Welcome!

Python Authors: Matt Davis, AppDynamics Blog, Pat Romanski, Donald Meyer, Liz McMillan

Related Topics: Java IoT, Microservices Expo, Open Source Cloud, Machine Learning , Ruby-On-Rails, Python

Java IoT: Article

The Taming of the Queue

Measuring the Impact of Request Queueing

A few weeks back webserver request queueing came under heightened scrutiny as rapgenius blasted Heroku for not using as much autotune as promised in their “intelligent load balancing”. If you somehow missed the write-up (or response), check it out for its great simulations of load balancing strategies on Heroku.

What if you’re not running on Heroku? Well, the same wisdom still applies – know your application’s load balancing and concurrency and measure its performance. Let’s explore how request queueing affects applications in the non-PaaS world and what you can do about it.

Full-stack apps have full-stack problems
Rapgenius had been monitoring server-side request latency as only the time the request spent being processed in the app layer – leading to large discrepancies between what their APM tools were reporting and what the actual user experience was. The missing latency was attributable to queueing happening just before the application processed each request, which was outside the visibility of the tools being used to monitor the site.

If your application processes requests at a constant speed but receives an increasing volume of requests (generally a good problem to have), you’ll start to face request queueing.

What does this queueing look like?
(I’ll be using nginx and gunicorn as examples here because that’s what we use, but the same reasoning and analysis principles apply no matter what stack you’re running.)

To visualize this problem, let’s look at a simple test stack running nginx in front of a Python app with eight worker processes. In our case, it’s actually intelligently load balanced by gunicorn because there’s a single queue that knows which workers are busy (unlike Heroku at scale). However, we can still run into plenty of problems.

I’ve instrumented it so we watch the latency of requests moving through the full stack, starting at the load balancer:queueing

In this image, orange represents time spent queued in a webserver, while the other colors represent the components of the application (app, DB, cache).

As you can see, the application performs admirably, slowing a bit under load but never getting slower than 150 ms to process a response. If that’s all you were looking at, you’d be delighted! But the slow buildup of queue depth results in and increased amount of time spent in each request, which is shown in orange. Yikes!

Mind your Ps and Queues
In your application, there’s likely to be queueing anywhere you distribute request load over multiple backends. In the simplest app, this might be happening between your webserver and application layer, as above. Dynamic requests must be handled by the app, and if all the app workers are busy, requests will have to wait. Here’s what that might look like for a single Heroku dyno, or an app you stand up on a development server:

queueing

In fact, a common problem we see is that an app is underprovisioning app workers in production, even if the nodes they’re running on aren’t working very hard. If you see request queueing with low server load, consider running more app worker processes:

queueing

This has the great property of helping you get the most out of your frontend node, but assuming that your local app server can do intelligent load balancing like gunicorn, it also has some beneficial load distribution properties. We’ll get to those in a second.

Third scenario: you’re running single application workers on multiple frontend nodes. This is your Thin app running on a number of Heroku dynos. It will look more like this:queueing

The challenge now is that unless the remote load balancer is keeping track of which workers are busy, it will have to distribute load less intelligently.

What’s wrong with random balancing?
Random assignment sounds pretty good intuitively. Let’s say I’m going to route 100 requests to two app workers, with a 50% probability of choosing each worker each time. At the end, you’d expect me to have around 50 processed by each. Sounds fair, right?

The problem is that at any given time during the handling of those 50 requests, one node might be two or three deep while the other is empty, which is a problem for latency. Compounding this is the possibility that different requests take different amounts of time to process.

For a mathematical analysis, check out this blog post. For a simulation, I’ll cite this cool animated gif from the rapgenius analysis:

So, it seems like we want to have at least some level of intelligence in our load balancing.

Alleviating the pain of scale
Heroku’s response is that it can be difficult to keep track of which workers are busy and which are free when you’re at scale – that’s why their routing mesh degrades to semi-random behavior.  This is definitely not an easy problem, because their “load balancer” is actually a distributed system.  However, even without tackling this omnipotence problem at the top level, local intelligence under a random umbrella can be very effective.

There’s a lot of app servers that support this. For instance, if you’re running Unicorn for Ruby, or gunicorn for Python, each app server has a pool of workers which have a local queue and are routed to intelligently. So, your setup looks more like this:

queueing

This actually makes a big impact on performance. If you replace each single-worker dyno with a two-worker intelligently-routed app server, you get much-improved performance.

However, that assumes evented workers, where the cost of adding a second worker to a node is minimal. What if you’re using non-evented threads or processes, so you care about the total CPU and memory consumption of your workers?

