Welcome!

@CloudExpo Authors: Liz McMillan, APM Blog, Elizabeth White, Xenia von Wedel, Mauro Carniel

Related Topics: @CloudExpo, Microservices Expo, Containers Expo Blog, Agile Computing, Release Management , Cloud Security

@CloudExpo: Article

Lessons Learned from Real-World Big Data Implementations

The value of Big Data is in the insights that the data can provide

In the past few weeks I visited several Cloud and Big Data conferences that provided me with a lot of insight. Some people only consider the technology side of Big Data technologies like Hadoop or Cassandra. The real driver however is a different one. Business analysts have discovered Big Data technologies as a way to leverage tons of existing data and ask questions about customer behavior and all sorts relationships to drive business strategy. By doing that they are pushing their IT departments to run ever bigger Hadoop environments and ever faster real-time systems.

What's interesting from a technical side is that ad-hoc analytics on existing data is allowed to take some time. However ad-hoc implies people waiting for an answer, meaning we are talking about minutes and not hours. Another interesting insight is that Hadoop environments are never static or standalone. Most companies take in new data on a continuous basis via technologies like flume. This means Hadoop MapReduce jobs need to be able to keep up with the data flow, either by adding more hardware or by optimizing them.

There are multiple drivers to Big Data (actually there are a lot) but the two most important ones are these: Analytics and Technical Need for Speed. Let's look at some of those and the resulting takeaways.

The Value Is in the Insight Not the Volume
The value of Big Data is in the insights that the data can provide, not the sheer volume of it. The reason that more and more companies are keeping all of their log and transaction data is that they want to gain those insights. The sheer size of the data is rather an obstacle to this goal and has been for a long time. With Big Data technologies this value can be harnessed.

Don't Forget That Data Analysts Are People Too
Ad-hoc analytics doesn't have to be instant, but must not take hours either. It was interesting to see that time to result on ad-hoc analytics is considered important. This is because people are doing those queries, and people don't like to wait for hours. But even more important is that business analytics is often an iterative process. Ask a question, check the answer, refine or change the question. Hours long MapReduce jobs are prohibitive to this process.

New Data Is Coming in All the Time
Big Data environments are constantly fed new data. This is not really big news, but I was still surprised by the constant reiteration of this fact. The constant data growth means that ad-hoc queries get either slower over time or need to work on samples. To remedy this, companies are writing, scrubbing and categorizing MapReduce jobs. These jobs basically strip out all the unimportant stuff and put cleansed, streamline easy-to-access data into new files. Instead of executing analytics against raw files, the analyst works on a cleansed data set. The implications are that scrubbing jobs need to be maintained all the time (as data input is changing over time) and they need to be able to keep up with the velocity of the input. MapReduce is not allowed to run for hours, but needs to be quick and iterative.

Big Data Is Not Cheap
While it sounds obvious, it's something that's not talked about by the vendors unless specifically asked. Hadoop requires a lot of hardware and a lot of expertise. Especially the expertise is hard to come by as of yet. While hardware might be cheap (you don't need expensive boxes for Hadoop) the bigger the environment the higher the operational costs. That operational cost is the reason some Hadoop vendors exist on services alone and also why customers are demanding better monitoring and management solutions.

Data Must Be Accessible at Low Latencies to Provide Value
One very interesting fact is that most early adopters that use Hadoop for analytics use it for ad-hoc analytics and not as a traditional warehouse. They use MapReduce to do the heavy lifting that is usually reserved for ETL jobs and put the resulting dimensions in existing data warehouses or into a NoSQL solution like HBase, Cassandra or MongoDB. These solutions provide low latency access semantics and are then integrated in the transactional application world, e.g. to provide recommendations to the end users.

This does not absolve them from optimizing their Hadoop environment where they can, but it gives them the much needed real time access that Hadoop so far does not provide. This also makes for additional complexity that needs to be maintained and monitored.

NoSQL Solutions Need Management and Monitoring as Well
NoSQL solutions are most often used to provide low latency databases with failover and horizontal scaling characteristics. As expected, practitioners quickly run into new issues like distribution and wrong access patterns. Most NoSQL solutions lack sophisticated monitoring or performance analysis tools and require experts instead. Fortunately several companies are working on providing those tools and some APM vendors work hard to support NoSQL databases similar to normal databases. This is emphasized by another interesting finding: With a fast and scalable data storage, the application itself quickly becomes the response time and scaling bottleneck.

Applications Using NoSQL Technologies Are More Complex
Most NoSQL solutions surrender more complex logic like joins in order to achieve horizontally scalable data distribution. That logic is moved to the application - arguably this is where it should be anyway. NoSQL solutions require data to be stored in a query access optimized way - de-normalization is the key. The flip side of storing data multiple times and the need to keep it in sync on updates, is that the storage logic again becomes more complex. More application logic usually means less performance.

