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Temporal Ops

OpenAIOfficialCreated by TemporalDistributed by OpenAI

  • Skill
  • Tool integration
  • Cloud and DevOps
  • MIT
  • No issues found

From the author

Administer and diagnose running Temporal Cloud or self-hosted Temporal Server environments via CLI (temporal, tcld) — not SDK code. Operations: namespace CRUD, Cloud capacity/APS, API-key rotation, mTLS cert rotation, workflow health, batch cancel/terminate/reset, export, search attributes, Ops API, billing, audit logs, Terraform, SAML/SCIM, migration. Diagnosis: bottom-up triage of stuck workflows, non-determinism, worker-health, task-queue problems, HA failover, payload size limits, performance bottlenecks, missed schedules. Do NOT trigger for generic TLS/gRPC errors unrelated to Temporal, writing application code (temporal-developer), or worker tuning/sizing (temporal-workertuning).
— the description by Temporal

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides a structured approach to managing and troubleshooting Temporal environments. It covers two primary modes: Operations, for administrative tasks like namespace management, API key rotation, and batch workflow actions; and Diagnosis, for investigating issues like stuck workflows, connectivity errors, and performance bottlenecks. It enforces strict operational discipline, including explicit confirmation for destructive commands and a bottom-up diagnostic methodology to ensure root causes are identified accurately.

What it does

  • Performs administrative operations on Temporal Cloud via tcld and self-hosted clusters via temporal operator.
  • Executes batch operations on workflows using query-based filtering with safety-first confirmation steps.
  • Diagnoses system issues using a layered, bottom-up approach from network connectivity to workflow logic.
  • Manages security configurations including API keys, mTLS certificates, and SAML/SCIM integrations.
  • Provides guidance on interpreting audit logs and cloud capacity metrics.
  • Routes complex tasks to specialized skills for development, worker tuning, or infrastructure configuration.

When to use it

  • When you need to perform administrative tasks like creating namespaces or rotating credentials.
  • When a Temporal environment is experiencing errors such as connection timeouts or authentication failures.
  • When you need to investigate or recover from stuck, non-deterministic, or unhealthy workflows.
  • When you need to perform bulk operations on workflows and require a safe, verified execution process.
  • When you need to audit or monitor the health and capacity of your Temporal Cloud account.

Advantages

  • Enforces safe operational practices by requiring explicit approval for destructive commands.
  • Provides a systematic diagnostic ladder to avoid speculative fixes.
  • Distinguishes clearly between Cloud and self-hosted administrative procedures.
  • Integrates safety checks like counting affected workflows before executing batch mutations.
  • Standardizes the interpretation of common gRPC and Temporal-specific error codes.

Usage examples

“How do I rotate my mTLS certificates for my Temporal Cloud namespace?”
The agent will guide you through the tcld commands for generating new certificates and updating the namespace configuration, ensuring you follow the correct rotation sequence.
“I am seeing 'context deadline exceeded' errors in my workflow. How do I debug this?”
The agent will initiate a bottom-up diagnosis, starting by verifying network connectivity and gRPC health before investigating specific workflow task execution logs.
“Terminate all workflows of type 'OrderProcessing' that are currently stuck.”
The agent will first run a count to identify the number of affected workflows, present this number to you for confirmation, and then execute the batch termination only after your approval.

Install

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/openai/temporal-ops/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip temporal-ops.zip -d .agents/skills

Documentation by Temporal

Skill: temporal-ops

Overview

This skill operates and diagnoses Temporal environments. It has two modes:

  • Operations: the user wants to do something — create a namespace, rotate a key, check capacity, find unhealthy workflows, cancel a batch, set up export. The skill executes the right commands and interprets the output.

  • Diagnosis: the user arrives with a symptom — a stuck workflow, a cert error, a connection timeout, a non-determinism panic. The skill routes the investigation through a layered, bottom-up diagnosis until a root cause is identified with a confidence score.

It does not teach how to write workflows or activities (use skill-temporal-developer for that), and it does not reproduce exhaustive CLI flag tables — run temporal <cmd> --help for those, and see cli-conventions.md for cross-command CLI conventions. The boundary is: if the user needs to administer or troubleshoot a running Temporal environment, this skill applies.

Out of scope

  • Writing workflows, activities, or SDK code → skill-temporal-developer.

  • Exhaustive CLI flags / command reference → run temporal <cmd> --help; cross-command CLI conventions → cli-conventions.md.

  • Worker performance tuning, sizing, capacity planning → skill-temporal-workertuning.

  • Helm, Kubernetes, database admin, monitoring stack config for self-hosted — beyond the CLI surface.

If the conversation drifts into one of these areas, hand off to the relevant sibling skill rather than improvising.

Philosophy

Operator discipline

When the user wants to perform an operational task:

  1. Identify the intent and backend. Is this a Cloud operation (tcld) or a self-hosted operation (temporal operator)? Data-plane operations (temporal workflow, temporal batch, etc.) work on both. If the backend is ambiguous, ask before proceeding — do not assume Cloud or self-hosted and do not output environment-specific commands until you know.

  2. Execute commands and interpret output. Run the documented command, read the result, and report what it means — or act on it if the user asked for an action. Read-only commands (get, list, describe, count, show) run freely. Anything listed under Destructive operations is proposed to the user first.

  3. Verify the result. After a mutating operation, confirm the new state matches the user's intent.

Destructive operations

An operation belongs to this tier if it is irreversible (tcld namespace delete), revokes access for a live identity (tcld apikey delete), moves production traffic (tcld namespace failover), or fans out to every match (any --query form). Apply the test to the operation in front of you — this is a rule, not a list, and a command's absence from any list in this skill does not place it outside the tier.

