> ## Documentation Index
> Fetch the complete documentation index at: https://vietbui.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Error Budget (Agentic)

> SRE error budget concept adapted to autonomous agent loops. The budget defines how much failure — in retries, cost, runtime, or error rate — is tolerable bef…

# Error Budget (Agentic)

SRE error budget concept adapted to autonomous agent loops. The budget defines how much failure — in retries, cost, runtime, or error rate — is tolerable before the system must stop, narrow its capabilities, or roll back. Without a budget, self-healing loops run indefinitely.

***

## SRE Origin

**Error budget** (GitLab/Google SRE definition): the acceptable amount of unreliability over a time window, derived from the Service Level Objective (SLO).

```
error_budget = 1 - SLO_target

Example: SLO = 99.9% → error_budget = 0.1% of requests may fail per month
```

When budget is exhausted: freeze feature releases until reliability recovers. The budget is a shared contract between engineering and the business on how much downtime is acceptable.

***

## Agentic Adaptation

In agent loops, "unreliability" maps to multiple resource axes simultaneously:

| Budget type           | What it measures                 | Exhaustion action                  |
| --------------------- | -------------------------------- | ---------------------------------- |
| **Retry budget**      | Attempts per failure type        | Stop retrying → rollback           |
| **Token budget**      | LLM tokens consumed per task     | Escalate → don't continue spending |
| **Runtime budget**    | Wall-clock time per session      | Timeout → checkpoint → stop        |
| **Error rate budget** | Failure rate over rolling window | Rollback staging → halt deploy     |
| **Session budget**    | Total autonomous iterations      | Human review before continuing     |

An agent loop without budget definitions can spend unbounded resources on a task it cannot solve, accumulating debt (bad code, flaky fixes, wasted compute) while reporting "still working."

***

## Budget Policy Rules

**Rule 1: Define budget before starting, not during failure**
Budget values must be set in config, not chosen adaptively by the agent. An agent under pressure will rationalize higher budgets.

**Rule 2: Budget exhaustion stops, not pauses**
When any budget is exhausted: stop, rollback if applicable, write incident note. Do not "just try one more time."

**Rule 3: No progress = budget consumption**
If the agent makes N attempts with identical failure signatures and zero test improvement, that is budget exhausted regardless of remaining retry count. Signature-based detection catches this without counting.

**Rule 4: Token/time exhaustion escalates, not loops**
If the agent consumes its token or runtime budget without completing: checkpoint state, stop cleanly, flag for human. Looping on a budget-exhausted task is the failure mode, not the fix.

***

## Reference Budget Defaults (Starting Point)

Calibrate these per project; these are conservative starting values:

```yaml theme={null}
budgets:
  retry_per_failure: 3          # max attempts before rollback per distinct failure
  retry_total_per_session: 10   # total retry attempts across all failures in one session
  token_per_task: 50000         # LLM tokens per discrete task (not per session)
  runtime_per_task: 1800        # seconds (30 min) per task; wall-clock
  staging_error_rate: 0.01      # 1% of synthetic checks may fail before rollback triggered
  session_iterations: 20        # total ralph-loop iterations before requiring human check-in
```

***

## Budget as Rollback Trigger

Error budget integrates with [Self-Healing Loop](/concepts/self-healing-loop) rollback conditions:

```
staging deploy → health monitor starts
  every 30s: check /health + run 1 synthetic test
  error_rate = failures / total_checks

if error_rate > staging_error_rate budget:
    rollback to last known-good image
    write incident note
    set ESCALATE=1
    stop

if agent retry_count > retry_per_failure budget:
    same action
```

The budget threshold replaces "wait and see" with a machine-enforceable condition. The health monitor runs independently of the agent — agent cannot suppress or override it.

***

## Detecting No-Progress Without Budget

When an agent loops on the same failure with different patches but no improvement, retry count alone doesn't catch it:

```python theme={null}
progress_score = (passing_tests_now - passing_tests_before_repair) / total_tests

if progress_score <= 0 and retry_count >= 2:
    # Agent is not making progress — escalate even if budget remains
    trigger_rollback()
```

This is the "spending without improving" detector: progress score of 0 across two retries = budget exhausted regardless of counter.

***

## Budget vs Retry Count

These are related but distinct:

| Concept        | Scope                         | What it prevents                       |
| -------------- | ----------------------------- | -------------------------------------- |
| Retry count    | Per failure event             | Infinite loops on one broken thing     |
| Error budget   | Across the session/deployment | Accumulated failure across many events |
| Progress score | Per repair attempt            | Retrying useless fixes                 |

All three are needed. Retry count alone doesn't stop an agent that tries 100 different fixes on 100 different things, each failing once. Budget covers the aggregate; progress score covers the per-attempt signal.

