Elysia Tools
Navigation
Workflow Playbook
Parse logs, decode traces, inspect webhook/API evidence, explore JSON payloads, and extract recurring patterns before writing an incident-ready debugging note.
New to this workflow? Follow the steps in order, starting with the first tool below. Already know what you need? Jump straight to the matching step — every tool in this workflow is listed in the comparison table.
First tool: Log Parser - Apache/Nginx Access Log Parser
Hubs
| Tool | What it does | Category |
|---|---|---|
| Log Parser - Apache/Nginx Access Log Parser | Parse Apache/Nginx access logs using regex patterns and extract structured data | Data Processing |
| Structured Log Analyzer | Detect common log formats, extract core fields, infer field types, and export parsed logs as JSON, CSV, or SQL inserts | Data Processing |
| IP Address Extractor | Extract IPv4 and IPv6 addresses from log files, server logs, network traces, or any text content | Text Processing |
| Text Pattern Stats | Statistics and frequency analysis of text patterns (numbers, emails, URLs, etc.) | Text Processing |
Hubs
| Decode Jaeger, Zipkin, or OpenTelemetry trace JSON and render span timing, dependencies, and error hotspots as an interactive waterfall report |
| Development |
| Log Sequence Diagram Converter | Convert structured service logs into Mermaid or PlantUML sequence diagrams, with optional latency and error annotations | Development |
| Webhook Debugger & Relay | Generate a unique webhook capture URL, inspect incoming requests, validate signatures, and replay payloads to a target endpoint | Network |
| API Response Diff & Semantic Analyzer | Compare two API response payloads, highlight field-level diffs, and classify likely functional changes versus harmless runtime drift | Development |
| JSON Path Visualizer | Visualize JSON or JSONL as an expandable tree and copy JSONPath expressions for every node | Developer Tools |
| JSON Data Lineage Tracer | Trace JSON field paths, derived dependencies, and transformation history to build a field-level lineage graph | Data Processing |
| JSONata Query & Transform Studio | Preview JSONata-style queries and transformations, compare results across sample payloads, and export the transformed output as JSON, CSV, YAML, or Markdown | Data Processing |
| Multi-Pattern Matcher | Match multiple regex patterns against text in one operation | Development |
| Named Group Tester | Parse and display named capture groups from regex patterns | Development |
An observability debugging session is strongest when every claim can be traced back to a concrete artifact: a log sample, a trace export, a webhook capture, an API response pair, or a payload fixture. Begin by parsing raw logs with log-parser and structured-log-analyzer, then use ip-address-extractor and text-pattern-stats to identify the actors, status codes, request IDs, and recurring error phrases that deserve attention.
Once the raw evidence is structured, move from isolated lines to a timeline. distributed-trace-decoder-waterfall-visualizer shows span timing and dependency depth, while log-sequence-diagram-converter turns service interactions into a diagram reviewers can follow. If the symptom depends on delivery behavior, capture it with webhook-debugger-relay and compare response changes with api-response-diff-semantic-analyzer.
The last step is to remove guesswork from the final incident note. Use json-path-visualizer and json-data-lineage-tracer to name the exact fields involved, jsonata-query-transform-studio to test a repeatable transformation, and multi-pattern-matcher or named-group-tester to preserve the extraction rules. A good result says what was observed, where it came from, what remains a hypothesis, and what should be instrumented or tested next.
Workflow playbook
Parse access logs and structured application logs first, then extract IPs and recurring tokens so the investigation starts from stable fields instead of loose text.
Decode exported traces and convert interaction-like logs into sequence diagrams so latency, dependency order, and error hotspots are visible to reviewers.
Capture webhook evidence, replay only to safe targets, and compare response payloads to separate contract drift from harmless runtime values.
Map nested JSON fields, test JSONata transforms, and validate named or multi-pattern regex rules before turning the findings into an incident summary.
Start with log parsing when the failure appears in application output, trace decoding when latency or dependency order matters, and webhook/API comparison when delivery or response shape changed.
Use regex and IP extraction to isolate signals, sequence and waterfall views to explain ordering, and JSONPath or JSONata when nested payload fields need to be traced or reshaped for comparison.