Operations | Monitoring | ITSM | DevOps | Cloud

Change is the only constant in the IT landscape. These changes might involve adding new observability tools, retiring existing monitoring systems, establishing new business units, or integrating IT systems from acquisitions. Managing these changes can challenge even expert ITOps teams. Organizing your monitoring setup can seem overwhelming, especially with issues like monitoring gaps, observability redundancy, complex toolsets, or significant technical debt.

As organizations move their application workloads to the cloud, understanding the difference between cloud observability vs monitoring is crucial to ensure optimal performance and seamless operations. While both concepts are often mentioned in tandem, they serve different purposes, and mastering each can help organizations thrive in increasingly complex cloud environments.

It’s no secret that many businesses rely heavily on Amazon Web Services (AWS) for their infrastructure and application needs. While AWS offers scalability, flexibility, and reliability, managing and monitoring cloud resources can be challenging. That’s where AWS monitoring and observability can be a tremendous asset. Today, we will explore how implementing these practices is crucial for ensuring that your cloud environment operates smoothly, efficiently, and securely.

As our software complexity increases, so does our telemetry—and as our telemetry increases, it needs more and more tweaking en route to its final destination. You’ve likely needed to change an attribute, parse a log body, or touch up a metric before it landed in your backend of choice. At Honeycomb, we think the OpenTelemetry Collector is the perfect tool to handle data transformation in flight. The Collector can receive data, process it, and then export it wherever it needs to go.

Real user monitoring (RUM) tools are great if you want to give your developers a very high level view of the health of your frontend. But when it comes to actually debugging issues in your web app, you’re often left piecing together outputs from browser devtools, with details (if you’re lucky) from customer support tickets to replicate issues locally in hopes of identifying the source of the issue. Debugging Core Web Vitals (CWVs) to improve your scores can be even worse.

Log analysis tools are essential for organizations of all sizes. This guide provides an in-depth analysis of the top 10 log analysis tools in 2024. It compares their features, pricing models, and integration capabilities to assist you in making an informed decision based on your specific requirements.

Interaction to Next Paint is the newest of Google’s Core Web Vitals. The three metrics that make up the CWVs are Google’s attempt at defining proxy metrics for measuring things they believe are critical to a good user experience on the web. The three metrics are: Debugging and fixing these metrics can be quite complicated. In this post, I’m going to walk through how you can use Honeycomb for Frontend Observability to debug INP, which was just promoted to a stable Core Web Vital in March.

There are a lot of factors that go into choosing an observability solution. And even after all that careful consideration, sometimes the platform you initially invest in doesn’t meet your needs, especially as your organization grows and evolves. For that very reason, we’ve seen users begin their observability journeys with another tool, and then decide to migrate to Grafana Cloud, our fully managed cloud-hosted observability platform.