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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.
Open-source, encrypted web terminal sharing tool letting people collaborate live on one command line via a browser link.
Agentic AI SRE using dynamic code analysis to find, root-cause, and remediate code and infrastructure issues before production.
Continuously analyzes MySQL, MariaDB, and PostgreSQL workloads to recommend and safely apply configuration and query fixes.
No public pricing
Free trial available
No public pricing
Free trial available
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
- ✦One-command installation and session sharing via link
- ✦End-to-end encryption so the server cannot read terminal data
- ✦Multiplayer infinite canvas for arranging multiple terminals
- ✦Live cursors and chat for real-time collaboration
- ✦Cross-platform CLI for macOS, Linux and Windows
- ✦Distributed mesh networking for low-latency global connections
- ✦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
- ✦Workload-based configuration tuning
- ✦SQL query analytics and optimization suggestions
- ✦Schema optimization (duplicate/unused index detection)
- ✦24/7 automated health and security monitoring
- ✦One-command agent installation
- ✦Human approval required before applying changes
- →Source code management
- →CI/CD automation
- →Team code review
- →DevOps for Jira-based teams
- →Pair debugging a remote server with a teammate
- →Teaching command-line skills over a shared live session
- →Sharing a CI/CD pipeline terminal for troubleshooting on GitHub Actions
- →Providing temporary cloud access without exposing SSH credentials
- →Reducing incident resolution time
- →Catching performance issues pre-production
- →Enhancing AI code reviews with runtime data
- →Monitoring microservice performance
- →Database teams reducing manual tuning workload
- →Hosting providers optimizing customer databases at scale
- →Engineering teams without a dedicated DBA fixing performance issues
- →AWS RDS users tuning managed database instances