'retries' 검색 결과

Configure how traffic moves between services in Istio, a system for managing service communication. Includes routing, load balancing, gradual releases, retries, failure isolation, copied traffic for testing, and commands for inspecting configuration.

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• Send a small share of traffic to a new service version
• Configure retries, timeouts, and failure isolation
• Copy traffic to a test environment

Generate Python code for Dataverse SDK workflows, including retries, bulk data changes, efficient queries, table metadata, and large file uploads. The skill also covers pandas integration and asks for type hints, docstrings, and official API references.

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• Implement retries for temporary Dataverse errors
• Create bulk data operations and efficient queries
• Manage custom tables and metadata caches

Generate Python code for Dataverse integrations with error handling, retries, logging, and shared connection management. Include type hints, usage examples, and queries that retrieve only the records and columns needed for the task.

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• Build Python integrations with Dataverse
• Add retries and logging to API operations
• Limit retrieved records and columns

Build connections between applications and external APIs, interfaces used to exchange data with other services. The skill guides authentication, data conversion, webhook verification, request limits, retries, and troubleshooting to support reliable API clients.

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• Connect payment, email, or SMS services to an application
• Implement OAuth and manage API credentials
• Verify webhooks and process incoming events

Plan transactional and marketing email systems with delivery queues, retries, monitoring, and event tracking. Review sender authentication, bounce handling, unsubscribe links, and template practices to address delivery problems and support growing email volumes.

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• Designing queues and retries for transactional emails
• Reviewing authentication and email delivery issues
• Tracking deliveries, opens, clicks, and bounces

Prepare trained machine learning models for production with deployment, monitoring, and retraining workflows. Build RAG systems that retrieve documents for answers, and integrate language model APIs with retries, fallback providers, and cost tracking.

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• Deploying a trained model to production
• Setting up model monitoring and retraining workflows
• Building a RAG pipeline for document-based answers

Reproduce chat errors, retries, parallel tool calls, and app creation in a running desktop application. Check how messages and cards appear, including interrupted replies, grouped steps, and error details.

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• Check error messages and retry progress
• Inspect text retained after an interrupted reply
• Review grouped parallel tool calls

Add error handling to n8n workflows with connected error outputs, retries, and failure notifications. Return HTTP status codes that explain what went wrong, distinguish invalid requests from service failures, and keep internal error details out of public responses.

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• Investigating workflows that fail without notification
• Returning clear errors from webhook APIs
• Retrying temporary network failures

Implement and debug Google OAuth 2.0 refresh tokens bound to a client key. Covers key generation, signed DPoP proofs that demonstrate key possession, and nonce challenge retries in WebCrypto and JavaScript environments.

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• Bind Google OAuth refresh tokens to a client key
• Debug DPoP proof signatures and nonce retries
• Plan a backend for a browser application using DPoP

Design iii backends by combining functions, queues, and shared state. Choose patterns for workflows with retries, live updates, cooperating AI agents, and event-driven processing, with examples showing how the pieces connect.

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• Designing order workflows with retries and step tracking
• Updating screens or caches when stored data changes
• Passing tasks between specialized AI agents

Build dashboard panels in plain TypeScript with automatic retries for failed requests, error messages, and retry buttons. Save expanded or collapsed state and panel dimensions in localStorage, the browser’s local storage.

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• Building dashboard panels in TypeScript
• Adding automatic retries to failed requests
• Saving panel size and collapsed state

Build dashboard panels in plain TypeScript with saved sizes and expanded or collapsed states. The pattern includes data fetching retries with increasing delays, loading indicators, error messages, and a shared base class for consistent panel behavior.

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• Restoring panel sizes and expanded or collapsed states
• Adding automatic retries when data fetching fails
• Standardizing loading and error displays across panels

Build dashboard panels in plain TypeScript with automatic retries, saved panel settings, and clear error states. Keep panel-specific helper functions in the same file to make each component easier to understand and maintain.

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• Build a panel that retries failed data requests
• Save panel dimensions and expanded or collapsed state
• Keep time and status formatting helpers beside panel code

Build TypeScript interface panels with badges, thumbnails, and colors driven by data. Organize shared behavior in a base class, including fetch retries, error recovery, and saved panel size and expansion state.

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• Building a news panel with thumbnails
• Adding badges colored by data source
• Preserving panel size and expansion state

Run scheduled Douyin tasks through iPolloWork, including draft preparation, publishing, replies, and data checks. The skill keeps account and operation identifiers consistent and checks results to prevent duplicate submissions during retries.

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• Schedule posts for a specific Douyin account
• Prepare drafts without publishing
• Check account data regularly

Plan when an agent’s tool environments are created, kept available, released, and restored. Estimate peak concurrency, resource use during work and waiting, total task duration, and cost across model calls, tool execution, validation, and retries.

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• Estimating peak concurrent agent environments
• Comparing environment retention and recreation
• Assessing cold starts and shared environment pools

Build failure handling into n8n workflows with separate error paths, retries, alerts, and clear API responses. Use it for webhooks and unattended jobs to make failures visible and return status codes that explain what went wrong.

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• Add error responses to a webhook API
• Receive alerts when scheduled jobs fail
• Retry temporary external service failures

Guides the design of data pipelines, continuous stream processing, and data quality checks. It compares tools such as Airflow, Dagster, and Flink, and provides implementation patterns and checklists for scheduling, retries, validation, and monitoring.

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• Compare tools for data pipeline scheduling
• Design continuous data processing
• Define checks for missing, duplicate, or stale data

Inspect automatic retries for failed Codex and Claude Code turns in bb after provider overloads or subscription usage windows. Check pending retry times and recorded decisions, send a scheduled retry immediately, or cancel it.

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• Check retry schedules after provider overloads
• Find out why a retry was scheduled or skipped
• Run a pending retry immediately

Use when you need to design or implement Kafka messaging in Spring Boot — including topic design, producer/consumer implementation, JSON serialization with Boot factory customizers, Testcontainers `@ServiceConnection` integration tests, retries and dead-letter topics, idempotency, and error handling. This should trigger for requests such as Add Kafka in Spring Boot; Review Spring Kafka consumers; Improve retries and DLT in Spring Kafka; Configure Spring Kafka topics serializers or listener containers; Add Spring Kafka dead-letter topic handling. Part of Plinth Toolkit

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Use when adding retries, backoff, or concurrency limits to Spring Boot 4 / Spring Framework 7 code with core Retryable and ConcurrencyLimit support. Covers enablement, backoff, proxy limits, and behavior after retries are exhausted.

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Fix Node.js pg-pool not reconnecting after CloudSQL connection reset (ECONNRESET). Use when: (1) Retries fail with same ECONNRESET error despite retry logic, (2) "Connection terminated" or "connection already closed" errors persist across retries, (3) "remaining connection slots are reserved" errors in CloudSQL, (4) High-concurrency Node.js app with pg-pool and CloudSQL/managed PostgreSQL. The pool caches dead connections - you must recreate the pool, not just retry.

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Idempotent API operations with idempotency keys, Redis caching, DB constraints. Use for payment systems, webhook retries, safe retries, or encountering duplicate processing, race conditions, key expiry errors.

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Use when code calls another service, runs in the background, consumes a queue or retries anything — timeouts, safe retries, idempotent handlers, outbox, graceful shutdown

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