Google Apps Script’s 6-minute execution limit is a brutal wall. I ran into this last week while trying to sync 150 contacts to an external CRM. The script kept dying around contact 110 because each sequential API call took about 3 seconds. Instead of waiting minutes for your script to crawl through a loop, you can use UrlFetchApp.fetchAll() to fire all your requests at once. Here is how I used it to drop my execution times from minutes to seconds.
The 6-Minute Wall: Why Sequential Loops Fail
When you write a standard for loop to hit an API, your script sits there doing absolutely nothing while waiting for each response. If you have 100 rows in a sheet and each API call takes 800ms, that’s over a minute of idle waiting. If the API slows down or network latency spikes, you’ll easily blow past the 360-second limit.
According to the official Google Apps Script quotas, both free accounts and enterprise Workspace accounts have this same hard 6-minute ceiling. If you’re pulling huge datasets, you’ll also run into pagination issues. I wrote a guide on how to fetch paginated API data in Google Apps Script that pairs perfectly with the parallel execution we’re setting up here.
How UrlFetchApp.fetchAll Actually Works
If you're used to modern JavaScript, you'd probably reach for Promise.all(). But Apps Script runs on a synchronous, single-threaded V8 engine. Traditional async/await patterns won't actually run your HTTP requests in parallel here.
To get around this, Google built UrlFetchApp.fetchAll(). Instead of executing requests in your script’s thread, you pass an array of request objects directly to Google’s backend infrastructure. Google fires them all off at once and hands you back an array of responses in the exact same order. It works just like JS’s Promise.all, but without the async syntax headaches.
Setting Up the Request Array
Let’s say we have a list of user IDs in a Google Sheet and need to fetch their profile details from an external API. To use fetchAll(), we have to build an array of request configuration objects. Each object in that array needs to look like this:
{ url: "https://api.example.com/users/123", method: "get", headers: { "Authorization": "Bearer MY_SECRET_TOKEN", "Content-Type": "application/json" }, muteHttpExceptions: true
}Do not forget muteHttpExceptions: true. If you omit this and even a single request in your batch fails with a 404 or 500, the entire fetchAll() call will crash your script. Setting this to true ensures you get a response object back for every single item, letting you handle errors gracefully.
The Slow Way: Sequential Loops
I benchmarked this using a mock API endpoint that forces a 500ms delay per request. First, I wrote the standard, sequential loop that most of us write when we’re first starting out. Here’s the slow code:
function fetchSequentially() { var userIds = [101, 102, 103, 104, 105, 106, 107, 108, 109, 110]; var results = []; var startTime = new Date().getTime(); for (var i = 0; i < userIds.length; i++) { var url = "https://httpbin.org/delay/1?id=" + userIds[i]; var response = UrlFetchApp.fetch(url); results.push(response.getContentText()); } var endTime = new Date().getTime(); Logger.log("Sequential execution took: " + (endTime - startTime) + "ms");
}Running this for just 10 requests took 11,432ms—over 11 seconds. If I scaled this up to 300 requests, it would take over two and a half minutes, putting us dangerously close to that 6-minute timeout wall if the network hiccuped.
The Fast Way: Implementing fetchAll
Now let’s rewrite this using UrlFetchApp.fetchAll(). We’ll map our array of user IDs into an array of request configurations, pass that whole array to the fetch engine at once, and then parse the responses. Here’s the optimized version:
function fetchInParallel() { var userIds = [101, 102, 103, 104, 105, 106, 107, 108, 109, 110]; var startTime = new Date().getTime(); // Step 1: Map your data into an array of request objects var requests = userIds.map(function(id) { return { url: "https://httpbin.org/delay/1?id=" + id, method: "get", muteHttpExceptions: true }; }); // Step 2: Execute all requests in parallel var responses = UrlFetchApp.fetchAll(requests); // Step 3: Map responses to get their text content var results = responses.map(function(response) { return response.getContentText(); }); var endTime = new Date().getTime(); Logger.log("Parallel execution took: " + (endTime - startTime) + "ms");
}This parallel version finished the exact same 10 requests in 1,245ms. That’s a 10x speedup. When you scale this to 100 requests, the difference is night and day—it usually finishes in under 3 seconds total.
