Why Google Cloud's instances.bulkInsert Isn't Just a Faster instances.insert

Most developers assume instances.bulkInsert exists simply to reduce HTTP requests. That explanation is true, but it misses the real engineering story. The biggest difference between instances.insert and instances.bulkInsert isn't network efficiency. It's how Google Compute Engine thinks about infrastructure. One API creates an individual virtual machine. The other allocates an entire fleet. That distinction fundamentally changes how the control plane validates requests, reserves capacity, schedules workloads, and provisions virtual machines.

Why Google Cloud's instances.bulkInsert Isn't Just a Faster instances.insert

The Problem With Calling instances.insert in a Loop

Imagine you're building a platform that needs to provision 1,000 ephemeral virtual machines.

Most developers would naturally write something like:

for i := 0; i < 1000; i++ {
    compute.Instances.Insert(...)
}

Modern SDKs already use HTTP/2, connection pooling, and concurrent requests, so reducing network latency isn't the biggest challenge.

The real bottleneck exists inside the Compute Engine control plane.

Every instances.insert request independently performs authentication, IAM authorization, organization policy evaluation, image lookup, machine type resolution, quota checks, scheduling, and operation creation.

Even though all 1,000 virtual machines are identical, the control plane repeats the same admission process for every request.

Worse, every request races against every other request and every other customer provisioning resources in the same region. The first 600 requests may succeed, while the remaining requests fail because capacity changes during provisioning.

The result is partial infrastructure, retry logic, cleanup scripts, and unnecessary operational complexity.

bulkInsert Changes the Unit of Work

Instead of treating every virtual machine as an independent request, instances.bulkInsert submits the entire fleet as a single allocation request.

Rather than asking:

"Can I create this VM?"

the API asks:

"Can I provision this workload?"

This seemingly small change allows Compute Engine to optimize the entire request.

Instead of repeating work thousands of times, the control plane can validate the configuration once, evaluate quotas once, resolve machine types once, generate VM names automatically, and build an optimized placement plan before provisioning begins.

The actual virtual machines are still created individually, but the expensive admission phase is dramatically simplified.

Admission Is Different From Provisioning

One of the biggest misconceptions about bulkInsert is that it makes virtual machines boot faster.

It doesn't.

Every VM still requires a boot disk, networking, host selection, hypervisor startup, and operating system boot.

Those operations are inherently per instance.

The optimization happens before provisioning even starts.

You can think of Compute Engine as having two major phases.

The first is admission, where requests are authenticated, validated, checked against quotas, and scheduled.

The second is provisioning, where disks are created, networking is configured, hosts are selected, and virtual machines actually start.

bulkInsert compresses the admission phase from thousands of repeated operations into a single coordinated decision while leaving provisioning unchanged.

This distinction explains why bulkInsert scales better without magically making VM startup itself faster.

Smarter Scheduling

Another important advantage of bulkInsert is placement planning.

With instances.insert, the client decides which zone should receive the request.

If that zone runs out of capacity, the client is responsible for retrying somewhere else.

The client has no visibility into Google's internal scheduling information.

bulkInsert moves that responsibility into the Compute Engine control plane.

Instead of blindly attempting to create every VM in one zone, Compute Engine can intelligently distribute the workload across multiple zones based on available capacity, reservations, quotas, and placement policies.

This is one of the biggest architectural advantages of bulkInsert.

It isn't simply creating virtual machines more efficiently.

It's making better scheduling decisions because it has a complete view of the workload.

More Than a Batch API

Many engineers compare bulkInsert to batching multiple HTTP requests together.

That comparison is misleading.

HTTP batching only reduces transport overhead.

bulkInsert introduces capabilities that batching cannot provide.

The control plane performs fleet-level quota evaluation instead of evaluating every request independently.

It builds placement plans before provisioning begins.

It supports rollback behavior based on minimum instance requirements.

It generates virtual machine names automatically.

It tracks an entire fleet through aggregated operations.

These are orchestration capabilities rather than transport optimizations.

Calling instances.insert one thousand times can never reproduce this behavior because every request remains independent.

What We Learned While Building Monk CI

We discovered this distinction while building Monk CI, our high-performance GitHub Actions runner replacement.

One of the core challenges in any CI platform is provisioning large numbers of ephemeral runners during traffic spikes. When hundreds of repositories trigger builds simultaneously, infrastructure has to scale almost instantly.

Our first instinct was the obvious one.

Provision virtual machines using instances.insert with aggressive parallelism.

After studying Compute Engine's APIs more deeply, we realized Google had already solved this problem.

instances.bulkInsert isn't simply about reducing API calls. It's designed to let the Compute Engine control plane optimize an entire fleet before provisioning begins.

Validation, quota reservation, placement planning, and orchestration happen once for the workload instead of once per virtual machine.

That realization changed how we think about infrastructure APIs.

The biggest performance optimization wasn't making VM creation faster.

It was choosing an API that lets the cloud provider optimize the workload as a whole.

Choosing the Right API

Each Compute Engine API solves a different problem.

Use instances.insert when provisioning a small number of unique virtual machines with different configurations.

Use instances.bulkInsert when provisioning hundreds or thousands of identical, short-lived instances such as CI runners, batch processing workers, rendering nodes, or HPC clusters.

If you need autoscaling, rolling deployments, autohealing, or long-term lifecycle management, Managed Instance Groups remain the better choice.

A simple mental model is:

instances.insert creates a VM.

instances.bulkInsert creates a fleet.

Managed Instance Groups continuously manage that fleet.

Final Thoughts

The biggest insight about instances.bulkInsert isn't that it reduces HTTP requests.

It changes the abstraction.

instances.insert is a resource creation API.

instances.bulkInsert is a workload allocation API.

That shift allows Compute Engine to validate requests, reserve quotas, plan placement, and orchestrate provisioning at the fleet level instead of repeating the same admission work thousands of times.

As cloud platforms continue to support increasingly large workloads, from CI/CD systems to AI training clusters and large-scale batch processing, we'll see more infrastructure APIs evolve in the same direction.

Sometimes the most important optimization isn't making infrastructure faster.

It's choosing the right unit of work.

Aishwarya Palta

Last updated August 5, 2026