For anything in the tier: gather the evidence and propose. Do not run it on your own initiative, and do not run one to find out what it would do. The reference file for each command states its specific blast radius; read that before proposing, not after.

  1. Blast radius as a number, not a description. For any --query form, run temporal workflow count --query '<query>' with the byte-identical query first and carry the result into the proposal. A filter with no narrowing predicate beyond ExecutionStatus="Running" matches every open Execution in the Namespace.

  2. Name the target. State the exact command, the target, and the Namespace it resolves to. Connection settings can come from TEMPORAL_* env vars or a config-file profile, so the target is frequently not visible in the command text. If the backend or Namespace was inferred from context rather than stated by the user, say so — a destructive command aimed at the wrong Namespace is the most common way this goes wrong.

  3. Ask explicitly, then run it so it completes. Put the command, the target, and — for any --query form — the count from step 1 to the user as a direct question, and wait for an answer. Once they approve, run it with --yes on the --query batch forms; that flag is what lets an approved batch finish, since the interactive prompt needs a terminal and without one the command reports user denied confirmation and does nothing. --yes belongs in a command the user approved, never in a retry of one that failed its prompt. Do not substitute a loop over single-target workflow terminate --workflow-id. Approval covers one command against one target; it does not carry to the next command, a widened query, or a second Namespace.

  4. Verify, and know the abort path. Re-run the corresponding get, describe, or count. A batch job drains asynchronously: temporal batch describe --job-id <id> shows how far it has gotten and temporal batch terminate --job-id <id> stops it before it reaches the rest of its matches.

When a reversible sibling reaches the same goal, propose it alongside: cancel lets Workflow cleanup code run where terminate does not; apikey disable is reversible where delete is not; accepted-client-ca add appends where set replaces.

Assume nothing in the environment will stop a destructive command on your behalf. Credential scope, command denylists, and confirmation prompts may or may not be configured, and their possible presence is not a reason to skip any step above — you are the safeguard the user is relying on.

Diagnostic discipline

When the user arrives with a failure or anomaly:

  1. Bottom-up diagnosis. Verify the lower layer before blaming the upper one. The layers, from bottom to top:

    1. DNS / network path

    2. TCP / port reachability

    3. TLS handshake

    4. Authentication (API key or mTLS client cert)

    5. gRPC health and Temporal frontend reachability

    6. Temporal namespace, task queues, workers

    7. Workflow code (determinism, signals, timers, child workflows)

    The full ladder lives in diagnostic-ladder.md.

  2. Always verify the next layer up rather than prescribing a speculative fix. If TLS works, prove auth works before blaming the workflow. If pollers are present, prove the workflow's last event before blaming the worker.

  3. Attach a confidence score (1-10) to every proposed diagnosis:

    • 9-10: symptoms, operation, and confirming signals line up cleanly.

    • 6-8: evidence is good but at least one alternative remains plausible.

    • 1-5: the issue is still ambiguous; the "fix" is the next discriminating check, not a root cause.

  4. Name ambiguity explicitly. Errors like context deadline exceeded are not self-describing, and a single code such as RESOURCE_EXHAUSTED can mean more than one condition (account-limit throttling vs. per-Workflow lock contention). Surface that, gather more context, and scope the next step narrowly.

These are skill conventions, not docs-derived facts.

Intent routing

Operations

Find the row that matches the user's intent. The reference file contains the commands and procedures.

IntentCategoryReference
Create, get, list, delete a Cloud namespaceCloud namespace admincloud-namespace-admin.md
Add/remove region, failover, HA configCloud namespace admincloud-namespace-admin.md
Set retention, tags, codec-server, connectivity rulesCloud namespace admincloud-namespace-admin.md
Add or rename Cloud search attributesCloud namespace admincloud-namespace-admin.md
Check current APS / capacity modeCloud capacitycloud-capacity.md
Switch On-Demand ↔ Provisioned, set TRUsCloud capacitycloud-capacity.md
Understand APS / RPS / OPS limits and throttlingCloud capacitycloud-capacity.md
Create, disable, enable, delete an API keyCloud IAMcloud-iam.md
Invite, list, remove users; set roles/permissionsCloud IAMcloud-iam.md
Manage user groups and service accountsCloud IAMcloud-iam.md
Generate mTLS certs, upload CA, set cert filtersCloud certscloud-certs.md
Rotate mTLS certificatesCloud certscloud-certs.md
Set up Workflow History Export (S3 / GCS)Cloud namespace admincloud-namespace-admin.md
Set up PrivateLink / PSC, manage connectivity rulesCloud connectivitycloud-connectivity.md
Self-hosted cluster health, describe, namespace CRUDSelf-hosted adminself-hosted-admin.md
Self-hosted search attributes, Nexus endpointsSelf-hosted adminself-hosted-admin.md
Check or manage a Cloud Nexus Endpoint's caller-Namespace allowlist; the 1,000-caller defaultCloud namespace admincloud-namespace-admin.md#tcld-nexus-endpoint-allowed-namespace
Find stuck/hung/unhealthy workflows via list queriesWorkflow healthworkflow-health.md
Task queue poller status, workflow countsWorkflow healthworkflow-health.md
Cancel, terminate, or reset workflowsWorkflow recoveryworkflow-stuck.md#recovery-commands
Bulk / batch operations on workflows (--query)CLI conventionscli-conventions.md
Schedule CRUD, time-spec, and operationsCLI conventionscli-conventions.md
Complete or fail an activity externallyCLI conventionscli-conventions.md
Cloud Ops API access, rate limits, Go SDKCloud Ops APIcloud-ops-api.md
View billing, generate billing report, cost attributionCloud billingcloud-billing.md
Audit Logs: view, query via API, configure sink (AWS/GCP)Cloud audit logscloud-audit-logs.md
Terraform provider: Namespace/User/SA/API Key/Nexus CRUDCloud Terraformcloud-terraform.md
Expiry alerts (cert, API key, credit), status pageCloud notificationscloud-notifications.md
SAML SSO, SCIM provisioning, IdP integrationCloud SAML/SCIMcloud-saml-scim.md
Migrate self-hosted to Cloud (automated or manual), migrate between Cloud regionsCloud migrationcloud-migration.md
End-to-end ops playbook (setup, rotation, audit, billing, Terraform)Ops recipesops/recipes.md
Diagnosis

