Google Cloud Platform Blog
Product updates, customer stories, and tips and tricks on Google Cloud Platform
Compute Engine Load Balancing hits 1 million requests per second!
Monday, November 25, 2013
The
C10k problem
is so last century. How about serving 1 million load balanced requests per second in the cloud? Using publicly available Google Cloud Platform services, including Google Compute Load Balancing, we have done exactly that. Within 5 seconds after the setup and without any pre-warming, our load balancer was able to serve 1 million requests per second and sustain that level.
This number is 20 times greater than the throughput in last year’s
Eurovision Song Contest
, which served 125 million users in Europe and was hosted on Google Compute Engine. The Eurovision setup used DNS load balancing, which increases the complexity of setup, maintenance and cost. We were able to simplify this process using Compute Engine Load Balancing, which avoids these issues by providing simple APIs and allowing a single IP address to serve all traffic at a lower cost than do-it-yourself options. In addition, Compute Engine Load Balancing has the ability to detect unhealthy instances and dynamically add and remove new instances to serve traffic. This addresses the hard-to-solve problem of cached DNS entries in end-user browsers. No more “404’s”.
Starting with an empty Compute Engine project and ending with 456 cores provisioned (for the load generator and web servers VMs) and one load-balanced IP address actively processing 1.016M Requests Per Second (+-0.007M) took a total of 7 minutes 30 seconds. The 1M number is measuring a complete request and successful response. You can read more on how to set up the
Compute Engine Load Balancing
and
how to provision Compute Engine VMs
on the Google Cloud Platform website.
The following depicts the setup used:
This setup demonstrated a couple of features, including scaling of the Compute Engine Load Balancing, use of different machine types and rapid provisioning. For generating the load we used 64 n1-standard-4’s running
curl_loader
with 16 threads and 1000 connections. Each curl_loader ran the same config to generate roughly the same number of requests to the LB. The load was directed at a single IP address, which then fanned out to the web servers.
To demonstrate scaling of the Compute Engine Load Balancing fanout we used 200 n1-standard-1’s Web Server running
Apache v2.2.22
on Debian 7.1 Wheezy Images. Users are encouraged to use larger VM types for better single machine backend web serving, however here we demonstrated the scaling of the load balancer to backends and were not concerned with the backends themselves using every cycle to serve responses. Each backend web server received ~5K requests per second, which is an even distribution.
Compute Engine Load Balancing distributed the load by using a tuple of source address+port, destination address+port and protocol. Each web response was 1 byte in size not including the http headers. All of this was configured from an empty Compute Engine project. To reproduce the data yourself you can use the following
Gist
.
This entire setup and test cost just $10 USD!
-Posted by, Anthony F. Voellm, Performance Engineering Manager
Free Trial
GCP Blogs
Big Data & Machine Learning
Kubernetes
GCP Japan Blog
Firebase Blog
Apigee Blog
Popular Posts
Understanding Cloud Pricing
World's largest event dataset now publicly available in BigQuery
A look inside Google’s Data Center Networks
Enter the Andromeda zone - Google Cloud Platform’s latest networking stack
New in Google Cloud Storage: auto-delete, regional buckets and faster uploads
Labels
Announcements
193
Big Data & Machine Learning
134
Compute
271
Containers & Kubernetes
92
CRE
27
Customers
107
Developer Tools & Insights
151
Events
38
Infrastructure
44
Management Tools
87
Networking
43
Open
1
Open Source
135
Partners
102
Pricing
28
Security & Identity
85
Solutions
24
Stackdriver
24
Storage & Databases
164
Weekly Roundups
20
Feed
Subscribe by email
Demonstrate your proficiency to design, build and manage solutions on Google Cloud Platform.
Learn More
Technical questions? Check us out on
Stack Overflow
.
Subscribe to
our monthly newsletter
.
Google
on
Follow @googlecloud
Follow
Follow
Follow