#72 Reliability in Data Mesh: Why SLAs and SLOs are Crucial - Interview w/ Emily Gorcenski

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.Transcript for this episode (link) provided by Starburst. See their Data Mesh Summit recordings here and their great data mesh resource center here.Emily's LinkedIn: https://www.linkedin.com/in/emily-gorcenski-0a3830200/Emily's Twitter: @EmilyGorcenski / https://twitter.com/EmilyGorcenskiEmily's Polywork profile: https://www.polywork.com/emilygorcenskiEmily's website: https://www.emilygorcenski.com/Alex Hidalgo's Implementing Service Level Objectives book as mentioned: https://www.alex-hidalgo.com/the-slo-bookIn this episode, Scott interviewed Emily Gorcenski, Head of Data and AI at Thoughtworks Germany. Emily has put out some great content relative to data mesh.As a data scientist by training, Emily has a data consumer bent in her views on data mesh. She is therefore often focused on how can data mesh help "me" (her) as a data consumer.SLAs and SLOs come right out of the site reliability engineering playbook from Google. Overall, systems reliability engineering practices are crucial - Emily asked why don't we bring the rigor of other engineering disciplines to software engineering?So, what is an SLA and an SLO? Per Emily, an SLA is a contract between two parties - hence why agreement is in the name. This agreement should be written around an SLO with the SLO serving as a specific target. That can be uptime or latency in the microservices realm but with data, SLOs can get a little - or a lot - more tricky.The theory around developing an SLO is for it to directly connect to business value. Emily believes that when we think about SLOs and data, we shouldn't apply SLOs directly to the data but should shift those SLOs to the left and have SLOs in the software engineering practice that apply to data.Emily mentioned another antipattern for SLAs in general, which is not connecting them to SLOs. But when it comes to data, most teams don't even have any SLAs, connected to an SLO or not. As an industry, software engineering has figured out...

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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