cloudrun-development
Skill80 starsChanged 9 days agoMITView on GitHub
CloudBase Run backend development rules (Function mode/Container mode). Use this skill when deploying backend services that require long connections, multi-language support, custom environments, AI agent development, or migrating existing/GitHub apps that need VPC access to MySQL/PostgreSQL/Redis. Also use when diagnosing CloudRun container deploy failures (deploy_failed, readiness/probe failed, image won't start, docker.io pull loops) or a deploy stuck behind a running deploy task. For stateless HTTP services, prefer HTTP cloud functions.
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1 other project uses a version of this, 1 of them edited.
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Most recently taken up by
- TencentCloudBase/cloudbase-pluginedited, first seen Nov 15, 2026
Other versions1 project uses a version of this.
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Edited · 1
- TencentCloudBase/cloudbase-plugin★ 4100% same
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How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository33 other files it gives its agents.
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- cloudbase-mcpSkill
- cloudbase-platformSkill
- cloudbaseSkill
- cloudbase-wechat-integrationSkill
- cloud-functionsSkill
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- http-api-cloudbaseSkill
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- miniprogram-developmentSkill
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- postgresql-best-practices-cloudbaseSkill
- postgresql-development-cloudbaseSkill
- relational-database-mcp-cloudbaseSkill
- relational-database-web-cloudbaseSkill
- spec-workflowSkill
- ui-designSkill
- web-developmentSkill
The file
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We split this skill into the rules it gives an agent
17 rules. About 0 are common, 9 are distinctive, and 8 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈9
Distinctive · estimate
This author's own choices. Worth a look.
8
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 13
If a referenced sibling skill file is missing from this environment, ask the user to install the full CloudBase plugin (or the missing …
- Very specific: line 85
If the app uses TCP databases/caches, resolve and set VpcConf (egress / private network) before deploy — see references/vpc-and-database.md.
- Distinctive: line 86
Keep the service stateless and externalize durable data.
- Distinctive: line 89
Use absolute paths for every local project path.
- Distinctive: line 95
Use CloudBase Run when the task needs a deployed backend service rather than a short-lived serverless function.
- Distinctive: line 181
Keep the service stateless
- Very specific: line 182
Put durable data in DB/storage/cache
- Distinctive: line 183
Keep dependencies and image size small — the image carries code and dependencies only.
- Very specific: line 189
Delete requires explicit confirmation and force: true
- Very specific: line 190
Always use absolute targetPath
- Very specific: line 197
If TCP DB access is required, complete the VPC checklist in references/vpc-and-database.md before deploy
- Very specific: line 202
If deploy fails, follow the Container deploy failure SOP (references/image-deploy-troubleshooting.md) — docs → getProcessLog → config.
- Distinctive: line 428
Prefer PRIVATE/VPC or mini-program internal ingress when possible.
- Very specific: line 430
Use environment variables for secrets and per-environment configuration — read them server-side only.
- Very specific: line 431
Verify configuration before and after deployment with queryCloudRun(action="detail").
- Distinctive: line 432
Keep startup work small to reduce cold-start impact.
- Distinctive: line 450
All packaged reference files (required for skill lint reachability):
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Sibling skills (local only)
Sibling CloudBase skills ship beside this skill. Use local relative paths such as ../auth-tool-cloudbase/SKILL.md.
If a referenced sibling skill file is missing from this environment, ask the user to install the full CloudBase plugin (or the missing skill). Do not HTTP-fetch remote skill or protocol markdown into the agent context.
Cross-cutting protocols (required before writing HTTP handlers or deploying images):
- Sensitive Runtime Data Protection:
../cloudbase-platform/references/protocols/sensitive-runtime-data-protection.md - Deployment Gate:
../cloudbase-platform/references/protocols/deployment-gate.md
CloudBase Run Development
Activation Contract
Use this first when
- The task is to initialize, run, deploy, inspect, or debug a CloudBase Run service.
- The request needs a long-lived HTTP service, SSE, WebSocket, custom system dependencies, or container-style deployment.
- The task is to create or run an Agent service on CloudBase Run.
- The task migrates an existing / GitHub / third-party backend that uses classic
DATABASE_URL/ TCP database clients. - The service requires a stable independent process (long connections, custom runtime, VPC database access) — see the 「云托管 vs HTTP 云函数」 decision section below. A Dockerfile alone is not a strong trigger.
Read before writing code if
- You still need to choose between Function mode and Container mode.
- The prompt mentions
queryCloudRun,manageCloudRun, Dockerfile, service domains, or public/private access. - The app depends on MySQL, PostgreSQL, Redis, or other VPC-private resources over TCP → 先做数据库访问方式决策(SDK/网关优先,见下方「数据库访问方式决策门」);确认必须 TCP 直连后 → also read
references/vpc-and-database.md. - You are choosing between CloudRun and HTTP cloud functions for a stateless HTTP service.
