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Atlassian's Git repository hosting for teams with built-in CI/CD pipelines and tight Jira integration for code review and deployment.
Full-stack observability platform with an AI SRE agent that detects, debugs, and auto-fixes issues across infra, apps, and users.
Developer tool that deploys Docker Compose apps (with LLMs and databases) into your own AWS, GCP or Azure account via one command.
Free cloud cost-optimization platform that pools buying power to give startups enterprise-level AWS, GCP, and Azure discounts.
Agentic AI SRE using dynamic code analysis to find, root-cause, and remediate code and infrastructure issues before production.
No public pricing
Free trial available
No public pricing
No public pricing
Free trial available
- ✦Git repository hosting
- ✦Bitbucket Pipelines CI/CD
- ✦Pull requests and code review
- ✦Native Jira integration
- ✦Branch permissions and access controls
- ✦IP allowlisting and security features
- ✦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
- ✦One-command deploy from Docker Compose
- ✦Deploys into your own or a customer's cloud account
- ✦Native managed LLM access (Bedrock/Vertex/Azure AI)
- ✦Managed Postgres, MongoDB and Redis
- ✦Auto-configured IAM, VPC, TLS and load balancing
- ✦Open-source CLI and cloud providers
- ✦Automated cloud spend optimization
- ✦Group buying for enterprise discounts
- ✦Cost visibility and insights dashboards
- ✦Coverage across AWS, GCP, and Azure
- ✦No-cost service model
- ✦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
- →Source code management
- →CI/CD automation
- →Team code review
- →DevOps for Jira-based teams
- →Monitor full-stack app and infra health
- →Debug incidents faster with AI
- →Correlate frontend and backend issues
- →Observe Kubernetes and cloud environments
- →Shipping AI agents and web apps to production
- →Deploying the same app across many customer clouds
- →Agencies deploying into client cloud accounts
- →Avoiding hand-written Terraform or Kubernetes
- →Reducing startup cloud bills
- →Automating reserved-capacity savings
- →Gaining visibility into multi-cloud spend
- →Accessing enterprise pricing without scale
- →Reducing incident resolution time
- →Catching performance issues pre-production
- →Enhancing AI code reviews with runtime data
- →Monitoring microservice performance