Operations | Monitoring | ITSM | DevOps | Cloud

JFrog’s new log analytics integration with New Relic brings together powerful observability capabilities to monitor, analyze, and visualize logs and metrics from self-hosted JFrog environments. The integration is free for all tiers of self-hosted JFrog customers and utilizes the powerful, open source log management tool, Fluentd, to collect, process, and surface data in New Relic dashboards.

In software observability, we often talk about three signal types - metrics, logs, and distributed traces. More recently I've been hearing about profiles as another signal type. In this article I will explain the different observability signals and when to use them in a clear and concise way.

This is the final blog of a three-part blog series on Observability—the challenges and the solutions.

Observability is a critical step for digital transformation and cloud journeys. Any enterprise building applications and delivering them to customers is on the hook to keep those applications running smoothly to ensure seamless digital experiences. To gain visibility into a system’s health and performance, there is no real alternative to observability. The stakes are high for getting observability right — poor digital experiences can damage reputations and prevent revenue generation.

It’s been a minute since our last Feature Focus, and we have a bit of catching up to do! I’m happy to report we’ll resume monthly updates next month, but until then, please enjoy this super-sized winter digest of what we’ve been up to at Honeycomb.

Today’s enterprises must have the capability to cope with the growing volumes of observability data, including metrics, logs, and traces. This data is a critical asset for IT operations, site reliability engineers (SREs), and security teams that are responsible for maintaining the performance and protection of data and infrastructure. As systems become more complex, the ability to effectively manage and analyze observability data becomes increasingly important.

I'm no stranger to ranting about deploys. But there's one thing I haven't sufficiently ranted about yet, which is this: Deploying software is a terrible, horrible, no good, very bad way to go about the process of changing user-facing code. It sucks even if you have excellent, fast, fully automated deploys (which most of you do not). Relying on deploys to change user experience is a problem because it fundamentally confuses and scrambles up two very different actions: Deploys and releases.