- The service calls CloudBase resources (PG
app.rdb(), NoSQL, storage, functions) through an SDK → 先过「计算资源访问 CloudBase 的凭证决策门」:凭证谁签发、怎么注入、怎么吊销,都必须在写代码之前定下来。 - Container deploy fails (
deploy_failed, Pod not ready, readiness/probe failed, third-partyimageUrlwon't stay up) → also readreferences/image-deploy-troubleshooting.mdand follow the Container deploy failure SOP below. Do not start by raisingInitialDelaySeconds.
Then also read
- Cloud functions instead of CloudRun ->
../cloud-functions/SKILL.md - Agent SDK and AG-UI specifics ->
../cloudbase-agent/SKILL.md - Web authentication for browser callers ->
../auth-web-cloudbase/SKILL.md - Existing app + TCP database networking ->
references/vpc-and-database.md - Container image deploy failure / probe /
deploy_failed->references/image-deploy-troubleshooting.md - Service calls CloudBase resources through an SDK (credential source / injection / revocation) ->
../cloud-functions/references/http-function-credentials.md - Billing questions about a CloudRun charge ("why was I charged when nothing was deployed", "the free quota wasn't used up") ->
../cloud-api-operations/references/recipes/billing-charges-explained.md(the gifted quota is a 3-month total, and a container bills while instance count is not 0)
Do NOT use for
- Simple Event Function or HTTP Function workflows that fit the function model better.
- Frontend-only projects with no backend service.
- Database-schema design tasks.
Common mistakes / gotchas
- Choosing CloudRun when the request only needs a normal cloud function.
- Forgetting to listen on the platform-provided
PORTin Container mode — and its mirror image in Function mode: callingapp.listen()there, where the framework already owns the port and the second bind dies withEADDRINUSE. - Guessing the credential environment variable name.
@cloudbase/node-sdkreadsCLOUDBASE_APIKEY; an invented name (for exampleTCB_API_KEY) is silently ignored and only shows up later as "no credentials at runtime". - Copying a server credential out of the local client login state (
auth.json,.cloudbase/) and injecting it into a deployed service. Issue the key withmanageAppAuth(action="createApiKey", keyType="api_key")instead, so it has an owner, a rotation path, and akeyIdyou can revoke. See../cloud-functions/references/http-function-credentials.md. - Baking static content into the image — media files, user uploads, or assets that change on their own cadence. Three cases, one root cause: the image is rebuilt, re-pushed and re-pulled on every deploy and on every scale-up, so anything large or independently-changing makes every deploy slower for no reason.
- Media files (
*.mp4, large images, fonts) pulled in by aCOPY . .— one demo video can turn a 30-second deploy into a multi-minute one. Media belongs in cloud storage, referenced by URL. Add a.dockerignorecovering*.mp4,*.mov,*.zip,*.psd, and media directories such aspublic/videos/. - User uploads written to the container filesystem — the service is stateless; anything on local disk is gone on the next deploy, restart, or scale-out. Uploads go to cloud storage.
- Frequently-updated static resources served from the image — if an asset changes on its own schedule, every change forces a full service redeploy. Serve it from cloud storage so the service only redeploys when the code changes.
- Media files (
- Treating CloudRun as stateful app hosting and storing important state on local disk.
- Assuming local run is available for Container mode.
- Opening public access by default when the scenario only needs private or mini-program internal access.
