NodeSource Unveils N|Solid v1.2

Date 2016/1/19 10:04:08 | Topic: Product News

NodeSource has announced an update to N|Solid providing increased visibility into Node.js applications running at scale. Monitoring Node.js applications is straightforward when managing a small number of processes across a few hosts, but can become unwieldy in larger environments. At the same time, simple command-line tools and graphs aren’t optimal for finding performance outliers, or drilling down to find relevant data in environments with hundreds of processes and hosts.

 addressing enterprise requirements for running and monitoring Node.js at scale

Latest release complements existing APM solutions, adds flexible tagging, filtering and StatsD integration for more granular, high-frequency views
January 13, 2016 09:00 AM Eastern Standard Time
N|Solid v1.2 complements existing enterprise application performance monitoring (APM) solutions, providing granular, high-frequency views of Node application as well as the underlying runtime and host. Users can assign multiple user-defined tags to every process, which then can be used as filters in the N|Solid Console Cluster view to help triage performance issues. Users can also tag processes with additional identifiers relating to an application’s role, hosting environment, development or production area, or any attribute that might aid with rapid identification.

In addition, processes can be filtered by hostname, process title and process ID (PID) to easily create a subset of processes from a much larger environment, greatly shortening process selection time. A unique Cluster view provides a live scatterplot of CPU and memory utilization across application services, enabling visual identification of individual process outliers. Once identified, application profile data is only a few clicks away.

Broad availability of metrics and ease of access is critical for managing production environments. N|Solid v1.2 adds StatsD integration that makes it simple to surface N|Solid process and system metrics into existing monitoring dashboards, and report on all applications and processes. No individual process configuration is required. This provides deeper context for teams managing large environments with less effort. Metrics are easily reported for all applications and processes through an aggregated connection. 



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