To answer that question, and to try out R for the first time, I modified the rapgenius simulations to look at the effects of scaling the overall number of workers and workers-per-node, on request queueing:

queueing

(source on github)

Queueing performance improves quite well with the number of workers on each naively-balanced endpoint. (The shelf in the eight-worker line is due to the fact that 10 and 15 are both < 16). You can see that, in fact, two naively-routed pairs of eight-worker (intelligently-routed) nodes are better than 100 naively-routed one-worker nodes. See the pattern? The lines are converging on a single, fully intelligently-routed cluster.

This is possible with app worker processes or threads on each node, but if you’re running evented workers, each individual worker is capable of handling quite a number of requests simultaneously!

How do I know if I have this problem?
Okay, so it’s an interesting problem to think about, but really the practical question is, “Is queuing affecting my application’s responsiveness?” Monitoring the full stack is the best way to stay on top of performance problems – webserver queueing among many others.

You can usually get an isolated look at webserver queueing from your load balancer and/or app server. For instance, if you’re running FCGI on lighttpd, you can check the queue depth of each worker.

But the ultimate determinant of the success or failure of your load balancing is the impact on latency and concurrency. Check out this 3-minute video on understanding webserver queueing.

Related Articles

More Stories By Dan Kuebrich

Dan Kuebrich is a web performance geek, currently working on Application Performance Management at AppNeta. He was previously a founder of Tracelytics (acquired by AppNeta), and before that worked on AmieStreet/Songza.com.