- Deploying an existing app with
DATABASE_URL/ MySQL / PostgreSQL / Redis but omittingserverConfig.VpcConf— deploy appears to succeed, then runtime DB connections fail. - 新应用部署默认选 TCP 直连数据库 — 能用 SDK/网关访问的数据(PG
app.rdb()、NoSQL、storage)不需要VpcConf也不需要数据库账号密码;仅迁移类应用(经典驱动/ORM 无法替换)才走 TCP 直连 +VpcConf。见「数据库访问方式决策门」。 - Confusing
OpenAccessTypes(how users reach the service) withVpcConf(how the service reaches VPC databases). - Deploying to an environment that has not initialized CloudRun —
CreateCloudRunServeron an environment with no 大租户 record silently lands in the legacy 小租户 path, creating wrong small-tenant services/versions. Always ensure the environment is initialized first (manageCloudRun(action="initEnv"), tcbr) before the first deploy.manageCloudRun(action="deploy")now blocks new-service creation on uninitialized environments with guidance. - Using the legacy
tcbCloudRun API (CreateCloudBaseRunResource/DescribeCloudBaseRunResource/DeleteCloudBaseRunResource) — these are deprecated 小租户 open APIs and are blocked incallCloudApi. CloudRun always goes throughtcbr(CreateCloudRunEnv/CreateCloudRunServer). Query a single environment's base info / whether CloudRun is enabled withDescribeEnvBaseInfo(EnvIdrequired) — usemanageCloudRun(action="initEnv")to open andqueryCloudRun(action="envStatus")to poll status; query the environment list / resource info withDescribeCloudRunEnvs(EnvIdoptional filter). - Deploying
httpbin/ request-echo images or returningreq.headers/process.env— CloudBase may injectx-cloudbase-context(base64 temporary credentials). Echoing it leaks account cloud access. Follow../cloudbase-platform/references/protocols/sensitive-runtime-data-protection.md. - Seeing readiness probe failed /
deploy_failedand immediately raisingInitialDelaySeconds— the probe window is already ~N+150s; crash loops and loopback binds are not slow-start. Follow the Container deploy failure SOP. - Deploying a third-party image without reading its run docs — missing
Cmd, bind-address env, orVolumesConflooks identical to a probe failure. - Calling
getDeployLogforimageUrldeploys — that is CODING build log; usegetProcessLog. - Treating startup banners as proof the service is healthy — pull
getProcessLogtwice and compare; a repeated boot sequence is a restart loop.
Minimal checklist
- Choose Function mode or Container mode explicitly.
- Confirm the environment has CloudRun initialized before the first deploy — a brand-new environment must call
CreateCloudRunEnv(tcbr) first; neverCreateCloudRunServeron an uninitialized environment (it falls back to the legacy 小租户 path).manageCloudRun(action="deploy")validates this automatically and blocks new services on uninitialized environments. When blocked, first callmanageCloudRun(action="initEnv", envId=...)(异步开通) and pollqueryCloudRun(action="envStatus")untilStatus=normal, or reconsider an HTTP cloud function to bypass CloudRun entirely. - Confirm whether the service should be public, VPC-only, or mini-program internal (ingress).
- If the app uses TCP databases/caches, resolve and set
VpcConf(egress / private network) before deploy — seereferences/vpc-and-database.md. - Keep the service stateless and externalize durable data.
- Separate static from dynamic: media files, user uploads, and frequently-updated assets live in cloud storage, not in the image. Check what the Dockerfile copies in.
- Settle the credential path for every CloudBase SDK call before writing code — a server API Key issued through
manageAppAuth(action="createApiKey")and injected viaEnvParams, never a key copied out of the local client login state. - Use absolute paths for every local project path.