Find the row that matches the user's symptom. Start the investigation at the first check, then read the linked reference.

SymptomCategoryFirst checkReference
connection refused, cannot reach frontendConnectivitync -zvw10 <host> 7233connectivity.md#connection-refused
no such host, DNS resolution failsConnectivitydig +short <host> or nslookup <host>connectivity.md#dns
tls: handshake failure, server rejects handshakeCertificatesopenssl s_client -connect <host>:7233 -servername <host> </dev/nullcertificates.md#handshake-failure
x509: certificate has expired or not yet validCertificatesopenssl x509 -enddate -noout -in cert.pemcertificates.md#expired-or-not-yet-valid
x509: certificate signed by unknown authorityCertificatesopenssl verify -CAfile ca.pem client.pemcertificates.md#unknown-authority
tcld session / auth fails, Cloud role unclearAuthenticationtcld account getauthentication.md#cloud-role-and-permission-model
UNAUTHENTICATED, API key rejectedAuthenticationenv | grep -i TEMPORAL_API_KEY, then tcld apikey get --id <apikey_id>authentication.md#things-to-check-when-unauthenticated-is-returned-with-an-api-key
namespace not found / wrong namespace string with an API keyAuthenticationConfirm Regional Endpoint form <region>.<cloud_provider>.api.temporal.io:7233authentication.md#address-form-for-api-key-connections
RESOURCE_EXHAUSTED gRPC statusRate limitsIdentify which limit fired: throttle metrics on Cloud v1, the resource_exhausted_cause label on v0 / self-hostedrate-limits.md#identifying-which-limit-was-hit
Task queue shows no pollersWorker healthtemporal task-queue describe --task-queue <q>worker-health.md#what-no-pollers-looks-like
Workflow stuck on a pending activity / timer / child / signalWorkflow stucktemporal workflow describe --workflow-id <id>workflow-stuck.md#the-primary-inspection-command-temporal-workflow-describe
NondeterminismError, repeating WorkflowTaskFailedNon-determinismIdentify the last WorkflowTaskFailed cause in the Event Historynon-determinism.md#the-wft-failure-signature-of-non-determinism
Replay fails locally but prod workflow was runningNon-determinismFetch the history and run the SDK replayer in one testreplay.md#step-2--run-the-sdk-replayer-all-supported-sdks
HA failover did not route traffic to failover regionHA failovertcld namespace get --namespace <ns>.<acct> vs. DNS CNAMEha-failover.md#start-here-establish-ground-truth
Serverless Worker (AWS Lambda) stopped processing work after a Namespace failoverHA failoverConfirm a FailoverNamespace audit event, then compare the new active region against the Lambda ARN on the Worker Deployment Versionha-failover.md#symptom-serverless-workers-kept-running-in-the-old-region-after-failover
context deadline exceeded (unknown layer)Runtime errorsIdentify which operation and SDK emitted itruntime-errors.md#deadline-exceeded
Workflow is busy / ResourceExhausted on signal/update/query to one Workflow (BusyWorkflow)Runtime errorsRule out account-limit throttling, then split temporal_cloud_v1_resource_exhausted_error_count by operationruntime-errors.md#workflow-lock-contention-busyworkflow
PAYLOADS_TOO_LARGE, exceeds size limit, payload/gRPC blob size errorBlob size limitsCheck whether the issue is payload (2 MB) or gRPC message (4 MB)blob-size-limits.md
Workflow stuck in invisible retry loop (gRPC message too large)Blob size limitsCheck Worker logs for ResourceExhausted, reduce batch sizeblob-size-limits.md
High schedule-to-start latency, task slot depletion, slow Workflow TasksPerformance bottlenecksCheck temporal_workflow_task_schedule_to_start_latency P95performance-bottlenecks.md
High replay latency, cache evictions, deadlock detectedPerformance bottlenecksCheck workflow_task_replay_latency and sticky cache metricsperformance-bottlenecks.md
Schedule did not fire, missed catchup windowMissed Schedule ActionsAlert on temporal_cloud_v1_schedule_missed_catchup_window_countschedule-missed.md

If a symptom does not map to a row, start at diagnostic-ladder.md and work up from whichever layer was last known healthy.

The process

Operations path
Step 1: Identify intent and backend

Determine what the user wants to do and whether it targets:

  • Temporal Cloud → use tcld commands (requires tcld login)

  • Self-hosted cluster → use temporal operator commands

  • Data plane (either backend) → use temporal workflow, temporal batch, temporal schedule, etc.

