Last month we talked about the PHP monitoring landscape in 2019 and announced that Scout APM would soon be available for monitoring your Laravel applications too (as well as your Ruby, Python and Elixir apps of course!). Now that our PHP monitoring agent is ready for beta testing, we thought it would be a good idea to show you folks how easy it is to get started with it and to highlight the main features to the Laravel community.

We are happy to announce that Scout now integrates with the popular error monitoring solution, Honeybadger. This integration brings a similar feature set to our existing Rollbar, Sentry and Bugsnag integrations, and it allows you to see your errors and exceptions alongside your performance metrics all on a single page. So let’s take this opportunity to take a closer look at Honeybadger and see how you can get it setup within Scout in just a few minutes!

One of the joys of using the Ruby language is the many different ways that you can solve the same problem, it’s a very expressive language with a rich set of libraries. But how do we know which is the best, most efficient, use of the language? When we are talking about algorithms which are critical to the performance of your application, understanding the most efficient approach to take is essential. Perhaps you’ve been using Scout to hunt down issues, and now that you have found an issue, you want to optimize it. Ruby’s Benchmark module provides a very handy way for you to compare and contrast possible optimizations, and when used in conjunction with a good APM solution it will ensure that you have all bases covered. Let’s take a look at how you can get started with it today!

Some members of the Tokyo Scout team travelled to Taipei last week to take part in RubyConf Taiwan. It was the first time that Scout has sponsored this event, so we were very excited to be invited to take part! During the conference we had the opportunity to speak with many interesting developers from all over Taiwan and Asia. It was a fantastic opportunity to show Scout in a new environment and to make connections with Ruby developers from all across Asia.

You might be familiar with Linux load averages already. Load averages are the three numbers shown with the uptime and top commands - they look like this: load average: 0.09, 0.05, 0.01 Most people have an inkling of what the load averages mean: the three numbers represent averages over progressively ...

There is no doubt that looking at response times and memory usage is essential to understanding the general health and performance of your application. But as I am sure you are aware, there is more than one way to monitor an application. Approaching monitoring from a different angle can be a powerful way of gaining new insights. If all you did was watch for high response times or areas of memory bloat, then you might overlook something far more simple: the user’s general level of satisfaction. So how can we monitor this rather broad concept of user satisfaction? Well, we can monitor this with a rather useful metric known as the Apdex score...

Some of the Scout members travelled from Tokyo to Ireland via boats and trains… and no planes! On day 18 of the 20 day adventure, we had our first London drink-up! We hosted the event at Guy Ritchie's old pub called The Punchbowl.

With the official release of Rails 6 just around the corner, we round up all the major new features coming your way. It is an exciting release due to some big features coming upstream from the Basecamp and GitHub projects. Amongst the many minor updates, useful tweaks and bug fixes, Rails 6 will ship with two completely new frameworks: ActionText and ActionMailbox, and two big scalable-by-default features: parallel testing and multiple database support. So set your Gemfile to get Rails 6.0.0.rc1 and let’s get started!

The Ruby app server ecosystem has consolidated around three app servers: Unicorn , Puma , and Passenger 5 . What specific problems must an app server solve for Ruby? How do you pick the right app server? Is there a need for each of these app servers in ...

Optimizing performance in Python What does "Optimizing" code mean anyway? The term "optimization" can apply to a broad level of metrics. But two general metrics of most interest are; CPU performance (execution time) and memory footprint. For this post, you can think of an optimized code as the one which ...