The massive proliferation of log data forces teams to manage the costs to process, route, and store it. Teams need access to this data to gain critical insights into their services, but for many organizations this presents a challenge for their budget. Logging can get expensive, fast, which often results in teams making difficult tradeoffs between aggregating enough logging information to be useful and controlling the cost of storing all those logs.

Unsurprisingly, application crashes due to fatal errors can be a major pain point for iOS users. Recent research shows that roughly 20 percent of mobile application uninstalls were due to crashes or other code errors. As a developer, it’s paramount to manage this potential churn by capturing comprehensive crash data in order to track, triage, and debug recurring issues in your iOS apps.

Apache Cassandra is a distributed database known for its high availability, fault tolerance, and near-linear scaling. It was initially developed by Facebook, but it is a widely used open-source system used by the largest tech companies in the world. There are numerous reasons behind its popularity, including no single point of failure, exceptional horizontal scaling with a data layout designed as a perfect fit for time-series data.

In the first four parts of our series on correlation analysis, we discussed the importance of this capability in root cause analysis in a number of business use cases, and then specifically in the context of promotional marketing, telco and algorithmic trading. In this blog we walk through how to leverage correlation analysis to address the challenges in ensuring a seamless online payment experience by the end-user.

Ever since the very beginning, Honeycomb has poured a lot of heart and soul into our blog. We take pride in knowing it isn’t just your typical stream of feature updates and marketing promotions, but rather real, meaty pieces of technical depth, practical how-to guides, highly detailed retrospectives, and techno-philosophical pieces. One of my favorite things is when people who aren’t customers tell me how much they love our blog.