Run analytical processes in the cloud without the need to provision servers or manage infrastructure. In addition, you will save money by paying only for the computing capacity used.
Your data scientists can focus on doing their job, being able to deploy their solutions in a productive cloud environment completely autonomously, without requiring cloud architecture or data engineering skills, and in the industry standard code languages: SQL, Python, R, or Docker containers.
Intelek compute module allows you to maintain a registry of algorithms by linking to git code repositories. Once your algorithms have been defined and the parameters they require have been declared, you can create execution tasks, defining the branch of the repository to use, the algorithms to execute, the appropriate parameter values and the execution time using crontab-type rules.
Upload algorithms manually or select them by browsing git repositories:
Github, GitLab, Bitbucket, or CodeCommit.
SQL scripts, Python, or Jupyter notebooks.
Declare the parameters or variables of your algorithms to be able to manage execution tasks with different input values.
Parameterize SQL, Python, or Jupyter scripts.
Define the set or range of valid values of the parameters.
Create your execution tasks based on the algorithm registry.
Choose the algorithms and the order of execution.
If you have parameterized algorithms, define the parameter values to be injected.
You can run your tasks manually at any time or in an automated way:
Periodic execution using crontab rules.
Execution on demand via API from your IT systems.
User grants for allowing the deployment of algorithms.
Computing resources limits at user or group level.
Grant task execution rights to groups of users.
Real-time inishgts of the status of the executions in progress.
Tasks execution history
Errors, type and detail of errors
Duration of executions
Access to the logs issued by the algorithms.
Global CPU-usage statistics of the computing module.
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