npx skills add https://github.com/incept5/eve-skillpacks --skill eve-pipelines-workflows使用这些模式来自动化构建和部署操作,并调用工作流任务。
.eve/manifest.yaml 的 pipelines 下定义流水线。action、script 或 agent。depends_on 来控制执行顺序。build、release、deploy、run、、。Use these patterns to automate build and deploy actions and invoke workflow jobs.
pipelines in .eve/manifest.yaml.action, script, or agent.depends_on to control ordering.build, release, deploy, , , .广告位招租
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jobcreate-preve pipeline listeve pipeline show <project> <name>eve pipeline run <name> --ref <sha> --env <env> --repo-dir ./my-appbuild 操作构建操作会创建被跟踪和可观察的 BuildSpec 和 BuildRun 记录:
build_id 和 image_digests 映射(服务名称到 SHA256 摘要)eve build show、eve build diagnose、eve build runs、eve build logs当流水线阶段需要运行 AI 代理任务时,使用 agent 步骤:
pipelines:
remediation:
steps:
- name: analyze
agent:
prompt: "Analyze the failure and propose a fix"
每个部署流水线都应遵循此模式:
pipelines:
deploy:
steps:
- name: build
action:
type: build
# 创建 BuildSpec + BuildRun,输出 build_id + image_digests
- name: release
depends_on: [build]
action:
type: release
# 引用 build_id,从 BuildArtifacts 派生摘要
- name: deploy
depends_on: [release]
action:
type: deploy
env_name: staging
# 使用基于摘要的镜像引用进行不可变部署
在测试环境中构建一次,然后将相同的构建产物提升到预发布/生产环境:
跟踪流水线执行:
eve job list --phase active
eve job follow <job-id>
eve job result <job-id>
实时监控流水线运行:
# 获取运行的快照日志
eve pipeline logs <pipeline> <run-id>
# 实时 SSE 流式传输
eve pipeline logs <pipeline> <run-id> --follow
# 流式传输特定步骤
eve pipeline logs <pipeline> <run-id> --follow --step <name>
失败的步骤会包含失败提示,并在适用时链接到构建诊断信息。
当环境中在清单中配置了 pipeline 时,eve env deploy <env> --ref <sha> 会自动触发该流水线,而不是执行直接部署。
# 触发为测试环境配置的流水线
eve env deploy test --ref 0123456789abcdef0123456789abcdef01234567
# 向流水线传递输入
eve env deploy staging --ref 0123456789abcdef0123456789abcdef01234567 --inputs '{"release_id":"rel_xxx"}'
# 绕过流水线,执行直接部署
eve env deploy staging --ref 0123456789abcdef0123456789abcdef01234567 --direct
# 1. 构建并部署到测试环境
eve env deploy test --ref 0123456789abcdef0123456789abcdef01234567
# 2. 从测试构建中获取发布信息
eve release resolve v1.2.3
# 输出: rel_xxx
# 3. 使用 release_id 提升到预发布环境
eve env deploy staging --ref 0123456789abcdef0123456789abcdef01234567 --inputs '{"release_id":"rel_xxx"}'
environments.<env>.pipeline,eve env deploy <env> 会触发该流水线--direct 标志来绕过流水线并执行直接部署--inputs '{"key":"value"}' 向流水线运行传递输入environments.<env>.pipeline_inputs 进行配置--ref 标志指定要部署的 git SHA(40 字符的 SHA 或通过 --repo-dir 解析的引用)此模式支持提升工作流,您可以在较低环境中构建一次,然后将相同的产物提升到更高的环境中。
workflows 下定义工作流。db_access 时,会遵循其设置(read_only、read_write)。eve workflow listeve workflow show <project> <name>eve workflow run <project> <name> --input '{"k":"v"}'(触发后不管)eve workflow invoke <project> <name> --input '{"k":"v"}'(等待结果)eve workflow logs <job-id>通过 hints 控制门控、超时和工具偏好:
workflows:
remediate:
hints:
gates: ["remediate:proj_abc123:staging"]
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runjobcreate-preve pipeline listeve pipeline show <project> <name>eve pipeline run <name> --ref <sha> --env <env> --repo-dir ./my-appbuild actionBuild actions create BuildSpec and BuildRun records that are tracked and observable:
build_id and image_digests map (service name to SHA256 digest)eve build show, eve build diagnose, eve build runs, eve build logsUse agent steps when a pipeline stage should run an AI agent job:
pipelines:
remediation:
steps:
- name: analyze
agent:
prompt: "Analyze the failure and propose a fix"
Every deploy pipeline should follow this pattern:
pipelines:
deploy:
steps:
- name: build
action:
type: build
# Creates BuildSpec + BuildRun, outputs build_id + image_digests
- name: release
depends_on: [build]
action:
type: release
# References build_id, derives digests from BuildArtifacts
- name: deploy
depends_on: [release]
action:
type: deploy
env_name: staging
# Uses digest-based image refs for immutable deploys
Build once in test, then promote the same build artifacts to staging/production:
Track pipeline execution:
eve job list --phase active
eve job follow <job-id>
eve job result <job-id>
Monitor pipeline runs in real time:
# Snapshot logs for a run
eve pipeline logs <pipeline> <run-id>
# Real-time SSE streaming
eve pipeline logs <pipeline> <run-id> --follow
# Stream specific step
eve pipeline logs <pipeline> <run-id> --follow --step <name>
Failed steps include failure hints and link to build diagnostics when applicable.
When an environment has a pipeline configured in the manifest, eve env deploy <env> --ref <sha> automatically triggers that pipeline instead of doing a direct deploy.
# Triggers the configured pipeline for test environment
eve env deploy test --ref 0123456789abcdef0123456789abcdef01234567
# Pass inputs to the pipeline
eve env deploy staging --ref 0123456789abcdef0123456789abcdef01234567 --inputs '{"release_id":"rel_xxx"}'
# Bypass pipeline and do direct deploy
eve env deploy staging --ref 0123456789abcdef0123456789abcdef01234567 --direct
# 1. Build and deploy to test environment
eve env deploy test --ref 0123456789abcdef0123456789abcdef01234567
# 2. Get release info from the test build
eve release resolve v1.2.3
# Output: rel_xxx
# 3. Promote to staging using the release_id
eve env deploy staging --ref 0123456789abcdef0123456789abcdef01234567 --inputs '{"release_id":"rel_xxx"}'
environments.<env>.pipeline is set, eve env deploy <env> triggers that pipeline--direct flag to bypass the pipeline and perform a direct deploy--inputs '{"key":"value"}' to pass inputs to the pipeline runenvironments.<env>.pipeline_inputs in the manifest--ref flag specifies which git SHA to deploy (40-character SHA or ref resolved via --repo-dir)This pattern enables promotion workflows where you build once in a lower environment and promote the same artifact through higher environments.
workflows in the manifest.db_access is honored when present (read_only, read_write).eve workflow listeve workflow show <project> <name>eve workflow run <project> <name> --input '{"k":"v"}' (fire-and-forget)eve workflow invoke <project> <name> --input '{"k":"v"}' (wait for result)eve workflow logs <job-id>Control gating, timeouts, and harness preferences via hints:
workflows:
remediate:
hints:
gates: ["remediate:proj_abc123:staging"]
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