# Share and embed > The dashboard has to leave the tool and keep meaning something. - Canonical: https://patterns.konigi.com/dashboards/share-and-embed - Group: Product mechanics - Level: flow - Status: published - Updated: September 10, 2026 - Also called: public link, snapshot, iframe embed, scheduled export --- ## Problem Someone found something. The people who need to see it do not have accounts, or will read it in a channel, or need it in a document next Thursday. Whatever leaves the tool has to still be true when it arrives. ## Solution Several mechanisms, because "share" is four different needs wearing one button. **A link** to live state. Cheapest and best when the recipient has access. Everything hinges on whether the URL carries the whole state—range, filters, variables, selection—which is why the URL-state discipline that shows up across this collection pays off here. **A snapshot.** A frozen copy of the data as it was, viewable without access to the source. This is the one that solves the incident-writeup problem, where a live link degrades into a link to a healthy system a week later. **An embed.** The panel rendered inside somebody else's page, usually a wiki or an internal portal, updating live. **A scheduled export.** A PDF or an image arriving on a timetable, for people who will never open the tool. Each has a different failure mode, and the common thread is that context does not travel. A screenshot in a chat loses the time range, the filters and the fact that someone had isolated one series. The image looks authoritative and is missing the thing that makes it true. Any share mechanism worth building stamps the range and the filters into what it produces. The second common thread is access. A public snapshot is a data-exposure decision made by whoever clicked the button, usually without a review step, and snapshots are exactly the artefact that ends up indexed. Products that make public sharing frictionless without making the consequence visible are handing a security decision to someone who thinks they are sending a picture. ## Use when The audience is outside the tool, or the moment needs preserving, or the same view needs to arrive somewhere on a schedule. ## Don't use when The recipient has access and the link would do. A snapshot where a link would work creates a second copy that immediately starts diverging from reality. ## Trade-offs Every share mechanism creates an artefact that outlives its context. Snapshots accumulate and nobody prunes them. Embeds break silently when the source panel is renamed or deleted, and the page they live in shows an empty box nobody reports. Scheduled exports keep arriving long after anyone reads them, which is the least harmful and most common form of this. And public sharing is a standing exposure risk that scales with how easy the button is to press. ## Checklist - Does a link carry range, filters, variables and selection? - Is a snapshot's capture time stamped on the snapshot itself? - Does a shared artefact say what was filtered when it was made? - Who can create a public link, and is the consequence visible at the moment of clicking? - Do public snapshots expire, and is there any inventory of them? - What does an embed show when the source panel is deleted? - Do scheduled exports have an owner and a review, or do they run forever? - Does a shared artefact carry a route back to the live view? - Does a snapshot include data the recipient should not see? - Is a stale artefact distinguishable from a current one at a glance? ## Compare **Grafana** offers the fullest set—direct link with current state, snapshots that can be public, panel embeds and image rendering—which covers every case and puts the public-exposure decision one click away without much ceremony. **Datadog** leans on scheduled reports and embeddable graphs with per-embed tokens, so an embed can be revoked without deleting the panel it came from. **Honeycomb** shares the query rather than a rendered result, which is the most robust artefact of the lot: a query re-run next week is honest about being a different answer, where an image pretends it is the same one. **Public status pages** are the extreme case, built entirely for readers with no access, and they show what a share-first design looks like when it is the product rather than a feature. ## Related Saved view is the internal cousin, keeping state for yourself rather than sending it. Freshness indicator is what a shared artefact most needs and most often lacks. Time-range picker is the state most often lost in transit. Comment and annotate is the collaborative alternative that keeps the discussion attached to the view. Data source badge answers the provenance question a shared image raises and cannot answer. ## Examples ### Netdata Per-second charts, hundreds per node, with a per-chart anomaly ribbon instead of a band on the series. **Anomalies / Anomaly advisor** — captured September 11, 2026, Netdata Agent, Anomaly advisor (public registry node, signed out). operational, medium density, dark theme, desktop-web. Netdata answers the anomaly problem without drawing a band at all, and the difference is worth recording. Rather than shading an expected range around each series, it scores every metric continuously and plots the result as its own series: the percentage of dimensions currently anomalous, and beneath it the count. Both sit near zero for most of the window and spike to about 0.04% at five separate