Imaging Overview

This dashboard provides a consolidated, near real-time view of imaging job activity, throughput, and outcomes across your Relativity environment. It tracks how imaging jobs move through the pipeline - from submission, to pickup by the request agent, to completion - and summarizes the documents and images produced, the mix of imaging job types, and the success/error/skip breakdown of processed documents. It helps administrators validate that imaging is processing efficiently, detect stalled or failing jobs, understand which file types drive volume or warnings, and confirm imaging health after installations, upgrades, or configuration changes.

Availability

The Imaging Overview dashboard is available in Relativity Server 2026 and later. Its visualizations depend on imaging instrumentation shipped with the server and its built-in applications. If the dashboard loads empty, the likeliest causes are that no imaging activity occurred in the selected time range, or telemetry is not reaching the Elastic/Kibana stack.

Prerequisites

• Environment Watch is included by default with Relativity Server 2026+, and the Elastic/Kibana stack is receiving telemetry from the target Relativity Server.
• The Relativity Server is version 2026+ so that imaging OpenTelemetry (OTEL) metrics are emitted.
• Imaging jobs have run within the selected time range so that the panels have data to display.

Navigation

The Imaging dashboards are part of the Document Transformation feature domain. Two navigation strips sit at the top of every imaging dashboard:

• Feature-domain tab strip - switches between the related Document Transformation views:
  • Document Transformation Overview
  • Imaging Overview
  • OCR Overview
  • PDF Overview
  • Production Overview
• Imaging sub-tab strip - switches between the four imaging dashboards that make up the imaging suite:
  • Overview (this dashboard)
  • Native & Basic
  • Errors & Warnings
  • Queue & Latency

A left-hand navigation panel provides quick links to other Environment Watch feature domains (Platform, Applications, Logs/Searches/Alerts), making it easy to move between imaging and adjacent areas such as Processing, Review, and Monitoring.

Filters and Time Range

• Time range - Use the time picker in the top-right to scope every panel to a specific window. The dashboard does not save a fixed time range, so it opens with your Kibana default (or last-used) range; set the window you need and all visualizations respect the selected range.
• KQL filter bar - Use the query bar to narrow results with Kibana Query Language (for example, by host or job type field) and add ad-hoc filters. Filters apply across all panels on the tab.

Job Activity and Throughput Summary

The metric tiles across the top of the dashboard summarize imaging job flow and output for the selected time range:

• Jobs Completed - Total number of imaging jobs that finished.
• Jobs Submitted - Total number of imaging jobs submitted to the queue.
• Jobs Picked Up by Request Agent - Total number of jobs picked up for processing by the request agent. Comparing this with Jobs Submitted and Jobs Completed reveals whether jobs are being drained from the queue and finishing as expected.
• Documents Processed - Total documents processed across completed imaging jobs.
• Images Produced - Total images generated across completed imaging jobs.
• Job Duration (Avg) - Average end-to-end duration of a completed imaging job, giving a quick read on processing performance.

Large values are automatically formatted into compact, human-readable form (for example, 1.2k, 3.4M) for consistency with the other Environment Watch dashboards.

The Job Queue Composition donut shows the distribution of imaging jobs by job type for the period, with the total job count displayed in the center. The most common job types are:

• On-the-Fly - Images a single document as users work.
• Mass Imaging - Images many documents in one operation.
• Imaging Set - Images many documents from the Imaging Set console.

The mix of job types varies by environment and workflow. Less common job types (such as Retry Imaging Set) appear as additional slices when present. This breakdown helps administrators understand what kind of imaging work is running in the environment and spot unexpected spikes in mass operations or retries.

How to read it: A slice that is much larger than usual - for example a sudden jump in Mass Imaging or retry work - often explains a spike in queue depth or latency on the Queue & Latency dashboard. Hover any slice to see its exact job count and percentage.

Error and Warning Indicators

A row of status tiles and a donut summarize the health of imaging output for the selected range (shown together with the throughput tiles in the figure above):

• Errored Documents - Total documents that failed during imaging.
• Error Rate - Errored documents as a percentage of documents processed. A rising value is an early signal of file-type, configuration, or resource problems.
• Total Warnings - Total imaging warnings raised (the sum of the seven imaging warning-type counts - see Errors & Warnings).
• Warning Rate - The rate of imaging warnings relative to imaging output for the range.

The Error Breakdown: Real vs Expected donut splits errored documents into expected failures (for example, password-protected documents or unsupported file types) and real failures (unexpected errors that warrant investigation). Separating the two helps administrators focus remediation effort on genuine processing problems rather than on failures that usually need no action.

How to read it: Expected failures are normal and usually need no action; a growing real slice is the signal to investigate (start with the Errors & Warnings dashboard). Hover a slice for its exact document count and share of total errors.

Document Outcomes and Throughput

The Document Outcome donut summarizes the result of processed documents as a percentage of the total, with the imaged percentage highlighted in the center and the total document count shown beneath the chart:

• Imaged - Documents successfully imaged.
• Errored - Documents that failed during imaging.
• Skipped - Documents skipped during imaging.

