Let's start with "why". Imagine you have an operation that you'd like to perform, but before that operation is performed, some other things need to take place first. Maybe it needs to be approved by someone, maybe you need an explicit record of what method is to be executed.

Now you could build a mechanism to manually cater for each scenario that triggered a method call. But that's a lot of boilerplate code for each implementation, and given we might want to cater for many scenarios, it wouldn't scale particularly well as an approach.

So how can we take a method call, serialise it, perhaps store it in a database, and then later rehydrate and execute?

Of late, I've been involved in work to integrate APIs into LLM interactions, using Semantic Kernel. This post is something of a brain dump on the topic. Given how fast this space is moving, I expect what is written here to be out of date, possibly even before I hit publish. But nevertheless, I hope it's useful.

I've recently been working on building retrieval augmented generation (RAG) experiences into applications; building systems where large language models (LLMs) can query documents. To achieve this, we first need a strategy to chunk those documents and make them LLM-friendly. Kernel Memory, a sister project of Semantic Kernel supports this.

If you're a JavaScript developer, you've probably heard of webpack. It's a JavaScript bundler that helps you bundle your code into a single file. It's a great tool for optimizing your code and improving performance. This article will give you an overview of webpack, its history and how it works.

It'll be a little different than your typical "what is webpack?" article, in that I write this as the maintainer of ts-loader, a loader used for integrating TypeScript with webpack. I've worked in the webpack ecosystem for some years now and I'll share some of my experiences with you. I'll go through a little history around bundling, and try to understand why webpack came to be such a popular choice.

Cosmos DB is a great database for storing objects. But what if you want to store subtly different types of object in the same container? This post demonstrates how you can use generics to store and retrieve different types of object in an Azure Cosmos DB Container using C#.

I love the Material-UI (MUI) library for React. Hand on heart, I'm not very good at making UIs that are attractive. So I always grab for something to paper over the cracks. MUI is awesome for that.

One of the components that I use frequently is the tabs component. However, I've found that it can be a little tricky to use in a "text-first" way, that also remains strongly typed. This post documents how to do just that!

Generating a Word document in the context of an ASP.NET controller is quite simple to do. However, it took me a little experimentation to work out just what was required. This post documents (pun very much intended) what we need to do.

Imagine you're deploying a solution to Azure. It'll feature some resources like a database or a storage account. How do can you configure your application with access to these resources? One approach would be using Managed Identity. Another approach is configuring the connection strings and access keys in our application's configuration store as the Bicep templates are deployed. This is a common approach when working with Azure Functions, Azure Static Web Apps, Azure Container Apps and similar.

A wonderful aspect of this approach is that no human need ever get to see the connection strings / access keys. They'll be discovered and consumed by Azure during a deployment, and known to your application at runtime, but untrustworthy humans need never get to see them. This is secure, and therefore good.

I love using .env files to configure my applications. They're a great way to keep configuration in one place and to keep it out of the codebase. They're also a great way to keep secrets out of the codebase.

But what if you need to use a multiline string in a .env file? How do you do that? You just do it:

SINGLE_LINE="you know what..."
MULTI_LINE="you know what you did
LAST SUMMER"

That's right, you just use a newline character. It's that simple. Oddly, searching for that on the internet didn't yield the answer I was looking for. So I'm writing it down here for posterity.

With your .env file in place, you can then consume it in your application using a package like dotenv. Or if you'd like to use a bash script to consume the .env file, you can do it like this:

#!/usr/bin/env bash
set -a
source test.env
set +a

npm run start # or whatever you need to do

I'm a longtime user of TypeScripts noUnusedLocals and noUnusedParameters settings. I like to avoid leaving unused variables in my code; these compiler options help me do that.

I use ESLint alongside TypeScript. The no-unused-vars rule provides similar functionality to TypeScripts noUnusedLocals and noUnusedParameters settings, but has more power and more flexibility. For instance, no-unused-vars can catch unused error variables; TypeScript's noUnusedLocals and noUnusedParameters cannot.

One thing that I missed when switching to the ESLint option is that, with noUnusedLocals and noUnusedParameters, you can simply ignore unused variables by prefixing a variable with the _ character. That's right, sometimes I want to declare a variable that I know I'm not going to use, and I want to do that without getting shouted at by the linter.

It turns out you can get ESLint to respect the TypeScript default of ignoring variables prefixed with _; it's just not the default configuration for no-unused-vars. But with a little configuration we can have it. This post is a quick guide to how to implement that configuration.

I'm a keen user of Bun. Bun is a fast TypeScript / JavaScript runtime which can be used to speed up the TypeScript / JavaScript you have. It's a drop-in replacement for Node.js, and it's compatible with the vast majority of the Node.js ecosystem. (There are still rough edges that have issues.) In this post we'll look at how to use it in Azure Pipelines.