- Confirm handlers never echo
x-cloudbase-context, full headers, or credential env vars; do not deploy httpbin-style reflectors. - For third-party images, complete the five-item docs checklist (Cmd / port / bind env / volume / health) before deploy.
Overview
Use CloudBase Run when the task needs a deployed backend service rather than a short-lived serverless function.
云托管 vs HTTP 云函数(按需求选,不按文件选)
核心原则:HTTP 云函数优先。只有需求真正需要云托管时才用云托管;有
Dockerfile不等于必须上云托管。
HTTP 云函数更合适(优先):
- 无状态 HTTP 服务,监听
PORT/9000,只做「请求进来 → 处理 → 响应」的响应式逻辑 - 短生命周期请求,无长连接需求(SSE/WebSocket 之外的普通 API、CRUD、转发)
- 标准 runtime 够用(不需要自定义系统依赖、不需要非标准语言)——需要时也能用镜像函数(Custom Image HTTP Function)跑,仍然在函数这条线上
- 部署更快、费用更低(按请求计费,可缩容到 0)、无需初始化云托管环境
- 有
Dockerfile但服务本质是无状态 HTTP → 优先 HTTP 云函数(HTTP Function / Custom Image HTTP Function),不必上云托管
云托管才需要(只有以下之一才选云托管):
- 长连接:WebSocket、SSE 长连接、服务端推送
- 需要常驻的独立进程:后台任务循环、常驻缓存 / 连接池、自管端口的服务
- VPC 内数据库 / Redis 访问(
VpcConf私有网络连通) - Agent 服务(Function mode CloudRun)
- 迁移已有 / GitHub / 第三方应用
语言不是上云托管的条件:非标准语言(Java / Rust / C++ / PHP / .NET 等)或需要自定义系统依赖时,只要服务仍是「请求进来 → 响应」且无长连接,打成镜像用 Custom Image HTTP Function,就还是函数;只有再叠加常驻 / 长连接 / VPC 才上云托管。
决策示例: 一个带 Dockerfile 的 Go/Python HTTP API,无长连接、无自定义系统依赖、不碰 VPC 数据库 → 选 HTTP 云函数而不是云托管;同一份代码若有 WebSocket 长连接 → 才选云托管。
数据库访问方式决策门(部署前必答:SDK 优先,TCP 直连兜底)
核心原则:能用 CloudBase SDK/网关访问的数据,一律优先 SDK 路径。 TCP 直连会引入 VPC、安全组、数据库账号密码三件套,全是部署后才暴露的问题(
ETIMEDOUT、安全组拦截、密码注入),能不碰就不碰。
优先:SDK / 网关路径(无需 VpcConf、无需数据库账号密码)
- CloudBase PG →
app.rdb()(js-sdk v3 / node-sdk,走 PG HTTP 网关;详见../postgresql-development-cloudbase/SKILL.md) - NoSQL →
app.database();对象存储 →app.storage - 新应用 / CloudBase 原生数据 → 数据层直接按 SDK 路径设计,部署时完全不需要 VPC 配置;若只用到这些数据面,还可结合上一节的「HTTP 云函数优先」进一步免掉云托管
仅当以下情况才走 TCP 直连(须完成 references/vpc-and-database.md 全流程):
- 迁移已有 / GitHub / 第三方应用,数据层是经典驱动或 ORM(mysql2、pg、Prisma、SQLAlchemy、WordPress / Ghost 等),改造成 SDK 的成本高或用户明确要求保留
- 需要 SDK 不覆盖的能力(特定 SQL 方言、存储过程、Redis 原生协议等)
决策动作: 扫描到 DATABASE_URL / DB 依赖信号时,先停下来回答「这个数据访问能不能换成 SDK/网关」,再决定是否进入 VPC checklist——不要默认按 TCP 直连方案往下走。
计算资源访问 CloudBase 的凭证决策门(部署前必答)
核心原则:SDK 路径免掉的是数据库账号密码,不是 CloudBase 资源访问凭证。 服务代码要调 CloudBase 资源(PG
app.rdb()/ NoSQL / storage / functions)时,先把凭证来源定下来,再写代码、再部署。
三件事必须先答:
- 谁签发 — CloudBase 服务端 API Key:
manageAppAuth(action="createApiKey", keyType="api_key", keyName="<service>-<env>"),或 CLItcb env apikey create my-key -e env-xxx。不要从本地客户端登录态(auth.json/.cloudbase/)里取一把来用。 - 怎么注入 — 经
serverConfig.EnvParams注入CLOUDBASE_APIKEY(@cloudbase/node-sdk自动读取该变量;显式字段是accessKey)。变量名以官方为准,不要自造。改环境变量时保留已有键值,不要整份覆盖。 - 怎么吊销 — 每个服务一把专用 key,记录
keyName与轮换负责人;下线或轮换时manageAppAuth(action="deleteApiKey", keyId=...)并重新部署。轮换后旧实例里残留的副本不会报错,只会静默失效。
不要假设云托管容器已自动带上可用的 CloudBase 凭证 —— 部署后用一次真实的 SDK 读取验证(验证两次以上,不要只看进程起没起来)。完整步骤、Manager SDK 的腾讯云密钥对路径、环境变量合并的安全写法见 ../cloud-functions/references/http-function-credentials.md。
api_key 是环境级凭证:可绕过 RLS,单环境签发数量有限。不要给每个服务灌同一把 —— 任一实例失陷即整环境失陷。
When CloudRun is a better fit
- Long connections: WebSocket, SSE, server push
- Long-running request handling or persistent service processes
- Custom runtime environments or system libraries
- Arbitrary languages or frameworks
- Stable external service endpoints with elastic scaling
- AI Agent deployment on Function mode CloudRun
- Migrating existing containerized or multi-language apps that need VPC access to databases
Mode selection
| Dimension | Function mode | Container mode |
| Best for | Fast start, Node.js service patterns, built-in framework, Agent flows | Existing containers, arbitrary runtimes, custom system dependencies |
| Port model | The function framework binds the platform port itself — your code must not call app.listen() | App must listen on the injected PORT |