If the backend is unambiguous from context — .tmprl.cloud address, tcld command, Cloud namespace format ns.account → Cloud; Kubernetes/Helm, docker-compose, self-hosted config files → self-hosted — proceed without asking. Otherwise, stop and ask: "Are you on Temporal Cloud or self-hosted?" before outputting any environment-specific commands. Do not default to either environment. Once known, save the answer to memory so you don't ask again in future conversations.

Step 2: Execute and interpret

Look up the intent in the Operations table above. Read the linked reference file for the exact commands, flags, and expected output. Run the command and interpret the result for the user.

Step 3: Verify

After a mutating operation (create, update, delete, rotate), confirm the new state:

  • Re-run the corresponding get or describe command

  • Confirm the output matches the user's intent

  • Report the result

Diagnosis path
Step 1: Identify the symptom

Ask the user for the exact, copy-pasted error text. Do not accept paraphrases — the exact string often encodes the layer (e.g., x509: prefix means TLS/cert layer, RESOURCE_EXHAUSTED: prefix means gRPC rate limit, NondeterminismError means workflow replay layer). Note that RESOURCE_EXHAUSTED alone does not tell you which condition fired — account-limit throttling and per-Workflow lock contention (Workflow is busy, i.e. BusyWorkflow) share the code. Split the resource-exhausted metric by its label (operation on the Cloud v1 family, resource_exhausted_cause on v0 and self-hosted) rather than parsing the free-text message.

Confirm three things before continuing:

  • What command was run, or what SDK call produced the error?

  • What environment produced it (local dev server, self-hosted cluster, Temporal Cloud)? If clear from context (addresses, commands, namespace format), don't ask — but if uncertain, ask now before proceeding with any diagnosis. Save the answer to memory for future conversations.

  • What changed recently (new deploy, new certs, new namespace, new region)?

Step 2: Gather context

The context the investigation needs depends on the category. At minimum:

  • For any Cloud auth / connectivity issue: auth method (API key vs mTLS), exact address, exact namespace, SDK + version. The endpoint family differs by auth method — see connectivity.md#endpoint-formats. For private connectivity (PrivateLink / PSC), TLS server name overrides also vary by auth method — see cloud-connectivity.md.

  • For a stuck workflow: namespace, workflow ID, run ID, and the output of temporal workflow describe --workflow-id <id> (pending-operation state lives here, not in the Event History alone). Event History via temporal workflow show is the companion view.

  • For a worker health issue: worker logs (registration errors, auth errors, panics), the output of temporal task-queue describe --task-queue <q>, and temporal worker describe --task-queue <q> for per-worker details.

  • For a non-determinism error: the worker log line containing the error, the workflow type name, and access to the history JSON for replay.

Step 3: Validate pasted SDK config (if any)

If the user has pasted SDK connection code — even just the address/namespace/auth fields — review it against sdk-snippet-review.md before descending the ladder. Wrong endpoint family, short namespace, or mismatched auth method will make every network-layer probe below look broken when nothing lower actually is.

Skip this step when the user has an established, previously-working config and the symptom is new — the snippet is not the culprit, the environment changed. Otherwise treat snippet validation as Layer 0.

Step 4: Descend the ladder

Use diagnostic-ladder.md to pick the right starting layer. As a rule of thumb:

  • Auth / connectivity / cert symptom → start at layer 1 (DNS) and walk up.

  • Worker / task-queue symptom → start at layer 6 (namespace + pollers).

  • Stuck workflow / determinism symptom → start at layer 7 (workflow code), but confirm layer 6 (worker is actually polling) first.

Each layer has a command that proves it healthy and a failure signature that tells you whether the problem lives at that layer or higher.

Step 5: Fix and verify

Prescribe the fix scoped to the root cause. Then verify by re-running the layer's healthy-check command and, if possible, the original user operation. Attach the confidence score to the diagnosis.

If the layer above the fix is still failing, return to step 4 and continue walking upward — the first broken layer is rarely the only one.

Prerequisites

  • Temporal CLI (temporal) — required for data-plane operations and self-hosted admin. Install: brew install temporal or see Temporal CLI docs.

  • tcld — required for Cloud operations. Install: brew install temporal-cloud-cli or see tcld docs. Authenticate with tcld login before use.

Reference files

Operations
  • cloud-namespace-admin.md — Cloud namespace lifecycle via tcld: create, get, list, delete, failover, add-region, retention, tags, codec-server, HA config, connectivity rules, search attributes, accepted-client-ca, certificate filters, export, and the tcld nexus endpoint allowed-namespace caller allowlist (1,000-caller Access Policy ceiling).

  • cloud-capacity.md — Capacity modes (On-Demand / Provisioned), APS/RPS/OPS definitions, TRUs, tcld namespace capacity update, default limits, throttling, APS management best practices.

  • cloud-iam.md — API key lifecycle (tcld apikey), users (tcld user), user groups (tcld user-group), service accounts, account operations (tcld account), roles, namespace permissions.

  • cloud-certs.md — mTLS cert management: generating certs with tcld generate-certificates, uploading CAs, certificate filters, cert rotation, switching mTLS ↔ API keys.

  • cloud-connectivity.md — Private connectivity (AWS PrivateLink / GCP PSC), connectivity rules: setup, rule parameters, tcld commands, attaching rules to namespaces.

  • cloud-migration.md — Migration paths: automated self-hosted→Cloud (S2S proxy, tcld migration commands, 5 phases), manual self-hosted→Cloud (client changes, workflow strategies), within-Cloud region-to-region (HA add-region/failover).