moments. The trade is clear once you see it. A band tells you whether this metric is behaving, on the same axes as the metric, and needs one per chart. A rate tells you whether anything at all is behaving, in one chart, and cannot tell you which thing without a second step—which is what the panel at the bottom is for, and why it currently reads "You haven't highlighted any timeframe yet." The finding requires a brush selection before it will name a single metric. Hotspots in this capture: - [Anomaly band](https://patterns.konigi.com/dashboards/anomaly-band) — Not a band. An anomaly rate as its own series, so one chart covers every metric instead of one band per chart. - [Explain this metric](https://patterns.konigi.com/dashboards/explain-this-metric) — Every section carries a sentence saying what it counts, directly under its heading rather than behind an icon. - [Cross-filter](https://patterns.konigi.com/dashboards/cross-filter) — Highlight a timeframe and the page names which metrics drove it. The selection is the query. - [Empty state](https://patterns.konigi.com/dashboards/empty-state) — "You haven't highlighted any timeframe yet"—the reason for the blank, and the action that fills it. - [Share and embed](https://patterns.konigi.com/dashboards/share-and-embed) *(this pattern)* — Generate report, top right. Whether the highlighted window travels with it is the question the button raises. ### Kibana (Elastic) Query-first rather than panel-first: the search bar is the primary control and the charts are downstream of it, which inverts Grafana's arrangement. **Dashboards / [Flights] Global Flight Dashboard** — captured September 10, 2026, Elastic demo environment, sample flight data (guest session). analytical, dense density, light theme, desktop-web. Two things on this page are worth arguing with. The first is the table on the right, sorted by delay rate: Chicago/Rockford 100%, Syracuse 100%, Birmingham 75%. A hundred percent of flights delayed is either a catastrophe or one flight, and nothing in the table says which, because the denominator isn't a column. The cells are on a red ramp, so the two rows that are almost certainly a sample of one are the loudest thing in the panel. The second is the tile row: Delayed 25.2%, then beside it "Delayed vs 1 week earlier—76.9%". Seventy-six point nine percent of what? It could be last week's rate, it could be this week as a proportion of last week, it could be the change. Three different numbers, one label, and the tile picks whichever the query returned. What the page gets right is the filtering: a KQL bar for people who know the syntax and three declared controls underneath for people who don't, both visible at once. Hotspots in this capture: - [Ratio and rate](https://patterns.konigi.com/dashboards/ratio-and-rate) — Delay rates up to 100% with no denominator anywhere. One flight and a thousand flights render identically. - [Compare periods](https://patterns.konigi.com/dashboards/compare-periods) — "vs 1 week earlier, 76.9%"—the comparison base is named and the expression isn't. - [Share and embed](https://patterns.konigi.com/dashboards/share-and-embed) *(this pattern)* — Share, export and full-screen in the header. Whether the range and filters travel with them is the whole question. - [Filter bar](https://patterns.konigi.com/dashboards/filter-bar) — Declared controls under the query bar: two pickers and a price range. Both mechanisms on screen at once. - [Panel grid](https://patterns.konigi.com/dashboards/panel-grid) — Twelve columns, and the biggest panel is a table rather than the headline chart. Size isn't carrying priority here. - [Stacked composition](https://patterns.konigi.com/dashboards/stacked-composition) — Stacked to 100%, so the total is discarded on purpose and only the mix of delay types remains. - [Annotation](https://patterns.konigi.com/dashboards/annotation) — Event markers along the top of the series, numbered and grouped, on the data's own axis. - [Header KPI strip](https://patterns.konigi.com/dashboards/header-kpi-strip) — Five tiles in three different sizes and two different layouts, so the row reads as five things. ## Related patterns - [Saved view](https://patterns.konigi.com/dashboards/saved-view) — The team re-selects the same five filters every morning. - [Freshness indicator](https://patterns.konigi.com/dashboards/freshness-indicator) — The viewer is about to act on a number and doesn't know how old it is. - [Time-range picker](https://patterns.konigi.com/dashboards/time-range-picker) — Every question about a metric starts with 'over what window', and the control has to be fast for the common windows. - [Comment and annotate](https://patterns.konigi.com/dashboards/comment-and-annotate) — Two people are looking at the same spike and need to talk about it in place. - [Data source badge](https://patterns.konigi.com/dashboards/data-source-badge) — The viewer needs to know where a panel's data comes from and whether that source is healthy. ## Sources - [Grafana, Share dashboards and panels](https://grafana.com/docs/grafana/latest/visualizations/dashboards/share-dashboards-panels/) - [Nielsen Norman Group, Visibility of System Status](https://www.nngroup.com/articles/visibility-system-status/) - [Bach et al., Dashboard Design Patterns](https://dashboarddesignpatterns.github.io/patterns.html) --- Screenshots on patterns.konigi.com are reproduced for commentary and criticism. Product names and marks belong to their owners.