Visualize Data Your Way, with Intelligence Dashboards Built for Your Stack

When something goes wrong in production, you do not want to spend the first five minutes rearranging charts. You want the error rate, throughput, queue depth, memory, and view metrics that show when customers are having issues while using your app.

What slows you down is not always missing data. Often, it is having the right data in the wrong shape at the wrong moment. AppSignal fixes that in two ways: you can reshape the dashboards you already use, and when it recognizes metrics from supported parts of your stack, it generates Intelligence dashboards for them. That means you start with views built around what AppSignal detected, such as Active Job, Action Mailer, Puma, NGINX, or AWS, so the right signals are easier to scan when something changes.

Arrange the dashboard around your investigation

In Edit dashboard, the layout is yours to change, and what you save is there the next time you investigate.

See what changed after a deploy

Deploy markers show where a new revision took over. Each marker carries the deploy time and the revision, so you can compare a chart from before and after a release. When errors rise or throughput shifts, that context helps you see faster whether the change is noise, a regression, or the start of a real incident.

Intelligence dashboards give you a head start

AppSignal automatically creates Intelligence dashboards when it detects metrics from a supported integration. They appear in Dashboards labeled Intelligence, with pre-built charts for the metrics that matter most.

That matters because a useful dashboard is often less about charting power and more about getting to a sensible first view quickly. Intelligence dashboards are designed around common operational questions: is anything broken, what is under pressure, and what changed? Health and error indicators come first, followed by resource utilization, then operational context. In a Ruby app, for example, AppSignal can generate Intelligence dashboards for Active Job and Action Mailer, so if background jobs slow down or email delivery starts misbehaving, you already have a dashboard tailored to that part of the system.

AppSignal maintains the charts, layout, and descriptions on these dashboards unless you customize them. Each chart description explains what the value means and what to look at next, so you do not have to translate raw metrics before you can act.

If you have already customized one of these dashboards, AppSignal does not hide that decision from you. When a newer version of the dashboard is available, AppSignal says so and lets you decide what to do next.

Intelligence dashboards cover a wide range of systems

Intelligence dashboards already cover a broad set of systems, including AWS; Ruby dashboards for Sidekiq, Active Job, Action Mailer, and more; Elixir integrations; infrastructure like NGINX and Kubernetes; and platforms like Heroku, Render, and Vercel Speed Insights.

For the full list, including every AWS service-specific dashboard, see the Intelligence dashboards docs and AWS Intelligence dashboards docs.

Apdex tells you when your app's users feel the slowdown

You can have perfect-looking infrastructure charts and still ship a frustrating experience. That is where Apdex helps.

Apdex, short for Application Performance Index, turns response times into a score between 0 and 1 for each namespace in your app. You decide what counts as satisfied and tolerating response times. AppSignal charts the score, counts, throughput, and response times together on the Apdex page.

That makes it easier to answer a question dashboards alone do not always answer quickly: “Are users merely seeing a slower system, or are they now feeling a degraded experience?”

You do not have to set those thresholds blindly. AppSignal shows recent response times, so you can set them against traffic you already have.

Once you configure Apdex for a namespace, AppSignal reports apdex and apdex_counts as metrics. You can use them on your own dashboards, use them in anomaly detection triggers, and read them alongside throughput and response time on the Apdex page itself. If you want the setup details, see the Apdex docs.

Your own metrics belong here too

Dashboards are not only for infrastructure. Custom metrics let you track business and application signals in the same place as your operational ones.

That could be webshop error count, error rate, checkout successes, checkout queue depth, or the runtime of a background job that starts drifting before customers complain. AppSignal supports three metric types:

• Gauge for a current value that changes over time.
• Measurement for durations and distributions.
• Counter for how often something happened.

A Number chart, also called a Big Number, is useful when you want one value at a glance, like your current error count or error rate. A line graph helps when you want to watch something like checkout successes move through the day. If you want more detail on chart types, value formatting, or missing data, see the dashboards documentation.

Build dashboards from the terminal or with an AI tool

You, or an agent working on your behalf, can manage dashboards without opening the UI:

• appsignal-cli dashboards lists your dashboards, creates a new one, and updates it later, without opening another browser tab.
• AppSignal MCP lets an AI tool create a dashboard and add charts to it, either line and area graphs or Big Number tiles, built from the metrics already flowing into your app.
• The GraphQL API can import a whole dashboard from a JSON definition, which is useful when you want dashboard definitions closer to code.

This matters because dashboards are no longer only something you assemble by hand. You can shape them in the UI, script parts of your workflow in the terminal, or let an AI tool draft the first version from a prompt and then refine it with your team.

Better dashboards mean faster decisions

If you already use AppSignal, open a dashboard and arrange it around the way your team actually investigates. If you are new to AppSignal, start a free trial and see how far the Intelligence dashboards can get you before you change anything.

Related reading

• Log-Based Metrics, Now in AppSignal Labs covers how to turn a log query into a metric you can put on any dashboard.
• Building a CloudWatch Metrics Pipeline: Parsing OpenTelemetry Data is the story behind the AWS Intelligence dashboards.
• AppSignal MCP Server: Get Started in Your IDE walks through setting up the MCP server that can build dashboards for you.
• Triage Production Incidents with a Single Prompt Using the AppSignal CLI wraps the same CLI, dashboard commands included, in an agent skill.