Dealing with Rate Limits and Errors
While parallel fetching is awesome, you can’t just dump 1,000 requests on an API at once. You’ll get hit with HTTP 429 Too Many Requests and crash your integration. For instance, if you’re using a CRM API to push contacts from Google Sheets to GoHighLevel, you have to play by their rate limit rules.
The fix is batching. If you have 500 requests, split them into chunks of 30 or 50, run fetchAll() on each chunk, pause for a second with Utilities.sleep(), and then move to the next batch. Here’s how I handle batching and error checking in my production scripts:
function fetchInBatches() { var items = []; for (var i = 1; i <= 100; i++) { items.push(i); } var batchSize = 25; var allResults = []; for (var i = 0; i < items.length; i += batchSize) { var batch = items.slice(i, i + batchSize); var requests = batch.map(function(id) { return { url: "https://jsonplaceholder.typicode.com/posts/" + id, method: "get", muteHttpExceptions: true }; }); Logger.log("Fetching batch starting at index " + i); var responses = UrlFetchApp.fetchAll(requests); responses.forEach(function(response, index) { var statusCode = response.getResponseCode(); if (statusCode === 200) { allResults.push(JSON.parse(response.getContentText())); } else { Logger.log("Failed request for ID " + batch[index] + " Status: " + statusCode); } }); // Pause for 1 second between batches to avoid hitting rate limits if (i + batchSize < items.length) { Utilities.sleep(1000); } } Logger.log("Successfully processed " + allResults.length + " items.");
}Advanced: Syncing Parallel API Data Back to Sheets
Let’s put this into a real-world scenario: reading emails from a Google Sheet, checking their status via an API, and writing the results back. A common mistake here is writing to the sheet row-by-row inside a loop—that’s another massive bottleneck that will time out your script.
Instead, we’ll read the sheet in bulk, fetch the API data in parallel batches, compile everything in memory, and write it all back in one single setValues() call. (If you also need to trigger external workflows when the sheet updates, check out my guide on how to send webhooks from Google Sheets with Apps Script). Here is the full production-ready script:
function updateSheetWithApiData() { var sheet = SpreadsheetApp.getActiveSpreadsheet().getActiveSheet(); var dataRange = sheet.getDataRange(); var data = dataRange.getValues(); // Skip header row var rowsToProcess = data.slice(1); var requests = rowsToProcess.map(function(row) { var email = row[0]; // Assuming email is in the first column return { url: "https://api.hunter.io/v2/email-verifier?email=" + encodeURIComponent(email) + "&api_key=YOUR_API_KEY", method: "get", muteHttpExceptions: true }; }); Logger.log("Sending " + requests.length + " parallel validation requests..."); var responses = UrlFetchApp.fetchAll(requests); var outputValues = []; responses.forEach(function(response) { var statusCode = response.getResponseCode(); if (statusCode === 200) { var json = JSON.parse(response.getContentText()); var status = json.data.status || "unknown"; outputValues.push([status]); } else { outputValues.push(["error_code_" + statusCode]); } }); // Write results to Column B (2nd column), starting from row 2 if (outputValues.length > 0) { sheet.getRange(2, 2, outputValues.length, 1).setValues(outputValues); Logger.log("Sheet successfully updated."); }
}Frequently Asked Questions
Does fetchAll bypass the daily Google Apps Script URL Fetch quota?
No, unfortunately. Every single request in your fetchAll() array still counts against your daily URL Fetch quota. Free accounts get 20,000 calls per day, and Google Workspace accounts get 100,000.
Can I use different HTTP methods or headers for each request in fetchAll?
Yes, absolutely. Because fetchAll() takes an array of individual config objects, you can mix and match GET, POST, or PUT requests, use different headers, and hit different endpoints in the exact same batch.
What is the maximum array size I can pass to fetchAll?
Google doesn’t explicitly document a hard limit, but throwing more than 100 requests into a single batch often triggers gateway timeouts or gets you rate-limited by the destination server. I find keeping batches between 20 and 50 is the sweet spot for stability.
How do I handle authentication tokens that expire mid-execution?
Since fetchAll() fires everything at once, you need to make sure your API token is valid before you build and send the array. If you’re processing a massive list in batches, check the token’s expiration and refresh it before starting a new batch.
Next Steps
Now that your API calls aren’t timing out, you can start building more complex automations. If you want to see how to apply these scripting techniques to real-world workflows, check out my tutorial on how to automate invoice reminders from Google Sheets with Apps Script.