  • cloud-ops-api.md — Cloud Ops API: HTTP and gRPC endpoints (saas-api.tmprl.cloud), Go SDK, protobuf compilation, rate limits (160 RPS account, 40 user, 80 SA, 10 concurrent async), API version header, use cases.

  • cloud-billing.md — Cloud billing: Billing Center (invoices, credits, plans, cost by namespace), Usage Dashboards, Billing API: async CSV report generation, FOCUS-friendly format, 27-column report schema, date range constraints.

  • cloud-audit-logs.md — Cloud Audit Logs: supported control plane events (Account, API Keys, Connectivity Rules, Namespace, Export, Nexus, Service Accounts, User, User Groups), JSON format, API access (30-day retention), AWS Kinesis and GCP Pub/Sub sink configuration.

  • cloud-terraform.md — Terraform provider: setup (TEMPORAL_CLOUD_API_KEY), temporalcloud_namespace/temporalcloud_user/temporalcloud_service_account/temporalcloud_apikey/temporalcloud_nexus_endpoint CRUD, import, data sources (regions, namespaces), limitations (API keys not importable, cannot manage Account Owner).

  • cloud-notifications.md — Cloud notifications: certificate expiry (15/10/5 days), API key expiry (30/20/10 days), credit consumption/expiry alerts, plan changes, failover events, recipient roles, [email protected] sender.

  • cloud-saml-scim.md — SAML SSO (Entra ID, Okta): entity identifier (urn:auth0:prod-tmprl:ACCOUNT_ID-saml), callback URL (login.tmprl.cloud), IdP configuration steps, support ticket workflow. SCIM: supported vendors, prerequisites (SAML first), 10-minute sync window, group-to-role mapping.

  • self-hosted-admin.md — Self-hosted control plane via temporal operator: cluster health/describe, namespace CRUD, search-attribute create/list/remove, Nexus endpoint CRUD.

  • workflow-health.md — Data-plane health queries: temporal workflow list with List Filters, temporal workflow describe/show/count, temporal task-queue describe for poller status.

  • cli-conventions.md — Cross-command temporal CLI conventions: connection/identity (TEMPORAL_* env vars ↔ --address/--namespace/--api-key, --identity), output/formatting (--output, --time-format, payload shorthand), the --query ⇒ batch-job bridge (with temporal batch describe/list/terminate), and schedule time-spec forms. Ends with an operation→command index that routes each data-plane operation to its owner file. Delegates exhaustive flags to temporal <cmd> --help.

  • ops/recipes.md — End-to-end ops playbooks: set up new namespace, check APS, switch capacity mode, find hung workflows, rotate API key, audit access, rotate mTLS certs, check self-hosted health, view billing / generate billing report, configure audit log sink, provision resources with Terraform, set up SAML SSO.

Diagnosis
  • sdk-snippet-review.md — Layer-0 config check for pasted SDK connection snippets: endpoint form per auth method, namespace format, auth / TLS expectations, TEMPORAL_* env vars, common misconfigurations. Run before the diagnostic ladder.

  • diagnostic-ladder.md — the seven-layer bottom-up model, with one canonical command per layer and cross-links into the topical leaves.

  • connectivity.md — DNS, TCP, endpoint families (Namespace Endpoint for mTLS vs. Regional Endpoint for API keys), firewall/proxy shapes, PrivateLink/PSC, quick diagnostic scripts.

  • certificates.md — x509 and TLS alert strings, expiry / unknown-authority / hostname-mismatch / key-mismatch diagnosis, Cloud accepted-client-CA set via tcld namespace accepted-client-ca, Cloud mTLS certificate requirements, rotation and expiry notifications, openssl recipes.

  • authentication.md — UNAUTHENTICATED vs PERMISSION_DENIED, API-key lifecycle (tcld apikey commands, env var propagation, required Regional Endpoint form), mTLS after TLS (certificate filters, identity-to-role mapping), Cloud account-level roles and namespace-level permissions.

  • workflow-stuck.md — Workflow Execution Status values, temporal workflow describe as the primary inspection command, Event History via temporal workflow show, pending activities / child workflows / signals / Nexus operations / Workflow Tasks, WorkflowTaskFailed retry loops, recovery commands (signal, terminate, cancel, reset, pause/unpause).

  • non-determinism.md — determinism definition, WFT-failure signature, ND-inducing code patterns, per-SDK error shapes, identifying ND from Event History, local replay reproduction, remediation via Worker Versioning / patching / reset.

  • worker-health.md — no-pollers runbook via temporal task-queue describe, reachability and versioning, worker-level describe, schedule-to-start latency, worker task slots, sticky execution and sticky cache, worker heartbeating, Cloud namespace-level poller limits, worker log signatures.

  • rate-limits.md — what RESOURCE_EXHAUSTED means (and does not), Cloud APS / RPS / OPS under On-Demand and Provisioned capacity modes, self-hosted frontend.rps / frontend.namespaceRPS dynamic config, identifying which limit fired via the throttle metrics (Cloud v1) or the resource_exhausted_cause label (v0 / self-hosted), and separating account-limit throttling from single-resource exhaustion.

  • ha-failover.md — Cloud HA routing via the Namespace Endpoint CNAME, verifying the active region (control-plane tcld namespace get vs. DNS view), clients that did not follow the failover, PrivateLink after failover, failover-not-executing, handover-window errors, platform limits, RPO/RTO semantics, and Serverless Workers (AWS Lambda) not following a failover because compute-provider configuration is region-scoped.