This visualization provides an at-a-glance measure of imaging quality and reliability.

How to read it: A healthy environment is dominated by the Imaged slice. A growing Errored slice points to content or configuration problems - use the Error Breakdown donut to tell real failures from expected ones - and a growing Skipped slice usually reflects documents intentionally excluded from imaging.

The Documents / Minute line chart plots document imaging throughput over time. It reveals demand patterns, ramp-up and ramp-down behavior, and dips or plateaus that may indicate contention, throttling, or stalled processing.

How to read it: Steady throughput appears as a continuous line; flat stretches are idle periods, and a sudden drop during active imaging can signal contention, throttling, or stalled agents. Hover any point for the exact documents-per-minute value at that time.

Job Timing and Detailed Results

The Job Runs by Time of Day chart is a time series of imaging job starts, plotted per day over the selected range and split into a separate line per job type. This chart, the Job Queue Composition donut, and the Job Type column in Job Results all use the same job-type names:

• On-the-Fly - Images a single document as users work.
• Mass Imaging - Images many documents in one operation.
• Imaging Set - Images many documents from the Imaging Set console.
• Retry Imaging Set - Retries an imaging set's errored documents.
• Cleanup - Internal cleanup job after another imaging job errors.
• Stop - Stops an imaging job in progress.

Other, less common internal job types - QC (hold or release images for QC), Diagnostics (a diagnostics request), and Change Priority (change the priority of a running job) - can occasionally appear in the Job Results table's Job Type column. The chart helps administrators see day-over-day imaging load, spot bursts or quiet periods, and understand which job types drive activity on any given day.

How to read it: Each point is the number of jobs of that type that started in the day bucket; hover a point for the exact count. Look for regular daily peaks (normal working-hour load) versus unexpected off-hours bursts, and watch for a job type that climbs steadily over several days.

The Daily Status (All Jobs) table rolls imaging activity up per day (most recent day first), including:

• Timestamp per day - The day bucket.
• Total Jobs Successful / Total Jobs Failed - Completed job counts by outcome.
• % Jobs Successful / % Jobs Failed - Job success and failure rates for the day.
• Total Docs Successful / Total Docs Failed - Document counts by outcome.
• % Docs Imaged / % Docs Failed - Document success and failure rates for the day.

The Job Results table lists individual imaging jobs for the range, one row per job correlation ID, including:

• Correlation Id - Unique identifier for the job.
• Latest Timestamp - Most recent event for the job.
• Job Type, Job Priority, Profile Type, Status - Job attributes and current status. Job Type uses the job-type names described under Job Runs by Time of Day above. Profile Type is the imaging profile's engine - Basic or Native; see Native & Basic. Status uses the raw imaging job-status codes described below the table.
• Workspace ID, Imaging Set ID - The workspace and imaging set the job belongs to.
• Images Created Per Hour (Thousands) - Throughput rate for the job.
• Run Time (Minutes) - End-to-end job duration.
• Documents Imaged, Documents Errored, Documents Skipped, Total Images, Total Documents - Per-job document and image counts.

The Status column shows each job's current processing stage as a raw status code:

• Created - The job has been created by the imaging API.
• PickedUpByAgent - The job has been picked up by the Imaging Request Agent for processing.
• SubmittedToInvariant - All of the job's documents have been submitted to Invariant (the worker platform) for imaging.
• CancelRequested - The job has been flagged for cancellation through the imaging API.
• Invalid - A placeholder status used for in-flight jobs during an upgrade; it is not a normal operating state.

Together these panels let administrators drill from the aggregate KPIs down to the behavior of a specific imaging job.

Use Cases

Use Case	Description
Monitor imaging throughput	Track jobs submitted, picked up, and completed along with documents and images produced to confirm imaging is keeping pace with demand.
Detect queue backlog or stalls	Compare Jobs Submitted, Jobs Picked Up by Request Agent, and Jobs Completed to identify jobs that are queued but not draining or completing.
Assess imaging quality	Use the Document Outcome donut and the Error Rate / Errored Documents tiles to watch the imaged/errored/skipped mix and catch rising error rates early.
Separate real failures from expected ones	Use the Error Breakdown: Real vs Expected donut to distinguish genuine processing errors from failures that usually need no action (password-protected or unsupported file types).
Analyze workload composition	Use the Job Queue Composition donut to understand the balance between on-the-fly, imaging set, mass imaging, and retry work.
Review daily trends	Use the Daily Status (All Jobs) table and Job Runs by Time of Day to track day-over-day success/failure rates and see which job types drive imaging load on each day.
Investigate a specific job	Use the Job Results table to drill into an individual job's status, timing, and document/image counts by correlation ID.
Validate post-install/upgrade health	After a deployment or configuration change, confirm imaging jobs complete successfully and durations remain within expected ranges.
Investigate performance trends	Use the Documents / Minute chart and Job Duration (Avg) to correlate throughput dips or duration spikes with load or resource constraints.

Associated Alerts

No imaging-specific Environment Watch alerts are currently associated with this dashboard. This section will be updated as imaging alerts are published.