While Instrumental offers broad support and integrations for application, server, service, and custom monitoring, certain AWS data is only available within the AWS CloudWatch service. Over the past few months, we’ve been testing a deep integration with CloudWatch and are excited to release it to all users.
Like the rest of Instrumental, our CloudWatch integration is designed to be simple, configurable, and lightning-fast. Read More
We’ve updated Instrumental’s pricing to be fully metered and we replaced our 30-day trial with an entirely free Development Plan. While Instrumental’s pricing has been usage-based for a long time, this new model eliminates our plans and minimum spend requirements. With no minimum monthly spend, Instrumental is now a much better fit for smaller projects. Read More
Instrumental receives a lot of raw data, upwards of 1,000,000 metrics per second. Because of this, we’ve always used an event queue to aggregate the data before we permanently store it.
Before switching to AWS Kinesis, this aggregation was based on many processes writing to AWS Simple Queue Service (SQS) with a one-at-a-time reader that would aggregate data, then push it into another SQS queue, where multiple readers would store the data in MongoDB.
Read MoreWe’re excited to announce two improvements to Instrumental that’ll make it easier to understand the context of your application and server monitoring graphs. Read More
Instrumental is a key piece of infrastructure for many businesses, including Instrumental! We put significant effort into making sure that Instrumental customers can rely on us to be accurate, available, and consistent, but no system is perfect. There are two key components of our approach to reliability:
With that approach mind, let’s talk about what happened on the 16th of November. Read More
Confused about the price of an application and server monitoring tool? So were we! Every tool is priced differently and there are a lot of nuances. We’ll walk you through important terminology differences, the pros and cons of different plans, and then discuss the pricing details for Librato, New Relic, SignalFX, Datadog, and of course, Instrumental. Read More
A few weeks ago, our alert klaxons started blaring (alert notifications – we don’t really have klaxons, but maybe we should). We had a massive spike in failed background jobs. With the scale of data processing at Instrumental, a few minutes of background jobs is potentially hundreds of millions of data points. Read More
Today, we’re launching InstrumentalD as a major upgrade and replacement of Instrumental Tools. Since 2011, Instrumental Tools has provided a system metrics daemon and a powerful plugin framework to write custom scripts for service monitoring.
While the ability to write fully custom service monitoring in a language of your choice is an important feature (and we’re keeping the plugin framework!), InstrumentalD includes out-of-the-box service monitoring for the following:
For each service, we’ve selected the critical metrics everyone should be monitoring, and we list each metric sent in the service documentation page. Read More
Today we’re launching a big upgrade to Instrumental’s time navigation. Before, Instrumental always showed data relative to now, and graphs would always update with new data. That’s great for every-day use. But sometimes, like during incident investigation and root cause analysis, it’s really useful to look at specific start/end dates and times. Read More
Many developers analyze background job queues too simply: queues are either too full (bad) or mostly empty (good). This is a dangerous perspective, especially at scale. To get the full picture of your queue’s health, you need to measure both queue depth and job age.
Queue depth is the common metric for measuring a queue’s health. Read More