| Dockerfile | Not required | Required — but a Dockerfile alone does not mean CloudRun; first check whether the service needs long connections / custom runtime. Stateless HTTP services with a Dockerfile may fit HTTP cloud functions better. |
| Local run through tools | Supported | Not supported |
| Typical use | Streaming APIs, low-latency backend, Agent service | Custom language stack, migrated container app |
How to use this skill (for a coding agent)
- Choose mode first
- Function mode -> quickest path for HTTP/SSE/WebSocket or Agent scenarios
- Container mode -> use when Docker/custom runtime is a real requirement
- Follow mandatory runtime rules
- Container mode: listen on the injected
PORT. Function mode: the framework binds the port for you — never callapp.listen() - Settle the credential gate (who issues / how injected / how revoked) before writing any CloudBase SDK call
- Keep the service stateless
- Put durable data in DB/storage/cache
- Keep dependencies and image size small — the image carries code and dependencies only; media, user uploads and frequently-updated assets go to cloud storage (see Common mistakes)
- Respect resource ratio guidance:
Mem = 2 × CPU
- Container mode: listen on the injected
- Use the correct tools
- Read operations ->
queryCloudRun - Write operations ->
manageCloudRun - Delete requires explicit confirmation and
force: true - Always use absolute
targetPath
- Read operations ->
- Follow the deployment sequence
- Initialize or download code
- For a brand-new environment, ensure CloudRun is initialized first — call
manageCloudRun(action="initEnv", envId=...)(async, idempotent) before the first deploy;manageCloudRun(action="deploy")blocks new services on uninitialized environments and tells you to callinitEnv - For Container mode, verify Dockerfile
- Scan for DB/cache dependency signals (
DATABASE_URL, docker-compose DB services, ORM configs) - If TCP DB access is required, complete the VPC checklist in
references/vpc-and-database.mdbefore deploy - Local run when available
- Configure ingress access model and egress
VpcConfwhen needed - For
imageUrl/ third-party images, complete the five-item docs checklist in the Container deploy failure SOP before deploy - Deploy and verify detail output + DB connectivity
- If deploy fails, follow the Container deploy failure SOP (
references/image-deploy-troubleshooting.md) — docs →getProcessLog→ config; do not start withInitialDelaySeconds
Tool routing
Read operations
queryCloudRun(action="list")-> list servicesqueryCloudRun(action="detail")-> inspect one service and its latest deploy status when availablequeryCloudRun(action="templates")-> see available startersqueryCloudRun(action="getDeployLog")-> 构建日志(CODING /DescribeCloudRunBuildLog)。仅云端源码构建有意义;已有镜像部署(imageUrl)没有构建过程,不要用它诊断镜像部署失败。未登录 CODING 的账号会报错(如User not created or may not qcloud user)queryCloudRun(action="getProcessLog")-> 运行日志(tcbr/DescribeCloudRunProcessLog)。返回部署阶段步骤(如create_version_check_vpc/create_eks_virtual_service/check_eks_virtual_service)+ 容器启动/运行日志(s6-overlay、应用进程、readiness probe 失败原因)。镜像部署与源码构建均可用,不依赖 CODING。参数:detailServerName/serverName+ 可选runId(不传则取最新部署的RunId;RunId也可从detail/getDeployRecords的latestDeploy.RunId取得)queryCloudRun(action="getDeployRecords")-> list deploy records (newest first; includesBuildId/RunId/FlowRatio/Status) — use to review release history and rollback context before a traffic operationqueryCloudRun(action="envStatus")-> check whether the environment's CloudRun is opened and its provisioning status (Status=creatingopening /normalopened) — use afterinitEnvto poll progress or beforedeployto confirm readinessqueryCloudRun(action="getManageTask")-> 发布任务状态(tcbr/DescribeServerManageTask)。返回taskId/taskStatus与最新部署记录状态latestDeployStatus。用于两件事:撞到「已有部署发布任务运行中」时先确认任务是否真在推进;以及部署长时间无进展时,区分「任务仍在推进」和「任务已卡住」。不知道任务状态就不要反复重试 deploy
