Dec 5, 2018 · 22m · mad

A New Kind of Logging System // Zach Sherman & Ben Johnson, Timber (FirstMark's Data Driven NYC)

Ben Johnson · 9m spoken Zach Sherman · 8m spoken Matt Turck · 1m spoken
0:00 / 0:00
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gold bands on the timeline = statements, start to end. Hover to read, click to jump. CC turns on captions

At Data Driven NYC, Timber.io co-founders Ben Johnson and Zach Sherman discuss the architectural challenges of handling high-volume telemetry data and present the concept of an observability data routing layer. They demonstrate how decoupling data streams into specialized storage engines dramatically improves system reliability, operational flexibility, and infrastructure cost efficiency.

How this conversation actually went

Every chapter scored 0–10 on four independent dynamics. Hover any point for the reasoning behind the score. Matt holds 7.5% of the talking time here. How this is scored →

Matt as informed peer 0.6 Guest teaching 2.6 Guest disagreement 0.0 Matt pushing back 0.2
05100:0010:0020:001:05–3:34 · Matt as informed peer 0/10 The Scale and Challenges of Telemetry Data This is a solo presentation monologue by Ben Johnson outlining Timber's scale and logging challenges. The host does not participate during the presentation, so host metrics are zero.3:34–6:46 · Matt as informed peer 0/10 Diversifying Data Demands & Navigating Tool Overload Ben continues the presentation monologue, explaining the shift from Elasticsearch to multi-storage routing and referencing Matt Turck's landscape slide. Host does not interact.6:46–9:04 · Matt as informed peer 0/10 Defining Routing Layer Requirements Zach Sherman takes over the presentation monologue to explain technical routing requirements and control/data plane concepts. Host is silent during the presentation.9:04–12:39 · Matt as informed peer 0/10 Timber's Modern Routing Architecture & Cost Reduction Zach presents Timber's modern stack built with Rust and Lua, along with dynamic configuration benefits. Host remains silent as this concludes the talk.12:39–22:01 · Matt as informed peer 3/10 Real-World Use Cases, Key Takeaways, and Presentation Wrap-Up Matt Turck conducts a live Q&A session, guiding the talk to cover basic definitions, ideal customer ICPs, and industry trends. The dynamic is fully collaborative and informative.1:05–3:34 · Guest teaching 2/10 The Scale and Challenges of Telemetry Data This is a solo presentation monologue by Ben Johnson outlining Timber's scale and logging challenges. The host does not participate during the presentation, so host metrics are zero.3:34–6:46 · Guest teaching 2/10 Diversifying Data Demands & Navigating Tool Overload Ben continues the presentation monologue, explaining the shift from Elasticsearch to multi-storage routing and referencing Matt Turck's landscape slide. Host does not interact.6:46–9:04 · Guest teaching 3/10 Defining Routing Layer Requirements Zach Sherman takes over the presentation monologue to explain technical routing requirements and control/data plane concepts. Host is silent during the presentation.9:04–12:39 · Guest teaching 3/10 Timber's Modern Routing Architecture & Cost Reduction Zach presents Timber's modern stack built with Rust and Lua, along with dynamic configuration benefits. Host remains silent as this concludes the talk.12:39–22:01 · Guest teaching 3/10 Real-World Use Cases, Key Takeaways, and Presentation Wrap-Up Matt Turck conducts a live Q&A session, guiding the talk to cover basic definitions, ideal customer ICPs, and industry trends. The dynamic is fully collaborative and informative.1:05–3:34 · Guest disagreement 0/10 The Scale and Challenges of Telemetry Data This is a solo presentation monologue by Ben Johnson outlining Timber's scale and logging challenges. The host does not participate during the presentation, so host metrics are zero.3:34–6:46 · Guest disagreement 0/10 Diversifying Data Demands & Navigating Tool Overload Ben continues the presentation monologue, explaining the shift from Elasticsearch to multi-storage routing and referencing Matt Turck's landscape slide. Host does not interact.6:46–9:04 · Guest disagreement 0/10 Defining Routing Layer Requirements Zach Sherman takes over the presentation monologue to explain technical routing requirements and control/data plane concepts. Host is silent during the presentation.9:04–12:39 · Guest disagreement 0/10 Timber's Modern Routing Architecture & Cost Reduction Zach presents Timber's modern stack built with Rust and Lua, along with dynamic configuration benefits. Host remains silent as this concludes the talk.12:39–22:01 · Guest disagreement 0/10 Real-World Use Cases, Key Takeaways, and Presentation Wrap-Up Matt Turck conducts a live Q&A session, guiding the talk to cover basic definitions, ideal customer ICPs, and industry trends. The dynamic is fully collaborative and informative.1:05–3:34 · Matt pushing back 0/10 The Scale and Challenges of Telemetry Data This is a solo presentation monologue by Ben Johnson outlining Timber's scale and logging challenges. The host does not participate during the presentation, so host metrics are zero.3:34–6:46 · Matt pushing back 0/10 Diversifying Data Demands & Navigating Tool Overload Ben continues the presentation monologue, explaining the shift from Elasticsearch to multi-storage routing and referencing Matt Turck's landscape slide. Host does not interact.6:46–9:04 · Matt pushing back 0/10 Defining Routing Layer Requirements Zach Sherman takes over the presentation monologue to explain technical routing requirements and control/data plane concepts. Host is silent during the presentation.9:04–12:39 · Matt pushing back 0/10 Timber's Modern Routing Architecture & Cost Reduction Zach presents Timber's modern stack built with Rust and Lua, along with dynamic configuration benefits. Host remains silent as this concludes the talk.12:39–22:01 · Matt pushing back 1/10 Real-World Use Cases, Key Takeaways, and Presentation Wrap-Up Matt Turck conducts a live Q&A session, guiding the talk to cover basic definitions, ideal customer ICPs, and industry trends. The dynamic is fully collaborative and informative.

