What we shipped in 2017

By Derek Bullet_white Comments Comments

In 2017, we focused our engineering time on reducing the painful, time-consuming investigation workflow that comes with fixing performance issues. We think that approach is working: we're now analyzing billions of web requests and background jobs every day.

Here's some of the highlights from 2017:

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Real User Monitoring with Raygun

By Derek Bullet_white

Most of a web page's load time is on the front-end. You can monitor the performance of the end-to-end page load time with a Real User Monitoring (RUM) service, and one of the more attractive ones is Raygun Pulse.

Let's take a deep dive.

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Python Application Monitoring: comparing New Relic and Opbeat

By Derek Bullet_white

There are several options for monitoring Python web apps (New Relic, Opbeat, AppDynamics, and DataDog to name a few). Let's take a look at two with a contrasting approach: New Relic and Opbeat. I'll focus on the 2 highly-used areas of an APM solution: the app overview and transaction details.

Sidenote: we're adding Python app monitoring to Scout. You can signup for early access.

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Introducing the Scout database monitoring addon

By Derek Bullet_white Comments Comments

Perhaps the most significant performance problem spot in web apps is the database. In apps monitored by Scout, database queries account for nearly a third of the time spent in the average Rails web request. Just as important, the more time an app spends in the database, the more volatile its response times. Here's a breakdown:

Service Layer % of Response Time Correlation to Response Time Volatility
Database 32%
0.35
Ruby 24%
0.23
HTTP calls 9%
0.06

Data is based on apps monitored by Scout averaging 50 requests per-minute or higher.
The response time correlation measures the ratio of an app's 95th response time duration to the mean response time. This value may range from -1 to 1.

Database queries deserve some extra performance love, and our database monitoring addon is here to help.

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Super-charge ActiveRecord#explain with pg-eyeballs 👀

By Derek Bullet_white Comments Comments

When I have a slow Postgres ActiveRecord query, one of the first tools I reach for is EXPLAIN. pg-eyeballs is a Ruby gem that makes acting on this frequently noisy output easier.

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Does team size impact app performance?

By Derek Bullet_white

In 2014, CodeClimate published a blog post investigating the impact of team size on code quality. I was curious: are there correlations with app performance and team sizes as well?

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