Bitbucket Pipelines

GPTKB entity

Statements (87)
Predicate Object
gptkbp:instance_of gptkb:software
gptkbp:bfsLayer 3
gptkbp:bfsParent gptkb:football_club
gptkbp:allows team collaboration
custom scripts
environment variables
automated testing
custom notifications
environment-specific configurations
gptkbp:can_be_used_with microservices architecture
pull requests
gptkbp:developed_by gptkb:Atlassian
gptkbp:enables CI/ CD workflows
gptkbp:has customizable build environments
https://www.w3.org/2000/01/rdf-schema#label Bitbucket Pipelines
gptkbp:integrates_with gptkb:Bitbucket
gptkbp:is_accessible_by web interface
gptkbp:is_available_for open source projects
gptkbp:is_available_in gptkb:Bitbucket_Server
multiple languages
gptkbp:is_available_on cloud platforms
gptkbp:is_compatible_with gptkb:Git
legacy systems
CI/ CD tools
gptkbp:is_documented_in developer guides
Atlassian documentation
official Atlassian blog
gptkbp:is_integrated_with gptkb:Slack
gptkb:Git_Hub_Actions
monitoring tools
gptkbp:is_optimized_for Agile development
team productivity
gptkbp:is_part_of gptkb:Bitbucket_Cloud
Agile methodologies
software development lifecycle
Atlassian ecosystem
software engineering best practices
Dev Ops practices
gptkbp:is_scalable large projects
gptkbp:is_supported_by community forums
gptkbp:is_used_by software development teams
startups
gptkbp:is_used_for continuous delivery
build automation
release management
streamline workflows
automate testing processes
code quality checks
automate deployments
manage dependencies
reduce manual errors
manage build artifacts
track build status
gptkbp:offers customizable dashboards
integration with third-party tools
artifacts storage
deployment to cloud providers
integration with monitoring services
parallel step execution
gptkbp:provides API access
build logs
notifications
performance monitoring
version control integration
real-time feedback
user management features
security scanning
deployment options
integration with Jira
gptkbp:setting bitbucket-pipelines.yml
run on schedule
gptkbp:supports gptkb:lake
API testing
automated deployments
caching
cloud-native applications
code reviews
cross-platform development
multiple programming languages
test automation
containerized applications
branch-specific configurations
manual triggers
automated code reviews
serverless deployments
multi-step pipelines
gptkbp:uses YAML configuration files