Term 31
Blue-green deployment
Blue-green deployment is a release strategy that reduces downtime and risk by running two identical production environments, one live and one idle, enabling instant traffic switching between them.
Acronym study
Terms 31–60 of 206 AZ-400 acronyms and key terms. Each entry includes a plain-English definition and a link to the full 800-word glossary page with exam context and practice questions.
Term 31
Blue-green deployment is a release strategy that reduces downtime and risk by running two identical production environments, one live and one idle, enabling instant traffic switching between them.
Term 32
In Azure DevOps, a Board is a visual tool that helps teams plan, track, and manage work items through different stages of a development process.
Term 33
A branch is a pointer to a specific commit in a version control system that allows you to work on features or fixes in isolation from the main codebase.
Term 34
A branch policy is a set of rules and conditions enforced on a Git branch to control how code changes are proposed, reviewed, and merged, ensuring code quality and protecting critical branches.
Term 35
Budgets in cloud computing are monitoring tools that allow you to set spending limits and receive alerts when your costs approach or exceed those limits.
Term 36
A bug is an error, flaw, or fault in software that causes it to produce an incorrect or unexpected result, or to behave in unintended ways.
Term 37
A build artifact is the packaged, deployable output created by a build process, such as a compiled binary, ZIP file, or container image, that is stored for later use in testing or release.
Term 38
A build pipeline is an automated sequence of steps that compiles source code into a deployable artifact, running tests and checks along the way.
Term 39
A canary deployment is a software release strategy where a new version of an application is gradually rolled out to a small subset of users before being made available to everyone.
Term 40
A catch block is a section of code in programming that handles errors by specifying what to do when a particular type of exception or error occurs in a try block.
Term 41
Continuous Delivery is a software engineering practice where code changes are automatically built, tested, and prepared for release to production.
Term 42
The AWS Cloud Development Kit (CDK) is an infrastructure-as-code tool that lets you define cloud resources using familiar programming languages instead of writing YAML or JSON templates.
Term 43
Chaos engineering is the practice of intentionally injecting failures into a system to test its resilience and find weaknesses before they cause real outages.
Term 44
A Check in Azure DevOps is a gating mechanism that evaluates predefined conditions before allowing a pipeline deployment to proceed to a specific environment.
Term 45
A Choice state in AWS Step Functions is a branching element that evaluates conditions and directs the workflow to a specific next state based on the input data.
Term 46
CI (Continuous Integration) is a software development practice where developers frequently merge their code changes into a shared repository, and each merge is automatically built and tested to catch errors early.
Term 47
A centralized network management and automation platform from Cisco that provides intent-based networking for easier configuration, monitoring, and troubleshooting of Cisco devices.
Term 48
A Classic pipeline is a traditional, UI-driven build and release management system in Azure DevOps that uses a visual designer rather than YAML code to define continuous integration and continuous delivery workflows.
Term 49
Cloud Build is a managed service that compiles source code into deployable artifacts, often used in continuous integration and continuous delivery pipelines.
Term 50
Cloud Deploy is the process of releasing software applications and updates from development to production environments that run on cloud infrastructure.
Term 51
A Cloud Deployment Manager is a service or tool that helps IT teams define, deploy, and manage cloud infrastructure resources as reusable, code-defined templates.
Term 52
Cloud logging is the practice of collecting, storing, and analyzing log data generated by cloud-based resources and applications to monitor performance, troubleshoot issues, and maintain security.
Term 53
Cloud monitoring is the process of observing, measuring, and managing an organization's cloud infrastructure and applications to ensure performance, availability, and security.
Term 54
A cloud profiler is a tool that continuously monitors and analyzes the performance characteristics of applications running in the cloud, helping identify which parts of the code consume the most resources like CPU, memory, or time.
Term 55
Cloud Run for Anthos is a Google Cloud service that lets you run containerized applications in a serverless way on your own Kubernetes clusters, whether on-premises or in the cloud.
Term 56
Cloud Source Repositories are fully managed, private Git repositories hosted on a cloud provider that allow teams to store, manage, and collaborate on source code with built-in access control and integration with CI/CD pipelines.
Term 57
Cloud Trace is a managed service that collects latency data from applications and infrastructure to help you understand and troubleshoot performance bottlenecks across distributed systems.
Term 58
CloudFormation is an AWS service that lets you define and provision your cloud infrastructure using code, so you can create and manage resources consistently and repeatably.
Term 59
AWS CloudTrail is a service that records every action taken in your AWS account, creating a detailed log of who did what and when for security and auditing purposes.
Term 60
CloudWatch is an AWS monitoring service that tracks metrics, logs, and alarms for your cloud resources so you can see what’s happening and respond to issues.