New Feature – Metric Deletion

Behind the scenes in Metricfire we’re constantly at work building new features and improving old ones, but a feature we’ve deliberately held back on until now is the ability to delete a metric. Our philosophy is that you should measure everything that your application does, and figure out the most useful data points later. That said, it’s human nature that mistakes will happen when creating a metric – typos in a metric name, test sites sending data you’re not interested in, or anything else that creates metrics that aren’t useful to you.

We’ve finally added an interface to quickly and easily determine which metrics are not used, and then delete them. A simple spark line chart will show whether the metric has been collecting data, and a summary screen will tell you whether it’s used on any graphs before you make a decision to remove it.

Just select “Apps and Data” from the main navigation menu and you’ll see all your applications, metrics, and a spark line of the data from each.  See our 30-day free trial and try it for yourself.



37Signals on Metrics

37signals Logo37Signals had a fantastic blog post last week detailing their internal metrics service they use for all their products. After using a larger stats package, they moved to a custom system for all of the reasons that we’ve created Metricfire:

While we still use some of those tools today, we found ourselves wanting more – more information about the distribution of timing, more control over what’s being measured, a more intuitive user interface, and more real-time access to data when something’s going wrong.


We’re pleased to see that the reasons they moved away from existing tools, and the design decisions they made in their own system are not a million miles away from our own. We’re also using stats delivery over UDP, and instant aggregations of min, max, sum, observations, standard deviation – as well as data transformations baked in which make other statistical information like moving averages available without you having to mess with code.

We started Metricfire to solve the ‘Everything in One Place’ problem where you try to get several systems designed for different purposes working together to produce a holistic service that covers the whole problem. Generally, it either doesn’t work or just takes too long and leaves you with plenty of quirks to work around. We’re taking care of the entire chain, from where you want to know how a certain part of your app is performing, right up to the point at which you wake someone up in the middle of the night.

It’s interesting to get this sort of perspective (and validation) from a company like 37Signals. Let us know how we can help you get the same sort of application monitoring for your own systems.

New Features – Data Transformations and Graph Cosmetics

We’re rolling out new features at a regular pace here at Metricfire, and we’ve just added two we’re particularly pleased with – Data Transformations and some basic graph cosmetics.

The transformations option allows you to alter each point of data from the metrics you’ve sent to us in a way that’s useful to you.

These options let you:

  • scale – Apply a coefficient of your choosing to each point
  • timeshift  – Retrieve the data for this metric from a period of time in the past (Seconds, minutes, hours, days, months)
  • derivative – Calculate the change between each value
  • integral – Add successive values together
  • movingaverage  – Calculate a moving average over a supplied time period.

For example, let’s say you’re comparing two different hypothetical metrics with vastly different ranges:

  • The bytes received per second over your network interface
  • The number of packets received per second over the same interface

At their base levels, mapping this data is not very useful – the data units are too different to make sense:

The blue line representing the packets per second has a useful relationship to the bytes received but at this resolution you’ll never know.

We add in our Scaling factor – our new interface will highlight correct syntax as you type:

Scaling the data to ranges closer to each other will give you something that will let you compare:

Well, that makes more sense...

Cosmetic enhancements

In addition to things to allow you to manipulate the data you’re sending to Metricfire, we’ve added the ability to customize the look and feel of your graph:

  • Line width and Color
  • Line vs Stacked Area Graphs
  • Display / Hide the graph legend

This can produce some attractive-looking graphs, (even if the end result in this case is only good for trolling your co-founder).