Log query SOP(构建日志 vs 运行日志)
部署失败排查时必须区分两类日志,不要只用 getDeployLog:
- 云端源码构建(传
targetPath、走 CODING 构建)- 先
queryCloudRun(action="getDeployLog", detailServerName=..., buildId=...)查构建日志(编译/打包失败) - 再
queryCloudRun(action="getProcessLog", detailServerName=..., runId=...)查运行日志(部署步骤 + 容器启动/健康检查)
- 先
- 已有镜像部署(传
imageUrl、DeployType=image)- 跳过
getDeployLog(无构建过程;且依赖 CODING,未登录会直接失败) - 直接
queryCloudRun(action="detail")或getDeployRecords取latestDeploy.RunId,再getProcessLog查运行日志
- 跳过
{
"action": "getProcessLog",
"detailServerName": "my-svc",
"runId": "<from latestDeploy.RunId>"
}Deploy-task SOP(撞到「已有部署发布任务运行中」时)
manageCloudRun(action="deploy") 报「已有部署发布任务运行中」/ already has a deploy task running 时,不要盲目重试,也不要反复改 Dockerfile / serverConfig —— 先确认任务真实状态:
queryCloudRun(action="getManageTask", detailServerName=...)→ 读taskId/taskStatus/latestDeployStatusqueryCloudRun(action="getProcessLog")→ 隔 20–40 秒对比两次拉取,确认部署阶段步骤是否还在推进- 按结果分支:
| 观察 | 动作 |
taskStatus 仍是运行态,部署步骤有推进 | 继续等,不要重发 deploy |
| 任务已结束(非运行态),而 deploy 仍被拒 | 才考虑重试 |
任务长时间停在非终态,版本也停在 creating 不动 | 记录 taskId / latestDeployStatus / 时间窗作为证据,不要空转重试 |
force=true 不解决这个问题:它只跳过本工具的确认提示,不会取消或覆盖服务端已有的发布任务 —— 把它当「强制覆盖」用只会白撞一次。
日志侧的排查顺序(构建日志 vs 运行日志、先日志后配置)见上面的 Log query SOP 与 Container deploy failure SOP。
Write operations
manageCloudRun(action="initEnv")-> open (initialize) CloudRun for the environment — async, idempotent (Status=normal→ already opened, no re-create). Use on a brand-new environment before the first deploy, or whendeployis blocked with an "尚未初始化云托管" message. Params:envId(defaults to the configured env),packageType(defaultTrial). PollqueryCloudRun(action="envStatus")untilStatus=normal.manageCloudRun(action="init")-> create local projectmanageCloudRun(action="download")-> pull remote codemanageCloudRun(action="run")-> local run for Function modemanageCloudRun(action="deploy")-> trigger deploy + lightweight wait for registration (does not hang for full build; passwaitRegistration=falseto skip even that wait when you don't needbuildId). ReturnsbuildId/runId/taskId+ DeployType-awarenext_step: source →getDeployLogthengetProcessLog; image (imageUrl, BuildId often0) → skipgetDeployLog, usegetDeployRecords/detailforRunIdthengetProcessLog. Follow the returnednext_step— do not always poll build logs. Existing services: RMW preserves remote VpcConf / EnvParams keys / OpenAccessTypes; new services automatically validate that the environment's CloudRun is initialized — if not, deploy is blocked with guidance to callinitEnvfirstmanageCloudRun(action="updateConfig")-> config-only update (no code upload; VPC / EnvParams / scaling / access types)manageCloudRun(action="traffic")-> traffic management / canary release (aligns withtcb cloudrun traffic):trafficOp="set"adjusts the stable/canary traffic ratio (stablePercent+canaryPercentmust equal 100, e.g. 90/10);trafficOp="promote"promotes the canary version to full release (100%, closes gray release, irreversible);trafficOp="rollback"rolls back to the previous stable version (stops the releasing canary). CheckqueryCloudRun(action="getDeployRecords")first to understand current versions and trafficmanageCloudRun(action="delete")-> delete servicemanageCloudRun(action="createAgent")-> create Agent service
Deploying an existing image (imageUrl)
已有一个现成镜像(本地构建好、或第三方发布)时,不需要本地源码目录,直接
