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Side-by-side features, use cases and pricing — because the right pick depends on your job and budget, not just the ranking.

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Zeabur logo
Zeabur
✓ verifiedFreemium

Cloud deployment platform for developers that auto-detects code and frameworks to ship apps, servers, and AI-hub services with one push.

455K visits/mo72 saves
Digma.ai logo
Digma.ai
✓ verifiedFreemium

Agentic AI SRE using dynamic code analysis to find, root-cause, and remediate code and infrastructure issues before production.

13K visits/mo
StackGen logo
StackGen
✓ verifiedPaid

Agentic AI platform ('Aiden') that automates incident response, infrastructure-as-code and observability tasks with policy-based governance.

13K visits/mo
Union Cloud logo
Union Cloud
✓ verifiedPaid

Cloud-agnostic AI/ML workflow orchestrator that runs pipelines inside a customer's own infrastructure for compute-heavy teams.

25K visits/mo
Middleware logo
Middleware
✓ verifiedFreemium

Full-stack observability platform with an AI SRE agent that detects, debugs, and auto-fixes issues across infra, apps, and users.

47K visits/mo713 saves
Pricing
Free: $0/mo (1 manageable server)
Dev: $5/mo (first 14 days free, 3 servers)
Pro: $19/mo (first 14 days free, 10 servers)
Team: $79/mo (3 seats included, +$24/seat/mo)

Free trial available

Free for Developers: $0 (local, single user)
Teams: $450/month (5 microservices, unlimited users)

Free trial available

No public pricing

Team: $950/month + usage (1,000 concurrent actions, 30-day retention, 1 cluster)

No public pricing

Core features
  • Automatic language and framework detection and deployment
  • Git-push CI/CD with zero configuration
  • Auto-scaling compute resources
  • Built-in object storage similar to S3
  • One-click managed VPS purchase
  • Unified AI Hub API for multiple AI models
  • Domain and DNS management
  • In-browser file management console
  • Dynamic Code Analysis engine
  • Automated root-cause analysis and remediation
  • Pull-request and config fix suggestions
  • MCP server for AI-assisted code review
  • Observability and data-source integrations
  • Runs locally or on-prem/private cloud
  • Automated service discovery and dependency topology mapping
  • SLO-based alert triage and prioritization
  • AI-driven root cause analysis with pre-built workflows
  • Human-approved remediation with full audit trails
  • Works alongside existing tools like Datadog, Grafana, New Relic
  • Governance and policy enforcement layer for agent actions
  • Python-native dynamic workflow authoring
  • Automatic failure recovery, caching, and versioning
  • Zero Trust architecture keeping data inside customer's cloud
  • Real-time inference and agentic-AI workflow support
  • High-throughput scaling (tens of thousands of actions per run)
  • Local development environment matching production behavior
  • Infrastructure and application performance monitoring
  • Log monitoring with AI insights
  • Real user monitoring
  • OpsAI SRE agent for detection and auto-fix
  • Synthetic and browser testing
  • LLM observability
Use cases
  • Developers deploying apps without manual server config
  • Teams wanting predictable, fixed-plan hosting costs
  • Startups needing quick CI/CD pipelines
  • Projects needing bundled AI model access alongside hosting
  • Reducing incident resolution time
  • Catching performance issues pre-production
  • Enhancing AI code reviews with runtime data
  • Monitoring microservice performance
  • SRE teams reducing mean-time-to-resolution during incidents
  • Platform engineers wanting policy-governed AI infrastructure management
  • Enterprises needing SOC 2 / PCI / HIPAA-compliant AI operations
  • ML teams orchestrating training and inference pipelines at scale
  • Biotech/geospatial companies needing GPU-heavy pipeline orchestration
  • Enterprises migrating off Airflow for ML workflow management
  • Teams requiring workflows that never send data outside their own cloud
  • Monitor full-stack app and infra health
  • Debug incidents faster with AI
  • Correlate frontend and backend issues
  • Observe Kubernetes and cloud environments
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