My conclusion as a performance engineer is relatively clear: Big Data requires Performance Management and Monitoring Tools to fulfill its promise in a cost effective and timely manner. Here are some suggestions on what you should think about when you start a Big Data project.

  1. Large Hadoop environments are hard to manage and operate. Without automation in terms of deployment, operations, monitoring and root cause analysis they quickly become unmanageable. Make sure to have a monitoring solution in place that informs you pro-actively of any infrastructure or software issues that would affect your operation. It needs to give you an easy way to pinpoint the root cause.
  2. The easiest way to identify new performance issues is to detect and analyze change. Adopt a life cycle and 24/7 production APM approach. It will enable you to notice changes in data and compute distribution over time. In addition a life cycle approach will allow you to immediately pin point any negative changes introduced by a new software release.
  3. Don't just throw more and more hardware at the problem. While you can use cheaper hardware for Hadoop, it's still cost. But more than that you have to consider the operational drag. Every node you add will make traditional log based analysis more complicated. Instead ensure that you have an APM solution in place that lets you understand and optimize MapReduce jobs at their core and reduce both the time and resources it takes to run them.
  4. Your Hadoop cluster is no island, but will always be connected in some form or the other to a real time or at least transactional system. Make sure that you have a monitoring solution in place that can support both.

NoSQL applications tend to have more complex logic. The very performance and scalability of the store depends on correct data access and data distribution. An good monitoring solution allows you to monitor and optimize that additional complexity with ease; it also enables you to understand how your application access the data and how that access is distributed across your NoSQL cluster in your production system. The best way to ensure a scalable and fast NoSQL store is to ensure optimal distribution and access patterns.

Conclusion
Big Data is still very much an emerging technology and its promises are huge. But in order to deliver on those promises it must be cost and time effective to those that harness its value - The Business and not just technology experts.

More Stories By Michael Kopp

Michael Kopp has over 12 years of experience as an architect and developer in the Enterprise Java space. Before coming to CompuwareAPM dynaTrace he was the Chief Architect at GoldenSource, a major player in the EDM space. In 2009 he joined dynaTrace as a technology strategist in the center of excellence. He specializes application performance management in large scale production environments with special focus on virtualized and cloud environments. His current focus is how to effectively leverage BigData Solutions and how these technologies impact and change the application landscape.

