SleekView Charts for WPGraphQL
SleekView Charts reads WPGraphQL's query log table and per-request debug payloads, then renders operation volume, error rate, response time and root-type usage as chart cards next to the GraphiQL workbench.
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Queries land. The pattern across queries is what needs measuring.
WPGraphQL exposes a single endpoint that handles dozens of operations across a headless frontend, a mobile client, a Gatsby or Next build and ad hoc developer tooling. Each individual query is easy to inspect in GraphiQL. The pattern across thousands of queries per day is the part that decides whether the schema is healthy or quietly bloating response times for the entire frontend.
SleekView Charts reads WPGraphQL's query log option (or the debug payload when the GraphQL Debug constant is on) and renders it as a dashboard. A Number card shows total operations per day. A Pie splits operations by name so the team sees which queries dominate traffic. A Bar groups by query depth or root type to catch ballooning selection sets. An Area trends average response time per hour so a regression after a schema change is visible the same afternoon, not a week later when a customer complains.
Because the data comes from the same log WPGraphQL already writes, the dashboard works on every install that turns logging on. No external APM is required, and no proxy sits between the frontend and the GraphQL endpoint. Filters carry between the chart view and the raw query table, so a spike on the Area card drills into the exact failing operations behind it.
Workflow
Turn WPGraphQL logs into a dashboard
Enable query logging
Point SleekView at the log
Compose the chart cards
Share with the team
Sample dashboard
Charts you can build from WPGraphQL data
Operations per day
Count
Operations by name
Count
group by operation_name
Average response time by operation
Average(response_time_ms)
group by operation_name
Errors per hour
Count
group by logged_at
Comparison
Default WPGraphQL admin vs SleekView Charts
Default WPGraphQL admin
- GraphiQL is one query at a time, not an aggregate view
- Query log screen lists rows, not totals, splits or trends
- No per-operation latency average for spotting fat queries
- Error volume over time stays buried in individual log rows
- No way to share a read-only query health snapshot outside the WP admin
SleekView Charts
- KPI card for operations per day across the GraphQL endpoint
- Pie split of operation names so traffic shape is visible
- Per-operation average latency to catch fat queries early
- Errors-per-hour trend that exposes regressions after deploys
- Filters carry between chart cards and the raw query log table
Features
What SleekView Charts gives you for WPGraphQL
Dashboard, not just a log scroll
Render WPGraphQL's query log as Number, Pie, Bar and Area cards so headless teams see operation shape, latency and error rate at a glance instead of scrolling row by row.
Per-operation latency
Average response time grouped by operation_name surfaces the one fat query that's dragging the frontend, before it becomes a user-visible Time To Interactive regression.
Share a read-only snapshot
Send the headless lead a URL of the query health dashboard or export the filtered set to CSV. Release postmortems get a before-and-after instead of "it felt slower".
Audience
Who builds WPGraphQL charts dashboards with SleekView
Headless engineers
Watch operation volume, per-query latency and error rate on one screen during release week, so a slow frontend points at the offending query in minutes instead of hours.
Schema owners
Track query depth and root-type usage to plan schema cleanups. If a root type is never queried in thirty days, archive it instead of carrying it forward into the next version.
On-call developers
Filter the dashboard to has_errors = true and group by operation_name. The card surfaces the broken caller immediately, with a CSV export for the bug ticket.
The bigger picture
Why a single endpoint needs an aggregate view
WPGraphQL collapses what used to be a sprawl of REST endpoints into one URL, which is wonderful for the frontend and a problem for observability. Every operation hits the same path, so the standard web-server access log gives you a single line per query: same method, same URL, no shape. The pattern across operations only emerges if something turns the raw log into an aggregate.
A KPI for operations per day shows whether the endpoint is keeping up with traffic. A pie of operation names shows which queries to prioritise for caching. Per-operation latency averages catch the one fat query that drags the entire frontend before users complain.
An errors-per-hour trend turns a quiet regression after a deploy into a visible spike the same afternoon. Same query log, completely different operational posture.
Questions
Common questions about SleekView Charts for WPGraphQL
WPGraphQL's own query log (or the GRAPHQL_DEBUG payload it produces) plus the request meta around it: operation name, root type, query depth, response time, response size and the error flag. No external APM is required, and no proxy sits between the frontend and the endpoint.
No. WPGraphQL ships its own query log option. Turn it on in WPGraphQL settings, or set GRAPHQL_DEBUG to true on a staging environment, and SleekView Charts reads the resulting log table directly.
Yes. Group by root_type, query_depth, status code, has_errors flag or any hour or day bucket on logged_at. The same log columns also support Average, Sum, Minimum and Maximum on response_time_ms and response_size_bytes.
Yes. Persisted queries still write a row to the log with the resolved operation name, so the dashboard sees them the same way it sees ad hoc operations. The pie of operation names lets a team measure how much of total traffic is genuinely persisted.
WPGraphQL's logger is optimised to write once per request with minimal overhead. SleekView Charts only reads the resulting rows, so the dashboard itself adds nothing to the request path. Teams that don't want production logging typically run the dashboard on staging and a sampled subset of prod.
Yes. Group by logged_at as a day or hour bucket with an Area or Line card and aggregate as Average on response_time_ms. A flat baseline plus a step up after a deploy is the clearest possible signal that the new schema added cost.
Yes. Any filtered set behind a chart card exports as CSV with the same columns the query log table would show. On-call engineers typically attach the export to a regression ticket alongside the failing operation.
Yes. WPGraphQL for ACF, WooCommerce, Custom Post Type UI and the rest add types and resolvers to the same schema, and their operations land in the same query log. The dashboard groups them by name like any other operation, with no extension-specific configuration.
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