Welcome!

Machine Learning Authors: Progress Blog, Kevin Jackson, Jason Bloomberg, Liz McMillan, Elizabeth White

Related Topics: Microservices Expo, Java IoT, Linux Containers, Containers Expo Blog, Machine Learning , @DXWorldExpo

Microservices Expo: Article

Understanding Application Performance on the Network | Part 2

Bandwidth and Congestion

When we think of application performance problems that are network-related, we often immediately think of bandwidth and congestion as likely culprits; faster speeds and less traffic will solve everything, right? This is reminiscent of recent ISP wars; which is better, DSL or cable modems? Cable modem proponents touted the higher bandwidth while DSL proponents warned of the dangers of sharing the network with your potentially bandwidth-hogging neighbors. In this blog entry, we'll examine these two closely-related constraints, beginning the series of performance analyses using the framework we introduced in Part I. I'll use graphics from Compuware's application-centric protocol analyzer - Transaction Trace - as illustrations.

Bandwidth
We define bandwidth delay as the serialization delay encountered as bits are clocked out onto the network medium. Most important for performance analysis is what we refer to as the "bottleneck bandwidth" - the speed of the link at its slowest point - as this will be the primary influencer on the packet arrival rate at the destination. Each packet incurs the serialization delay dictated by the link speed; for example, at 4Mbps, a 1500 byte packet takes approximately 3 milliseconds to be serialized. Extending this bandwidth calculation to an entire operation is relatively straightforward. We observe (on the wire) the number of bytes sent or received and multiply that by 8 bits, then divide by the bottleneck link speed, understanding that asymmetric links may have different upstream and downstream speeds.

Bandwidth effect = [ [# bytes sent or received] x [8 bits] ]/ [Bottleneck link speed]

For example, we can calculate the bandwidth effect for an operation that sends 100KB and receives 1024KB on a 2048Kbps link:

  • Upstream effect: [100,000 * 8] / 2,048,000] = 390 milliseconds
  • Downstream effect: [1,024,000 *8] / 2,048,000] = 4000 milliseconds

For better precision, you should account for frame header size differences between the packet capture medium - Ethernet, likely - and the WAN link; this difference might be as much as 8 or 10 bytes per packet.

Bandwidth constraints impact only the data transfer periods within an operation - the request and reply flows. Each flow also incurs (at a minimum) additional delay due to network latency, as the first bit traverses the network from sender to receiver; TCP flow control or other factors may introduce further delays. (As an operation's chattiness increases, its sensitivity to network latency increases and the overall impact of bandwidth tends to decrease, becoming overshadowed by latency.)

Transaction Trace Illustration: Bandwidth
One way to frame the question is "does the operation use all of the available bandwidth?" The simplest way to visualize this is to graph throughput in each direction, comparing uni-directional throughput with the link's measured bandwidth. If the answer is yes, then the operation bottleneck is bandwidth; if the answer is no, then there is some other constraint limiting performance. (This doesn't mean that bandwidth isn't a significant, or even the dominant, constraint; it simply means that there are other factors that prevent the operation from reaching the bandwidth limitation. The formula we used to calculate the impact of bandwidth still applies as a definition of the contribution of bandwidth to the overall operation time.)

This FTP transfer is frequently limited by the 10Mbps available bandwidth.

Networks are generally shared resources; when there are multiple connections on a link, TCP flow control will prevent a single flow from using all of the available bandwidth as it detects and adjusts for congestion. We will evaluate the impact of congestion next, but fundamentally, the diagnosis is the same; bandwidth constrains throughput.

Congestion
Congestion occurs when data arrives at a network interface at a rate faster than the media can service; when this occurs, packets must be placed in an output queue, waiting until earlier packets have been serviced. These queue delays add to the end-to-end network delay, with a potentially significant effect on both chatty and non-chatty operations. (Chatty operations will be impacted due to the increase in round-trip delay, while non-chatty operations may be impacted by TCP flow control and congestion avoidance algorithms.)

