Console
When you hit Run, Dobermann opens the Console — your real-time window into what’s happening. Single requests complete in a flash. Batches stream results as they run, with live progress, pause/resume controls, and full transaction detail.
Starting an Execution
Dobermann uses a smart Run button that automatically detects the right execution mode:
- No template variables → Runs a single API request (shows as “Run API”)
- Has template variables → Opens the batch runner (shows as “Run Batch”)
This works the same everywhere: the endpoint footer button, the sidebar play icon, and Quick Access search.
Single Request (Run API)
Execute a single API request to test configuration, verify responses, or perform one-off operations. The button shows “Run API” when the endpoint has no {{template variables}}.
From endpoint webview:
- Configure endpoint (method, URL, headers, body) — no template variables
- Click Run API
- Console opens with results
From sidebar:
- Click the play icon on the endpoint
From Quick Access (Alt+D E):
- Press Alt+D E to open fuzzy search
- Select endpoint → choose Run
Batch Execution (Run Batch)
Execute the same endpoint multiple times with different data — entered in the grid or loaded from a file. The button shows “Run Batch” when the endpoint has {{template variables}}.
From endpoint webview:
- Click Run Batch to open the batch preparation flow
- Walk through the 5-step process: Load Data → Map & Transform → Review & Edit Data → Review JSON → Execute
- Click Execute in Step 5 — the Console opens and the batch begins
From sidebar:
- Click the play icon on the endpoint — Dobermann detects template variables and opens the batch runner
See Batch Preparation for the full 5-step workflow.
Execution Queue
Running multiple batches? Dobermann queues them automatically.
How it works:
- Start a batch on one endpoint, then start another — the second batch enters the queue
- A notification tells you: “Batch has been queued and will start when the current batch completes”
- Queue position and wait time are displayed while waiting
- Queued batches start automatically in order when the previous batch finishes
Use cases:
- Prepare several batches across different endpoints, then kick them all off
- Queue overnight data loads without babysitting each one
- Process different data sets against the same endpoint back-to-back
Console Layout
The Console is where everything happens — monitoring progress during a batch, inspecting results after completion, and exporting data for further analysis.
Execution Summary
The top section displays high-level execution metrics in compact stat cards:
Status Badge:
- Success — All requests succeeded (2xx responses)
- Partial — Some requests failed
- Failed — All requests failed
- Paused — Batch paused by user
- Running — Batch currently executing
- Queued — Waiting for another batch to complete
Summary Statistics:
- URL — Full resolved API endpoint with query parameters
- HTTP Status — Response status code (single executions only)
- Time — Execution start timestamp
- Duration — Total execution time in
HH:MM:SSformat - ID — Unique execution identifier for tracking
- Calls (batch only) — Completed vs planned transaction count (e.g.,
77/77) - Threads (batch only) — Parallel processing level (e.g.,
1= sequential,16= 16 concurrent)
Batch Controls
During a batch execution:
Pause — Halts execution after the current request completes. All progress is saved. Click Resume to continue from the exact position. Useful for rate limit cooling or reviewing errors mid-run.
Rename — Edit the batch name during execution for easier identification in history.
Real-Time Progress (Batch)
While a batch runs, you see live updates:
- Progress bar — Visual completion percentage
- Row counter — “Processing 45 of 100…”
- Success rate — Green counter with checkmark
- Failure count — Red counter (if any)
- Elapsed time — Running timer
- Requests per second — Throughput metric
- Estimated time remaining
Results stream into the tabs below as each request completes — no need to wait for the batch to finish.
Tabs
The Console organises data across five tabs:
Input Tab
Shows the source data used to generate API requests.
What’s displayed:
- All rows from your data grid or uploaded file
- Column headers and values as loaded
- Record count indicator
Key behaviour:
- Available for batch executions with loaded data
- Exportable as CSV during or after execution
- Views control doesn’t apply to the Input tab (source data is always one row per record)
Raw Tab
The Raw tab gives you complete visibility into every request and response — the full HTTP conversation for each transaction.
Features:
- Transaction navigation — Browse through all transactions
- Full request/response JSON — Syntax-highlighted in a Monaco editor
- View Logs — Per-transaction log entries for debugging
- View modes — Toggle between Raw, Rendered, and Text views (useful for HTML responses)
- Response count indicator
Use cases:
- Debug a specific failed request by inspecting the exact payload sent
- Verify variable substitution worked correctly
- Check response headers and status codes
- View API error messages in full detail
Completed Tab
Shows all successful transactions (2xx responses) in a data table.
