We're thrilled to announce a native integration with ilert, combining Honeybadger's full-stack application monitoring with ilert's real-time alert routing and on-call management platform. ilert handles alert routing, escalations, and on-call scheduling, ensuring critical issues always reach the right person at the right time.

The Domain Name System (DNS) is often described as the address book of the Internet. A and AAAA records map a human-friendly hostname like honeybadger.io to some machine-friendly IP address like 104.198.14.52. Other types of DNS records also exist; in particular, CNAME records are records that map a hostname to some other hostname, thereby delegating IP resolution to the latter.

Great news, Laravel friends! You can now monitor the performance of your Laravel apps with Honeybadger. Yes, you read that right: Laravel performance monitoring in Honeybadger! Many of you have asked for this, and we're excited to tell you about it. Earlier this year, we launched Honeybadger Insights, a new logging and performance monitoring tool bundled with Honeybadger.

In web application development, server-side logging is an important concept to get right. Great server logging helps developers quickly fix bugs and tends to enhance an application's overall reliability. This contributes to application observability, something that software teams are often working to improve. JavaScript logging is a crucial component of modern web application development and enables developers to create more reliable and secure applications.

Git is one of the most widely used collaboration tools in Software development. Even software developers working without teams often use Git as a version control system. Most people interact with Git through the command line, but many code editors and IDEs have Git integrations with built-in tools to make your workflow easier. Though Git is widely used, many developers only have a surface-level appreciation of all that Git has to offer.

If you're like me and have less than twenty years of software engineering experience, the thought of a world without Git doesn't seem possible. When I started to research for this post, I almost fell out of my chair when I read that Git was created in 2005. It doesn't seem that long ago... either that, or I'm simply getting old. When I started programming, I asked myself a question I sometimes still ask myself today - How does git work? I often find myself being scared of certain Git commands.

Earlier this year, we introduced a new logging and performance monitoring tool, Honeybadger Insights. You can finally send your logs, application events, and telemetry data to Honeybadger! Once you do, you can query your logs and events to diagnose performance issues, perform root-cause analyses, and create beautiful charts and dashboards to see what's happening in real time.

When deploying Docker containers to AWS ECS, you can encounter a situation where you want to run an image that requires some configuration. For example, let's say you wanted to run Vector1 as a sidecar to your main application so you can ship your application's metrics to a service like Honeybadger Insights. To run Vector, you only need to provide one configuration file (/etc/vector/vector.yaml) to the image available on Docker Hub.

Oh, I didn't see you there. Hi, I'm Kevin, a developer here at Honeybadger. I've worked for the last year or so developing Honeybadger Insights, our new logging and observability platform. Let's peek into some of the design decisions and philosophy behind the product. In modern software development, the hunt for observable systems has traditionally revolved around the holy trinity of logs, metrics, and traces.

I'm pleased to announce a new feature that we've been building for over a year: Honeybadger Insights. Insights is our take on logging and performance monitoring, helping application developers gain deeper visibility into what's happening with their applications. It goes beyond application monitoring and responding to exceptions and downtime. Insights lets you drill down into the details and step back to see patterns in your data.