Developer Community

Hi Cognite Team,I'm building a React dashboard using Cognite Data Fusion for my portfolio and would like to know if there are any demo projects available for working with CDF data.

Hello,What are the best practices around setting the max-workers for a sdk. If I do not set the Global Config all the default values for workers and retries would be picked correct ? Can you give any reference on how we can set GlobalConfig, I mean I did not see any way to pass the GlobalConfig to ClientConfig ?

Hello,I am running a function ‘dq_validate_model_integrity’ and ‘dq_validate_broken_references’ which give a 403 unauthorized error for a timeseries intermittently. There has been no change in access or data yet its failing sometimes with a 403 error.Could you please let us know why this issue is coming up frequently?PS: I have attached the screenshots of the passed and failed statuses of both functions with the timestamp as well as the logs of both failed functions. Do let me know if there’s any more information required from my end. Thanks alot :)

I created an asset hierarchy with the Cogntie Core Data Model, then I created a custom data model through neat and I need to migrate the assets from the core data model to the custom extended data model, I tried creating a transformation but got the following error: failed with status 403: Properties [assetHierarchy_path, assetHierarchy_path_last_updated_time, assetHierarchy_root] are maintained by DMS and cannot be modified by end users. is there a way I can migrate/update the core data model assets to our extended data model?

I’m trying to use Update extraction pipelines method to update my extraction pipelines created. Here are some issues i face:1. I’m unable to update contacts for an extraction pipeline, it throws the below error:code - contact_info = [ExtractionPipelineContact(name="sangs", email="sm6@slb.com", role = "MAINTAINER", send_notification=True)]to_update = ExtractionPipelineUpdate(external_id="<PIPELINE-EXT-ID-2>")to_update.contacts.set(contact_info)client.extraction_pipelines.update(to_update)error - “CogniteAPIError: Unexpected field - items[0].update.contacts.set[0].send_notification - did you mean sendNotification? | code: 400 | X-Request-ID: 918d1113-6a5e-9d38-b850-61e3dc54c220 The API Failed to process some items. Successful (2xx): [] Unknown (5xx): [] Failed (4xx): [<PIPELINE-EXT-ID-2>, ...]”2. I’m unable to set the specified fields to None using sdk : description, source, schedule,documentation, name and dataset-id. Im able to set only metadata and raw-tables to None. Wond

Hi Cognite Team,Is there any document which can show , how to fetch confidential information from private end point key vault  on Microsoft azure key vault. 

Description / Problem StatementWe are using the Cognite 3D File Extractor to migrate 3D model files from an on-premises Windows VM to Cognite Data Fusion (CDF).The majority of 3D files are ingested successfully with multiple sizes mostly > 10 GB. However, four specific files consistently fail ingestion, even after multiple retries.Key observations:All failing files are close to 5 GB in size Example sizes (as shown in Windows Explorer): 4.99 GB 4.94 GB 4.91 GB When checked via terminal/command line, these same files report a larger actual size (~5.3 GB) It appears that based on the Windows VM file size, the 3D extractor determines it should use a single-part upload. However, when it attempts to upload the actual file, the process fails because the size exceeds 5 GB      

Hi everyone,While querying the CogniteAsset view, I encountered an error when including the activities field in the selection. The API returns the following message: "Cannot traverse lists of direct relations inwards." Upon investigating, I noticed that the activities field in the CogniteAsset view is defined as a @reverseDirectRelation: activities: [CogniteActivity] @reverseDirectRelation(throughProperty: "assets") In turn, the assets field in the CogniteActivity view is defined as a list of direct relations:assets: [CogniteAsset] @directRelationThis makes sense as the root cause, since reverse traversal over a list of direct relations is not allowed, which explains the error.Given that this field leads to an invalid query pattern and always results in an error, should the activities field be removed from the CogniteAsset view to avoid confusion and runtime errors? Here’s a minimal query that reproduces the issue:query MyQuery {  listCogniteAsset {    items {      aliases      activit

