Logs
Structured, high-cardinality log pipelines: ingestion, parsing, indexing and query that survive burst traffic without dropping a line.
- ingestion
- parsing
- indexing
- retention
I started out as a Site Reliability Engineer, on the receiving end of pages at 3 AM, chasing cascading failures, tuning SLOs, and learning that you can't fix what you can't see.
That lesson pulled me into Observability. Today I build the systems that make other engineers' systems legible: high-throughput log pipelines and event platforms that stay fast, cheap, and trustworthy at scale.
Reliability isn't a team; it's a property you engineer in. Observability is how you prove it.
SLOs, incident response, capacity, resilience @ LinkedIn.
Full-stack + DevOps tooling for global cloud networks.
Logs & Events platforms at scale @ LinkedIn.
Cheaper, smarter telemetry: signal without the noise.
CareerLog | where engineer == "likith.srinath" | order by ts desc
Structured, high-cardinality log pipelines: ingestion, parsing, indexing and query that survive burst traffic without dropping a line.
Event streams as a first-class signal: schematized, ordered, replayable, and joined with logs to reconstruct exactly what happened.
SLOs, error budgets and alerting that pages on symptoms, not noise. The SRE instincts I never left behind.
More on GitHub ↗
Co-led the Radicul committee, planning and hosting events for the engineering team to boost morale and strengthen collaboration.
Mentored college students to identify and navigate better career opportunities.
Organized an internal engineering Capture The Flag event to promote security awareness and team building.
🏆 College innovation award, smart ticketing system (facial recognition)
Building something that needs to stay up and stay observable? I'm always up for a conversation about logs, events, and reliability at scale.