Analytics API 413 on 90-day query split

Configuration is broken for some reason…

• HTTP 413 Entity Too Large returned by /api/v2/analytics/conversations/summaries when requesting a 90-day window despite chunking logic in my Python SDK wrapper.
• I attempted to split the dateFrom and dateTo into 7-day intervals but the cumulative payload size still triggers the limit before the server processes the individual requests.
• Current payload structure uses a single POST body with aggregated filter criteria; is there a specific header or batching mechanism required to avoid this?

Have you tried shifting the chunking logic to run entirely within Deno Deploy instead of relying on a local Python wrapper to batch requests? The 413 error usually hits because the POST body includes a massive groupBy or select array that inflates the JSON size before the date range even matters. I’ve seen this exact issue when pulling 90-day conversation summaries via webhooks. Instead of sending one giant request, spin up a simple Deno Deploy endpoint that accepts the start/end dates, then uses an internal loop to fetch 7-day chunks sequentially. This keeps each payload tiny and avoids the entity limit. Here’s a minimal repro using Deno’s fetch API:

const getSummaries = async (from: string, to: string, token: string) => {
 const results = [];
 const chunkSizeDays = 7;
 let currentStart = new Date(from);
 const end = new Date(to);
 
 while (currentStart < end) {
 let currentEnd = new Date(currentStart.getTime() + chunkSizeDays * 86400000);
 if (currentEnd > end) currentEnd = end;
 
 const body = JSON.stringify({
 dateFrom: currentStart.toISOString(),
 dateTo: currentEnd.toISOString(),
 view: "conversation",
 select: ["conversationId", "wrapUpCode"], // Keep select minimal
 groupBy: ["wrapUpCode"]
 });

 const res = await fetch("https://api.genesyscloud.com/api/v2/analytics/conversations/summaries", {
 method: "POST",
 headers: {
 "Authorization": `Bearer ${token}`,
 "Content-Type": "application/json"
 },
 body: body
 });

 if (res.ok) {
 const data = await res.json();
 results.push(...data.entities);
 } else {
 console.error(`Chunk failed: ${currentStart.toISOString()} - ${currentEnd.toISOString()}`);
 }
 currentStart = currentEnd;
 }
 return results;
};

This approach bypasses the 413 by ensuring no single request exceeds the size threshold. Also, check if you’re including unnecessary fields in the select array; stripping down to only required metrics like conversationId and wrapUpCode significantly reduces payload weight. If you’re still hitting limits, verify your OAuth token scope includes analytics:read. I run similar logic on Supabase edge functions for GC events, and splitting by week with minimal select fields solved my 413 issues completely.

You should probably look at at the payload bloat from select fields. Deno Deploy helps with concurrency, but the 413 error is strictly about the JSON body size of a single request, not the aggregate throughput.

Trim your select array to only essential metrics. Use pd.concat() to stitch the results in pandas after fetching smaller 7-day chunks. This keeps each POST under the limit.

# Trim selects to reduce payload size
payload = {"dateFrom": start, "dateTo": end, "select": ["conversationId", "duration"]}
df = pd.DataFrame(platformClient.AnalyticsApi.post_analytics_conversations_summaries(payload).entities)

According to the docs, they say the 413 is strictly about the request body size, not the date range itself. trim your select array to the bare minimum and chunk by 7 days to keep each payload under the limit.

Make sure you audit the select array before worrying about the date chunking strategy. The suggestion above about trimming fields is correct, but there is a specific gotcha in the PHP SDK that often catches people out when they try to optimize these queries.

Cause: The 413 error is triggered by the total byte size of the JSON payload sent to /api/v2/analytics/conversations/summaries. When you request a 90-day window, you might assume the issue is the time range, but it is usually the cardinality of the groupBy combined with a verbose select list. If you include metrics like agent.talk, hold, work, and wrapup alongside a high-cardinality groupBy like skill or queue, the resulting JSON object can easily exceed the 1MB limit for a single POST request, even if the date range is only 7 days.

Solution: In my Laravel projects, I use Guzzle to manually construct the request body to ensure strict size control. You must strip the select array down to only the metrics you absolutely need. Here is a snippet showing how I prepare the payload before sending it via the SDK’s underlying HTTP client to bypass any SDK-level serialization bloat:

// Define minimal select to keep payload small
$select = ['queue.name', 'agent.talk', 'hold']; 

$body = [
 'dateFrom' => '2023-10-01T00:00:00.000Z',
 'dateTo' => '2023-10-08T00:00:00.000Z',
 'interval' => 'P7D',
 'select' => $select,
 'groupBy' => ['queue'], // Avoid high-cardinality groupBy if possible
 'filter' => ['metric' => 'talk', 'operator' => '>', 'value' => 0]
];

// Serialize and check size before sending
$jsonBody = json_encode($body);
if (strlen($jsonBody) > 500000) {
 // Fallback: further reduce select or split groupBy
}

$response = $analyticsApi->postAnalyticsConversationsSummaries(
 $jsonBody, 
 null, 
 null, 
 null, 
 null, 
 null, 
 null, 
 null, 
 null, 
 null
);

By keeping the select array tight and verifying the JSON string length before the request, you can reliably fetch 7-day chunks without hitting the 413 limit.