I’m getting the below error details when trying to access a new sandbox environment that has been setup.  What details do I need to share w/my team to unblock access?Your network administrator has blocked accessExternal access is blocked by policy. Contact your IT department for access. Troubleshooting detailsIf you contact your administrator, send this info to them.Copy info to clipboardRequest Id: f3b6e072-9289-427c-97e4-766a40af0700Correlation Id: e24e2dc7-9a3a-488c-92a3-fb333dc35281Timestamp: 2026-06-01T21:34:21ZMessage: AADSTS500021: Access to 'XXXXXXXX' tenant is denied. App name: Cognite Data FusionDevice platform: Windows 10Device state: UnregisteredIP address: 35.199.59.75Signed in as: XXXXXXXXXXFlag sign-in errors for review: Enable flaggingIf you plan on getting help for this problem, enable flagging and try to reproduce the error within 20 minutes. Flagged events make diagnostics available and are raised to admin attention.

Hello, Currently using cdf-tk version 0.5.111. The bySpace param on btree indexes is not yet supported in this version.We are trying to migrate to version 0.7.220. Although, this version sets correctly the bySpace param on indexes it does not seem to resolve correctly the view dependencies in our data model.Error trace:  Deploying 375 views to CDF...WARNING [MEDIUM]: Found a strongly interdependent set of 75 views: sp_dm_dap_knowledge_graph:BHAComponent(version=4.3), sp_dm_dap_knowledge_graph:BHARun(version=4.3), (...)sp_dm_dap_knowledge_graph:WellPath(version=4.3), sp_dm_dap_knowledge_graph:Wellbore(version=4.3) and sp_dm_dap_knowledge_graph:WellboreSection(version=4.3). This might indicate a data model design issue, and the deployment might fail due to API batch size limits.Traceback (most recent call last):  File "pypoetry/virtualenvs/drillx-dwdap-cdf-toolkit-fxS2v_xU-py3.13/bin/cdf-tk", line 8, in <module>    sys.exit(app())             ~~~^^  File "pypoetry/virtualenvs/drill

What capabilities are required to run a transformation using client credentials? I have a client_id and client_secret that when I add to the transformation and hit ‘Test credentials’ it says ‘Credentials verified’. However when I run with client credentials I get an error: Transformation job could not be created. Error code: 403 API error: Invalid source/destination credentials: Token did not provide access to project kuraray-america. Request ID: eb5136ee-594d-971f-b27a-7be0d1a60b15these credentials are a part of a group that that has read and write capabilities to:transformations sessions datamodelinstances (that is what this particular trasformation is creating)Additionally I am part of the same groups as this client_id, and I am able to run the transformation using ‘run as current user’ successfully

I'm using python sdk and wanted to query instances based on a condition using “data_modeling.instances.query” method. i have a view “TimeseriesProperty” and it has a direct relation/reference to "TimeseriesPropertyType" view. Is it possible to have a distinct filter on the result, because multiple “TimeseriesProperty” instances can have the same "TimeseriesPropertyType"  instances , we don't want duplicated "TimeseriesPropertyType"  instances coming in response for below query: view_id= ViewId(space="slb-pdm-dm-governed", external_id="TimeseriesProperty",version="2_0")v_id_2_PROP = ViewId(space="slb-pdm-dm-governed", external_id="TimeseriesPropertyType",version="2_0")query= Query( with_= { "TimeseriesProperty":NodeResultSetExpression( limit=10, filter= HasData(views=[view_id])), "TimeseriesPropertyType":NodeResultSetExpression( limit=10000, direction="outwards",

The MQTT hosted extractor is erroring out and showing the following message: Internal database error: Session has expired: Session was not foundI’ve tried pausing and resuming the extractor, and modifying the configured sink, without success.