Features:
- Tabular view of all completed requests
- Full response data for each transaction
- Response times and status codes
- Count indicator
Use case: Analyse successful patterns, extract data from responses, verify expected output.
Error Tab
Shows all failed transactions — 4xx client errors, 5xx server errors, network errors, and timeouts.
Features:
- Error messages from the API
- Request context that caused the error
- Status codes and response times
- Automatically hidden if there are zero errors
Use case: Debug failures, identify data quality issues, spot rate limiting or API problems.
Settings Tab
Execution metadata and configuration details.
What’s shown:
- Execution ID and timestamps
- Endpoint and environment details
- Execution lineage (parent/child relationships)
- Links to request/response files saved in workspace
Data Table Features
The Completed and Error tabs use a powerful data table for analysing results:
Named Views
The Completed and Errors tabs run on Named Views — saved configurations that control which columns appear and which array in the response produces one row each. Multiple views per tab; switch instantly; views save on the endpoint so they travel with it on export/share.
→ Read the Named Views guide for the View dropdown, View Editor, Row Basis, Set as Row, Save As, and how views travel with endpoints.
Search
Search across all visible columns simultaneously. Plain text search works as before (case-insensitive substring matching). Advanced patterns let you combine terms, use wildcards, exclude rows, and match exact phrases.
| Syntax | Meaning | Example | Matches |
|---|---|---|---|
, |
OR between terms | abc123,abc124 |
rows containing either term |
+ |
AND between terms | active+Dallas |
rows containing both terms |
* |
Zero or more characters | abc* |
“abcdef”, “abc123” |
? |
Exactly one character | a?c |
“abc”, “a1c” |
- prefix |
Exclude rows | -error |
rows NOT containing “error” |
"quoted" |
Exact cell value | "New York" |
only literal “New York” |
| plain text | Substring (default) | hello |
“Hello World” |
Patterns are combinable: active+pending,-error, "exact",-exclude,wild*
- Always shows the row count — total rows when no search is active, filtered/total when searching
- Case-insensitive matching across all patterns
- Copy and Export respect the active search filter — only the filtered rows are included
Tips:
- Search for specific error messages or exclude them:
-error - Find rows with particular values using wildcards:
SHIP* - Filter by status codes:
200or exclude failures:-4?? - Combine terms with commas:
abc123,abc124 - Require multiple terms with +:
active+Chicago - Match exact cell values with quotes:
"New York"
Sorting
Click any column header to sort. Sort is saved on the active view, so it persists across tab switches and console reloads.
- First click: Sort ascending
- Second click: Sort descending
- Third click: Remove sort
Sub-tables (rendered when expanding an ▸ N records cell) sort independently — their sort state is local to the open expand-cell.
Pagination
Dobermann has full support for paginated APIs — configure page and size parameters, auto-detect settings from API responses, and fetch hundreds of pages with concurrent execution.
See the dedicated Pagination guide for the complete workflow.
Copy & Export
Copy data to the clipboard or export to a file. All options respect the current tab, search filter, sort order, and visible columns.
Copy
The Copy dropdown copies data straight to your clipboard — no file needed.
| Format | Best for | What you get |
|---|---|---|
| Standard | Outlook, Gmail, Word, Teams, Confluence | Styled HTML table with formatting |
| Excel | Excel, Google Sheets | Tab-separated values with text-type preservation — pastes directly into cells with leading zeros and large numbers intact |
| CSV | Scripts, data pipelines | Comma-separated plain text |
| CSV (Excel) | CSV consumers that need type preservation | CSV with text fields prefixed to prevent number coercion |
| Markdown | GitHub, Jira, Notion | GitHub Flavoured Markdown table |
Example workflow:
- Switch to Error tab
- Search for a specific error pattern
- Sort by timestamp
- Click Copy → Standard
- Paste into Outlook — formatted table appears inline
Preserving leading zeros in Excel:
When pasting into Excel, numeric-looking text fields (e.g. GLN codes like 0012345000015) are automatically converted to numbers, losing leading zeros. Use the Excel or CSV (Excel) copy options to prevent this — they prefix text columns with an apostrophe (') that tells Excel to treat the value as text. For guaranteed type preservation without any prefix characters, use Export → Excel (.xlsx) instead.
