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Courses About Blog Pricing Network training Contact
Courses About Blog Pricing Network training Contact

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Data Pipelines for Logs

Buffering, parsing, and cardinality control for noisy syslog streams.

Illustration for Data Pipelines for Logs
Data · Self-paced · 6 weeks · Intermediate · Rolling start

7,200,000 VND (informational)

Overview

Ingest synthetic bursts, tame rogue fields, and build a dashboard that does not melt GPUs. Mentors grade on clarity, not chart flashiness.

Included focus areas

  • Docker-compose lab stack
  • Parser tests with golden files
  • Sampling vs drop policies exercise
  • Retention tier spreadsheet template
  • SLO draft for search latency
  • On-call runbook snippet
  • Cost estimate worksheet

Outcomes

  1. Cut indexed field count on a sample stream
  2. Write a runbook entry for parser failure
  3. Present a sane retention proposal

Lead mentor

Avatar image for Nhat Linh Dang

Nhat Linh Dang

Observability engineer; hates expensive dashboards.

FAQ

We teach patterns; week one picks a stack for exercises based on cohort vote.

Experience notes

Cardinality lab embarrassed our old “log everything” default — politely.
Vy · Support lead · survey

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