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Category: Deployment

Creating a Power BI Deployment Pipeline

Published 2023-07-20 by Kevin Feasel

Richard Swinbank does some deployment:

In part 4 of this series, I introduced a standard pattern for organising report files and pipelines, with a standard process for creating new reports. Repeatable patterns and processes are great candidates for automation, and in this post I’ll build a report creation process that automatically configures a new report and creates its deployment pipeline .

This video (5m31s) shows you the process in action, from creating a new report to seeing it deployed automatically to Power BI:

Click through for the video, as well as plenty of written instruction.

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Power BI Report Deployment with Connections to Shared Datasets

Published 2023-07-17 by Kevin Feasel

Rayis Imayev does some large-scale deployment:

Let’s say you have a collection of Power BI .pbix files stored in a git-based source control system (GitHub, Azure DevOps, or any other system). Among these files, one is your data model, while the others are Power BI visual reports and dashboards connected to the published dataset from your data model. Your published dataset is located in a separate workspace dedicated to shared content, and the visualization Power BI reports are placed in another workspace with appropriate permissions to access them.

Now, let’s consider an additional complexity: you have this collection of files not only in one development environment but also in two others. These environments support your Power BI reporting testing (UAT) and the release of your Power BI reports to end-users (Production).

The questions that arise are: How do you deploy your solution, and most importantly, how do you automate it?

Click through for an architectural diagram, as well as the answer to this question.

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Creating an Azure DevOps YAML Pipeline for SQL Server Deploys

Published 2023-06-20 by Kevin Feasel

Oilivier Van Steenlandt updates to the new Azure DevOps model:

In one of my previous blog posts, I used the SQL Server database deploy task to deploy my DACPAC to SQL Server. Unfortunately, this task became deprecated in Release Pipelines. In this blog post, I would like to share the alternative.

Additionally, we will be moving from a Classic Release pipeline to a YAML pipeline. The YAML pipeline will be responsible for building and deploying our Database Projects.

Click through for the walkthrough.

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Deploying to Multiple Power BI Dataset Environments

Published 2023-06-07 by Kevin Feasel

Richard Swinbank configures some deployments:

In earlier posts in this series, I talked about to developing and deploying standalone Power BI datasets and automating report deployment into different environments. I’ll bring together those approaches in this post, to enable deployment of shared datasets into multiple environments. This has consequences for automated report deployment, and I’ll take a look at that too.

Read the whole thing.

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Postgres Change Management Rollbacks

Published 2023-06-05 by Kevin Feasel

Grant Fritchey explains why stateful systems are difficult to roll back:

The invitation this month for #PGSqlPhriday comes from Dian Fay. The topic is pretty simple, database change management. Now, I may have, once or twice, spoken about database change management, database DevOps, automating deployments, and all that sort of thing. Maybe. Once or twice.

OK. This is my topic.

I’ve got some great examples on taking changes from the schema on your PostgreSQL databases and then deploying them. All the technical stuff you could want. However, I don’t want to talk about that today. Instead, I want to talk about something really important, the concept of rollbacks when it comes to database deployments.

I completely agree with Grant’s description of the pain and his recommendation. With stateful systems, roll forward, not backward.

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Thoughts on Postgres File Layout and Migration

Published 2023-06-05 by Kevin Feasel

Dian Fay shares some advice:

I’ve used several migration frameworks in my time. Most have been variations on a common theme dating back lo these past fifteen-twenty years: an ordered directory of SQL scripts with an in-database registry table recording those which have been executed. The good ones checksum each script and validate them every run to make sure nobody’s trying to change the old files out from under you. But I’ve run into three so far, and used two in production, that do something different. Each revolves around a central idea that sets it apart and makes developing and deploying changes easier, faster, or better-organized than its competition — provided you’re able to work within the assumptions and constraints that idea implies.

Read on for thoughts about three tools: sqitch, graphile-migrate, and migra.

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Source Control and Change Management for Postgres

Published 2023-06-05 by Kevin Feasel

Ryan Booz relives an older story:

For those of you that don’t know, those ER tools were really expensive (probably still are for the ones that exist) and only a few developers had access to the tool. They didn’t have a great DX either.

Aside from the lack of automation and ability of our developers to be more integrated into the process, there was always the one looming issue that we just couldn’t reconcile.

If Joe left and joined the circus (see, I got you there), we were stuck.

We knew this was a bottleneck for some time and we had tried multiple times to change the process. Our ability to iterate on new feature development went through one person and a set of 15-year-old scripts. It didn’t match our otherwise Agile process of front-end code and data analysis projects.

Read on for Ryan’s thoughts on database change management. Some of the tools mentioned work with multiple database platforms, whereas others are specific to Postgres.

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Reusable Power BI Deployment Pipelines

Published 2023-05-23 by Kevin Feasel

Richard Swinbank re-uses a pipeline:

Implementation of one pipeline per report makes additional demands of a developer when creating a new report. To make this easier to manage, in this post I look how to make pipeline creation as simple as possible, by building each pipeline from a set of reusable components.

Click through to see how this works in Azure DevOps. I’d expect the process to be reasonably similar for GitHub Actions as well.

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Feature Branching and Hotfixes for Azure DevOps

Published 2023-05-12 by Kevin Feasel

Vytas Suopys covers a bit of source control strategy:

Have you ever deployed a release to production only to find out a bug has escaped your testing process and now users are being severely impacted? In this post, I’ll discuss how to deploy a fix from your development Synapse Workspace into a production Synapse Workspace without adversely affecting ongoing development projects.

This example uses Azure DevOps for CICD along with a Synapse extension for Azure DevOps: Synapse Workspace Deployment. In this example, I assume Synapse is already configured for source control with Azure DevOps Git and Build and Release pipelines are already defined in Azure DevOps. Instructions on how to apply this this can be found in the Azure Synapse documentation for continuous integration and delivery.

The specific example covers Synapse, though the general principle applies no matter what you’re deploying.

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Publish to Power BI Environments via ADO

Published 2023-05-10 by Kevin Feasel

Richard Swinbank deploys a report:

In the first post in this series, I built an Azure DevOps pipeline to automate steps in a Power BI development workflow. The pipeline implemented a very basic workflow – as soon as a developer committed a new report version to Git, the pipeline deployed it immediately into a Power BI workspace.

In this post I’ll be building a pipeline to support a more sophisticated workflow that enables peer review and stakeholder testing.

Click through for the step-by-step process.

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