Bicep has had linting since version 0.4.1. It's a great way to ensure that your bicep files conform to best practices. Interestingly, when the linting feature first shipped, there wasn't an explicit lint command as part of the CLI. Instead, you had to run bicep build and it would run the linter as part of the build process. This was a little confusing as it was not obvious that the linter was running.

As of version 0.21.1 there is a dedicated bicep lint command. This is a nice step forwards; it allows you to explicitly lint your your code, rather than have it happen as a side effect of build. And it is useful if you want to run the linter as part of a CI/CD pipeline. What's more the bicep lint command is now available in the Azure CLI as well. You can run az bicep lint to lint your bicep files.

In this post we'll look at how to run lint Bicep in Azure Pipelines and GitHub Actions, and surface the output in the UI.

Of late, I've found myself getting more and more into structured data. Structured data is a way of adding machine-readable information to web pages. To entertain myself, I liken it to static typing for websites. I've written about structured data before, but in this post I want to focus on how to validate structured data.

Specifically, how can we validate structured data in the context of a GitHub workflow? I've created a GitHub Action called Schemar that facilitates just that. In this post we'll see how to use it.

Writing tests is important. The easier it is to write tests, the more likely they'll be written. I've long loved snapshot testing for this reason. Snapshot testing takes away the need to manually write verification code in your tests. Instead, you write tests that compare the output of a call to your method with JSON serialised output you've generated on a previous occasion. This approach takes less time to write, less time to maintain, and the solid readability of JSON makes it more likely you'll pick up on bugs. It's so much easier to scan JSON than it is a list of assertions.

Loving snapshot testing as I do, I want to show you how to write high quality and low effort log assertions using snapshot testing. The behaviour of logging code is really important; it's this that we tend to rely upon when debugging production issues. But how do you test logging code? Well, you could write a bunch of assertions that check how your logger is used. But that's a lot of work, it's not super readable and it's not fun. (Always remember: if it's not fun, you're doing it wrong.)

Instead, we'll achieve this using snapshot testing.

Like Node.js and Deno, Bun is a JavaScript runtime that provides a faster development experience while you’re building frontend applications. It’s gaining ground as a competitor to these widely used runtime environments — and for good reason.

In this evaluation guide, we’ll explore the features that make Bun an excellent choice for developing fast, performant, error-free frontend apps. By the end of this article, you’ll have a clear understanding of when and why you should use Bun in your projects.

We might also call this:

I ruined my SEO and a stranger from Hacker News help me fix it​

This is a follow up to my "How I ruined my SEO" post. That was about how my site stopped ranking in Google's search results around October 2022. This post is about how Growtika and I worked together to fix it.

As we'll see, the art of SEO (Search Engine Optimisation) is a mysterious one. We made a number of changes that we believe helped. All told, my site spent about a year out in the cold - barely surfacing in search results. But in October 2023 it started ranking again. And it's been ranking ever since.

I put that down to the assistance rendered by Growtika. What was the nature of that assistance? I'll tell you. This post is a biggie; so buckle up!

The Graph API is a great way to get information about users in Azure Active Directory. I recently needed to get the names and ids of the Active Directory groups that a user was a member of. Here's how to do it with the C# SDK.

I'm writing this post as, whilst it ends up being a relatively small amount of code and configuration required, if you don't know what that is, you can end up somewhat stuck. This should hopefully unstick you.

There's a new programming model available for Node.js Azure Functions known as v4. There's documentation out there for how to migrate JavaScript Azure Functions from v3 to v4, but at the time of writing, TypeScript wasn't covered.

This post fills in the gaps for a TypeScript Azure Function. It's probably worth mentioning that my blog is an Azure Static Web App with a TypeScript Node.js Azure Functions back end. So, this post is based on my experience migrating my blog to v4.

If you're looking into a Production issue with your Azure Static Web App, you'll want to be able to get to your logs as fast as possible. You can do this by linking your Static Web App to an Azure Application Insights instance. If you've used the Azure Portal to create your Static Web App, the setup phase will likely have done this for you already. But if you're using Bicep to create your Static Web App, you'll need to do this yourself.

This post will show you how to do that using Bicep.

Docusaurus v3 is on the way. One of the big changes that is coming with Docusaurus 3 is MDX 3. My blog has been built with Docusaurus 2 and I have a number of rehype plugins that I use to improve the experience of the blog. These include:

• a plugin to improve Core Web Vitals with fetchpriority / lazy loading
• a plugin to serving Docusaurus images with Cloudinary

I wanted to migrate these plugins to Docusaurus 3. This post is about how I did that - and if you've got a rehype plugin it could probably provide some guidance on the changes you'd need to make.