#43 Applying Resilience Engineering Practices to Scale Data Sharing - Interview w/ Tim Tischler

Sign up for Data Mesh Understanding's free roundtable and introduction programs here: https://landing.datameshunderstanding.com/Please Rate and Review us on your podcast app of choice!If you want to be a guest or give feedback (suggestions for topics, comments, etc.), please see hereEpisode list and links to all available episode transcripts here.Provided as a free resource by Data Mesh Understanding / Scott Hirleman. Get in touch with Scott on LinkedIn if you want to chat data mesh.Books/posts/papers mentioned:Blameless PostMortems and a Just Culture by John Allspaw - LinkThe Theory of Graceful Extensibility: Basic rules that govern adaptive systems by David D Woods - LinkThe Field Guide to Understanding 'Human Error' by Sidney Dekker - LinkIn this episode, Scott interviewed Tim Tischler, Principal Engineer at Wayfair. Prior to Wayfair, Tim worked as a Site Reliability Champion at New Relic and is well known in the "human factors" and resilience engineering space. Per Tim, our current work culture is overly action-item driven - every meeting must have a set of agenda items generated from it. This prevents people from having learning-focused meetings exclusively designed for context sharing. Humans' brains work differently between learning and fixing mode and we ask totally different questions. To be able to scale our knowledge sharing, we need to have the space to have learning-focused meetings.A good way to center learning-focused meetings, be they "show and tell" or event storming sessions, is via sharing stories - human communication is founded on story sharing through the millennia. Tim's "show and tell" and event storming sessions at Wayfair have had extremely positive reviews so far. Tim sees ticket-based interactions - just throwing requirements on someone's JIRA backlog or similar - as fundamentally flawed. If Team A gives Team B requirements, Team B just looks to close the ticket versus getting both sides in the room to exchange context and have a negotiation. Tim prefers two modes of interactions over ticket systems: #1 - no human-touch, automated interactions, e.g. an API; and #2 - high touch, high context sharing interactions.For resilience engineering specifically, you should apply learnings to each data product AND the mesh as a whole. Part of that is a broad acceptance that you are in a highly dynamic and highly changing org - there will be changes! A few anti-patterns to resilience engineering that apply to data mesh are: 1) a hub and spoke relationship model where one person is the key glue - this is bad at a human level and even worse at a technical level :); 2) business leaders pushing for metrics without sharing the specific context as the results end up as completely empty and useless things you are tracking; and 3) not embedding people building platforms into the teams they are building the platform for - they must really understand the workflows.Data Mesh Radio...

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Interviews with data mesh practitioners, deep dives/how-tos, anti-patterns, panels, chats (not debates) with skeptics, "mesh musings", and so much more. Host Scott Hirleman (founder of the Data Mesh Learning Community) shares his learnings - and those of the broader data community - from over a year of deep diving into data mesh. Each episode contains a BLUF - bottom line, up front - so you can quickly absorb a few key takeaways and also decide if an episode will be useful to you - nothing worse than listening for 20+ minutes before figuring out if a podcast episode is going to be interesting and/or incremental ;) Hoping to provide quality transcripts in the future - if you want to help, please reach out! Data Mesh Radio is also looking for guests to share their experience with data mesh! Even if that experience is 'I am confused, let's chat about' some specific topic. Yes, that could be you! You can check out our guest and feedback FAQ, including how to submit your name to be a guest and how to submit feedback - including anonymously if you want - here: https://docs.google.com/document/d/1dDdb1mEhmcYqx3xYAvPuM1FZMuGiCszyY9x8X250KuQ/edit?usp=sharing Data Mesh Radio is committed to diversity and inclusion. This includes in our guests and guest hosts. If you are part of a minoritized group, please see this as an open invitation to being a guest, so please hit the link above. If you are looking for additional useful information on data mesh, we recommend the community resources from Data Mesh Learning. All are vendor independent. https://datameshlearning.com/community/ You should also follow Zhamak Dehghani (founder of the data mesh concept); she posts a lot of great things on LinkedIn and has a wonderful data mesh book through O'Reilly. Plus, she's just a nice person: https://www.linkedin.com/in/zhamak-dehghani/detail/recent-activity/shares/ Data Mesh Radio is provided as a free community resource by DataStax. If you need a database that is easy to scale - read: serverless - but also easy to develop for - many APIs including gRPC, REST, JSON, GraphQL, etc. all of which are OSS under the Stargate project - check out DataStax's AstraDB service :) Built on Apache Cassandra, AstraDB is very performant and oh yeah, is also multi-region/multi-cloud so you can focus on scaling your company, not your database. There's a free forever tier for poking around/home projects and you can also use code DAAP500 for a $500 free credit (apply under payment options): https://www.datastax.com/products/datastax-astra?utm_source=DataMeshRadio