Performance & reliability · Canada
Make GIS performance explainable before you make it faster.
Slow GIS is rarely one thing. SpatialX separates service behavior, compute, databases, file access, raster/vector I/O, queues, integrations, and workload patterns into evidence that teams can act on.
The challenge
Performance troubleshooting should produce an operating model, not just a one-time fix.
Teams often see the symptom first: a service is slow, a report takes longer, a geoprocessing job stalls, or response times vary across the day. Without instrumentation, the investigation becomes guesswork.
SpatialX focuses on repeatable diagnosis and operational visibility. The objective is to identify where time is spent, what dependencies correlate with degradation, and which signals should remain monitored after the incident is resolved.
Common situations
- ArcGIS Server or geoprocessing services with inconsistent response times.
- CPU appears moderate while jobs still take too long.
- Database, NAS/file share, raster, or network dependencies are suspected but not measured.
- Queues, instance limits, or job concurrency create unpredictable throughput.
- Logs exist but are not converted into useful operational signals.
- Teams repeatedly troubleshoot the same categories of incident from scratch.
What SpatialX helps with
- Request/job timing analysis and service-level evidence.
- ArcGIS Server/Portal and supporting infrastructure health patterns.
- Database, file-share, raster/vector I/O, and network dependency analysis.
- Capacity, concurrency, queue, and workload-pattern review.
- Operational dashboards, log patterns, alerts, and runbooks.
- Performance baseline and post-change validation.
Architecture-led delivery
What a focused engagement can produce.
Deliverables are scoped to the environment and decision at hand; the intent is to leave behind artifacts that remain useful after the engagement.
Performance evidence pack.
Bottleneck and dependency map.
Service-health indicators.
Capacity and concurrency recommendations.
Monitoring/dashboard requirements.
Incident and troubleshooting runbook.
Questions worth clarifying
Architecture starts by asking the right questions.
Where is elapsed time actually being spent?
Does the issue follow the service, data, machine, workload, or time of day?
Which metrics predict user impact?
What should be continuously monitored after the immediate issue is fixed?
A practical starting point
Need clarity before a larger modernization decision?
Start with a focused geospatial platform assessment: current state, material risks, target architecture direction, and a phased roadmap.
Related capabilities