Observability Engineering

Observability & Monitoring Services

Instrumentation, dashboards and alerting that tell you what broke and where — not just that something did.

Most teams have monitoring and still find out about outages from customers. The gap is usually not tooling but instrumentation: metrics that measure the infrastructure rather than the user's experience, logs with no correlation ID, traces that stop at the service boundary. We fix the instrumentation first, then the dashboards on top of it.

We build on OpenTelemetry so the data stays portable, and we are comfortable in Prometheus, Grafana, Loki, Tempo, Jaeger, and the commercial backends — Datadog, Honeycomb, New Relic — including moving between them when the bill stops making sense.

What we build

Instrumentation

OpenTelemetry traces, metrics and structured logs added to your services, with context propagated across boundaries so a request stays one story.

Dashboards that get used

A small number of dashboards answering the questions your on-call actually asks at 2am, instead of forty nobody opens.

SLOs & error budgets

Service level objectives derived from what users experience, with alerting tied to burn rate rather than raw thresholds.

Alerting & on-call

Alerts that page a human only when a human is needed, with runbooks attached — tuned to cut the noise that trains people to ignore them.

Log pipelines

Collection, parsing, sampling and retention that keeps the signal and stops paying to store the rest.

Cost control

Observability bills grow faster than traffic. We audit cardinality, sampling and retention, and cut spend without losing the data you need.

How an engagement runs

01

Assess

We review what you emit today, what your on-call actually uses, and which past incidents your current setup would have missed.

02

Instrument

OpenTelemetry into the services that matter first, with trace context threaded across service and queue boundaries.

03

Define SLOs

Objectives written against user-visible behavior, with alerting rebuilt around burn rate instead of static thresholds.

04

Hand over

Dashboards, runbooks and alert routing documented, and your team walked through them until they own it.

Open-Source Observability

We evaluate and deploy these in production. Browse all 349 guides, or talk to us about a specific tool.

Open-Source Observability

0xtools

0x.Tools is a Linux performance analysis and troubleshooting toolkit built with modern eBPF, providing kernel-level visibility into system behavior. I…

Open-Source Observability

ai-gateway

Helicone AI Gateway is an open-source Rust-based reverse proxy that unifies access to 100+ LLM providers (OpenAI, Anthropic, AWS Bedrock, etc.) throug…

Open-Source Observability

alerta

Alerta is an open-source, distributed monitoring and alerting system designed for scalability and minimal configuration. It ingests alerts from any so…

Open-Source Observability

alertmanager

Prometheus Alertmanager is a Go-based alert routing and management system that deduplicates, groups, and routes alerts from Prometheus and other sourc…

Open-Source Observability

ali

ali is a terminal-based HTTP load testing tool written in Go that generates configurable request loads and visualizes results in real-time through an …

Open-Source Observability

alive-progress

alive-progress is a Python terminal progress bar library that displays real-time throughput, ETA, and animated spinners. It supports multi-threaded up…

Open-Source Observability

alloy

Grafana Alloy is an open-source observability collector built on OpenTelemetry, allowing you to collect metrics, logs, traces, and profiles through pr…

Open-Source Observability

angle-grinder

Angle-grinder is a command-line tool for real-time log analysis and aggregation written in Rust. It enables parsing, filtering, and computing analytic…

Open-Source Observability

antigravity-panel

Antigravity Panel is a VS Code extension that monitors AI quota usage (Gemini, Claude, GPT) within Google's Antigravity IDE, displays consumption tren…

Questions clients ask us

We already have Datadog. Do we need this?
Having a backend is not the same as being instrumented. Most Datadog accounts we audit are collecting host metrics and unstructured logs, with little tracing and no SLOs — the tool is fine, the instrumentation underneath it is the gap.
Will OpenTelemetry lock us in?
The opposite — that is the reason to use it. Instrument once against a vendor-neutral standard and the backend becomes a swappable decision rather than a rewrite.
How much overhead does tracing add?
With head-based sampling at a sane rate, typically low single-digit percent. We measure it on your workload rather than quoting a number, and tune sampling until the cost is acceptable.
Can you cut our observability bill?
Usually, yes. The savings almost always come from metric cardinality and log retention rather than from collecting less of what matters.

Work with a software development company

DEV.co is a software development company with senior engineers across web, data, cloud, and AI development services. Observability Engineering work rarely arrives on its own — it comes attached to a product, a migration, or a platform, and we build all three.

Need help with observability engineering?

Have a real project conversation with a senior engineer before you commit to an approach.