Use CaseI am building a dashboard in Power BI that will visualize Events from CDF (about one million events per year). So to make the solution scale I want to use incremental refresh of the semantic model so I only refresh the model with the newest Events since the last refresh.I have followed your tutorial on Incremental refresh (which seems copy/paste of Microsoft’s tutorial), but I still have questions:What happens if the StartTime attribute of an Event is a date/time/zone when loaded into the model? The attribute needs to be a date/time type, which means I need to convert the type first. How will the incremental refresh work if the model needs to load the data in order to convert the type, and then apply the RangeStart/RangeEnd filters? Can I use Incremental refersh with the new REST API Connector? When I load events with the new connector I get the start times as number of milliseconds since epoch. So the type conversion from above also applies here. Thanks for your help!Anders

Hello, When I’m connecting to the virtual machine Ubuntu, I’m facing a pop-up “connection failed”. It seems that my internet connection is not set up, do you have any idea to do so ? I’m not able to do rest of the training without connection. Thanks 

Hi Everyone,I need to create query like it is creating on cognite UI’s  like   { "listEntity": { "with": { "0": { "limit": 50, "nodes": { "filter": { "and": [ { "matchAll": {} }, { "hasData": [ { "type": "view", "space": "slb-pdm-dm-governed", "externalId": "Entity", "version": "1_7" } ] }, { "or": [ { "and": [ { "nested": { "scope": [ "slb-pdm-dm-governed", "Entity/1_7", "parent" ],

Hi Everyone,Is there a way to create an alert directly on a calculated series in Cognite Charts?From what I’ve found, to create an alert for a calculation, I first need to schedule the calculation and then run the alert on that scheduled result. However, scheduling doesn’t seem to work well in my case.For example, if I receive machine data every hour, I also need to schedule the calculation every hour. Sometime scheduling stops by itself. It would be much easier if we could create alerts directly on the calculation without scheduling.Secondly, I’m not finding clear documentation or videos on how to schedule calculations properly and what best practices to follow. If anyone has experience with this or can share guidance, please let me know.Thanks!   

Hi,We're using the Cognite DB extractor (version 3.9.2) with a MongoDB database (Azure Cosmos DB via the MongoDB API) and are trying to set up incremental loading.The documentation for mongodb (https://docs.cognite.com/cdf/integration/guides/extraction/configuration/db#databases.mongodb) doesn't mention the use of start_at and incremental_field but after testing them and looking at the debug logs, we can see the extractor sends the {start_at} placeholder literally without substituting the state value. My questions are:    1. Is start_at substitution supported at all for MongoDB JSON queries, or is it SQL-only?    2. If incremental loading is not supported for MongoDB, is there a recommended workaround?Thanks.

Hello,I’m looking to compute the standard deviation of a timeseries on the fly with synthetic timeseries.I expected to use this pseudocode formula : sqrt(avg(pow(TS{externalid}-avg(TS{externalid}),2))) with endpoint :client.time_series.data.synthetic.query(    expressions=expression,    start="2w-ago",    end="now")Unfortunately, avg expect at least 2 inputs, I try to switch to aggregate feature but I found it available only for timeseries, not synthetic timeseries.expression = '''sqrt( avg( pow( ts{ID} - ts{ID, aggregate="average", granularity="14d"}, 2 ) ))'''Do you have any tips or workaround to compute this value when “start” value changes ? Dont hesitate to explain I'm open to any opportunity to calculate this metric using another method.Thanks in advance,Pierre edit : I find this function in additionnal library : Rolling standard deviation of data points time delta — indsl 8.7.0 documentation but i’m looking for a answer without additionn

Hi team,  do you have 2-3 articles on how to get started, like a simple quick start example as a starting point to be acquainted with the service ?Thanks !FYI ​@Marwen TALEB 

Hi,I have been updating the beta documentation a bit since the last edition linked in the invitation. This applies to both the planned standard Cognite documentation, and the developer API documentation. All of the documents are available using a direct link to our document rendering services (linked below), and should be updated as we privately deploy new information.Note that all of these documents are works in progress with ongoing updates, so please forgive any typos, omissions, and other errors at this stage: Streams API documentation Records API documentation Capabilities for CDF Records Updated Data Modeling concepts page Concepts page for CDF Records (and Streams) Example high level use case (alarms) for CDF RecordsPlease do not share these documents.