  • runtime-errors.md — deadline-exceeded disambiguated by operation and by where the call was made, Workflow lock contention (BusyWorkflow) separated from account-limit throttling and confirmed via the operation breakdown, routing for no pollers / INVALID_ARGUMENT / unspecified UNAVAILABLE.

  • replay.md — fetching Event History with the SDK client (CLI export as fallback), running the SDK replayer in every supported SDK (Go, Python, TypeScript, Java, .NET, Ruby, PHP), TEMPORAL_DEBUG and the deadlock detector, interpreting divergent and successful replays, and the TypeScript-only VS Code extension.

  • blob-size-limits.md — Payload size limit (2 MB) and gRPC message size limit (4 MB): error messages, per-SDK behavior (Python 1.23.0+ vs. others), claim check pattern, External Storage (Pre-release), batch-size reduction.

  • performance-bottlenecks.md — Latency and throughput diagnosis via SDK metrics: schedule-to-start latency, workflow task execution latency, replay latency, activity execution latency, task slot depletion, network request metrics, sticky cache metrics.

  • schedule-missed.md — Missed Schedule Actions: alerting via temporal_cloud_v1_schedule_missed_catchup_window_count / schedule_missed_catchup_window, investigation via temporal schedule list + temporal schedule describe, DescribeSchedule fields (missedCatchupWindow, overlapSkipped, bufferDropped), default catchup window (one year), root causes, overlap policies (6 values), backfill remediation.

  • recipes.md — four end-to-end triage walkthroughs: stuck workflow at 3am, cert expired with workers offline, task-queue backlog mystery, non-determinism caught in prod.

Feedback

Feedback prompt

When you have first loaded this skill, output this message to the user:

"Thank you for trying out the public preview of the Temporal Ops skill! We would love to hear your feedback - positive or negative - over in the Community Slack, in the #topic-ai channel."

Do not output this message multiple times in the same conversation.

Reporting Issues in This Skill

If you (the AI) find this skill's explanations are unclear, misleading, or missing important information, draft a GitHub issue body describing the problem encountered and what would have helped, then ask the user to file it at https://github.com/temporalio/skill-temporal-ops/issues/new. Do not file the issue autonomously.

Files

references/triage/rate-limits.md

Rate Limits

Diagnose gRPC RESOURCE_EXHAUSTED against Temporal — what budget was exceeded, which party enforced it, and how to tell from the error text and Cloud signals. This file covers one specific gRPC status code; it does not cover every "things feel slow" symptom.

Prerequisite: RESOURCE_EXHAUSTED is returned after the connection, TLS, and auth layers have succeeded. If you do not yet know that the caller is reaching the frontend, rule out layers 1–3 first via connectivity.md, certificates.md, and authentication.md.

Out of scope here:

Table of Contents

  • What RESOURCE_EXHAUSTED means and what it does not

  • Temporal Cloud: APS, RPS, OPS and capacity modes

  • Self-hosted: service-level RPS via dynamic configuration

  • Server throttled me vs. client throttled itself

  • Identifying which limit was hit

  • What RESOURCE_EXHAUSTED is not

  • Quick routing

What RESOURCE_EXHAUSTED means and what it does not

RESOURCE_EXHAUSTED is one of the 17 canonical gRPC status codes. In the spec it means "Some resource has been exhausted, perhaps a per-user quota, or perhaps the entire file system is out of space." On Temporal, it is the code the frontend returns when a request is throttled against a configured rate limit rather than rejected for identity or input reasons.

Key scoping facts:

  • It is not UNAVAILABLE (connectivity / transient peer failure), not DEADLINE_EXCEEDED (the caller's deadline fired), and not PERMISSION_DENIED (identity known, action forbidden). Mapping a rate-limit symptom onto one of those codes is a common triage mistake — see authentication.md → UNAUTHENTICATED vs PERMISSION_DENIED for the boundary.

  • Temporal Cloud documents the server-returned value as ResourceExhausted: "When throttled, the server returns a ResourceExhausted gRPC error." The gRPC wire name is RESOURCE_EXHAUSTED; client SDKs surface it as an ResourceExhausted-named exception. Both refer to the same code.

  • On self-hosted, the same code is emitted when the frontend's RPS budget is exceeded: "Exceeding these limits results in ResourceExhaustedError."

Temporal Cloud: APS, RPS, OPS and capacity modes

Cloud enforces three per-Namespace throughput limits, each of which can independently produce RESOURCE_EXHAUSTED:

LimitDefaultScopeWhat it counts
Actions per second (APS)500 APSNamespaceBillable Actions — starts, Signals, Updates, Activity starts / retries / heartbeats, Timers, etc.
Requests per second (RPS)2000 RPSNamespacegRPC requests to the frontend. A lower-level measure of load at the service level.
Operations per second (OPS)4000 OPSNamespaceOperations (user-driven or Temporal-internal) that hit the Temporal Server on the user's behalf. See the operations list for the set.

All three have the same automatic scaling behavior under the default On-Demand Capacity mode: the limit "automatically increases (and decreases) based on the last 7 days of [APS/RPS/OPS] usage. Will never go below the default limit." The On-Demand formula is documented as "the lesser of 4 × APS Average or 2 × APS P90 over the past 7 days."

Provisioned Capacity replaces the automatic envelope with a fixed allocation, expressed in Temporal Resource Units (TRUs); each TRU supplies 500 APS / 1500 RPS / 4000 OPS. TRUs are set via UI, tcld namespace capacity update, or the UpdateNamespace API. Adjustments are hourly.

