
prometheus10
golang10
functionfs10
orchestration10
metric10
aggregator9
testing9
orchestrate9
workflow-automation9
Programming languages (3)
Github contributions (5)
cadence-workflow/cadence-go-client
May 2019 - Jul 2019
Framework for authoring workflows and activities running on top of the Cadence orchestration engine.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:3 releases, 14 commits, 25 PRs in 2 months
Contributions summary:Shreyas primarily focused on enhancing the Cadence Go client with features related to metrics reporting and context propagation. Their contributions include adding support for Prometheus-style metrics, ensuring proper sanitization and compatibility. They also implemented context propagation for headers, child workflows, and continue-as-new functionality, enhancing the client's ability to transmit information across workflow executions. Furthermore, the user addressed locking issues within the workflow context.
golangworkflow-functionscadenceorchestrationauthoring-workflows
m3db/m3
Apr 2020 - Oct 2021
M3 monorepo - Distributed TSDB, Aggregator and Query Engine, Prometheus Sidecar, Graphite Compatible, Metrics Platform
Role in this project:Back-end Developer
Back-end DeveloperContributions:33 reviews, 48 commits, 37 PRs in 1 year 6 months
Contributions summary:Shreyas made several contributions focused on enhancing the M3 time-series database and its related components. Their work included adding new metric types and sources to the time-series message, indicating efforts to expand data ingestion capabilities. Furthermore, the user worked on supporting additional metric types for remote write and improving the handling of aggregation policies within the coordinator, and also added support for tags to the rollup rules. The contributions suggest a focus on improving the core functionality and flexibility of the M3 system.
distributedquerymonorepoquery-enginesidecar
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