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
Coca-Cola’s Google powered digital signage system lays the groundwork for a more valuable connection between Coke and its customers. Digital signs pair software with high-resolution displays so that a message can be changed instantly based on what the operator wants to communicate or sell. In their Day 3 Keynote at 21st Cloud Expo, Greg Chambers, Global Group Director, Digital Innovation, Coca-Cola, and Vidya Nagarajan, a Senior Product Manager at Google, discussed how from store operations and ...
"There's plenty of bandwidth out there but it's never in the right place. So what Cedexis does is uses data to work out the best pathways to get data from the origin to the person who wants to get it," explained Simon Jones, Evangelist and Head of Marketing at Cedexis, 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.
In his session at 21st Cloud Expo, Carl J. Levine, Senior Technical Evangelist for NS1, will objectively discuss how DNS is used to solve Digital Transformation challenges in large SaaS applications, CDNs, AdTech platforms, and other demanding use cases. Carl J. Levine is the Senior Technical Evangelist for NS1. A veteran of the Internet Infrastructure space, he has over a decade of experience with startups, networking protocols and Internet infrastructure, combined with the unique ability to it...
Agile has finally jumped the technology shark, expanding outside the software world. Enterprises are now increasingly adopting Agile practices across their organizations in order to successfully navigate the disruptive waters that threaten to drown them. In our quest for establishing change as a core competency in our organizations, this business-centric notion of Agile is an essential component of Agile Digital Transformation. In the years since the publication of the Agile Manifesto, the conn...
SYS-CON Events announced today that CrowdReviews.com has been named “Media Sponsor” of SYS-CON's 22nd International Cloud Expo, which will take place on June 5–7, 2018, at the Javits Center in New York City, NY. CrowdReviews.com is a transparent online platform for determining which products and services are the best based on the opinion of the crowd. The crowd consists of Internet users that have experienced products and services first-hand and have an interest in letting other potential buye...
Enterprises are moving to the cloud faster than most of us in security expected. CIOs are going from 0 to 100 in cloud adoption and leaving security teams in the dust. Once cloud is part of an enterprise stack, it’s unclear who has responsibility for the protection of applications, services, and data. When cloud breaches occur, whether active compromise or a publicly accessible database, the blame must fall on both service providers and users. In his session at 21st Cloud Expo, Ben Johnson, C...
"We're developing a software that is based on the cloud environment and we are providing those services to corporations and the general public," explained Seungmin Kim, CEO/CTO of SM Systems Inc., 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.
Enterprises are adopting Kubernetes to accelerate the development and the delivery of cloud-native applications. However, sharing a Kubernetes cluster between members of the same team can be challenging. And, sharing clusters across multiple teams is even harder. Kubernetes offers several constructs to help implement segmentation and isolation. However, these primitives can be complex to understand and apply. As a result, it’s becoming common for enterprises to end up with several clusters. Thi...
"MobiDev is a software development company and we do complex, custom software development for everybody from entrepreneurs to large enterprises," explained Alan Winters, U.S. Head of Business Development at MobiDev, 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.
Data scientists must access high-performance computing resources across a wide-area network. To achieve cloud-based HPC visualization, researchers must transfer datasets and visualization results efficiently. HPC clusters now compute GPU-accelerated visualization in the cloud cluster. To efficiently display results remotely, a high-performance, low-latency protocol transfers the display from the cluster to a remote desktop. Further, tools to easily mount remote datasets and efficiently transfer...
"Codigm is based on the cloud and we are here to explore marketing opportunities in America. Our mission is to make an ecosystem of the SW environment that anyone can understand, learn, teach, and develop the SW on the cloud," explained Sung Tae Ryu, CEO of Codigm, 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 Telecom Reseller has been named “Media Sponsor” of SYS-CON's 22nd International Cloud Expo, which will take place on June 5-7, 2018, at the Javits Center in New York, NY. Telecom Reseller reports on Unified Communications, UCaaS, BPaaS for enterprise and SMBs. They report extensively on both customer premises based solutions such as IP-PBX as well as cloud based and hosted platforms.
WebRTC is great technology to build your own communication tools. It will be even more exciting experience it with advanced devices, such as a 360 Camera, 360 microphone, and a depth sensor camera. In his session at @ThingsExpo, Masashi Ganeko, a manager at INFOCOM Corporation, introduced two experimental projects from his team and what they learned from them. "Shotoku Tamago" uses the robot audition software HARK to track speakers in 360 video of a remote party. "Virtual Teleport" uses a multip...
In his session at 21st Cloud Expo, James Henry, Co-CEO/CTO of Calgary Scientific Inc., introduced you to the challenges, solutions and benefits of training AI systems to solve visual problems with an emphasis on improving AIs with continuous training in the field. He explored applications in several industries and discussed technologies that allow the deployment of advanced visualization solutions to the cloud.
"Infoblox does DNS, DHCP and IP address management for not only enterprise networks but cloud networks as well. Customers are looking for a single platform that can extend not only in their private enterprise environment but private cloud, public cloud, tracking all the IP space and everything that is going on in that environment," explained Steve Salo, Principal Systems Engineer at Infoblox, in this SYS-CON.tv interview at 21st Cloud Expo, held Oct 31 – Nov 2, 2017, at the Santa Clara Conventio...
"We're focused on how to get some of the attributes that you would expect from an Amazon, Azure, Google, and doing that on-prem. We believe today that you can actually get those types of things done with certain architectures available in the market today," explained Steve Conner, VP of Sales at Cloudistics, 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.
"NetApp is known as a data management leader but we do a lot more than just data management on-prem with the data centers of our customers. We're also big in the hybrid cloud," explained Wes Talbert, Principal Architect at NetApp, 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.
Gemini is Yahoo’s native and search advertising platform. To ensure the quality of a complex distributed system that spans multiple products and components and across various desktop websites and mobile app and web experiences – both Yahoo owned and operated and third-party syndication (supply), with complex interaction with more than a billion users and numerous advertisers globally (demand) – it becomes imperative to automate a set of end-to-end tests 24x7 to detect bugs and regression. In th...
"Space Monkey by Vivent Smart Home is a product that is a distributed cloud-based edge storage network. Vivent Smart Home, our parent company, is a smart home provider that places a lot of hard drives across homes in North America," explained JT Olds, Director of Engineering, and Brandon Crowfeather, Product Manager, at Vivint Smart Home, in this SYS-CON.tv interview at @ThingsExpo, held Oct 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA.
The question before companies today is not whether to become intelligent, it’s a question of how and how fast. The key is to adopt and deploy an intelligent application strategy while simultaneously preparing to scale that intelligence. In her session at 21st Cloud Expo, Sangeeta Chakraborty, Chief Customer Officer at Ayasdi, provided a tactical framework to become a truly intelligent enterprise, including how to identify the right applications for AI, how to build a Center of Excellence to oper...