LaunchDarkly offers fast and reliable feature management for the modern enterprise.
- AWS, ALB
- Services written in Go, one especially large service
- Large collection of legacy metrics and alerts written against Graphite
LaunchDarkly’s engineering team works hard to ensure that the features they ship meet the requirements and goals of their customers. In the past, they had success using an in-house Graphite instance to collect the metrics they used to monitor customer health, but as their business grew, they found it could not keep up with the increasing volume and cardinality of the data stream. They would know something was wrong, but could not get the performance or detail they needed to find out what it was or who it was affecting.
Graphite still met their needs for monitoring some aspects of system health, but they needed something better able to dig into how their users actually experienced their service. They evaluated additional vendors but did not find the performance-to-pricing balance they were looking for, until Honeycomb.
With Honeycomb, it’s not a case of keeping huge volumes of data in storage so your costs rise and you still need to keep more. Cost is predictable; you know that you can rely on getting access to that one event or piece of raw data you need, so it’s more reliable.
What They Needed
- An observability service that allowed them to see user behaviors and feature adoption down to the individual customer level
- The ability to continue using the legacy metrics tooling their team was comfortable with while also achieving the observability needed to dig into new issues they were facing as they scaled
Honeycomb @ LaunchDarkly
Once Honeycomb was in the mix, LaunchDarkly’s engineers identified which services were causing Graphite the most pain, and adapted their data streams to send the wider, more context-rich events they needed to Honeycomb instead. As a result, their Graphite server became less oversubscribed and better able to serve their day-to-day desire for metric dashboards.
Now, with Honeycomb available, LaunchDarkly’s team is solving the problems they couldn’t before. For example, they were recently able to identify and resolve an issue related to a bug in the AWS ALB that was affecting a subset of customers that use the LaunchDarkly service in a very specific way. Once the issue was discovered, they were further able to identify which users would encounter the bug based on their usage pattern and contact that customer to pre-empt a bad experience.
Honeycomb,we would just speculate wildly about who was impacted by a given issue, or what changes would affect which customer.
At Honeycomb, our goal is to ensure you can meet your business requirements for quality of service and customer happiness. Working alongside the tools you already use to augment their capabilities is part of our strength. With Honeycomb on your side, your use case and requirements for high-cardinality queries capacity will scale up, and we’ll be there to keep you successful and growing the whole time.
Honeycomb in one word: comprehensive.
March 25, 2019
Calculating Costs for Observability
Debugging in production is a requirement for modern teams, especially for teams who ship frequently. DevOps teams need the best tools to debug issues when they come up, not just hope they can catch everything in staging. You need to make the move to next-gen APM--but how much will it cost? How much should it cost?
September 17, 2020
Progressive Delivery — Using feature flags & observability to ship confidently
Progressive delivery lets you see whether or not new changes will benefit users before they’re really released. This webinar explores how to use progressive delivery, feature flags, and observability together.