Operations | Monitoring | ITSM | DevOps | Cloud

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.

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.

For extremely high throughput web applications, it is important to load balance the traffic across multiple servers. However, load balancing the traffic alone is not enough at times. The reverse proxy server that handles the workload needs to be performant, too. In our previous article, we discussed the NGINX reverse proxy server and understood how to monitor it. In this article, we set up monitoring for an even more performant reverse proxy server - HAProxy.

As applications in the cloud become more distributed and complex, the Mean Time To Resolution (MTTR) for production issues is getting longer. Modern systems are built with hundreds of distinct, ephemeral, and interconnected cloud components, which can make it exceptionally hard for engineers to understand the current state of their applications, what problems are impacting customers, and why those problems are occurring.

Years before founding Logz.io, I was a software engineer, working with various tools to ensure my products and services performed correctly. There were few tools I dreaded using more than application performance management (APM), and I know that I’m not alone. I hated traditional APM. It’s heavy. It’s hard to implement. It’s expensive. It takes a very long time to derive business value.

Last week, I attended the Amazon Web Services (AWS) re:Invent conference in Las Vegas, NV, with 50,000+ others. It was quite a busy week with several keynotes, announcements, and many sessions. While the hot topic at re:Invent was generative AI, I’ll focus my blog post on a few customer sessions I attended around observability: Stripe, Capital One, and McDonald’s. ‍