Retry with Backoff
Automatically re-running failed tasks after increasing delays to avoid hammering a flaky downstream service.
Retry with backoff re-executes failed calls with increasing delays between attempts. It prevents hammering unstable services and improves success rates.
Ops teams use it for API calls, webhooks, database queries, and message processing. Backoff smooths transient failures without overwhelming dependencies.
In workflows, retries are bounded by limits and paired with idempotency and DLQs. The result is higher reliability and fewer cascading incidents.
Frequently Asked Questions
What backoff strategy should I use?
Exponential backoff with jitter is standard. Cap the maximum delay and total retries based on SLA and dependency guidance.
How many retries are enough?
Depends on SLA and error patterns. Start with a few attempts (3–5) and monitor success vs. added latency.
Should all errors be retried?
No. Retry transient errors (timeouts, 5xx). Do not retry hard failures (4xx validation errors). Classify errors first.
How do retries affect users?
They add latency. Communicate delays for user-facing actions or fall back gracefully if retries exhaust.
How do I avoid thundering herds?
Use jitter, spread retries, and add concurrency limits. Stagger restarts after outages.
How does idempotency relate to retries?
Idempotency makes retries safe by preventing duplicate effects. Pair retries with idempotent operations.
What should I log on retries?
Attempt count, error codes, backoff time, and correlation IDs. Logs help tune policies and debug failures.
Can retries hide real issues?
Yes—monitor retry volume and DLQ rates. If retries mask persistent failures, fix the root cause or add circuit breakers.
Should retries differ by endpoint?
Yes—tune backoff per dependency based on SLAs and rate limits. One-size-fits-all can overload sensitive services.
Agentic AI
An AI approach where models autonomously plan next steps, choose tools, and iterate toward an objective within guardrails.
Agentic Workflow
A sequence where an AI agent plans, executes tool calls, evaluates results, and loops until success criteria are met.
Agent Handoff
A pattern where one AI agent passes context and state to another specialized agent to keep multi-step automation modular.
Ship glossary-backed automations
Bring your terms into GrowthAX delivery—map them to owners, SLAs, and instrumentation so your automations launch with shared language.
Plan Your First 90 Days