Operations | Monitoring | ITSM | DevOps | Cloud

Data has become the most valuable thing in the modern world. According to earthweb, more than 2.5 quintillion bytes of data will be created every day in 2022. These large quantities of data should be appropriately organized to identify meaningful patterns for decision-making. Techniques like clustering are widely used to efficiently collect data into groups based on their similarities and differences and improve the observability of your data.

The line from observability to customer joy is straighter than you think. We recently learned this from NS1, a managed DNS provider and Honeycomb customer, in a panel discussion with Nate Daly, Head of Architecture at NS1 and Chris Bertinato, Software Architect at NS1.

In recent years, there has been a rapid expansion in the API market. Today, every piece of software is either an API or uses one. They are now a crucial component of the modern digital economy. As a result, it is becoming increasingly important to grasp how to examine them carefully. In this article, we'll discuss the definitions of API observability and API monitoring as well as how API observability is better than API monitoring.

Everyday when you come into work, you’re bombarded with a constant stream of problems. From service desk calls to network performance monitoring, you’re busy from the moment you login until the moment you click the “shut down” option on your device. Even more frustrating, your IT environment consists of an ever-expanding set of network segments, applications, devices, users, and databases across on-premises and cloud locations.

The growing popularity of serverless architectures has led to an increased need for solutions to the modern challenges of microservice observability—one of the most critical components for running high-performing, secure, and resilient serverless applications. Observability solutions have to break through the complexity of serverless systems, and with the right stack, observability enables not only fast and easy debugging of applications, but drives optimization and cost efficiency.

To help our customers reduce their overall observability costs, we’re excited to announce the Data Optimization Hub as part of our Open 360™ platform. The new hub inventories all of your incoming telemetry data, while providing simple filters to remove any data you don’t need. Gone are the days of paying for observability data you never use.

Bugs can remain dormant in a system for a long time, until they suddenly manifest themselves in weird and unexpected ways. The deeper in the stack they are, the more surprising they tend to be. One such bug reared its head within our columnar datastore in May this year, but had been present for more than two years before detection.

Observability is the ability to see and understand the internal state of a system from its external outputs. Logs, Metrics, and Traces, collectively called observability data, are external outputs widely considered to be three pillars of observability.