46 min
Klaviyo Data Science Podcast EP 41 | Incident Response, or: How I Learned to Stop Worrying and Break Production Klaviyo Data Science Podcast
-
- Marketing
Welcome back to the Klaviyo Data Science podcast! This episode, we dive into…
When Things Break
Welcome to the November episode of the Klaviyo Data Science Podcast for this year! November is a unique month for ecommerce, which makes it a unique month for any software solution built for ecommerce; it’s a tradition on this podcast to take the opportunity to celebrate some of those unique challenges.
In an ideal world, software and data science products would never break. We do not live in an ideal world, though, so an important question to answer is: what should you do when things do break? This month, we discuss incidents, incident response, and getting things back on track as quickly and effectively as possible to continue delivering value to your customers.
Listen along to learn more about:
Why not all ways of recognizing something has gone wrong are created equal
How to cut through disagreements when the stakes are at their highest
What sorts of unique challenges data science breakages and incidents pose
For the full show notes, including resources mentioned in the episode and who's who, see the Medium writeup.
Welcome back to the Klaviyo Data Science podcast! This episode, we dive into…
When Things Break
Welcome to the November episode of the Klaviyo Data Science Podcast for this year! November is a unique month for ecommerce, which makes it a unique month for any software solution built for ecommerce; it’s a tradition on this podcast to take the opportunity to celebrate some of those unique challenges.
In an ideal world, software and data science products would never break. We do not live in an ideal world, though, so an important question to answer is: what should you do when things do break? This month, we discuss incidents, incident response, and getting things back on track as quickly and effectively as possible to continue delivering value to your customers.
Listen along to learn more about:
Why not all ways of recognizing something has gone wrong are created equal
How to cut through disagreements when the stakes are at their highest
What sorts of unique challenges data science breakages and incidents pose
For the full show notes, including resources mentioned in the episode and who's who, see the Medium writeup.
46 min