There are additional, narrower Namespace-scoped rate limits that also surface as RESOURCE_EXHAUSTED:

  • Schedules rate limit: 10 schedule requests per second, per Namespace, not configurable via UI — raise via a support ticket. The Cloud metric temporal_cloud_v1_schedule_rate_limited_count tracks workflows delayed due to this limit.

  • Visibility API rate limit: 30 Visibility API calls per second per Namespace; not configurable. "All read calls are subject to the Visibility API rate limit."

  • Concurrent Task pollers: 20,000 Activity pollers and 20,000 Workflow Task pollers per Namespace concurrently. Per-Namespace poll saturation falls under poller health — see worker-health.md.

Throttling behavior (Cloud)

From the Cloud limits reference:

  • Priority-based throttling. "Low-priority operations are throttled first. Higher-priority operations like StartWorkflowExecution, SignalWorkflowExecution, and UpdateWorkflowExecution continue to go through when possible."

  • Throttling latency. "Rate limiting is not instantaneous, so usage may briefly exceed your limit before throttling takes effect."

  • SDK retry by default. "SDK clients automatically retry these based on the default gRPC retry policy."

  • Persistent throttling fails the call. "If throttling persists beyond the SDK's retry limit, client calls fail."

  • Per the Cloud docs, Actions that are external to the core Temporal service do not contribute to APS — e.g. Export and Capacity-related Actions.

Self-hosted: service-level RPS via dynamic configuration

On a self-hosted cluster, per-Namespace and per-host rate limits are dynamic-configuration keys. The docs name these explicitly as producers of ResourceExhaustedError: "Exceeding these limits results in ResourceExhaustedError."

Commonly referenced frontend keys (defaults from docs/references/dynamic-configuration.mdx, Temporal server v1.21; verify against the version you run):

KeyDefaultWhat it limits
frontend.rps2400Requests per second accepted by each Frontend Service host
frontend.namespaceRPS2400Requests per second per Namespace, per Frontend host
frontend.globalNamespaceRPS0 (disabled)Cluster-wide per-Namespace RPS, distributed across Frontend hosts. When set, overrides frontend.namespaceRPS.
history.rps3000Per History Service host
matching.rps1200Per Matching Service host

Defaults shift across server versions. Before quoting a number to a user, check their server version against docs/references/dynamic-configuration.mdx or the release notes.

Persistence-store QPS keys (frontend.persistenceMaxQPS, history.persistenceMaxQPS, etc.) are evaluated synchronously and produce latency / timeouts rather than RESOURCE_EXHAUSTED to the client: "If the number of queries made to the Persistence store exceeds the dynamic configuration value, you will see latencies and timeouts on your tasks." Persistence saturation therefore usually surfaces as DEADLINE_EXCEEDED, not RESOURCE_EXHAUSTED — see runtime-errors.md.

Server throttled me vs. client throttled itself

RESOURCE_EXHAUSTED on the wire is always server-emitted. But "why is my caller falling behind?" can also be the caller throttling itself — those two look alike from a dashboard but need different fixes.

  • Server-enforced limit hit → RESOURCE_EXHAUSTED returned to the caller. Cloud APS/RPS/OPS; self-hosted frontend.rps/frontend.namespaceRPS; Cloud Schedules limit; Visibility API limit. The SDK default retry policy retries the RPC with exponential backoff until its retry budget is exhausted, after which the call fails to the application.

  • Client-side throttling (no RESOURCE_EXHAUSTED on the wire). A worker may be limiting its own rate via SDK settings — e.g. TaskQueueActivitiesPerSecond or (Max)WorkerActivitiesPerSecond. These produce Activity schedule-to-start latency, not RESOURCE_EXHAUSTED: "Setting TaskQueueActivitiesPerSecond too low can limit the rate at which Activities are started, leading to increased Schedule-to-start latency." If the reported error is high temporal_activity_schedule_to_start_latency without RESOURCE_EXHAUSTED, the problem is worker-side — go to worker-health.md.

A quick discriminator: inspect the failed RPC's gRPC status. If the code is literally RESOURCE_EXHAUSTED, the server throttled it. If the RPC never left the worker or returned some other status, the ceiling is client-side.

Rule of thumb: retries themselves count against the budget. A caller that retries RESOURCE_EXHAUSTED without backoff makes the situation worse. The default gRPC retry policy used by the SDKs already includes backoff; custom clients that reimplement retry need to do the same.

Identifying which limit was hit

Two sources of signal: the gRPC error itself and the Cloud metrics endpoint.

From the error

RESOURCE_EXHAUSTED carries a free-text message whose wording varies by server version and by which internal limiter fired, so rely on the gRPC code plus the metric label rather than pattern-matching the text. Which label depends on the metric family:

EnvironmentMetricLabel to split by
Cloud, v1 metricstemporal_cloud_v1_resource_exhausted_error_countoperation
Cloud, v0 metricstemporal_cloud_v0_resource_exhausted_error_countresource_exhausted_cause, "Cause for resource exhaustion"
Self-hostedservice_errors_resource_exhaustedresource_exhausted_cause

Self-hosted: the deadline-exceeded troubleshooting page recommends sum(rate(service_errors_resource_exhausted{}[1m])) by (resource_exhausted_cause) to check for RpsLimit, ConcurrentLimit, and SystemOverloaded causes.

One documented message string does exist: per-Workflow lock contention appears in Service logs as Workflow is busy. That is a different condition from account-limit throttling and is not fixed by raising limits — see runtime-errors.md → Workflow lock contention (BusyWorkflow).

