Community Discussions

I hear that the Charts monitoring feature includes logic to prevent excessive and unnecessary alerts.Specifically, time series data uploaded at intervals longer than one minute is excluded from monitoring, and alerts are not triggered for such data.The reason for this is that the system cannot determine whether a lapse in recent values over a certain period is due to “legitimate low-frequency data” or “a system error causing missing data.” On the other hand, we have some time series with very low update frequencies.For example, we have data that is ingested only once every half day (see figure below).With such data, the Charts monitoring feature cannot detect anomalies and alerts are not triggered.*We have no plans to increase the number of acquisitions due to wireless system specifications. Could you consider adding a switch to the Charts monitoring feature that allows users to disable the current specification that excludes data uploaded at intervals longer than one minute from monit

To change the columns that are shown when selecting a specific View I use the “Select column” functionality. If I select multiple properties from the list and press Apply, it works well.However, if I locate the property by “Filter by name” search, select, and then repeat for another property, only the last property I selected will be added when I press Apply. You see the same behavior if you “Filter by name”, select a property, and then remove the filter characters either by deleting the characters or “x them out”, the selection is removed.This is a very unexpected behavior, and confuses users. It makes it very cumbersome if you want to add multiple properties from a very long list of properties (where you would prefer searching for the property)

There is a need to save the filter and grouping settings in InField check lists so that a user don’t have to set these manually each time he enters a new check list.This is both relevant for filters (I.e status filters to only show outstanding functional locations/assets) and also for the new grouping functionality where users can group tags by properties.For example if a user always want to filter out not relevant (Status) f.loc/asset and always group assets by location (Property) then he will have to manually each time he enters the check lists set these settings. It would save time for the user if these criteria can be saved. Either by filter-variants that can be chosen, or as standard for the user.

Recently, the use of Charts has been increasing, and more users are creating complex calculations for data visualization.In this context, we have received feedback requesting a “Back” button (undo function).When users are building complex calculation formulas, there have been multiple instances where the calculation source suddenly disappears, forcing them to restart from scratch. The more complex the calculation, the greater the impact of this issue.To mitigate this, it would be extremely helpful to have a function that allows users to go back one step (e.g., an undo or back button).We believe this feature would significantly improve usability and reduce the risk of losing work during calculation editing. Thank you for your consideration.

This might already be reported, but I was not able to find it when I searched.Currently Chart only uses an internal, and very limited, unit conversion. It would be a big step forward if we could also use the native unit conversion in timeseries, which is much richer than what is offered via Charts.Since you might have timeseries with no CogniteUnit, Charts still needs to support unit conversion defined in the UI, as a backup solution 

Would it be possible to provide a way to visualize trending content that is frequently viewed and utilized among those created using Charts, Canvas, and Streamlit?At present, even if someone creates an excellent Canvas or similar content, it does not easily spread to other users. However, if there were something like a trending ranking, high-quality content could naturally gain visibility and adoption. It could also serve as a helpful source of ideas for practical use cases.

Observed behaviorWhen a CDF Transformation produces rows with duplicate externalId values , the behavior depends on how CDF partitions the data across workers:Duplicates within the same API request (same batch) → the API raises an error → the transformation fails visibly ✅ Duplicates split across multiple API requests (different CDF partitions/workers) → each request succeeds individually → the transformation completes with status "success", but which version of the node was actually written to the knowledge graph is unknown and non-deterministic ❌ProblemThe second case is the dangerous one:Silent and invisible — the run reports success, no alert is triggered, no engineer investigates. The data in the knowledge graph may be incomplete or wrong with no trace. Non-deterministic — which duplicate "wins" depends entirely on which CDF worker flushes first. Two identical runs on the same input can produce different results. No user control — there is no way to express intent: "fail if duplic

 SummaryEnable aggregation operations (such as step_interpolation) on requests containing both numeric and string time series in the same SDK call.Currently, aggregation works correctly for numeric time series, but the request fails when a string/alphanumeric time series is included alongside numeric series. This limitation prevents users from retrieving synchronized operational datasets that combine process measurements and categorical/status information in a single query.Problem DescriptionWhen using the Cognite SDK method retrieve_dataframe() with aggregation enabled, requests containing mixed data types fail if at least one time series is of type string.Example:Numeric-only aggregation → works correctly Numeric + string aggregation → failsThe expected behavior for string time series using step_interpolation is to replicate the last known value across the aggregation interval, similar to how industrial historians such as PI System behave.Example Use CaseOperational dashboards and an

Hi,It would be great to have the creation of an endpoint based on the one below:https://api-docs.cognite.com/20230101/tag/Time-series/operation/getMultiTimeSeriesDatapointsCurrently, this endpoint allows requesting multiple items in a single call and returns the next page individually for each requested item.For Celonis’ REST extractor, this pagination model creates a limitation, as the platform works better with individual pagination, where each response contains only one component and a single pagination continuation token.Today, to enable this extraction, a Python-based workaround is being used within the environment, since the current model is not compatible with the standard extractor.We would like to check if it is possible to make the endpoint available in a more individualized format, with one time series per response, or if there is already an alternative endpoint that supports this scenario. This would greatly help improve the standardization and stability of the integration.

This idea is related to a previously submitted request:https://hub.cognite.com/product-ideas-492/charts-canvas-streamlit-lock-feature-to-prevent-accidental-deletion-6058?tid=6058&fid=492In most cases, charts with scheduled calculations are highly important. However, currently there is no clear way to distinguish them from regular charts in the list view, which creates a risk of accidental deletion.If a scheduled chart is accidentally deleted, the schedule itself may continue to run, but users would no longer be able to review or verify the calculation logic.To prevent this, it would be helpful to have:A clear visual indicator showing that a chart has a schedule configured, so it can be identified at a glanceA warning message when attempting to delete such a chartAdditionally, it would be even more useful if there were a filter option to display only charts with schedules.

When scheduling calculations created in Charts, the calculated time series is currently written starting from the time the schedule is configured. However, there are many cases where we would like to apply these calculation results to historical data as well.For example, it would be helpful if users could specify a start point in the past using options such as:・“6 months ago,” “1 year ago,” or “3 years ago” from the current date・A specific date and timeWould it be possible to add an option that allows users to apply calculation results starting from a user-defined point in the past?

Two needs:- I want to monitor time series in charts for windows longer than 60 minutes. Current limit is 60 minutes and should be longer.- I want to subscribe common emails to monitored time series (for example <asset-specific.process-engineers>@akerbp.com). Current limitation is that only individuals can subscribe to monitored time series. This is an issue for roles on rotations.What impact would a change have? Time savings Fewer errors / less manual work Better decision-making foundation Better data qualityRequested by: Sindre Fjermedal