Operational dashboards that stay current within a few minutes

Run wall dashboards and KPI boards from SQL copies of SharePoint lists, refreshed every few minutes, with Graph polled by one job only.

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Last updated

An operational dashboard needs to reflect what changed a few minutes ago, and querying SharePoint directly on a tight schedule is slow and gets throttled.

A screen on an operations floor showing open incidents by stage, pending approvals and the oldest unassigned item is only useful if it shows this morning’s queue. Refreshed overnight from SharePoint lists, it is stale by ten o’clock. Refreshed every minute straight from SharePoint, it gets throttled once a dozen people open the same dashboard, and each refresh still pays SharePoint’s cost of resolving lookups item by item.

One sync, many viewers

SPSync polls SharePoint once, on a schedule as short as a few minutes, and writes the result to a database table. The dashboard queries that table as often as it likes. SharePoint sees one well-behaved job that honours Retry-After and meters its own resource use; the dashboard sees a fast SQL table, however many people are watching.

How fresh the board will be

On the default five-minute schedule, the board is within a few minutes of SharePoint. That is close enough for an operations floor, and it is the accurate description: a schedule, with no real-time push. How short the schedule can usefully go depends on list size and on the tenant’s Graph throttling headroom. Below a couple of minutes, check that headroom first.

Counting by status without a lookup per row

The lists behind the board replicate as tables. When status or category is a lookup in SharePoint, it is a key column in the database, so “open incidents by status” is a GROUP BY over a join. Person columns resolve into the shared sp_users table, which makes “assigned to me” views simple. An item removed from the queue keeps its row with sp_deleted_at set, so it still counts in the closed totals and history does not shrink.

Per-list metrics for every run: rows read, inserted, updated, soft-deleted, and any errors.
Per-list metrics for every run: rows read, inserted, updated, soft-deleted, and any errors.

Include the status and category lists when you pick the operational lists, so the joins resolve. Point the dashboard at the destination database and let it refresh on its own short interval. A board other people rely on should not depend on one person’s laptop, so run the sync from SPSync in your Azure or from the command line on a server.

Desktop, Azure or command line

All three editions run the same engine, write the same tables and use the same licence key, so the choice comes down to who looks after the sync.

Desktop app

For macOS and Windows. Sign in with Microsoft, tick the lists, choose a database and sync from your own machine on the schedule you set. Delegated sign-in needs no admin unless your tenant requires admin consent for apps.

In your Azure

SPSync in your Azure, a managed application for your own subscription, is deployed with you on a call while the Marketplace listing is prepared. Once deployed it is always on, so the sync keeps running with every laptop closed.

Command line

Every replication is a YAML file you can review and commit. Run it from a server, a container or a CI pipeline, and re-run it safely any time.

Set it up

Ready to run this against your own site? The setup guide takes you from install to a first replication, and the SharePoint connection guide covers signing in.

Script it

Everything you can click, you can script. The CLI, YAML config and automation below reproduce this scenario exactly. See the CLI reference.

spsync auth login --client-id 00000000-0000-0000-0000-000000000000
spsync export-config --output replication.yaml --pipeline-name kpi_dashboards --prefix kpi_dashboards --destination-kind postgres --connection-string-env SPSYNC_DB_CONNECTION --dataset-name kpi_dashboards --client-id 00000000-0000-0000-0000-000000000000 --site-url https://contoso.sharepoint.com/sites/example --all-lists
spsync doctor replication.yaml
spsync run replication.yaml
pipeline_name: kpi_dashboards
prefix: kpi_dashboards
auth:
  mode: delegated
  client_id: 00000000-0000-0000-0000-000000000000
  tenant_id: common
destination:
  kind: postgres
  connection_string_env: SPSYNC_DB_CONNECTION
  dataset_name: kpi_dashboards
scopes:
  - site_url: https://contoso.sharepoint.com/sites/example
    mode: entire_site
reconcile_interval_days: 7
create_reporting_views: false

Cron (PostgreSQL nightly):

# every night at 02:00
0 2 * * * cd /opt/spsync && SPSYNC_DB_CONNECTION="$(cat /etc/spsync/db.env)" uv run spsync run replication.yaml >> /var/log/spsync/run.log 2>&1

GitHub Actions:

# .github/workflows/spsync-run.yml
name: SPSync
on:
  schedule:
    - cron: "0 2 * * *"
  workflow_dispatch: {}
jobs:
  run:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: astral-sh/setup-uv@v3
      - run: uv sync
      - run: uv run spsync run replication.yaml
        env:
          SPSYNC_DB_CONNECTION: ${{ secrets.SPSYNC_DB_CONNECTION }}
          SPSYNC_LICENCE_KEY: ${{ secrets.SPSYNC_LICENCE_KEY }}

Azure DevOps:

# azure-pipelines.yml
schedules:
  - cron: "0 2 * * *"
    branches: { include: [main] }
    always: true
steps:
  - script: uv sync
  - script: uv run spsync run replication.yaml
    env:
      SPSYNC_DB_CONNECTION: $(SPSYNC_DB_CONNECTION)
      SPSYNC_LICENCE_KEY: $(SPSYNC_LICENCE_KEY)

Windows (PowerShell + Task Scheduler):

# Windows Task Scheduler action (see /docs/cli/automation/)
$env:SPSYNC_DB_CONNECTION = (Get-Content C:\spsync\db.env)
uv run spsync run C:\spsync\replication.yaml
schtasks /Create /SC DAILY /ST 02:00 /TN "SPSync" /TR "powershell -File C:\spsync\run.ps1"

macOS (launchd):

# ~/Library/LaunchAgents/io.spsync.run.plist, then: launchctl load ~/Library/LaunchAgents/io.spsync.run.plist

Secrets (licence key, connection strings) come from the environment, so never write them into the YAML. See scheduling and secrets.

Book a call

Book a call to talk through your use case, see further walkthroughs or demos, and set up a trial in your own environment.