Operations | Monitoring | ITSM | DevOps | Cloud

3 things you need to know about headless observability

If you're building agents trying to figure out the best way to actually make them successful in production, you're going to want to know about headless observability. Headless observability means an agent can access information about the health of your system through a CLI instead of clicking around dashboards. It's the data layer that going to unlock serious autonomy and allow you to scale with agentic workloads.

What Is APM? A Guide to Application Performance Monitoring

A well-instrumented service tells your on-call engineer which deploy broke checkout, which span ate the latency budget, and which line to revert before the support queue fills up. Getting there depends on how cleanly your application performance monitoring layer turns telemetry into answers. The sections ahead walk through how APM works, the metrics and components worth tracking, the cloud-native challenges at scale, and how to evaluate APM tooling against your real workload.

What Is an Incident Commander? Role, Skills, and Best Practices

The fastest incident response teams treat coordination as a craft. Someone owns the call, drives the decisions, and keeps everyone moving in the same direction while the team puts the system back together. That person is the incident commander (IC), and getting the role right is what separates your 15-minute fix from a four-hour war room where nobody’s sure who’s making the call.

OpenTelemetry Fleet Management: Scalable Control

OpenTelemetry has turned observability pipelines into production infrastructure, but managing them at scale often creates a massive operational burden. In this demo, we show how Coralogix Fleet Management acts as the central control plane for your OTel ecosystem, providing the governance and orchestration required for modern DevOps. Stop the "manual marathon" of PRs and Helm upgrades. Move toward a safer, more predictable operating model where telemetry is consistent, audited, and scalable.

Managing OpenTelemetry at Scale: Why OTel Pipelines Need a Control Plane

OpenTelemetry made telemetry possible everywhere – turning observability pipelines into distributed production infrastructure. Distributed infrastructure requires a control plane for inventory, governance, and safe change. At 500 collectors across hybrid environments, operational overhead becomes a production risk. The moment telemetry pipelines become a distributed infrastructure, they inherit the operational problems of one.

The cost of knowledge

In the world of observability, “cardinality” has become a heavy word. It is a ghost used to justify skyrocketing bills or degraded query performance. When cardinality rises, the advice is almost always the same: reduce it. Drop your labels, or reduce the dimensions. It is usually framed as “optimization.” Every label you add to a metric is a dimension of knowledge. Each one gives you a way to slice, compare, and explain the chaos of production.

Introducing the Coralogix CLI: Headless Observability for Every Agent

This article is a high-level overview of the Coralogix CLI. For a deeper look at how it works in practice, read the full technical deep dive here. Agent-driven investigation sounds simple: read the alert, query the data, return the cause. In reality, most agents either overload their context window with raw logs or guess at queries and return incorrect results.

How the Coralogix CLI Adds Production Intelligence to Any Agent for Any Use Case

The new interface into production telemetry is a tool call, made from whichever agent runtime the operator happens to be using at that moment. A finance lead in Claude Code, a product manager in Cursor, an engineer in Codex. Three different jobs, three different agents, three different reasoning loops. The thing they have in common is the data layer underneath.

Real-Time Database Monitoring: Solving Database Latency with Zero-Code eBPF Tracing

In high-throughput database environments, a latency spike is rarely a simple story. Modern data layers are distributed, stateful, and constantly changing as shards move, nodes rebalance, caches warm, queries evolve, and connections churn. In practice, spikes usually come from one of three places: For many SRE and Platform teams, the real challenge is disconnected tooling. As one engineering lead recently shared during a technical workshop: “It’s all disconnected.

Your Team is Using Claude Code. Do You Know What It's Costing You?

The first two weeks of Claude Code are exciting. The third week is when you realize you don’t have visibility into what it’s doing or what it’s costing you. You would not run a production service without metrics, logs, and dashboards or deploy an API without knowing its latency, error rate, or cost per request.