manageCloudRun(action="deploy")传入imageUrl即可,走DeployType="image"(容器型)部署,targetPath可省略。若用户明确提到使用某个镜像或无需重新构建代码,必须传 imageUrl,不要仅因本地有源码目录就回退到源码构建。
决策路径(直填 vs 本地中转):
- 公网匿名可拉取(如
ccr.ccs.tencentyun.com/...、公开 Docker Hub 镜像)→ 直填 imageUrl:manageCloudRun(action="deploy", serverName=..., imageUrl="ccr.ccs.tencentyun.com/ns/img:v1", serverConfig={...})。CloudBase 会直接拉取该 registry 地址构建部署。若docker.io/ Docker Hub 在节点上反复拉取失败,不要空转重试:改用 DockerfileFROM <public-image>+targetPath源码构建(CODING 拉公网镜像,产物进 CCR 内网拉取)。见下方 SOP 第 4 步。 - 私有 / 需登录的 registry(
ghcr.io、私有 ECR/Harbor 等)→ 本地中转到 CCR:
然后把docker pull ghcr.io/example/app:latest docker tag ghcr.io/example/app:latest ccr.ccs.tencentyun.com/<ns>/app:latest docker login ccr.ccs.tencentyun.com docker push ccr.ccs.tencentyun.com/<ns>/app:latestccr.ccs.tencentyun.com/<ns>/app:latest作为imageUrl传入。中转只解决拉取,不能替代镜像文档里的启动命令 / 环境变量 / 数据目录。
与 initEnv 联动: 镜像部署同样要求环境已开通云托管。新环境首次部署前先 manageCloudRun(action="initEnv", envId=...),并用 queryCloudRun(action="envStatus") 轮询到 Status=normal;未开通时 deploy 会被拦截并引导先 initEnv。
示例:
{
"action": "deploy",
"serverName": "my-image-svc",
"imageUrl": "ccr.ccs.tencentyun.com/ns/app:latest",
"serverConfig": {
"OpenAccessTypes": ["PUBLIC"],
"Cpu": 0.5,
"Mem": 1,
"MinNum": 1,
"MaxNum": 3,
"Port": 8080,
"Cmd": ["node", "server.js"],
"EnvParams": "{\"PORT\":\"8080\",\"BIND_HOST\":\"0.0.0.0\"}"
}
}Port / Cmd / EnvParams 必须来自镜像官方文档的五要素清单,不要套用 3000 或省略启动命令。第三方镜像的完整对照见 references/image-deploy-troubleshooting.md 附录。
部署后:manageCloudRun(deploy) 对镜像返回的 next_step 默认指向 getProcessLog(或先 getDeployRecords 取 RunId),不要改去调 getDeployLog。也可用 queryCloudRun(action="detail") 查看 imageInfo(镜像地址与部署类型)。镜像部署失败排查走下方 SOP。
Container deploy failure SOP
顺序:先查镜像官方文档 → 再查运行日志 → 最后才动配置。禁止一看到 probe failed / deploy_failed 就调 InitialDelaySeconds。
详情与案例:references/image-deploy-troubleshooting.md。
1. 部署前:从镜像官方文档确认五要素
不要靠 Docker Hub tag 或「常见默认值」猜。部署前必须确认:
- 启动命令 EntryPoint / Cmd(进程如何前台常驻)→
serverConfig.EntryPoint/Cmd - 服务端口(进程真正 bind 的端口;不要假设 80/3000,也不要假设镜像尊重
PORT)→serverConfig.Port - 对外监听环境变量(必须
0.0.0.0而不是127.0.0.1、功能开关默认关闭等)→EnvParams - 数据目录挂载 →
serverConfig.VolumesConf - 健康端点(CloudRun readiness 探的是服务端口,不是任意 HTTP path)
缺任何一项再部署,失败看起来都会像「健康检查失败」。
2. 部署失败:用 getProcessLog 定性
镜像部署(imageUrl)跳过 getDeployLog(那是云端源码构建的构建日志)。从 detail / getDeployRecords 取 RunId,再 queryCloudRun(action="getProcessLog")。
启动日志存在 ≠ 服务正常运行。 banner、s6/tini 行、sidecar "listening" 都不能证明探针目标已起来。
两次日志对比判活: 隔 20–40 秒再拉一次 getProcessLog。
| 观察 | 定性 |
只有调度/创建步骤(create_eks_*),没有容器 stdout | Pod 调度中 / 镜像拉取 |
| 同一段启动 banner / PID 1 行重复出现(时间戳在走、内容几乎一样) | 容器启动即退出 / 重启循环 |
进程还在,但 listen 在 127.0.0.1 或端口 ≠ serverConfig.Port | 端口 / 绑定地址问题 |
| 两次拉取是同一条启动过程在往后打日志,banner 不重复 | 才可能是启动慢 |
3. Readiness probe 真实机制(严禁先调延迟)
部署步骤完成后:先等 N 秒(InitialDelaySeconds),再大约 每 5 秒 探一次服务端口,连续约 30 次全失败 才判本次部署失败。窗口 ≈ N+150s。不是「N 秒后立即失败」。
- 禁止: 看到 probe failed 就把 N 改成 120。崩溃循环和 loopback 绑定不会因为 N 变大而好。
- 允许调大 N 仅当: 两次日志证明同一个进程还在一次性初始化(JVM 预热、迁移)且尚未 listen。
4. 公网镜像(docker.io)反复失败 → Dockerfile 源码构建
节点直连 Docker Hub 反复失败时,不要空转 imageUrl。写:
FROM docker.io/example/app:latest用 targetPath 走云端源码构建:CODING 构建机拉公网镜像,产物进 CCR,云托管节点内网拉取。这只解决拉取拓扑,不替代第 1 步的 Cmd / 环境变量 / 卷。
5. Supervisor 镜像(s6 / tini / supervisord)启动即退出
PID 1 往往是监督进程,不是 HTTP 应用。用两次日志找子进程重启风暴。若镜像 issue 记录了 PID 1 / pgrep -f 误匹配,按文档 workaround(绝对路径 Cmd、关闭 supervise),不要调探针延迟。示例见 reference 附录。
Access guidance
- Web/public scenarios -> enable PUBLIC ingress intentionally and pair it with the right auth flow.
- Mini Program -> prefer internal direct connection and avoid unnecessary public exposure.
- Private ingress scenarios -> keep public access off unless the product requirement clearly needs it.