Hello Experts,I’m trying to use advanced filter on timeseries through SDK. I can do what I want except in the following situation: the asset_id property is null. Can anyone help me?I tried :from cognite.client.data_classes.time_series import TimeSeriesPropertyf = filters.And( filters.Equals("data_set_id", 123456), filters.Equals("name", "foobar"), filters.Equals(TimeSeriesProperty.asset_id, ""))[advancedFilter.[2].equals.value A string is not a valid value for the property "assetId"]from cognite.client.data_classes.time_series import TimeSeriesPropertyf = filters.And( filters.Equals("data_set_id", 123456), filters.Not(filters.Exists(TimeSeriesProperty.asset_id)),)-> 0I’m sure there is timeseries where timeseries.asset_id is None.Thanks experts !Regards,Pierre Rambourg

Hello esteemed members of the Cognite community,I come to you with a sense of urgency and a deep need for expert guidance. I've been attempting to familiarize myself with Cognite for the last six months, and despite my best efforts, I find myself at an impasse with some critical aspects. My situation is time-sensitive, and I am truly hoping for your assistance to navigate this complex but fascinating journey.My Setup:Environment: Google Colab (Free version)SDK: Cognite Python SDKAssets: Wind Farm with two sub-assets (Asset A and Asset B)My Goals:Connect to Cognite Project via Python SDK: I need to use my client ID and client secret to establish a connection from Google Colab.Create Hierarchical Assets: My aim is to create a parent asset, named "Wind Farm," and within this parent asset, include two child assets, Asset A and Asset B.Upload Time-Series Data from CSV: I have CSV files containing wind-speed and wind-power data for Asset A and Asset B. I need to upload these as time-series d

Hello,  We are using: Toolkit Version '0.5.20' We are having a file schedules.Function.yaml: - name: Run every 10 minutes to do some work functionExternalId: fn_name description: Run every 10 minutes to do some work cronExpression: "*/10 * * * *" data: extractionPipeline: "test"When deploying we have this error trace: Traceback (most recent call last): File "venv/bin/cdf-tk", line 8, in <module> sys.exit(app()) File "venv/lib/python3.10/site-packages/cognite_toolkit/_cdf.py", line 116, in app _app() File "venv/lib/python3.10/site-packages/typer/main.py", line 340, in __call__ raise e File "venv/lib/python3.10/site-packages/typer/main.py", line 323, in __call__ return get_command(self)(*args, **kwargs) File "venv/lib/python3.10/site-packages/click/core.py", line 1161, in __call__ return self.main(*args, **kwargs) File "venv/lib/python3.10/site-packages/typer/core.py", line 740, in main return _main( File "venv/lib/python3.10/site-packages/typer/core

How much time does it really take to build a full solution?We deployed a complete solution using Cognite CDF, Cursor, and Anthropic Claude Opus 4.6, powered heavily by Gen AI in just 4 hours.This was not just a prototype screen. It was a fully deployed solution for demo purpose.And here’s the most interesting part:All of the following steps were done using Gen AI:1️⃣ Creation of the data model in Cognite Data Fusion and the Terraform2️⃣ Deployment of the model in Cognite3️⃣ Data generation and ingestion into the Cognite Data Platform4️⃣ Development of a React application on top of Cognite using the Cognite SDK5️⃣ Creation of: Asset Map, KPIs, Production Time Series Dashboardand Well Intervention viewFrom data modeling to frontend application — accelerated with AI.This is not about replacing engineers.It’s about dramatically increasing speed, experimentation, and delivery capacity. The question is no longer “Can we build it?”It’s “How fast can we build it?”Post here!