From Cloud metrics

Temporal Cloud exposes an OpenMetrics endpoint whose limit / count / throttle triples let you tell "which budget is saturating" without guessing.

BudgetLimit metricCount metricThrottle metric
Actionstemporal_cloud_v1_action_limittemporal_cloud_v1_total_action_counttemporal_cloud_v1_total_action_throttled_count
Frontend gRPC requeststemporal_cloud_v1_service_request_limittemporal_cloud_v1_service_request_counttemporal_cloud_v1_service_request_throttled_count
Operationstemporal_cloud_v1_operations_limittemporal_cloud_v1_operations_counttemporal_cloud_v1_operations_throttled_count

The v1 metrics are pre-computed per-second rates aggregated over a 1-minute window, so a sustained non-zero value on a *_throttled_count metric is the definitive Cloud signal that a specific budget is being hit.

Do not read temporal_cloud_v1_resource_exhausted_error_count as the throttling signal. The throttle metrics in the table above are. "Tracking trends against your account limits is the most important throttling signal to monitor. Unlike Resource Exhaustion, which usually self-heals through retries, hitting a limit slows or stalls progress until the workload backs off or your capacity is increased." The v1 resource-exhausted metric explicitly "does not include throttling due to Namespace limits"; it counts bursts against a single resource — a Namespace, Task Queue, or Workflow ID — that the resource could not absorb in the moment, and persistent non-zero values indicate a hot resource. Route those to runtime-errors.md → Workflow lock contention (BusyWorkflow), which is the most common cause.

For the v0 metric family, the equivalent is temporal_cloud_v0_resource_exhausted_error_count, "gRPC requests received that were rate-limited by Temporal Cloud, aggregated by cause."

For Provisioned Capacity namespaces, the envelope metrics (temporal_cloud_v1_action_on_demand_envelope_limit, temporal_cloud_v1_operations_on_demand_envelope_limit, temporal_cloud_v1_service_request_on_demand_envelope_limit) show what the limit would be under On-Demand. Compare these against the currently provisioned limit metric to evaluate whether the provisioned allocation is too tight or too loose.

Without metrics (UI-only)

When the caller has no metrics pipeline, the Cloud UI shows a recent APS usage summary on the Namespace's Manage Capacity panel, which can confirm whether the Namespace is actually running hot.

What RESOURCE_EXHAUSTED is not

These are the common false positives — they look superficially similar but are not RESOURCE_EXHAUSTED:

  • Worker task-queue backlog. If Activity Tasks or Workflow Tasks sit in the queue without being picked up, the symptom is high temporal_workflow_task_schedule_to_start_latency or temporal_activity_schedule_to_start_latency. These are caused by "insufficient Worker capacity" or "worker configuration issues (too few pollers or task slots)" , not by server rate limiting. Diagnosis: see worker-health.md.

  • Workflow stuck with pending activities / children / signals. The workflow made a Command (ScheduleActivityTask, StartChildWorkflowExecution, etc.), but nothing moves forward. This is a worker / queue / dependency issue, not a RESOURCE_EXHAUSTED condition. See workflow-stuck.md.

  • context deadline exceeded. The caller's own deadline fired before the server responded. This can coincide with a saturated namespace (the server-side temporal_cloud_v0_resource_exhausted_error_count may be non-zero), but the wire code received by the client is DEADLINE_EXCEEDED, not RESOURCE_EXHAUSTED. See runtime-errors.md and the dedicated Cloud-side guidance.

  • temporal_long_request_failure spikes on poll RPCs. The performance-bottlenecks guide calls out that high temporal_long_request_failure may be caused by rate limiting ("often indicated by a ResourceExhausted status code"). But that metric is counted on the client side and aggregates all causes; confirm via the server-side throttle metric above before concluding the limiter is the root cause.

  • Per-Workflow concurrency caps. A single Workflow Execution hitting the 2000 incomplete Activities / Signals / Child Workflows / external Workflow Cancellation requests limit fails the Command at the programming-model level; it is not a Namespace-level rate limit and not diagnosed via this file.

Per the managing-APS guide: "In Temporal Cloud, the effect of rate limiting is increased latency, not lost work. Workers might take longer to complete Workflows." Combined with the Cloud limits note about failures if throttling persists beyond the SDK's retry budget, the distinction matters: short bursts of RESOURCE_EXHAUSTED are normal and self-recovering; sustained throttling plus application-visible failures is what warrants capacity action.

Quick routing

SymptomGo to
gRPC RESOURCE_EXHAUSTED on a client call to CloudTemporal Cloud: APS, RPS, OPS and capacity modes and Identifying which limit was hit
gRPC RESOURCE_EXHAUSTED from a self-hosted frontendSelf-hosted: service-level RPS via dynamic configuration
temporal_cloud_v0_resource_exhausted_error_count / temporal_cloud_v1_*_throttled_count non-zeroIdentify the specific budget via the metric triples in Identifying which limit was hit
Activity / Workflow Task schedule_to_start_latency rising but no RESOURCE_EXHAUSTEDworker-health.md
Workflow stuck with pending activities / children / signalsworkflow-stuck.md
context deadline exceeded on callerruntime-errors.md
UNAUTHENTICATED / PERMISSION_DENIEDauthentication.md
UNAVAILABLE with no rate-limit contextconnectivity.md and certificates.md

See the whole-stack picture in diagnostic-ladder.md. For concrete commands to pull these metrics and confirm a throttling hypothesis, see recipes.md.

Requirements and compatibility

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