Export
The Export dropdown saves data to a file.
| Format | Details |
|---|---|
| CSV | Plain text, streams line-by-line — handles any size |
| CSV (Excel) | CSV with text fields prefixed to prevent Excel number coercion |
| Excel (.xlsx) | Formatted workbook with colour-coded status codes and typed columns — guaranteed type preservation |
Limits
Large copy/export operations can overwhelm target applications or the extension host. Dobermann enforces sensible limits:
| Action | Format | Limit | Reason |
|---|---|---|---|
| Copy | Standard / Excel | 1,000 rows | Paste crashes Excel/Outlook with large tables |
| Copy | Markdown | 1,000 rows | Paste crashes target apps |
| Copy | CSV / CSV (Excel) | 10,000 rows | Lighter format, higher tolerance |
| Export | Excel (.xlsx) | 2,000,000 cells | XLSX library OOM in extension host |
| Export | CSV / CSV (Excel) | Unlimited | Streams line-by-line |
If you hit a limit, switch to CSV export (file) — it streams without memory constraints.
Execution History
All executions (single and batch) are saved in the sidebar.
Viewing History
Expand Executions in the sidebar to see past runs grouped by endpoint:
Icons:
- Checkmark — All successful
- Warning — Partial (some failures)
- X — All failed
- Pause — Paused/incomplete
Click any execution to reopen the Console with full results.
Context menu options:
- View — Open results
- Export Results — Save to file
- Re-run — Execute again with same data
- Delete — Remove from history
Workspace Files
Results are automatically saved to your Dobermann workspace:
.active8/
└── results/
└── {endpoint}/
└── {timestamp}.json
- Files open automatically in the editor after execution
- Compare executions using diff tools
- Excluded from git by default (
.active8/in.gitignore)
Error Handling
Error Tolerance
Configure how errors affect batch execution (set during batch preparation):
| Setting | Behaviour |
|---|---|
| Stop on First Error | Batch stops immediately on any failure |
| Maximum Error Count | Stops after N failures (e.g., 5) |
| Percentage-Based | Stops if error rate exceeds threshold (e.g., 10%) |
| Continue on All Errors | Runs to completion regardless of failures |
Choosing a setting:
- Stop on First Error — Critical data loads where any failure is unacceptable
- Max Error Count — Bulk updates where a few failures are OK
- Percentage-Based — Large batches (10,000+ rows) where some failures are expected
- Continue on All — Exploratory runs or data quality testing
Network Resilience
- Default timeout: 30 seconds (configurable per endpoint)
- Automatic retry (1 attempt) with exponential backoff for rate limits
- Clear error messages for timeouts, connection issues, and SSL errors
Performance
Parallel Processing
Concurrency is configured per environment (see Environments — Parallel Processing). Higher concurrency = faster batches, but more server load.
Large Batches
For batches over 1,000 rows:
- Results stream to disk incrementally (no memory buildup)
- Progress auto-saved periodically
- Split very large files into multiple batches if needed
- Run during off-peak hours to avoid rate limiting
Troubleshooting
Execution Won’t Start
Check:
- Endpoint is saved (no unsaved changes)
- Environment has valid authentication
- Required variables are configured
- No validation errors in endpoint
Batch Stops Unexpectedly
Check:
- Error tolerance setting (may be “Stop on First Error”)
- Recent error messages in Error tab
- API rate limits hit (look for 429 status codes)
- Network interruption
Execution Hangs
Possible causes:
- API server not responding
- Network connectivity issue
- Firewall blocking request
Solutions:
- Check API server status
- Test with curl/Postman
- Verify network connectivity
- Check the Raw tab for the last request sent
Wrong Data in Requests
Check:
- Column mapping is correct (Batch Preparation)
- Source data has correct values
- Variable names match exactly
- No extra spaces in column headers
Results Not Saving
Check:
- Write permissions in
.active8/directory - Disk space available
- File not locked by another process
- Check VS Code output panel for errors
Related Topics
- Named Views — Save column layouts and row-per-X shapes; switch and export instantly
- Pagination — Configure and run paginated API requests
- Batch Reprocessing — Re-run failed transactions without re-executing the whole batch
- Endpoints — Configuring API requests
- Batch Preparation — Data loading and column mapping
- Environments — Authentication, timezone, and parallel processing
- Troubleshooting — Common issues and solutions