Advanced Text Processing & Log Analysis Training

Duration: 2 days (8h/day) → 16 hours total
Tools: awk, sed, grep, cut, sort, uniq, jq, xargs, tee, tr, head/tail, regex, logrotate, syslog, journald, modern log pipelines.



Day 1 — Advanced Text Processing

Chapter 1 — Mastering grep & Regex

  • Extended regex
  • Lookaheads/lookbehinds
  • Grep performance tuning (-F, -P, -w, -m)
  • Multiline patterns
  • Grep in massive directories

Chapter 2 — awk Deep Dive

  • Field manipulation
  • Conditionals, loops, functions
  • Aggregations, statistics, reporting
  • Parsing CSV/JSON-like logs
  • Combining awk with pipes and xargs

Chapter 3 — sed for Editing Streams

  • Pattern space vs hold space
  • Stream editing in pipelines
  • Substitutions, global flags
  • Multi-line sed
  • In-place file transformations
  • Practical patching via sed scripts

Chapter 4 — Core Unix Filters

  • cut, paste, tr, sort, uniq, wc, tee
  • Efficient multi-stage pipelines
  • Optimizing pipe order for large logs
  • head/tail tricks
  • File descriptor redirection patterns

Chapter 5 — JSON, YAML, System Outputs

  • jq for JSON logs
  • YAML extraction using yq basics
  • Converting logs to structured data
  • Extracting metrics from APIs and CLI outputs

Day 2 — Log Analysis, Pipelines & Automated Processing

Chapter 6 — Linux Logging Systems

  • Syslog architecture
  • journald internals
  • journalctl filtering (boot, unit, priority, time)
  • Forwarding logs (syslog → remote destinations)
  • Logrotate patterns and performance tuning

Chapter 7 — Log Analysis Techniques

  • Pattern extraction
  • Frequency analysis
  • Error rate calculations
  • Correlating multi-file logs
  • Detecting anomalies in sequences
  • Time-based analysis

Chapter 8 — Building Analysis Pipelines

  • Streaming logs vs static files
  • Live monitoring with tail -F
  • Combining tools into long pipelines
  • Using make or shell scripts to automate analysis
  • Generating reports from logs

Chapter 9 — Handling Huge Files

  • 50GB+ log strategy
  • Using mmap-enabled tools (ripgrep, mawk)
  • Sampling techniques
  • Parallel processing using GNU parallel
  • Memory-safe pipelines

Chapter 10 — Practical Troubleshooting Scenarios

  • Performance issues
  • Authentication failures
  • Networking drops
  • Web server errors (Apache/Nginx/Balancers)
  • System crashes and kernel messages
  • Security incident traces (suspicious commands/user activity)