Unified Telemetry Collection
Replace multiple agents with a single Alloy binary for centralized collection of logs, metrics, and traces.
Observability · Courses
Alloy: From Discovery to Expertise
Complete training on Grafana Alloy, from discovery to expertise.
At your pace, through practice.By the end of this course you will be able to
- Write Alloy pipelines for metrics, logs, traces and profiles
- Structure configuration with modules and manage secrets
- Deploy Alloy as a cluster on Kubernetes with Helm
- Monitor Alloy itself
- Configure Alloy through the environment and know what it actually reads (OTEL_RESOURCE_ATTRIBUTES, sys.env)
LEARNING PATH
Course curriculum
0Course Overview1 lesson
1Discovering Grafana Alloy3 lessons
What Alloy is, its programmable pipelines and its architecture.
2Installing and getting started3 lessons
Install Alloy and explore its interface to see a pipeline at work.
3Writing a configuration6 lessons
Syntax, variables, secrets and environment, up to the first pipeline.
4Collecting metrics5 lessons
Discover targets, scrape, send to Prometheus or Mimir, receive OTLP.
5Collecting logs5 lessons
6Collecting traces3 lessons
Ingest, transform and sample traces to Tempo.
7Collecting profiles3 lessons
Set up continuous profiling with Pyroscope.
8The Grafana Labs ecosystem7 lessons
Faro, Beyla, Database Observability, k6, Fleet Management and Kubernetes Monitoring with Alloy.
- Alloy and the Grafana Labs ecosystemArticle · ⏱ 3 min
- Faro: RUM with faro.receiverArticle · ⏱ 9 min
- Beyla: eBPF instrumentationArticle · ⏱ 8 min
- Database ObservabilityArticle · ⏱ 6 min
- k6: load tests in AlloyArticle · ⏱ 8 min
- Fleet Management and Kubernetes MonitoringArticle · ⏱ 6 min
- Lab: Connecting Faro and k6 to AlloyHands-on lab · ⏱ 40 min · Level 2/5
9Deploying at scale4 lessons
High availability with clustering, then deployment on Kubernetes.
10Monitoring and optimising2 lessons
Monitor Alloy itself and apply collection best practices.
11Comparing and choosing4 lessons
Position Alloy against other collectors, once its concepts are mastered.
12Final project and reference2 lessons
Assemble a complete pipeline, with the component reference at hand.
LEARN BY DOING
Use cases & applications
OTLP Data Transformation
Receive, filter, modify, and route OpenTelemetry data to various observability databases.
Kubernetes Dynamic Discovery
Automatically discover and scrape pods and services dynamically deployed in a Kubernetes cluster.
Continuous Profiling
Collect application performance profiles (via Pyroscope) continuously to quickly identify bottlenecks.
Recommended prerequisites
What next?
Frequently asked questions
What is Grafana Alloy?
It is an open-source, vendor-neutral telemetry collector designed to replace Grafana Agent. It is OpenTelemetry (OTel) compatible.
Does Alloy replace Promtail and other agents?
Yes, Alloy combines the features of Promtail and Grafana Agent and includes native support for OpenTelemetry.
What configuration language does Alloy use?
Alloy uses a declarative syntax based on River (similar to Terraform's HCL) which simplifies pipeline creation.
Can Alloy be used for OpenTelemetry?
Absolutely, Alloy offers full native support for receiving, processing, and exporting data (Traces, Logs, Metrics) via the OTLP protocol.