Deploy your own Databricks Feature Store on Azure using Terraform
A tutorial on how to deploy one of the key pieces of the MLOps-enabling modern data platform: the Feature Store on Azure Databricks with Terraform as…
Read moreLearning new technologies is like falling in love. At the beginning, you enjoy it totally and it is like wearing pink glasses that prevent you from observing anything you don’t like. In software development, we call this phase Proof of Concept. Then a jazzy proof of concept starts being a casual project with corner cases that you cannot hide and need to resolve. At some point, a number of corner cases overwhelms you and maybe even bigger than the advantages gained by the brand-new technology. This may mean long weeks when you truly hate it, although being in love a moment earlier. If you are lucky, you will get Your problems solved quickly and will be able to deploy on production. At this point, you can sit back, eat caviar, drink champagne and put all together - all the findings and issues you solved and encountered during the project.
At GetInData, we have reached this point and this post series shares our hands-on, real-life experience with Apache NiFi. We will show our findings and opinions but we will not answer questions like: is NiFi good enough, do we recommend it, etc… We believe there are no general answers for that and focus on describing what issues can one encounter when deploying data flows in NiFi. All of the examples come from real project scenarios.
Our blog series will be divided into the following posts:
This is what we are planning to do. Please stay with us to read further posts, no matter if you are interested in all the topics or just some of them.
See you soon ;-)
A tutorial on how to deploy one of the key pieces of the MLOps-enabling modern data platform: the Feature Store on Azure Databricks with Terraform as…
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Read moreTogether, we will select the best Big Data solutions for your organization and build a project that will have a real impact on your organization.