speaking balance: gold is Matt, purple is the guest (3 minute bins)

0:00 · Matt 0% · guest 100%0:00 · Matt 0% · guest 100%3:00 · Matt 0% · guest 100%3:00 · Matt 0% · guest 100%6:00 · Matt 0% · guest 100%6:00 · Matt 0% · guest 100%9:00 · Matt 0% · guest 100%9:00 · Matt 0% · guest 100%12:00 · Matt 13.9% · guest 86.1%12:00 · Matt 13.9% · guest 86.1%15:00 · Matt 20.3% · guest 79.7%15:00 · Matt 20.3% · guest 79.7%18:00 · Matt 18.4% · guest 81.6%18:00 · Matt 18.4% · guest 81.6%21:00 · Matt 13.1% · guest 86.9%21:00 · Matt 13.1% · guest 86.9%
Sharpest disagreement ▶ 16:25 Ben clarifies lack of durability guarantees in routing layer

Responding to an audience question, Ben directly reframes expectations, clarifying that Timber does not offer processing guarantees as durability relies on Kafka.

Hardest push from Matt ▶ 20:15 Matt asks guests to ground complex technical terms for audience

Matt pushes past the dense data engineering talk, steering guests to explain fundamental definitions like metrics so everyone in the room can learn.

Biggest teaching moment ▶ 20:25 Ben educates on how aggregated metrics cut storage costs

Ben explains to the host and audience how rolling raw events into single numeric aggregates radically cuts storage and processing expenses.

Matt holds his own ▶ 17:36 Matt frames the burgeoning complexity of data engineering

Matt displays domain familiarity by highlighting how tool proliferation created the whole specialized discipline of data engineering, which the guest validates.

the scores for every segment, with the reasoning behind each
ChapterTopicMatt as informed peerGuest teachingGuest disagreementMatt pushing backWhy
The Scale and Challenges of Telemetry Data 0200 This is a solo presentation monologue by Ben Johnson outlining Timber's scale and logging challenges. The host does not participate during the presentation, so host metrics are zero.
Diversifying Data Demands & Navigating Tool Overload 0200 Ben continues the presentation monologue, explaining the shift from Elasticsearch to multi-storage routing and referencing Matt Turck's landscape slide. Host does not interact.
Defining Routing Layer Requirements 0300 Zach Sherman takes over the presentation monologue to explain technical routing requirements and control/data plane concepts. Host is silent during the presentation.
Timber's Modern Routing Architecture & Cost Reduction 0300 Zach presents Timber's modern stack built with Rust and Lua, along with dynamic configuration benefits. Host remains silent as this concludes the talk.
Real-World Use Cases, Key Takeaways, and Presentation Wrap-Up 3301 Matt Turck conducts a live Q&A session, guiding the talk to cover basic definitions, ideal customer ICPs, and industry trends. The dynamic is fully collaborative and informative.

Statements from this episode (10)

Disclosure
Ben Johnson: Routing layer is the most valuable part of Timber's pipeline
“We want to talk to you about what we have found to be the most valuable aspect of our data pipeline. We call it the routing layer. It's really been the foundation of all the value we've extracted out of that.”
Ben Johnson Dec 5, 2018 ▶ 0:16
Assertion Not checkable as stated
Ben Johnson: Developers increasingly use machine logs for user analytics
“Recently we've seen developers use that for understanding user behavior and analytics”
Ben Johnson Dec 5, 2018 ▶ 0:56
Assertion Not checkable as stated
Timber.io processes 3 billion events daily across 4,000 applications
“We process almost eight gigabytes a day. We do five to 6000 requests per second, three billion events. We have 4000 applications sending us data.”
Ben Johnson Dec 5, 2018 ▶ 1:09
Disclosure
Ben Johnson: Timber struggled to scale Elasticsearch past multiple terabytes
“What we found though is that while it was good getting started, we encountered a lot of challenges with it, especially when we started to cross over into the multiple terabyte range. And we had a lot of trouble scaling it.”
Ben Johnson Dec 5, 2018 ▶ 2:46
Assertion Not checkable as stated
Ben Johnson: Real-time data processing was a major challenge with Elasticsearch
“So being being real-time and processing this data was really important, and that was a real challenge with Elasticsearch.”
Ben Johnson Dec 5, 2018 ▶ 4:01
Assertion Not checkable as stated
Ben Johnson: No single storage engine could completely replace Elasticsearch
“What was interesting is that all of these storages have different strengths, but none of them really could just completely replace Elasticsearch.”
Ben Johnson Dec 5, 2018 ▶ 4:19
Assertion Not checkable as stated
Sherman: Timber reduced its data pipeline costs by about 90%
“And we actually reduce the cost of our pipeline by about 90% by doing this.”
Zach Sherman Dec 5, 2018 ▶ 9:55
Assertion Not checkable as stated
Sherman: Expensive Splunk bills are one of Timber's most common customer complaints
“One of the most common complaints that we hear is how expensive people's Splunk bills are. Can't tell you how many times I've heard that.”
Zach Sherman Dec 5, 2018 ▶ 10:48
Insight
Sherman advises against building logging or metrics systems from scratch
“I would recommend you don't build a logging or metric system from scratch, and you pull something off the shelf.”
Zach Sherman Dec 5, 2018 ▶ 13:35
Disclosure
Johnson: Timber intends to open-source its log routing technology
“Our intent is to open source this project.”
Ben Johnson Dec 5, 2018 ▶ 16:30
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