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Maps was released as generally available (GA) in Kibana 7.3. Reaching production-ready is not the final destination, but just another stop on a long journey. Each Kibana point release includes so many incredible features that it’s hard to keep up with them all. So, as 2020 comes to an end, let's look back and revisit some of the most impactful features since going to GA.
1. No loading screen when switching to Maps
Moving between Kibana applications is now immediate, with no loading screen. Seamlessly flow from Dashboard to Maps to Discover as you quickly find, analyze, and share your data. This was no small feat. The Kibana team has been working behind the scenes for more than 18 months to re-think Kibana’s entire architecture and remove the need for the loading screen between applications.
2. Embed Maps in Canvas
Canvas lets you create expressive, pixel-perfect reports backed by live data, making it a popular choice for management dashboards and highly visible large screen hallway displays. Location data is increasingly becoming a critical component within this kind of business reporting. Whether you’re looking at endpoint security threats, search metrics, or trying to gain a unified view of your logs, metrics, and APM traces — the need to incorporate a geospatial perspective is real. To support this effort, you can embed maps directly into Canvas workpads.
3. Dashboard-first experience and dashboard to dashboard drilldowns
Dashboards are what make Maps a powerful analytic tool. Viewing data from different angles provides better insights. Dimensions that are obscured in one visualization are illuminated in another. We have minimized the number of steps it takes to build a map and add it to a dashboard, streamlining dashboard authoring by getting you instantly back to your original starting point when you create or edit a map from a dashboard. This new “save and return” behavior simplifies the process for updating maps by removing the need to ever have to think about navigating away from, or back to, the dashboard you are using.
As soon as you create more than a single dashboard, you will want to define custom analytical navigation paths between dashboards. Dashboard drilldowns act as repeatable workflows to guide viewers in certain directions. A scenario where this is highly useful might be if you want to provide drilldown paths from a high-level observability dashboard to more granular analyses that incorporates additional data from APM, logs, or uptime. With map panels, you can now provide drilldown options for your viewers (e.g., “draw a spatial filter to drilldown to application traces, click a country name to drilldown to real user monitoring for that region,” etc.). Even better, you can also provide drilldown paths from those granular dashboards that drill back up to the higher-level view, so no matter where a viewer starts their journey, they have built-in ways to expand their perspective of the data. View this webinar to learn more about dashboard drilldowns.
4. Simplified upload of files with latitude and longitude data
We’ve updated file upload to recognize and combine latitude and longitude fields in file uploads. This process automatically creates a geo_point field in the resulting Elasticsearch index and saves you the time of manually having to configure this during import.
Whether you’re sifting through suspicious IP locations as a security practitioner or trying to understand why users hitting your site from a certain part of the world are experiencing performance issues, the need to quickly zero in on specific locations is real. Maps has added a powerful way to accomplish this goal with the fit-to-data button. Located under the left-hand zoom controls, this new button makes centering and zooming in on just the visible data points as easy as clicking your mouse one time. Don’t want to click a button? Enable auto fit-to-data and let the data drive exploration of the map, triggered by filters and data refreshes.
6. Categorical styling and custom color ramps
Want to color the data points on your map based on the discrete values in a categorical field? Say you have data with flights from cities across Europe and want every airport within the same country to have the same color. With categorical styling you can do all of that quickly using a single layer. Choose the custom colors you want or let Maps take care of that for you with a default palette.
7. Blended layer
Visualizing large amounts of data when it comes to mapping can be a challenge. On one hand you want to display all features for the area you are zoomed into. On the other hand, keeping that accuracy as you zoom out can quickly lead to visual confusion as the increasing number of features being shown can overwhelm your view.
Blended layers solve this problem by showing clusters on a map until zoomed in. When results exceed index.max_result_window, the layer uses GeoTile grid aggregation to group your documents into clusters and displays metrics for each cluster. When results are less than index.max_result_window, the layer displays features from individual documents.
An example of where this can be especially useful is any time you are mapping features in both dense urban areas as well as more rural locations. It might be the case that in a more sparsely populated region, your map view is fine to show every location. However, panning over to a large city might suddenly explode the number of features that need to be shown. Blended layers help you make that transition smoothly by simply aggregating the visual representation of the features while still conveying their total number.
8. Cluster lines and polygons
GeoTile grid aggregation is no longer just for points! You can now use GeoTile grid aggregation for all of your geometry, including lines and polygons. Unleash Elasticsearch’s scalability and show clusters, grids, and heatmaps for lines and polygons.
9. Text labels
Add and customize labels within the layer style panel. Provide your viewers with more information about the data you’re overlaying on your map and even format the label size and color to fit your analysis.
10. Tracking alerts
With tracking alerts, you can monitor the location of entities in real-time and trigger a notification or write-back to an index when any entity enters a specified boundary. This is a beta feature at the time of writing.
11. Vector tiles from your Elastic indices
Vector tiles are a modern technique for delivering large amounts of data. The benefit is that your map will load faster and interacting with your data will feel fast and fluid. Using vector tiles allows you to extend what is possible in the Maps app -- with clusters and grids, there is a new “super fine” option, allowing you to see even more detail in your dataset. Also, the document limit imposed by Elasticsearch is now per tile. If you are accustomed to working with 10,000 documents in total, now you can work with 10,000 documents per tile! The number of tiles will vary depending on zoom-level; but the impact is the same -- more data for you to explore and analyze. This is a beta feature at the time of writing.
12. EMS basemap vector tiles
The basemaps provided by the Elastic Maps Service are now lighter, sharper, and smoother when panning, zooming, and navigating your map. That's because the basemaps have been upgraded from raster tiles to vector tiles. Our maps are now as seamless to interact with as Google maps, which also use vector tiles for their basemap.