As digital applications and infrastructures grow increasingly complex, managing and understanding log data has become increasingly vital in achieving practical observability, enabling organizations to detect, diagnose, and prevent issues across their systems. However, traditional log analysis methods often struggle with the volume and complexities of modern log data in cloud-native environments.

A few weeks ago, members of Mezmo were at Kubecon and attended several sessions. You can see a post with my recap and session highlights. Today, though, I’m going to discuss three sessions that my colleagues found interesting for our peers in Observability.

Over the past year, I’ve noticed some interesting trends in my work with state and local governments. Across my conversations with organizations in this space, there’s a common thread: teams are getting creative about maximizing their limited resources. With budgets either flat or shrinking and operational demands increasing, these teams face tough choices. They’re being asked to maintain or improve services while working with the same, or in some cases, fewer resources than before.

This post was written by Charity Majors and Phillip Carter. In May of 2023, we released the Honeycomb Query Assistant, an LLM-backed feature that lets engineers use natural language to generate and execute queries against their telemetry data. Instead of having to master a domain-specific query language, you can simply type in things like “slow endpoints by status code” and the Query Assistant will generate a relevant Honeycomb query for you to iterate on.

Performance engineering transforms how organizations build and optimize software systems. System delays and performance issues directly impact revenue, user satisfaction, and business success. This guide covers performance engineering fundamentals, implementation approaches, and advanced strategies for building high-performing systems.

Refinery is a powerful tail-based sampler—but with great power comes great challenges. We heard your feedback and are excited to announce the release of Refinery 2.9, a rather large update that is packed with goodies to make your life easier when running Refinery in your network.

Full stack observability (FSO) includes the ability to measure and monitor all layers of business infrastructure, security, and applications, from the underlying hardware and network performance to the user-facing software. As businesses shift from traditional, monolithic systems to more complex environments involving on-premises (on-prem) and cloud infrastructure, there comes a critical need for holistic observability.

In modern IT systems, most businesses adopt new tools and technologies to stay ahead of competitors. These new technologies are resulting in the proliferation of distributed IT systems. For instance, some enterprises implement cloud computing, edge computing, or microservices architecture, contributing to complex distributed systems across organizations.

Distributed architectures with microservices, cloud-native components, and service meshes make traditional monitoring methods inadequate for system analysis. O11y (observability) implements advanced telemetry frameworks for deep system introspection through metrics, traces, and logs collection. This programmatic approach enables real-time debugging, performance optimization, and architectural decisions across distributed environments.

Observability refers to the ability of the DevOps team to track, monitor, and measure the state of their pipeline and operations. Without observability, you are working in the dark, unaware of what is working. With the growing complexity of modern IT systems, DevOps observability is no longer optional. Gartner estimates that by 2026, 50% of enterprises implementing distributed data architectures will have adopted data observability tools, up from less than 20% in 2024.