Polyaxon's new MLOps sandbox feature
At Polyaxon, we're always looking for ways to push the boundaries of what's possible with machine learning infrastructure, this is why we are excited about the upcoming sandbox deployment capabilities.
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Practical guides to building, running, and improving ML and AI in production.
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Manage cloud infrastructure for ML platforms
Operate cloud infrastructure for ML with declarative provisioning, clear ownership, workload isolation, capacity policies, cost allocation, and recovery exercises.
CloudInfrastructureMLOps
How Polyaxon streamlines MLOps
At Polyaxon, we're always looking for ways to push the boundaries of what's possible with machine learning. Our MLOps platform makes it easy to manage the entire lifecycle of your machine learning models.
MLOps
Kubernetes network policies: an actionable guide
Use Kubernetes network policies to control pod traffic, restrict lateral movement, and make cluster networking less permissive by default.
KubernetesGuides
Polyaxon v1.18: Improved run control
The run control, i.e. cog icon, is now visible on all tabs to allow users to easily perform actions on a run
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Polyaxon v1.18: New comparison features
Polyaxon UI has new features that allows users to quickly compare and filter their runs
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Polyaxon v1.18: New Tensorboard component and initializer
You can now start Tensorboard using the experiment names instead of the experiment uuids
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Plan GCP Persistent Disk for ML workloads
Choose, size, monitor, and retire Google Cloud Persistent Disk volumes for training, notebooks, caches, and stateful ML services.
GCPStorageMLOps
Polyaxon v1.18: Improve CLI with rich interface
We recently worked on an effort to improve the visual experience our CLI
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Polyaxon v1.18: Support for annotations and env vars in connections schema
You can now define annotations and environment variables in your connections' schema
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Polyaxon v1.18: Improved query language
Users can now filter by connections and artifacts
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Polyaxon v1.18: Admin command to force clean operations
Admin users with access to kubectl can now force kill operations in a namespace
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Polyaxon v1.17: Pulling & Pushing runs
Users can now package and pull runs to local paths or push runs from local paths to a Polyaxon deployment
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Polyaxon v1.16: Inspecting chart data
Using the line chart widget you can now inspect the underlying data as an interactive table.
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Polyaxon v1.16: Transferring runs, models, components, & artifacts
Users can now transfer runs, models, components, & artifacts from one project to another to reorganize their workspaces
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Polyaxon v1.16: Progress tracking
Users can now log the progress of their runs and have a progress bar in the UI to get a quick overview of their runs.
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Polyaxon v1.16: CLI Operation shell & inspection
Improved inspection and monitoring capabilities and Container Shell debugging capabilities in the CLI.
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Polyaxon v1.16: Automatic CSV/TSV/Dataframes/... rendering
Polyaxon UI can now render CSV/TSV/Dataframes/... automatically as a table
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DataOps vs. MLOps: Differences and How They Work Together
DataOps delivers reliable data; MLOps delivers reliable ML systems. Compare their responsibilities, checks, and handoffs using a practical example.
MLOpsDataOps
MLOps vs DevOps
How MLOps is different from DataOps.
MLOpsDevOps
Polyaxon v1.15: Global Search & Recently Viewed
Users can search organizations they belong to and project they have access and access recently viewed items.
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Using kubectl logs
Use kubectl logs to inspect pod, container, and owner resource logs, including timestamps, tailing, selectors, and recent output.
KubernetesGuides
Kubernetes vs. Docker for ML workloads
Understand how Docker containers and Kubernetes orchestration solve different parts of the ML delivery path, from reproducible images to scheduled production workloads.
KubernetesDockerMLOps
Polyaxon v1.14: Component Latest Runs
Users can quickly search by a specific component and see recent runs for a specific component.
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