About
Our Team
We've spent our careers building and scaling the kinds of software systems where failure isn't an option - from high-throughput data pipelines and distributed services at Tesla to global-scale platforms at Uber and Amazon.
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Along the way, we've led platform, developer experience, and data engineering teams, shipping products and infrastructure that power everything from clean energy to consumer tech. We know what it takes to move fast without breaking the things that matter, and how to align engineering execution with ambitious delivery goals.
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Now we're bringing that mix of operational discipline and product-driven engineering to Canary - so engineering teams can slash their MTTR and understand their systems with the confidence they need.
Why we started
We started Canary because engineering teams are drowning in logs while struggling to understand what actually happened when things go wrong. Organizations have invested millions in observability tools, but when an incident strikes, engineers still spend hours manually correlating logs across services to understand the execution path.
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The instrumentation tax. Teams are forced to choose between extensive code changes for proper tracing or flying blind with disconnected logs. The effort required to instrument legacy systems often means critical services remain opaque during incidents.
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Guesswork over evidence. Engineers piece together what might have happened based on timestamps and guesswork, but lack evidence-backed paths showing exactly how a request flowed through their system and where it failed.
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Data without answers. Teams generate terabytes of log data but lack the tools to automatically reconstruct execution paths, identify patterns, or get actionable recommendations on what to log next.
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Manual toil at scale. Senior engineers spend their time doing manual root cause analysis that should be automated, while junior engineers lack the context to effectively debug distributed systems.
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We created Canary to address these gaps. By reconstructing execution paths from existing logs, providing confidence scoring, enabling conversational RCA, and delivering actionable logging recommendations, Canary empowers engineering teams to resolve incidents faster with zero instrumentation required.