Operations | Monitoring | ITSM | DevOps | Cloud

Calculating log analytics ROI is often complicated. For many teams, this technology can be a cost center. Depending on your platform, the cost of a log management solution can quickly add up. For example, many organizations use solutions like the ELK stack because the initial startup costs are low. Yet, over time, costs can creep up for many reasons, including the volume of data collected and ingested per day, required retention periods, and the associated personnel needed to manage the deployment.

While OpenTelemetry (OTel) supports a wide variety of data sources and is constantly evolving to add more, there are still many data sources for which no receiver exists. Thankfully, OTel contains receivers that accept raw data over a TCP or UDP connection. This blog unveils how to leverage Linux Command Line Interface (CLI) tools, creating efficient data pipelines for ingestion through OTel's TCP receiver.

Node.js was introduced over 20 years ago and remains a popular choice for web application teams with over 30 million users. Sites such as Netflix, PayPal, and Uber continue to rely on Node.js to build and maintain their applications.

In the dynamic world of container orchestration, Kubernetes stands out as the undisputed champion, empowering organizations to scale and deploy applications seamlessly. Yet, as the deployment scope increases, so do the associated Kubernetes workload costs, and the need for effective resource capacity planning becomes more critical than ever. When dealing with containers and Kubernetes you can find yourself facing multiple challenges that can affect your cluster stability and your business performance.

Welcome to the next chapter of Grafana Loki! After five years of dedicated development, countless hours of refining, and the support of an incredible community, we are thrilled to announce that Grafana Loki 3.0 is now generally available. The journey from 2.0 to 3.0 saw a lot of impressive changes to Loki. Loki is now more performant, and it’s capable of handling larger scales — all while remaining true to its roots of efficiency and simplicity.