4 posts tagged with "Grafana"

As Parseable deployments in the wild are handling larger and larger volumes of logs, we needed a way to enable users to monitor their Parseable instances.

Typically this would mean setting up Prometheus to capture Parseable ingest and query node metrics and visualize those metrics on a Grafana dashboard. We added Prometheus metrics support in Parseable to enable this use case.

But we wanted a simpler, self-contained approach that allows users to monitor their Parseable instances without needing to set up Prometheus.

This led us to figuring out a way to store Parseable server's internal metrics in a special log stream called pmeta. This stream keeps track of important information about all of the ingestors in the cluster. This includes information like the URL of the ingestor, Commit id of that ingestor, number of events processed by the ingestor, and staging file location and size.

Behavioral data analysis examines detailed user activity logs to understand customer behavior on a website. Companies that utilize this tactic have a competitive advantage in their industry.

This article will explore how to analyze clickstream data generated from an eCommerce portal and use it to understand user preferences visitor traffic session information and more by building a report and dashboard using Parseable and Grafana.

Logs are critical components of an application. They help maintain system reliability, performance and most of the time also help understand user behaviors, uncover patterns in customer actions and much more. Problem however in managing logs is manifold - missing structure, ad-hoc formats and the sheer volumes making it difficult to manage and analyze.

OpenTelemetry (aka OTEL) is a community initiative to help standardize collection, querying and visualization of logs, traces and metrics. With a well defined standard for logs, users can choose the log processing system that best fits their needs.

In our previous post Get started with eBPF log analytics in your Kubernetes cluster, we saw how to ingest Tetragon logs in Parsable and generate alerts when a sensitive file like /etc/passwd is accessed by an unauthorized pod. However, it is time-consuming and generally difficult to work with large volume of raw logs. Visualizing logs in a dashboard helps better identify patterns.

This post is a continuation of the previous post. In this post, we will see how to visualize the eBPF logs in Grafana.