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Day: December 24, 2024

Prompt Flow in Azure AI

Published 2024-12-24 by Kevin Feasel

Tomaz Kastrun continues a series on Azure AI. First up is an introduction to Prompt Flow:

Prompt flow in Azure AI Foundry is development tool for designing the flows (streamlines) for the complete end-to-end development cycle of LLM’s AI application. You can create, iterate, test, orchestrate, debug, and monitor your flows.

After that, we get a demonstration a Prompt Flow in Python:

Prompty gives you the ability to create an end-to-end solution, like RAG where you can chat with LLM over an article or document, where you can ask to classify the input data (list of URLs,…)

Prompty is a markdown file, structured in YAML and encapsulates a series of metadata fields pivotal for defining the model’s configuration and the inputs. After this front matter is the prompt template, articulated in the Jinja format.

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Session, DataFrameWriter, and Table Configurations in Spark

Published 2024-12-24 by Kevin Feasel

Miles Cole makes a configuration change:

With Spark and Delta Lake, just like with Hudi and Iceberg, there are several ways to enable or disable settings that impact how tables are created. These settings may affect data layout or table format features, but it can be confusing to understand why different methods exist, when each should be used, and how property inheritance works.

While platform defaults should account for most use cases, Spark provides flexibility to optimize various workloads, whether adjusting for read or write performance, or for hot or cold path data processing. Inevitably, the need to adjust configurations from the default will arise. So, how do we do this effectively?

Read on to learn how.

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Securing a Kafka Ecosystem

Published 2024-12-24 by Kevin Feasel

Riya has a breakdown of how to protect your Apache Kafka installation and resources around it:

Apache Kafka is the backbone of many real-time data pipelines, making security an essential aspect of its deployment. Protecting your Kafka ecosystem involves implementing encryption to safeguard data, authentication to verify user identities, and authorization to control access. This guide provides a comprehensive overview of these three pillars of securing Kafka, complete with code examples to help you implement best practices.

Click through for demonstrations of encryption, authentication, and authorization.

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The Cost of Everything, Cloud Edition

Published 2024-12-24 by Kevin Feasel

Kevin Sookocheff noodles on a core concept:

At AWS re:Invent 2023, Amazon CTO Werner Vogels delivered a talk on the laws of frugal architecture. While I initially filed away those insights to review later, a year of cloud architecture experience crystallized a fundamental truth: in cloud computing, cost isn’t just a financial consideration — it is a first-class architectural concern through which we should design and optimize our systems.

Cloud providers charge for every conceivable resource: servers, API calls, data transfer, and computational milliseconds. But cost is more than just a line item on a monthly bill, it is a powerful forcing function that drives better architectural decisions.

Read on for more thoughts on the matter.

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Writing Loops in Powershell

Published 2024-12-24 by Kevin Feasel

Adam Bertram is spinning in circles:

One of PowerShell’s key features is its ability to loop through data collections, enabling you to execute a code block repeatedly.

In this tutorial, we will explore three fundamental loop structures in PowerShell: foreach, for, and do loops.

By the end of this tutorial, you will have a solid understanding of how to use these loops to handle repetitive tasks and process collections of data more effectively.

Click through for the tutorial.

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Filter and Parameter Passing from Power BI to Power Apps

Published 2024-12-24 by Kevin Feasel

Jon Voege runs into a problem:

A simple comment App embedded in Power BI was supposed to show all the comments in a Sharepoint List which matched the filters set in Power BI. But…. Not all comments were showing up, even though the Sharepoint List only held about 10 comments at the time!

Why you ask? Well, the issue stems from the fact that the table of data being sent from Power BI to Power Apps, the PowerBIIntegration.Data object, has a hard limitation of 1000 rows. And those 1000 rows, is all that we get to work with.

Read on to learn more, as well as a workaround to this issue.

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