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SHOW: 396
DESCRIPTION: Aaron and Brian talk with Renaud Boutet (@boutetren, VP Product Management @datadoghq) about logging, monitoring, observability, and the challenges of balancing the collection of the right data with the costs of all the data.
SHOW SPONSOR LINKS:
CLOUD NEWS OF THE WEEK:
SHOW INTERVIEW LINKS:
SHOW NOTES:
Topic 1 - Welcome to the show. Tell us about some of your background prior to joining Datadog, and about your focus areas today.
Topic 2 - Let’s start with some conceptual buckets - how do you sort out the differences when people say “monitoring” vs. “logging” vs. “observability”?
Topic 3 - Logging has the inherent tradeoff between the desire to “log everything” and the limitation of costs to log (and retain everything). What are some of the trends to potentially make this tradeoff more manageable?
Topic 4 - At some point, the tradeoff between sending logs, filtering logs, storing logs all boils down to a financial trade-off of immediate costs vs potential costs associated with failure. How do you see those conversations playing out in real life? Any suggestions on a framework for doing those types of analysis?
Topic 5 - What role do you see AI playing in the future of Logging/Observability? It seems like that needs to become the next big step if the industry solves the challenges of logging/storage more and more.
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By Massive Studios4.6
147147 ratings
SHOW: 396
DESCRIPTION: Aaron and Brian talk with Renaud Boutet (@boutetren, VP Product Management @datadoghq) about logging, monitoring, observability, and the challenges of balancing the collection of the right data with the costs of all the data.
SHOW SPONSOR LINKS:
CLOUD NEWS OF THE WEEK:
SHOW INTERVIEW LINKS:
SHOW NOTES:
Topic 1 - Welcome to the show. Tell us about some of your background prior to joining Datadog, and about your focus areas today.
Topic 2 - Let’s start with some conceptual buckets - how do you sort out the differences when people say “monitoring” vs. “logging” vs. “observability”?
Topic 3 - Logging has the inherent tradeoff between the desire to “log everything” and the limitation of costs to log (and retain everything). What are some of the trends to potentially make this tradeoff more manageable?
Topic 4 - At some point, the tradeoff between sending logs, filtering logs, storing logs all boils down to a financial trade-off of immediate costs vs potential costs associated with failure. How do you see those conversations playing out in real life? Any suggestions on a framework for doing those types of analysis?
Topic 5 - What role do you see AI playing in the future of Logging/Observability? It seems like that needs to become the next big step if the industry solves the challenges of logging/storage more and more.
FEEDBACK?
FEEDBACK?

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