@ThingsExpo Stories
To get the most out of their data, successful companies are not focusing on queries and data lakes, they are actively integrating analytics into their operations with a data-first application development approach. Real-time adjustments to improve revenues, reduce costs, or mitigate risk rely on applications that minimize latency on a variety of data sources. In his session at @BigDataExpo, Jack Norris, Senior Vice President, Data and Applications at MapR Technologies, reviewed best practices t...
"Evatronix provides design services to companies that need to integrate the IoT technology in their products but they don't necessarily have the expertise, knowledge and design team to do so," explained Adam Morawiec, VP of Business Development at Evatronix, in this SYS-CON.tv interview at @ThingsExpo, held Oct 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA.
Recently, REAN Cloud built a digital concierge for a North Carolina hospital that had observed that most patient call button questions were repetitive. In addition, the paper-based process used to measure patient health metrics was laborious, not in real-time and sometimes error-prone. In their session at 21st Cloud Expo, Sean Finnerty, Executive Director, Practice Lead, Health Care & Life Science at REAN Cloud, and Dr. S.P.T. Krishnan, Principal Architect at REAN Cloud, discussed how they built...
No hype cycles or predictions of a gazillion things here. IoT is here. You get it. You know your business and have great ideas for a business transformation strategy. What comes next? Time to make it happen. In his session at @ThingsExpo, Jay Mason, an Associate Partner of Analytics, IoT & Cybersecurity at M&S Consulting, presented a step-by-step plan to develop your technology implementation strategy. He also discussed the evaluation of communication standards and IoT messaging protocols, data...
With tough new regulations coming to Europe on data privacy in May 2018, Calligo will explain why in reality the effect is global and transforms how you consider critical data. EU GDPR fundamentally rewrites the rules for cloud, Big Data and IoT. In his session at 21st Cloud Expo, Adam Ryan, Vice President and General Manager EMEA at Calligo, examined the regulations and provided insight on how it affects technology, challenges the established rules and will usher in new levels of diligence arou...
Smart cities have the potential to change our lives at so many levels for citizens: less pollution, reduced parking obstacles, better health, education and more energy savings. Real-time data streaming and the Internet of Things (IoT) possess the power to turn this vision into a reality. However, most organizations today are building their data infrastructure to focus solely on addressing immediate business needs vs. a platform capable of quickly adapting emerging technologies to address future ...
In his Opening Keynote at 21st Cloud Expo, John Considine, General Manager of IBM Cloud Infrastructure, led attendees through the exciting evolution of the cloud. He looked at this major disruption from the perspective of technology, business models, and what this means for enterprises of all sizes. John Considine is General Manager of Cloud Infrastructure Services at IBM. In that role he is responsible for leading IBM’s public cloud infrastructure including strategy, development, and offering m...
In his session at 21st Cloud Expo, Raju Shreewastava, founder of Big Data Trunk, provided a fun and simple way to introduce Machine Leaning to anyone and everyone. He solved a machine learning problem and demonstrated an easy way to be able to do machine learning without even coding. Raju Shreewastava is the founder of Big Data Trunk (www.BigDataTrunk.com), a Big Data Training and consulting firm with offices in the United States. He previously led the data warehouse/business intelligence and B...
The 22nd International Cloud Expo | 1st DXWorld Expo has announced that its Call for Papers is open. Cloud Expo | DXWorld Expo, to be held June 5-7, 2018, at the Javits Center in New York, NY, brings together Cloud Computing, Digital Transformation, Big Data, Internet of Things, DevOps, Machine Learning and WebRTC to one location. With cloud computing driving a higher percentage of enterprise IT budgets every year, it becomes increasingly important to plant your flag in this fast-expanding busin...
Nordstrom is transforming the way that they do business and the cloud is the key to enabling speed and hyper personalized customer experiences. In his session at 21st Cloud Expo, Ken Schow, VP of Engineering at Nordstrom, discussed some of the key learnings and common pitfalls of large enterprises moving to the cloud. This includes strategies around choosing a cloud provider(s), architecture, and lessons learned. In addition, he covered some of the best practices for structured team migration an...
22nd International Cloud Expo, taking place June 5-7, 2018, at the Javits Center in New York City, NY, and co-located with the 1st DXWorld Expo will feature technical sessions from a rock star conference faculty and the leading industry players in the world. Cloud computing is now being embraced by a majority of enterprises of all sizes. Yesterday's debate about public vs. private has transformed into the reality of hybrid cloud: a recent survey shows that 74% of enterprises have a hybrid cloud ...
22nd International Cloud Expo, taking place June 5-7, 2018, at the Javits Center in New York City, NY, and co-located with the 1st DXWorld Expo will feature technical sessions from a rock star conference faculty and the leading industry players in the world. Cloud computing is now being embraced by a majority of enterprises of all sizes. Yesterday's debate about public vs. private has transformed into the reality of hybrid cloud: a recent survey shows that 74% of enterprises have a hybrid cloud ...
DevOps at Cloud Expo – being held June 5-7, 2018, at the Javits Center in New York, NY – announces that its Call for Papers is open. Born out of proven success in agile development, cloud computing, and process automation, DevOps is a macro trend you cannot afford to miss. From showcase success stories from early adopters and web-scale businesses, DevOps is expanding to organizations of all sizes, including the world's largest enterprises – and delivering real results. Among the proven benefits,...
@DevOpsSummit at Cloud Expo, taking place June 5-7, 2018, at the Javits Center in New York City, NY, is co-located with 22nd Cloud Expo | 1st DXWorld Expo and will feature technical sessions from a rock star conference faculty and the leading industry players in the world. The widespread success of cloud computing is driving the DevOps revolution in enterprise IT. Now as never before, development teams must communicate and collaborate in a dynamic, 24/7/365 environment. There is no time to wait...
Cloud Expo | DXWorld Expo have announced the conference tracks for Cloud Expo 2018. Cloud Expo will be held June 5-7, 2018, at the Javits Center in New York City, and November 6-8, 2018, at the Santa Clara Convention Center, Santa Clara, CA. Digital Transformation (DX) is a major focus with the introduction of DX Expo within the program. Successful transformation requires a laser focus on being data-driven and on using all the tools available that enable transformation if they plan to survive ov...
SYS-CON Events announced today that T-Mobile exhibited at SYS-CON's 20th International Cloud Expo®, which will take place on June 6-8, 2017, at the Javits Center in New York City, NY. As America's Un-carrier, T-Mobile US, Inc., is redefining the way consumers and businesses buy wireless services through leading product and service innovation. The Company's advanced nationwide 4G LTE network delivers outstanding wireless experiences to 67.4 million customers who are unwilling to compromise on qua...
SYS-CON Events announced today that Cedexis will exhibit at SYS-CON's 21st International Cloud Expo®, which will take place on Oct 31 - Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA. Cedexis is the leader in data-driven enterprise global traffic management. Whether optimizing traffic through datacenters, clouds, CDNs, or any combination, Cedexis solutions drive quality and cost-effectiveness. For more information, please visit https://www.cedexis.com.
SYS-CON Events announced today that Google Cloud has been named “Keynote Sponsor” of SYS-CON's 21st International Cloud Expo®, which will take place on Oct 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA. Companies come to Google Cloud to transform their businesses. Google Cloud’s comprehensive portfolio – from infrastructure to apps to devices – helps enterprises innovate faster, scale smarter, stay secure, and do more with data than ever before.
SYS-CON Events announced today that Vivint to exhibit at SYS-CON's 21st Cloud Expo, which will take place on October 31 through November 2nd 2017 at the Santa Clara Convention Center in Santa Clara, California. As a leading smart home technology provider, Vivint offers home security, energy management, home automation, local cloud storage, and high-speed Internet solutions to more than one million customers throughout the United States and Canada. The end result is a smart home solution that sav...
SYS-CON Events announced today that Opsani will exhibit at SYS-CON's 21st International Cloud Expo®, which will take place on Oct 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA. Opsani is the leading provider of deployment automation systems for running and scaling traditional enterprise applications on container infrastructure.