The latest News and Information on Log Management, Log Analytics and related technologies.
Red Hat is a Linux distribution known for its stability, security, and enterprise-grade features. Whether you’re running Red Hat on bare metal servers or virtual machines, monitoring the performance of your infrastructure is essential. In this article, we’ll explore the top performance monitoring tools for Red Hat servers. We’ll compare their pros, cons, and pricing to help you make an informed decision.
Many of us remember the public service announcements asking parents if they knew where their kids were at night. They were ominous and a little alarming. Asking yourself the same question about your data can be equally as scary, but Cribl Edge can help.
We’re thrilled to announce new feature updates for Logz.io’s Kubernetes 360 to provide deeper visibility and additional troubleshooting capabilities for your Kubernetes environment.
In the face of growing security threats and incidents, businesses must prioritize their ability to detect, investigate, and respond effectively. Timely incident response is crucial for maintaining the security and integrity of systems and data. Among the essential tools in the incident response arsenal, log monitoring stands out as a critical component. By closely analyzing logs, organizations gain valuable insights into system events, user activities, and network traffic.
Elasticsearch® recently released time series data streams for metrics. This not only provides better metrics support in Elastic Observability, but it also helps reduce storage costs. We discussed this in a previous blog. In this blog, we dive into how to enable and use time series data streams by reviewing what a time series metrics document is and the mapping used for enabling time series. In particular, we will showcase this by using Elastic Observability’s Nginx integration.
Python is a highly skilled language with a large developer community, which is essential in data science, machine learning, embedded applications, and back-end web and cloud applications. And logging is critical to understanding software behavior in Python. Once logs are in place, log monitoring can be utilized to make sense of what is happening in the software. Python includes several logging libraries that create and direct logs to their assigned targets.
The Elastic APM Java Agent automatically tracks many metrics, including those that are generated through Micrometer or the OpenTelemetry Metrics API. So if your application (or the libraries it includes) already exposes metrics from one of those APIs, installing the Elastic APM Java Agent is the only step required to capture them. You'll be able to visualize and configure thresholds, alerts, and anomaly detection — and anything else you want to use them for!
