In part 1, we looked at how the design plan of traditional monitoring technologies depended heavily on properties of the systems that were intended to monitor and then showed how those properties began to be undermined by an increase in complexity, an increase which can ultimately be captured by the concept of entropy. In this part, we will explore how increased entropy forces us to rethink what is required for monitoring.

In the rapidly evolving world of Large Language Models (LLMs), ensuring peak performance and reliability is more critical than ever. This is where the concept of 'LLM Observability' comes into play. It's not just about monitoring outputs; it's about gaining deep insights into the internal workings of these complex systems.

Kubernetes is a top container orchestration platform. The Kubernetes clusters manage everything much from collecting to storing vast magnitudes of data from your multiple applications. It is this very property that can sometimes boom into an unending data pile later on. Imagine a large warehouse of apparel, it has every size of clothing for men, women, and children. Now if you are asked to pick out one particular type from it within a small time frame, I know you will totally dread it.

Welcome to the last SigNal of 2023! 12 months of building and shipping things to make open-source observability available to teams of all sizes. What a great journey it has been for Team SigNoz in the year 2023. We crossed some great milestones - raised $6.5MN to supercharge our growth, more than 15,000 Github stars, and 8.6 million Docker downloads. And the best part of our journey has been building with our community.

Monitoring and observing application performance is a cornerstone for maintaining robust and efficient systems in the ever-evolving development landscape. One key player in this domain is OpenTelemetry. This post provides a comprehensive tutorial and unpacks what OpenTelemetry is, its applications and integration into the JavaScript ecosystem.

Using OpenTelemetry Collector, you can collect metrics from Azure monitor and export them to any backend of your choice. Azure Monitor is a powerful service within the Microsoft Azure ecosystem that provides extensive metrics and logging capabilities. Yet the siloed nature of data in such tools can obscure the bigger picture, hindering a holistic view of system health. In this tutorial, we cover: If you want to jump straight into implementation, start with this Prerequisites section.

Distributed tracing is the functionality to trace requests or messages flowing through different systems or environments like frontend, Backend, middleware. Distributed tracing brings connectivity or visibility of various services using a unique identifier. This identifier is passed to different services to correlate them as a single flow. We track data from different services with distributed tracing, but how do we visualize them? Visualization is a tedious task.

Events in Kubernetes are objects that provide insights into the state changes within the Kubernetes cluster. Kubernetes events monitoring is critical to provide real-time insights into the operational state of a Kubernetes cluster. It enables administrators to quickly identify and respond to issues, optimize resource allocation, and ensure the smooth and efficient functioning of their containerized applications.

OpenTelemetry can be used to monitor ECS clusters. In this tutorial, you will install OpenTelemetry Collector to collect ECS metrics and then send the collected data to SigNoz for monitoring and visualization. In this tutorial, we cover: If you want to jump straight into implementation, start with this Pre-requisites section.

Just in time for your holiday viewing! Learn how to solve real-time time series processing challenges with Quix—the stream processing framework using Kafka and Python—and purpose-built time series database InfluxDB.