Product Updates

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Air API General Availability

• OpenAI-compatible API: Use existing OpenAI SDKs and code to access AirCloud models with minimal changes.
• Public pricing: Per-token pricing is now published for all models with pay-as-you-go billing.
• Air API Playground: Test models directly in the browser without writing code.

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External API expansion and new model endpoints

• List Endpoints: Retrieve a paginated list of all accessible endpoints with status and configuration details.
• List Replicas: View live replica status for any active endpoint.
• List/Get Log Files: Access endpoint log files and download their contents for debugging.
• Patch Endpoint: Update runtime settings (replica count, scaling config) for inactive endpoints.
• Get API Key Context: Verify your API key’s authentication scope and permissions.

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Jupyter Notebook, Web IDE, and Persistent Volume support

• Pre-configured with TensorFlow, PyTorch, and other major libraries
• Full GPU resource access for experimentation and model development
• Browser-based access — no local installation required
• Built-in Jupyter AI integration

• Write and run code in the browser without a local development environment
• Container-based isolated workspace for each session
• Built-in development and debugging tools
• Code assistant integration included

• Store model checkpoints, logs, and data files across container restarts
• Data management independent of container lifecycle
• Ideal for long-running jobs and iterative experiments

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External API initial release

# Check endpoint status
curl -X GET https://external.aieev.cloud:5007/external/api/v1/endpoints/{id} \
  -H "Authorization: Bearer YOUR_API_KEY"

# Scale replicas
curl -X POST https://external.aieev.cloud:5007/external/api/v1/endpoints/{id}/scale \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{"replica_count": 3}'

• Get Endpoint Status: Check current status, configuration, and health of any endpoint.
• Start/Stop Endpoint: Start or stop endpoints on demand via API.
• Scale Replicas: Adjust replica count for active endpoints to match traffic requirements.

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Air API beta launch, observability, dashboards, and UX upgrades

• OpenAI SDK compatible — swap models without changing your code
• API key authentication with per-key endpoint access control
• Test models interactively in the Playground

• Log download and bulk export: Download logs for offline analysis with single or batch export.
• Advanced log filtering: Regex-based search and time-range filtering for faster troubleshooting.
• Raw log (JSON) view: Inspect unprocessed log data alongside the structured view.
• Scaling history: Track autoscale events, timeout-triggered changes, and error-driven replica adjustments over time.

• Project dashboards: Monitor status and usage at the project level with dedicated views.
• Organization usage breakdown: View usage and cost distribution by project, endpoint, and instance type.
• Extended request metrics: Cumulative request counts, job error rates, and other operational metrics.
• Transaction history filtering: Filter billing records by type and status.

• Korean language support: Full Korean UI now available.
• First-time user onboarding: Guided tutorial flow for new users to deploy their first endpoint.
• In-product feedback: Submit feedback directly from within the platform.

• OpenAI-compatible API keys: Issue API keys with OpenAI-compatible format. Control which endpoints each key can access.
• HTTPS endpoints: Enforced HTTPS for all inference endpoints.
• Path-based endpoint addressing: Moved from port-based to path-based routing with support for custom endpoint URLs.

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AirCloud General Availability

• Deploy custom container images directly on GPU clusters
• Autoscaling and scheduled scaling to match traffic patterns
• Full control over runtimes, dependencies, and service configuration
• Persistent storage integration for models and data

• Time-based scaling: Schedule minimum replica counts or enable/disable autoscaling by time of day.
• Custom endpoint URLs: Use your own URL identifiers instead of system-generated IDs for cleaner integration.
• API Playground: Test and integrate APIs interactively through the built-in Playground without writing code.
• One-click cluster deployment: Reduce repetitive setup with templated, automated cluster deployments.
• Actionable error messages: Detailed error guidance on failure screens to cut mean-time-to-resolution.
• Secure inference traffic (HTTPS): End-to-end HTTPS for all inference requests.

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Usage insights, autoscaling controls, and performance tuning

• Usage & billing dashboards: Monthly and daily usage visualization to track credit consumption and spending trends at a glance.
• Autoscaling sensitivity controls: Configure autoscale responsiveness (Heavy / Normal / Light) to match your workload’s characteristics—from bursty inference to steady throughput.
• Deployment template reuse: Reuse existing deployment configurations to quickly spin up new endpoints with the same settings.
• Predictable scaling behavior: Adjusted scale-in/out policies to reduce variability under varying load patterns.
• Concurrent request handling improvements: Improved stability for large-file transfers and concurrent request handling under peak traffic.

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Zero-downtime operations

• Zero-downtime updates: Minimized service disruption during platform updates.
• Request drop prevention: Improved handling during scale-in and updates to prevent in-flight request loss.
• Restart stability: Event processing pipelines now handle component restarts without data loss or ordering issues.
• HTTPS adoption: Began HTTPS rollout as the platform security baseline.

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Billing and team collaboration

• Credits-based billing: Manage usage costs through a prepaid credit system with top-up and balance tracking.
• Team invites: Invite team members to your organization via email for collaborative access to shared resources.
• Reserved capacity: Distinguish between reserved (term-based) and on-demand resources for predictable cost planning.
• Billing automation: Automated usage collection and settlement processing on scheduled intervals.

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Air Container beta launch and platform foundation upgrades

• Deploy custom container images on GPU clusters
• Basic autoscaling and monitoring support
• Container health checks with automatic recovery

• Custom metrics for user workloads: Collect and display per-container metrics (e.g., vLLM) with configurable metric targets.
• Improved health checks: Better readiness detection for containers with long boot times to prevent premature termination.
• Faster runtime environments: Lighter, faster packaging and deployment structures for reduced startup times.
• Offline-friendly deployment: Support for restricted-network environments with offline operation scenarios.
• Better model caching: More efficient HuggingFace model cache sharing and management for faster cold starts.
• Reliable event capture: Hardened autoscale and operational event capture for more stable scaling decisions.