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Rebuilding Observability for the Agentic AI Era with Suman Karumuri
Suman Karumuri has spent 17+ years building observability systems at Amazon, Twitter, Pinterest, Slack, and Airbnb. He was tech lead for Zipkin at Twitter, co-authored the OpenTracing specification that fed into OpenTelemetry, and has now replaced Elasticsearch twice at high-traffic platforms. In this episode of the Smooth Scaling Podcast, Suman walks host Jose Quaresma through KalDB, the open-source, cloud-native log search engine he is building into a product, which runs at petabyte scale at Slack and Airbnb. They get into why he keeps rewriting Elasticsearch instead of tuning it, how separating compute from storage on S3 changes what a log system can do, and the recovery-task trick that keeps fresh logs visible when volume spikes 10x. The back half turns to agentic AI: why agents querying logs in unpredictable bursts break traditional log stacks, why you can't sample data anymore, and what engineering leaders should measure before the bill explodes. A concrete, in-the-weeds look at running log search when the primary user is no longer human.
Episode page
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- (00:00) - Intro
Suman Karumuri is the founder of KalDB, the open-source cloud-native log search engine he is now building into a product. KalDB runs at petabyte scale at Slack, Salesforce, and Airbnb. He spent 17+ years building observability systems at Amazon, Twitter, Pinterest, Slack, and Airbnb, was tech lead for Zipkin at Twitter, and co-authored the OpenTracing specification under the CNCF, which became the foundation of OpenTelemetry. He is based in San Francisco.
Suman has replaced Elasticsearch twice at high-traffic platforms. And with the rise of Agentic AI querying log systems in non-deterministic bursts, this places a whole new kind of stress on those systems to perform at high scale.
Suman Karumuri: https://www.linkedin.com/in/mansu/
Host José Quaresma: https://www.linkedin.com/in/jose-quaresma/
This podcast is produced and researched by Perseu Mandillo, and brought to you by Queue-it, your virtual waiting room partner.
© Queue-it, 2026
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Suman Karumuri has spent 17+ years building observability systems at Amazon, Twitter, Pinterest, Slack, and Airbnb. He was tech lead for Zipkin at Twitter, co-authored the OpenTracing specification that fed into OpenTelemetry, and has now replaced Elasticsearch twice at high-traffic platforms. In this episode of the Smooth Scaling Podcast, Suman walks host Jose Quaresma through KalDB, the open-source, cloud-native log search engine he is building into a product, which runs at petabyte scale at Slack and Airbnb. They get into why he keeps rewriting Elasticsearch instead of tuning it, how separating compute from storage on S3 changes what a log system can do, and the recovery-task trick that keeps fresh logs visible when volume spikes 10x. The back half turns to agentic AI: why agents querying logs in unpredictable bursts break traditional log stacks, why you can't sample data anymore, and what engineering leaders should measure before the bill explodes. A concrete, in-the-weeds look at running log search when the primary user is no longer human.
Episode page
---
- (00:00) - Intro
Suman Karumuri is the founder of KalDB, the open-source cloud-native log search engine he is now building into a product. KalDB runs at petabyte scale at Slack, Salesforce, and Airbnb. He spent 17+ years building observability systems at Amazon, Twitter, Pinterest, Slack, and Airbnb, was tech lead for Zipkin at Twitter, and co-authored the OpenTracing specification under the CNCF, which became the foundation of OpenTelemetry. He is based in San Francisco.
Suman has replaced Elasticsearch twice at high-traffic platforms. And with the rise of Agentic AI querying log systems in non-deterministic bursts, this places a whole new kind of stress on those systems to perform at high scale.
Suman Karumuri: https://www.linkedin.com/in/mansu/
Host José Quaresma: https://www.linkedin.com/in/jose-quaresma/
This podcast is produced and researched by Perseu Mandillo, and brought to you by Queue-it, your virtual waiting room partner.
© Queue-it, 2026