Reduce storage costs
Filter, sample and derive metrics before shipping to the backend.
Observabilité · Courses
Vector: from discovery to expertise
Vector course: the high-performance observability pipeline written in Rust. Sources, transforms and sinks, the VRL language to parse and enrich logs, unit tests, buffering, deriving metrics, masking personal data, agent or aggregator deployment.
At your pace, through practice.By the end of this course you will be able to
- Understand the Vector topology (sources, transforms, sinks)
- Parse and enrich events with VRL
- Write unit tests for transforms
- Derive metrics and mask personal data
- Deploy Vector as an agent or aggregator and monitor it
LEARNING PATH
Course curriculum
0Course overview1 lesson
1Overview of collectors1 lesson
2Vector: topology and components4 lessons
3Transform with VRL and test3 lessons
4Choose and migrate1 lesson
5Best practices1 lesson
LEARN BY DOING
Use cases & applications
GDPR compliance
Mask e-mails, IP addresses and card numbers before storage.
Recommended prerequisites
What next?
Frequently asked questions
Is Vector tied to Datadog?
Vector is an open source project (MPL 2.0 licence) maintained by Datadog; it sends data to dozens of destinations, not only Datadog.
Do I need to learn VRL?
Yes, to get the most out of Vector: VRL is a simple, typed language checked before execution, replacing regexes scattered across configurations.