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Team, I am trying to schedule math functions, specifically addition of 4 tags and averaging of 4 tags.These need to run specifically at 10:05am as these are totals that are reported once a day, at approximately 10am EST.How can this be done and make these values available for use in Grafana? Thanks for helping!

I used to run this version to upload simulator connector, model and routines, but it is not working anymorehere is the error I pydantic_core._pydantic_core.ValidationError: 3 validation errors for PagedResponse[GroupResponse]items.324.capabilities.6.acl.scope.scope_nameInput should be 'all' [type=literal_error, input_value='agentExternalIdScope', input_type=str]For further information visit https://errors.pydantic.dev/2.13/v/literal_erroritems.526.capabilities.6.acl.scope.scope_nameInput should be 'all' [type=literal_error, input_value='agentExternalIdScope', input_type=str]For further information visit https://errors.pydantic.dev/2.13/v/literal_erroritems.639.capabilities.6.acl.scope.scope_nameInput should be 'all' [type=literal_error, input_value='agentExternalIdScope', input_type=str]For further information visit https://errors.pydantic.dev/2.13/v/literal_error

I am program manager with one of IT service organization. I want to know, what all the courses i need to complete in order to make sure i have all the information i need in order to manage a program?

Hi All,I just created an Asset in the Cognite Fundamentals workspace, following the guidelines from the course. After following all the steps mentioned I was expecting to find the asset Pranav1992 in the Search under Other Categories after logging into Industrial Tools workspace.However, upon filtering I do not see it there, can someone please help if I missed something?Thanks,Pranav

Hello experts,I have a question about Cognite Functions. I know there’s a limit on the size of the input data, as discussed here : Cognite Hub and documented there : Cloud provider limitations - Cognite Docs But is there a limit on the size of the function’s output? I have one that works perfectly fine but crashes without any explicit error message when handling a large output payload (>500 KB). I’m on Azure provider.Is there any information on this? Thank you,Best regards,Pierre Rambourg edit : the initial error was on my side, but i’m still interested for output limits !

Hi Cognite Team,We are currently defining an integration pattern for a partner who will provide data from an OPC UA source into Cognite Data Fusion.Our preference is to use a managed MQTT broker in CDF and avoid deploying any self-hosted MQTT broker or additional bridge components on-prem.Based on the documentation, we understand that the OPC UA Extractor supports an mqtt: output mode, but it also references a requirement for the MQTT-CDF Bridge and a configured broker host/port.To ensure we define the correct and supported architecture, could you please clarify: Is it supported to configure the OPC UA Extractor to publish directly to the Cognite-hosted MQTT broker in CDF? If using the Cognite-managed MQTT broker, is the MQTT-CDF Bridge still required? Is a self-hosted MQTT broker mandatory when using the mqtt: configuration in the OPC UA Extractor? What is the recommended architecture today for a partner delivering OPC UA data into CDF using MQTT? Our intended target architectur

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

I'd like to inquire about the current status of the monitoring functionality in the workflow orchestration. Specifically, I'm interested in the setup for notification emails. It would be helpful to know if we are able to receive notifications in the event of a workflow failure. Could you please provide an update on this?

Hello experts,I’m looking to work with data workflows.I’m looking to trigger on node with a specific attribute (direct relation to another view) empty.I’m trying to work with the UI but I struggle with the Data modeling query validation.I don’t understand why the validation fails and what is the expected format for the query : JSON seems to be the expected format as seen here : But documentation uses YAML : https://docs.cognite.com/cdf/dm/dm_concepts/dm_querying#graph-query-examplesI’m a bit lost and I need your help. And my query : { "with":[ { "ts":{ "nodes":{ "filter":{ "exists":{ "property":[ "nameTranslations" ] } } }, "limit":1000 } } ], "select":[ { "ts":{ "sources":[ { "source":{ "type":"view", "sp

Hello Team,I am going through the using-cognate-python-sdk-data-modeling course and noticed that the notebook is not returning any datamodelingInstancesList.instances.When I checked the UI, I noticed that I don’t have enough permission to see the Data ModelsPlease advise…….  

