Documentation
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Momentum
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MLOps
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Impulse EDW
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- 2.1 Create a Warehouse
- 2.2 Edit Warehouse
- 2.3 Datasources In Warehouse
- 2.4 Ingesting Data Into Tables or Datasources
- 2.4.1 Ingesting From Momentum Data Pipeline
- 2.4.2 Uploading File Using Impulse UI
- 2.4.3 Ingesting From External File/Storage System
- 2.5 Add Data to Existing Tables
- 2.5.1 Update Existing Index
- 2.6 Delete Table Records (Rows)
- 2.7 Delete Tables or Datasources
- 2.8 Monitoring Indexing Tasks
- 2.9 View Datasource Stats
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Inset BI
- Alerts and Reports
- Connecting to a new database
- Registering a new table
- Creating charts in Explore view
- Manage access to Dashboards
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- Articles coming soon
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- Articles coming soon
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- Articles coming soon
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- Articles coming soon
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- Articles coming soon
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APIs
- Articles coming soon
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Integrating MLOps with Momentum
Momentum provides a 1-click deployment of ML models to MLOps. Before deploying a model to MLOps, make sure that Momentum is properly configured to locate the MLOps deployment.
Check Settings and Configuration and ensure the following properties are configured correctly:
Parameters | Example Values | Explanation |
MLOPS_URL | https://host1.momentum.local:9443 | Use internal hostname or IP and not public domain/IP. Contact your admin to obtain the hostname where MLOps is hosted. Momentum internally communicates with MLOps using this host and port and therefore for security reason, use an internal host:port. |
MLOPS_PUBLIC_URL | http://<public-ip-or-domain>:9443 | This is public hostname and port to access the MLOps UI and securely login to access its services. |
MLOPS_TOKEN | See the MLOps Token How-tos | This is a security token that is used to communicate with MLOps for security. |
MLOPS_CLUSTER | default_cluster | MLOps can seamlessly deploy models in various environment such as QA, sandbox, staging, production that may be either local server, Azure, AWS or any other cloud service providers. The deafult_cluster means the model will be hosted within the same machine where MLOps is deployed. |
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