***

## Related Pages

* [Self-Healing Loop](/concepts/self-healing-loop) — the retry/rollback/escalation pattern budgets govern
* [Agentic CI/CD](/concepts/agentic-cicd) — where error rate budgets are monitored (staging health)
* [Ralph Loop](/concepts/ralph-loop) — the outer loop that session budgets constrain
* [Verification Pipeline](/concepts/verification-pipeline) — what passes/fails that feeds the error rate

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if(n.id===CUR){ctx.beginPath();ctx.arc(n.x,n.y,r+1.6,0,6.283);ctx.strokeStyle='#fff';ctx.lineWidth=1.2/scale;ctx.stroke();}
if(opt.to>0&&opt.ts>0){var t=n.label.length>28?n.label.slice(0,26)+'…':n.label;ctx.globalAlpha=opt.to;ctx.font=((n.id===CUR?opt.ts+1:opt.ts))+'px ui-sans-serif,sans-serif';ctx.fillStyle=(n.id===CUR)?'#ffffff':'#aab0c0';ctx.textAlign='center';ctx.textBaseline='top';ctx.fillText(t,n.x,n.y+r+1.5);ctx.globalAlpha=1;}})
.onNodeClick(function(n){if(window.top){window.top.location.href='/'+n.id;}});
G.graphData(visible());G.d3VelocityDecay(0.4);
function fit(){G.zoomToFit(400,20);}
setTimeout(fit,350);setTimeout(fit,1100);
// Stop the render/sim loop while idle so the fixed widget never repaints during
// parent-page scroll; resume only while the pointer is over the widget.
var pt;function pause(){G.pauseAnimation();}function resume(){G.resumeAnimation();}
function idle(ms){clearTimeout(pt);pt=setTimeout(pause,ms);}
document.body.addEventListener('pointerenter',function(){clearTimeout(pt);resume();});
document.body.addEventListener('pointerleave',function(){idle(250);});
addEventListener('resize',function(){resume();G.zoomToFit(0,20);idle(700);});
idle(2000);
function apply(re){resume();G.nodeRelSize(opt.ns).linkWidth(opt.lw).linkDirectionalArrowLength(opt.ar?2.6:0);if(re){G.graphData(visible());setTimeout(fit,450);}idle(re?2200:1400);}
function bind(id,key,fmt,re){var e=document.getElementById(id),o=document.getElementById('v'+id);e.value=opt[key];if(o)o.textContent=fmt(opt[key]);e.addEventListener('input',function(){opt[key]=parseFloat(e.value);if(o)o.textContent=fmt(opt[key]);apply(re);});}
bind('ns','ns',function(v){return v.toFixed(1);},false);
bind('lw','lw',function(v){return v.toFixed(1);},false);
bind('ts','ts',function(v){return v.toFixed(1);},false);
bind('to','to',function(v){return v.toFixed(2);},false);
var dE=document.getElementById('dp'),dO=document.getElementById('vd');dE.max=MAXD;dE.value=opt.dp;dO.textContent=opt.dp;dE.addEventListener('input',function(){opt.dp=parseInt(dE.value,10);dO.textContent=opt.dp;apply(true);});
if(!CUR)document.getElementById('depthRow').style.display='none';
var aE=document.getElementById('ar');aE.checked=opt.ar;aE.addEventListener('change',function(){opt.ar=aE.checked;apply(false);});
document.getElementById('gear').addEventListener('click',function(){document.getElementById('panel').classList.toggle('open');});
var hd=document.getElementById('hd');hd.textContent='⠿  '+(CUR?'Local graph':'Knowledge graph');
// free-form placement: drag by the header. Default is bottom-right (inline style);
// a moved position is saved per parent-origin and restored on every page.
function clampPos(fe,l,t){var TW=(window.top||window),r=fe.getBoundingClientRect();return [Math.min(Math.max(0,l),Math.max(0,TW.innerWidth-r.width)),Math.min(Math.max(0,t),Math.max(0,TW.innerHeight-r.height))];}
function place(fe,l,t){var p=clampPos(fe,l,t);fe.style.left=p[0]+'px';fe.style.top=p[1]+'px';fe.style.right='auto';fe.style.bottom='auto';}
try{var sp=JSON.parse(localStorage.getItem('llmwiki_graph_pos'));if(sp&&window.frameElement)place(window.frameElement,sp.l,sp.t);}catch(e){if(window.console)console.debug('graph: saved position unavailable',e);}
hd.addEventListener('pointerdown',function(e){var fe=window.frameElement;if(!fe)return;var rect=fe.getBoundingClientRect();var sx=e.screenX,sy=e.screenY,L=rect.left,T=rect.top;place(fe,L,T);hd.setPointerCapture(e.pointerId);
function mv(ev){place(fe,L+ev.screenX-sx,T+ev.screenY-sy);}
function up(){if(hd.hasPointerCapture(e.pointerId))hd.releasePointerCapture(e.pointerId);hd.removeEventListener('pointermove',mv);hd.removeEventListener('pointerup',up);try{localStorage.setItem('llmwiki_graph_pos',JSON.stringify({l:parseFloat(fe.style.left),t:parseFloat(fe.style.top)}));}catch(e2){if(window.console)console.debug('graph: could not persist position',e2);}}
hd.addEventListener('pointermove',mv);hd.addEventListener('pointerup',up);e.preventDefault();});
</script></body></html>"
  title="Knowledge graph"
  loading="lazy"
  style={{position:"fixed",right:"18px",bottom:"18px",width:"320px",height:"340px",border:0,borderRadius:"14px",boxShadow:"0 6px 28px rgba(0,0,0,0.38)",zIndex:50,background:"#0f1117"}}
/>