Hi, i was asked to bump the toolkit version to 0.7.137 or higher, so we can enable some config for agents tools.When i tested i got some errors,Last run worked fine, on toolkit version 0.7.69 (last friday), for both pipelines below. I have tried both version 0.7.137 and 0.7.139, getting the same error on both Error (on dry run step) - synergi pipeline: Pipelines - Run 20260302.2 logs ^^^^^^^^^^^^^^^^^^^^^^^^File "/home/vsts/.local/lib/python3.12/site-packages/cognite_toolkit/_cdf_tk/apps/_core_app.py", line 367, in <lambda>….^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^File "/home/vsts/.local/lib/python3.12/site-packages/cognite_toolkit/_cdf_tk/client/api/functions.py", line 62, in retrievereturn self._request_item_response(^^^^^^^^^^^^^^^^^^^^^^^^^^^^File "/home/vsts/.local/lib/python3.12/site-packages/cognite_toolkit/_cdf_tk/client/cdf_client/api.py", line 115, in _request_item_responseresponse_items.extend(self._validate_page_response(response).items)

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.

Dear Community,I am facing an issue when attempting to pull data from CDF into Excel through OData connector,Main purpose is to have data pulled into excel & get periodically updated (+ historian)As the Data from InField is required to be pushed into a specific Excel format for external reports.However, the main issue is that after adding URL :https:// westeurope-1.cognitedata.com/odata/v1/projects/{myProductionProject}I immediately get the Navigator view ( no prompt to sign in yet) Then once I try to get any data, the login pop-up window is there, but is rejecting all authentication methods:for both current & alternate credentials  and this is for all levels of the URL -For Web API Key Value, I wasn’t too sure where to get it fromTo note, I know I have the required access, as I can pull data normally in PowerBI REST API,Please advise, does the organization that has that  project need to add anything on azure ENTRAID side to allow this? or is it a different mistake I am making?

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 colleagues!I was seeking the course “Data Engineer Basics: Transformation and Contextualize” but the original link is broken: http://learn.cognite.com/path/data-engineer-basics-transform-and-contextualizeReference: Cognite Hub What happened?

Hi , I have the CogniteActivity in the CDM/EDM data model which the assets is part of the model: Below is the sample data of CogniteActivity:This is the data model for Event in PDM:I tried to transform from CDM/EDM to PDM using below transformation, but i am not sure what is the script to transform CogniteActivity to PDM Event:And i got below error: Anyone know how can I transform CDM/EDM asset node reference to Event entities attribute? Thank you.

Hello everyone. I’m looking to use a package from github the same way I already use it in requirements.txt for Cognite Function.The format is :git+https://<token>@<url>@<branch>When I add this line in settings :Error during booting upTraceback (most recent call last):  File "/lib/python3.12/site-packages/packaging/requirements.py", line 35, in __init__    parsed = _parse_requirement(requirement_string)             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^  File "/lib/python3.12/site-packages/packaging/_parser.py", line 64, in parse_requirement    return _parse_requirement(Tokenizer(source, rules=DEFAULT_RULES))           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^  File "/lib/python3.12/site-packages/packaging/_parser.py", line 82, in _parse_requirement    url, specifier, marker = _parse_requirement_details(tokenizer)                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^  File "/lib/python3.12/site-packages/packaging/_parser.py", line 126, in _

Hi Guys,I tried to use a transformation from the SDK but i keep getting error on Transformation credentials. Do you guys know what I need to do to solve this credentials issue. I have check the current credential for the Service Account that I use and the access for tranformation has been granted. def fetch_raw_table_via_transformation(    client: CogniteClient,    db_name: str,    table_name: str,    calculation_date: Optional[str] = None,    columns: Optional[List[str]] = None) -> pd.DataFrame:    """    Fetch data by running a temporary CDF Transformation (uses Spark SQL engine).        This is the RECOMMENDED approach for production workloads:    - Runs on CDF's managed Spark infrastructure    - Handles billions of rows efficiently    - Server-side filtering and aggregation    - Can write results to temp Raw table or return directly        Note: Requires transformation permissions in CDF        Args:        client: CogniteClient instance        db_name: Name of the RAW database 

