throughputHighestPut = totalPut
					// let the client see lower value as well
					throughputHighestGet = totalGet
				}
				sendResult()
				break
			}

			// We break if we did not see 2.5% growth rate in total GET
			// requests, we have reached our peak at this point.
			doBreak := float64(totalGet-throughputHighestGet)/float64(totalGet) < 0.025

			throughputHighestGet = totalGet
			throughputHighestResults = results

                    handleChannelFailure(channel, e);
                }
            }

            // Check error rate
            if (channel.getErrorRate() > 0.1) {
                log.warn("High error rate on channel {}: {}", channel.getChannelId(), channel.getErrorRate());
            }
        }
    }

	// we allocate buffers rounded up to the closest size class.
	c := len(b) + n // ensure enough space for n elements
	if c < 2*cap(b) {
		// The growth rate has historically always been 2x. In the future,
		// we could rely purely on append to determine the growth rate.
		c = 2 * cap(b)
	}
	b2 := append([]byte(nil), make([]byte, c)...)
	i := copy(b2, b)
	return b2[:i]
}

		return
	default:
		list.eventsSkipped.Add(1)
		err := fmt.Errorf("concurrent target notifications exceeded %d, configured notification target is too slow to accept events for the incoming request rate", maxConcurrentAsyncSend)
		for id := range targetIDset {
			reqInfo := &logger.ReqInfo{}
			reqInfo.AppendTags("targetID", id.String())

 * the life cycle methods.
 *
 * <h3>Usage Example</h3>
 *
 * <p>Here is a sketch of a service which crawls a website and uses the scheduling capabilities to
 * rate limit itself.
 *
 * {@snippet :
 * class CrawlingService extends AbstractScheduledService {
 *   private Set<Uri> visited;
 *   private Queue<Uri> toCrawl;
 *   protected void startUp() throws Exception {

we don't consider this as a vulnerability, given that models can exhaust
resources in many different ways and solutions exist to prevent this from
happening (e.g., rate limits, ACLs, monitors to restart broken servers).

### Model sharing

If the multitenant design allows sharing models, make sure that tenants and

    while discussion_edges:
        for discussion_edge in discussion_edges:
            discussion_nodes.append(discussion_edge.node)
        last_edge = discussion_edges[-1]
        # Handle GitHub secondary rate limits, requests per minute
        time.sleep(settings.sleep_interval)
        discussion_edges = get_graphql_question_discussion_edges(
            settings=settings, after=last_edge.cursor
        )

- **Flexible Configuration**: XML-based dependency injection with LastaFlute DI
- **Extensible Architecture**: Plugin system for custom extractors, transformers, and clients
- **Rate Limiting**: Politeness policies and interval controllers
- **URL Filtering**: Regex-based inclusion/exclusion patterns
- **Data Persistence**: Multiple backend options including OpenSearch integration

## Technology Stack

 * the life cycle methods.
 *
 * <h3>Usage Example</h3>
 *
 * <p>Here is a sketch of a service which crawls a website and uses the scheduling capabilities to
 * rate limit itself.
 *
 * {@snippet :
 * class CrawlingService extends AbstractScheduledService {
 *   private Set<Uri> visited;
 *   private Queue<Uri> toCrawl;
 *   protected void startUp() throws Exception {

		Code:           "SlowDownRead",
		Description:    "Resource requested is unreadable, please reduce your request rate",
		HTTPStatusCode: http.StatusServiceUnavailable,
	},
	ErrSlowDownWrite: {
		Code:           "SlowDownWrite",
		Description:    "Resource requested is unwritable, please reduce your request rate",
		HTTPStatusCode: http.StatusServiceUnavailable,
	},
	ErrMaxVersionsExceeded: {