- Database / Redis in a VPC -> this is not solved by
OpenAccessTypes. You must setserverConfig.VpcConfand use the database private address. Readreferences/vpc-and-database.md.
Quick examples
Initialize
{ "action": "init", "serverName": "my-svc", "targetPath": "/abs/ws/my-svc" }Local run (Function mode)
{ "action": "run", "serverName": "my-svc", "targetPath": "/abs/ws/my-svc", "runOptions": { "port": 3000 } }Deploy (no VPC-private dependencies)
{
"action": "deploy",
"serverName": "my-svc",
"targetPath": "/abs/ws/my-svc",
"serverConfig": {
"OpenAccessTypes": ["PUBLIC"],
"Cpu": 0.5,
"Mem": 1,
"MinNum": 1,
"MaxNum": 5
}
}Deploy (existing app that connects to MySQL / PostgreSQL / Redis over TCP)
{
"action": "deploy",
"serverName": "my-existing-app",
"targetPath": "/abs/ws/my-existing-app",
"serverConfig": {
"OpenAccessTypes": ["PUBLIC"],
"Cpu": 0.5,
"Mem": 1,
"MinNum": 1,
"MaxNum": 5,
"EnvParams": "{\"DATABASE_URL\":\"postgres://user:pass@10.x.x.x:5432/app\"}",
"VpcConf": {
"VpcId": "vpc-xxxxxxxx",
"SubnetId": "subnet-xxxxxxxx"
}
}
}Valid OpenAccessTypes values: OA (办公网访问), PUBLIC (公网访问), MINIAPP (小程序访问), VPC (VPC访问). Use PUBLIC for web applications that need public HTTPS access.
MinNum: 1 is the recommended default when you want to reduce cold-start latency. If the user explicitly prefers lower cost and accepts more cold starts, explain the tradeoff and let them reduce MinNum to 0.
Best practices
- Prefer PRIVATE/VPC or mini-program internal ingress when possible.
- For TCP database access, always pair private DB URLs with
VpcConfin the same VPC/region as the database. - Use environment variables for secrets and per-environment configuration — read them server-side only; never return them in HTTP responses. CloudBase API Keys come from
manageAppAuth(action="createApiKey"), not from a local client login file. - Verify configuration before and after deployment with
queryCloudRun(action="detail"). - Keep startup work small to reduce cold-start impact.
- For Agent scenarios, use the Agent SDK skill for protocol and adapter details instead of duplicating them here.
- For smoke tests, return a fixed
{ "ok": true }/ health payload — never deploy httpbin or any service that reflects request headers.
Troubleshooting hints
- Access failure -> check ingress access type, domain setup, and whether the instance scaled to zero.
- Deployment blocked with "尚未初始化云托管 / not initialized" -> the environment needs CloudRun enabled first: call
manageCloudRun(action="initEnv", envId=...)(异步开通) and pollqueryCloudRun(action="envStatus")untilStatus=normal; or open the console环境 → 云托管 → 开通. For stateless HTTP services, consider an HTTP cloud function instead of CloudRun entirely. - Deployment failure -> follow the Container deploy failure SOP above (and
references/image-deploy-troubleshooting.md): image deploys skipgetDeployLogand usegetProcessLogonly; classify scheduling vs port vs exit-on-start with two log pulls. Do not raiseInitialDelaySecondsuntil logs prove a single slow init. Also inspect Dockerfile (source) and CPU/memory ratio. - Deploy rejected with "a deploy task is already running" / 「已有部署发布任务运行中」 -> read the real task state with
queryCloudRun(action="getManageTask")first. Do not retry blindly, and do not setforce=trueexpecting an override — it only skips this tool's confirmation prompt. See the Deploy-task SOP above. - Deploy accepted but the version never leaves
creating->queryCloudRun(action="getManageTask")forlatestDeployStatus+taskStatus, thengetProcessLogfor the deploy-phase steps. Only change Dockerfile / serverConfig once the logs actually point at code or config. - Local run failure -> remember only Function mode is supported by local-run tools.
- Performance issues -> reduce dependencies, optimize initialization, and tune minimum instances.
- DB / Redis connection failure after a successful deploy -> almost always missing or wrong
VpcConf, wrong private host, or security group. Followreferences/vpc-and-database.mdbefore rewriting application code. - CloudBase SDK call fails inside the service with missing / invalid credentials -> the credential gate above was skipped, or the variable name is not the official one. Issue a key with
manageAppAuth(action="createApiKey"), inject it asCLOUDBASE_APIKEYthroughEnvParams, redeploy, then verify a real read. See../cloud-functions/references/http-function-credentials.md.
Reference index
All packaged reference files (required for skill lint reachability):
- vpc-and-database.md
- image-deploy-troubleshooting.md
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