For a given flow, congestion initially reduces the rate of TCP slow-start's ramp by slowing increases to the sender's Congestion Window (CWD); it also adds to the delay component of the Bandwidth Delay Product (BDP), increasing the likelihood of exhausting the receiver's TCP window. (We'll discuss TCP slow-start as well as the BDP later in this series.)

As congestion becomes more severe, the queue in one of the path's routers may become full. As packets arrive exceeding the queue's storage capacity, some packets must be discarded. Routers employ various algorithms to determine which packets should be dropped, perhaps attempting to distribute congestion's impact among multiple connections, or to more significantly impact lower-priority traffic. When TCP detects these dropped packets (by a triple-duplicate ACK, for example), congestion is the assumed cause. As we will discuss in more depth in an upcoming blog entry, packet loss causes the sending TCP to reduce its Congestion Window by 50%, after which slow-start begins to ramp up again in a relatively conservative congestion avoidance phase.

For more on congestion, and for further insight, click here for the full article.

More Stories By Gary Kaiser

Gary Kaiser is a Subject Matter Expert in Network Performance Analytics at Dynatrace, responsible for DC RUM’s technical marketing programs. He is a co-inventor of multiple performance analysis features, and continues to champion the value of network performance analytics. He is the author of Network Application Performance Analysis (WalrusInk, 2014).

Comments (0)

Share your thoughts on this story.

Add your comment
You must be signed in to add a comment. Sign-in | Register

In accordance with our Comment Policy, we encourage comments that are on topic, relevant and to-the-point. We will remove comments that include profanity, personal attacks, racial slurs, threats of violence, or other inappropriate material that violates our Terms and Conditions, and will block users who make repeated violations. We ask all readers to expect diversity of opinion and to treat one another with dignity and respect.


