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Klaviyo Data Science Podcast EP 41 | Incident Response, or: How I Learned to Stop Worrying and Break Production

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Manage episode 383573269 series 3251385
内容由Klaviyo Data Science Team提供。所有播客内容(包括剧集、图形和播客描述)均由 Klaviyo Data Science Team 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal

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.

  continue reading

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Manage episode 383573269 series 3251385
内容由Klaviyo Data Science Team提供。所有播客内容(包括剧集、图形和播客描述)均由 Klaviyo Data Science Team 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal

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.

  continue reading

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