Operations | Monitoring | ITSM | DevOps | Cloud

Mobile apps are a little different from services run on servers. You build your mobile app, you ship it off to the world, and then it gets run by the end user on their own machine. If your app is running poorly on some percentage of users’ devices, you may never know. That’s where observability comes in. There are certain important metrics that every mobile app has in common.

The last few months have been wild. Some of the busiest of my life, actually: For context: I’m Canadian, and all of this happened during the continued threats of annexation. All this to say, it’s been rough. I anticipated this would be a challenging time and that I would be exhausted. So, the plan became: do all the demanding things, take my sabbatical in May, and use April as an ‘in-between’ period with a bit less pressure.

There are many vendors, Honeycomb included, where actions on the application can emit a web request that goes to another service for coordination or tracking purposes. Many vendors have pre-built integrations, but some have a fallback that says “Custom Webhook” or similar. If you’re looking to create a full picture of your request flow, you would want these other services to show up in your trace waterfall.

I want to know what users are doing in my application. A distributed trace is the best way to show the data flow of one user interaction through my application, but it isn’t sufficient to show the overall user experience.

The HTTP Content-Security-Policy response header is used to control how the browser is allowed to load various content types. It is used to control which URLs, fonts, images, scripts, and more can be loaded onto the page. It’s a great defense against XSS (cross-site scripting), clickjacking, and cross-site vulnerabilities. The header can also specify a URL that will be used to send reports on violations of these properties.

Kubernetes is widely used for deploying, scaling, and managing systems and applications and is an industry standard for container orchestration. Google engineers originally developed Kubernetes as an open-source project. Its first release was in September 2014, and since then, it has matured into a graduate project maintained by the Cloud Native Computing Foundation (CNCF). With the complexities of scale and distributed systems, debugging in Kubernetes environments can be difficult.

Using server-side telemetry to understand what’s going on inside your system is incredibly valuable, but what about the responsiveness the user actually sees? In this post, I’ll cover what synthetic monitoring is and show an example of how you can create a simple monitor using OpenTelemetry, .NET, and an Azure function. If you only want to see how it’s built, skip ahead to building a synthetic monitor.