Five years ago today, Grafana Loki was introduced to the world on the KubeconNA 2018 stage when David Kaltschmidt, now a Senior Director of Engineering at Grafana Labs, clicked the button to make the Loki repo public live in front of the sold-out crowd. At the time, Loki was a prototype: We bolted together Grafana as a UI, Cortex internals, and Prometheus labels to find out if there was a need for a new open source tool to manage logs.

In the US, a recurring news topic is the state of the federal budget – and if we’ll get one signed. Government budgets have hundreds of thousands of line items; each bickered over to gain or lose political capital with one group or another. However, most government budgets aren’t up for debate. Only about 30% of the US federal budget is discretionary or flexible. Nearly two-thirds, or 63%, is mandatory spending required due to prior commitments.

Data is growing, and we are being asked to search larger and larger amounts of data. This puts larger and larger demands on Search resources. Reading all the data to find matching events is muscling through the data. Wouldn’t it be more efficient to be able to do filtering before reading the data? Cribl Search does precisely that by leveraging Parquet Pushdowns.

In this tutorial, you will learn how to collect logs using the Loki receiver in OpenTelemetry Collector to send logs to SigNoz. If you’re using Promtail to collect logs, you can send them to SigNoz instead of Loki via the OpenTelemetry Collector. In this tutorial, we cover: If you want to jump straight into implementation, start with this prerequisites section.

Traditional monitoring methods become inefficient as organizations shift from legacy software systems to complex cloud-native architectures. This transition renders these methods less effective, as they no longer provide the critical insights needed. In response, observability engineering has emerged as an important discipline, offering a more comprehensive understanding of modern software systems. This article will take you through the definition, importance, and processes of observability engineering.

Fault incidents are inevitable. They occur in any large-scale enterprise IT environment, especially when: In fact, research indicates, more than half (50%) the leaders in tech and business organizations consider the complexity of their data architecture a significant pain point. From an end-user perspective, businesses must overcome complex architecture in order to ensure service delivery and continuity.

As we reflect on AWS re:Invent 2023, the Coralogix team is invigorated by the incredible response and feedback we received from the thousands of participants who visited our booth. It was clear that a recurring theme among companies is the need for an observability solution that not only scales affordably with increasing data volumes but is also at the forefront of innovation. Coralogix stands out as the ideal match for these requirements.

In the ever-evolving world of data analysis, the ability to interact directly with live API endpoints is a significant advancement for practitioners. Cribl Search now offers this capability, enhancing your data analysis toolkit. This new feature allows you to gain broader visibility into the periphery of your infrastructure, enabling a more comprehensive analysis of user journeys and operational trends.

Engineering and ITOps teams have an important mission: keeping their software and digital systems performing and reliable. But as we’re about to embrace a new year full of changes, industry shifts, and AI developments, this mission is challenged by increasingly complex environments, technology alternatives, and an overwhelming number of tools available. The result? Overages, tool sprawl, and toil, which all lead to longer times to detect and resolve issues.