Console

When you hit Run API or Run Batch, 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

Single Request (Run API)

Execute a single API request to test configuration, verify responses, or perform one-off operations.

From endpoint webview:

  1. Configure endpoint (method, URL, headers, body)
  2. Click Run API
  3. Enter values for template variables (if any)
  4. Console opens with results

From sidebar:

  1. Right-click endpoint → Run API
  2. Enter variable values when prompted

From Quick Access (Alt+D E):

  1. Press Alt+D E to open fuzzy search
  2. Select endpoint → choose Run API

Batch Execution (Run Batch)

Execute the same endpoint multiple times with different data — entered in the grid or loaded from a file.

From endpoint webview:

  1. Click Run Batch to open the batch preparation flow
  2. Walk through the 5-step process: Load Data → Map & Transform → Review & Edit Data → Review JSON → Execute
  3. Click Execute in Step 5 — the Console opens and the batch begins

From sidebar:

  1. Right-click endpoint → Run Batch
  2. Walk through the batch preparation steps
  3. Click Execute — the Console opens automatically

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:SS format
  • 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
  • Root path selector is hidden (not applicable to source data)

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:

Root Path Navigation

Navigate nested JSON response structures without writing code.

How it works:

  • Dropdown labelled Root: in the toolbar
  • Select which JSON path to use as the table root
  • Changes which data fields appear as columns

Example:

{
  "data": {
    "items": [
      {"id": 1, "name": "Item A"},
      {"id": 2, "name": "Item B"}
    ]
  }
}
  • Select root path: data.items
  • Table shows columns: id, name

Search across all visible columns simultaneously.

  • Always shows the row count — total rows when no search is active, filtered/total when searching
  • Case-insensitive matching
  • Copy and Export respect the active search filter — only the filtered rows are included

Tips:

  • Search for specific error messages
  • Find rows with particular values
  • Filter by status codes (search “200” or “404”)

Column Management

Click Manage Columns to customise which columns are visible:

  • Search columns — Filter column list by name
  • Select All / Deselect All — Quick toggle
  • Reset to Default — Restore original column selection
  • Toggle checkboxes — Show/hide individual columns

Sorting

Click any column header to sort:

  • First click: Sort ascending
  • Second click: Sort descending
  • Third click: Remove sort
  • Multi-column sort: Hold Shift and click additional columns

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
For Spreadsheet (TSV) Excel, Google Sheets Tab-separated values — pastes directly into cells
For Email (HTML) Outlook, Gmail, Word, Teams, Confluence Styled HTML table with formatting
For Jira/Docs (Markdown) GitHub, Jira, Notion GitHub Flavoured Markdown table
CSV Scripts, data pipelines Comma-separated plain text

Example workflow:

  1. Switch to Error tab
  2. Search for a specific error pattern
  3. Sort by timestamp
  4. Click Copy → For Email (HTML)
  5. Paste into Outlook — formatted table appears inline

Export

The Export dropdown saves data to a file.

Format Details
CSV Plain text, streams line-by-line — handles any size
Excel (.xlsx) Formatted workbook with colour-coded status codes and typed columns

Limits

Large copy/export operations can overwhelm target applications or the extension host. Dobermann enforces sensible limits:

Action Format Limit Reason
Copy HTML / TSV 1,000 rows Paste crashes Excel/Outlook with large tables
Copy Markdown 1,000 rows Paste crashes target apps
Copy CSV 10,000 rows Lighter format, higher tolerance
Export Excel 2,000,000 cells XLSX library OOM in extension host
Export CSV 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 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

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