I have a bit of a conundrum here. I am trying to visualize the daily and weekly averages of a time series in Azure Managed Grafana v11.6.3 using the CDF datasource. Raw data is strictly on hourly resolution, and provided in CET/CEST. Grafana is set to browser tz (i.e. CET/CEST). I need the daily average to align with CET midnight (=23:00 UTC). I use these synthetic series parameters: aggregate='average', granularity='24h', alignment=82800000 (82800000 aligns the datapoints to the correct hour if I do aggregate='step_interpolation', granularity='1h'). The returned value is neither the UTC day average or the CET day average. It is exactly the average of the two. So from what I see it seems to be a 30-minute shift/interpolation in the backend. Case in point: CET day average for a specific day is 158,67, while its UTC equivalent is 159,83 (see screenshot). Neither value is found in Grafana for that day at 00:00 - here I see 159,25. Which coincidentally is equal to (158,67+159,83)/2. The ti

Hi Team, Is there any possibility that I can register for Bootcamp virtually or it can be in India location as I am from India.Also, want to know is the Bootcamp is for individual or group and the cost for attending the Bootcamp? Thanks,Navyasri Indupalli

Hello! I have got a new phone and am not able to restore microsoft authenticator from its backup.Could someboday please reset the MFA Access so that I can set up the authenticator again?

Dear Community,I have questions regarding the required access control for CDF  Canvas drag & drop featureand CDF Charts scheduling & creating a timeseries from calculation feature,As the people who use these features are usually granted read only capabilities (business users)But those two features I would assume require capability of writing to a dataset and files & timeseries create .I want to know what group permissions exactly need to be added for these users ( on the canvas&charts dataset)so that the new dataset start showing for them ( when needing to scheduel a timeseries in charts and drag/drop in canvas)So far we made an additional group, connected to the same azure group that includes the business users that have read only access,the permissions added to the new group are: timeseries read & write, files read & write ( scoped to the new dedicated dataset )but then, the new dataset still didn’t show in the drop down list for the business users ( in canvas

When doing the exercise “Valve mileage use case” of the Domain Expert training in CDF, this error appears (in Portuguese):It says:Competências necessáriasEntre em contato com seu administrador do CDF para solicitar as seguintes competências: timeSeriesAcl:WRITEIn English:Required SkillsContact your CDF administrator to request the following skills: timeSeriesAcl:WRITE Basically, someone should give me the timeSeriesAcl:WRITE permission. But who?   

Hello everyone,I observe a difference in behavior that I cannot explain.My input data, few datapoints, and before the value is 0, timeseries.is_step = TrueInput datapointsWith client.time_series.data.retrieve, behavior is as expected :And with every granularity results are okay as expected.Nevertheless, with client.time_series.data.synthetic.query it’s… different.that’s okthat’s okNot ok, why the result is not 2 groups : from 46 to 49 then 49 to 52 ? another wrong exampleWhy the start timestamp is 48 and not at 46 ? Again, the timeseries endoint is good : I have lost hope.If anyone has anything to try or an explanation, i’ll be grateful.Thanks in advance,Pierre 

Hi Everyone,We're currently managing multiple CDF Toolkit solutions in a mono-repo and evaluating whether to maintain this approach or migrate to a multi-repo structure. We'd love to learn from teams who've navigated through this decision.Current Setup (Mono-repo):1. Single repository housing multiple solutions with shared infrastructure. 2. Shared auth-governance across all solutions.3. Teams need independence but also need to prevent cross-team overwrites.We're Looking For: 1. Real-world examples: How did you decide between mono/multi-repo? What factors mattered most?2. Tooling patterns: How do you handle shared resources (auth governance) in multi-repo? How do you manage CDF Toolkit versioning across repos?3. At how many solutions/teams did you reach the limit of mono-repo and decide to switch to multi-repo?4. How do teams with multi-repos handle toolkit version synchronization? Do you enforce a minimum/maximum version across repos?5. Documentation (runbooks or migration guidelines)