@CloudExpo Stories
Sanjeev Sharma Joins June 5-7, 2018 @DevOpsSummit at @Cloud Expo New York Faculty. Sanjeev Sharma is an internationally known DevOps and Cloud Transformation thought leader, technology executive, and author. Sanjeev's industry experience includes tenures as CTO, Technical Sales leader, and Cloud Architect leader. As an IBM Distinguished Engineer, Sanjeev is recognized at the highest levels of IBM's core of technical leaders.
Digital transformation is about embracing digital technologies into a company's culture to better connect with its customers, automate processes, create better tools, enter new markets, etc. Such a transformation requires continuous orchestration across teams and an environment based on open collaboration and daily experiments. In his session at 21st Cloud Expo, Alex Casalboni, Technical (Cloud) Evangelist at Cloud Academy, explored and discussed the most urgent unsolved challenges to achieve f...
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...
Recently, WebRTC has a lot of eyes from market. The use cases of WebRTC are expanding - video chat, online education, online health care etc. Not only for human-to-human communication, but also IoT use cases such as machine to human use cases can be seen recently. One of the typical use-case is remote camera monitoring. With WebRTC, people can have interoperability and flexibility for deploying monitoring service. However, the benefit of WebRTC for IoT is not only its convenience and interopera...
"WineSOFT is a software company making proxy server software, which is widely used in the telecommunication industry or the content delivery networks or e-commerce," explained Jonathan Ahn, COO of WineSOFT, in this SYS-CON.tv interview at 21st Cloud Expo, held Oct 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA.
SYS-CON Events announced today that Synametrics Technologies will exhibit at SYS-CON's 22nd International Cloud Expo®, which will take place on June 5-7, 2018, at the Javits Center in New York, NY. Synametrics Technologies is a privately held company based in Plainsboro, New Jersey that has been providing solutions for the developer community since 1997. Based on the success of its initial product offerings such as WinSQL, Xeams, SynaMan and Syncrify, Synametrics continues to create and hone inn...
There is a huge demand for responsive, real-time mobile and web experiences, but current architectural patterns do not easily accommodate applications that respond to events in real time. Common solutions using message queues or HTTP long-polling quickly lead to resiliency, scalability and development velocity challenges. In his session at 21st Cloud Expo, Ryland Degnan, a Senior Software Engineer on the Netflix Edge Platform team, will discuss how by leveraging a reactive stream-based protocol,...
Modern software design has fundamentally changed how we manage applications, causing many to turn to containers as the new virtual machine for resource management. As container adoption grows beyond stateless applications to stateful workloads, the need for persistent storage is foundational - something customers routinely cite as a top pain point. In his session at @DevOpsSummit at 21st Cloud Expo, Bill Borsari, Head of Systems Engineering at Datera, explored how organizations can reap the bene...
The past few years have brought a sea change in the way applications are architected, developed, and consumed—increasing both the complexity of testing and the business impact of software failures. How can software testing professionals keep pace with modern application delivery, given the trends that impact both architectures (cloud, microservices, and APIs) and processes (DevOps, agile, and continuous delivery)? This is where continuous testing comes in. D
The dynamic nature of the cloud means that change is a constant when it comes to modern cloud-based infrastructure. Delivering modern applications to end users, therefore, is a constantly shifting challenge. Delivery automation helps IT Ops teams ensure that apps are providing an optimal end user experience over hybrid-cloud and multi-cloud environments, no matter what the current state of the infrastructure is. To employ a delivery automation strategy that reflects your business rules, making r...
Most technology leaders, contemporary and from the hardware era, are reshaping their businesses to do software. They hope to capture value from emerging technologies such as IoT, SDN, and AI. Ultimately, irrespective of the vertical, it is about deriving value from independent software applications participating in an ecosystem as one comprehensive solution. In his session at @ThingsExpo, Kausik Sridhar, founder and CTO of Pulzze Systems, discussed how given the magnitude of today's application ...
Digital Transformation (DX) is not a "one-size-fits all" strategy. Each organization needs to develop its own unique, long-term DX plan. It must do so by realizing that we now live in a data-driven age, and that technologies such as Cloud Computing, Big Data, the IoT, Cognitive Computing, and Blockchain are only tools. In her general session at 21st Cloud Expo, Rebecca Wanta explained how the strategy must focus on DX and include a commitment from top management to create great IT jobs, monitor ...
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...
Continuous Delivery makes it possible to exploit findings of cognitive psychology and neuroscience to increase the productivity and happiness of our teams. In his session at 22nd Cloud Expo | DXWorld Expo, Daniel Jones, CTO of EngineerBetter, will answer: How can we improve willpower and decrease technical debt? Is the present bias real? How can we turn it to our advantage? Can you increase a team’s effective IQ? How do DevOps & Product Teams increase empathy, and what impact does empath...
"Digital transformation - what we knew about it in the past has been redefined. Automation is going to play such a huge role in that because the culture, the technology, and the business operations are being shifted now," stated Brian Boeggeman, VP of Alliances & Partnerships at Ayehu, in this SYS-CON.tv interview at 21st Cloud Expo, held Oct 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA.
You know you need the cloud, but you're hesitant to simply dump everything at Amazon since you know that not all workloads are suitable for cloud. You know that you want the kind of ease of use and scalability that you get with public cloud, but your applications are architected in a way that makes the public cloud a non-starter. You're looking at private cloud solutions based on hyperconverged infrastructure, but you're concerned with the limits inherent in those technologies. What do you do?
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...
A strange thing is happening along the way to the Internet of Things, namely far too many devices to work with and manage. It has become clear that we'll need much higher efficiency user experiences that can allow us to more easily and scalably work with the thousands of devices that will soon be in each of our lives. Enter the conversational interface revolution, combining bots we can literally talk with, gesture to, and even direct with our thoughts, with embedded artificial intelligence, whic...
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...
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 ...