Click here to close now.




















Welcome!

Microservices Expo Authors: Pat Romanski, Trevor Parsons, Cloud Best Practices Network, Elizabeth White, Joe Pruitt

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.


@MicroservicesExpo Stories
Learn how to solve the problem of keeping files in sync between multiple Docker containers. In his session at 16th Cloud Expo, Aaron Brongersma, Senior Infrastructure Engineer at Modulus, discussed using rsync, GlusterFS, EBS and Bit Torrent Sync. He broke down the tools that are needed to help create a seamless user experience. In the end, can we have an environment where we can easily move Docker containers, servers, and volumes without impacting our applications? He shared his results so yo...
Auto-scaling environments, micro-service architectures and globally-distributed teams are just three common examples of why organizations today need automation and interoperability more than ever. But is interoperability something we simply start doing, or does it require a reexamination of our processes? And can we really improve our processes without first making interoperability a requirement for how we choose our tools?
Cloud Migration Management (CMM) refers to the best practices for planning and managing migration of IT systems from a legacy platform to a Cloud Provider through a combination professional services consulting and software tools. A Cloud migration project can be a relatively simple exercise, where applications are migrated ‘as is’, to gain benefits such as elastic capacity and utility pricing, but without making any changes to the application architecture, software development methods or busine...
The Software Defined Data Center (SDDC), which enables organizations to seamlessly run in a hybrid cloud model (public + private cloud), is here to stay. IDC estimates that the software-defined networking market will be valued at $3.7 billion by 2016. Security is a key component and benefit of the SDDC, and offers an opportunity to build security 'from the ground up' and weave it into the environment from day one. In his session at 16th Cloud Expo, Reuven Harrison, CTO and Co-Founder of Tufin,...
You often hear the two titles of "DevOps" and "Immutable Infrastructure" used independently. In his session at DevOps Summit, John Willis, Technical Evangelist for Docker, covered the union between the two topics and why this is important. He provided an overview of Immutable Infrastructure then showed how an Immutable Continuous Delivery pipeline can be applied as a best practice for "DevOps." He ended the session with some interesting case study examples.
JavaScript is primarily a client-based dynamic scripting language most commonly used within web browsers as client-side scripts to interact with the user, browser, and communicate asynchronously to servers. If you have been part of any web-based development, odds are you have worked with JavaScript in one form or another. In this article, I'll focus on the aspects of JavaScript that are relevant within the Node.js environment.
Approved this February by the Internet Engineering Task Force (IETF), HTTP/2 is the first major update to HTTP since 1999, when HTTP/1.1 was standardized. Designed with performance in mind, one of the biggest goals of HTTP/2 implementation is to decrease latency while maintaining a high-level compatibility with HTTP/1.1. Though not all testing activities will be impacted by the new protocol, it's important for testers to be aware of any changes moving forward.
One of the ways to increase scalability of services – and applications – is to go “stateless.” The reasons for this are many, but in general by eliminating the mapping between a single client and a single app or service instance you eliminate the need for resources to manage state in the app (overhead) and improve the distributability (I can make up words if I want) of requests across a pool of instances. The latter occurs because sessions don’t need to hang out and consume resources that could ...
Alibaba, the world’s largest ecommerce provider, has pumped over a $1 billion into its subsidiary, Aliya, a cloud services provider. This is perhaps one of the biggest moments in the global Cloud Wars that signals the entry of China into the main arena. Here is why this matters. The cloud industry worldwide is being propelled into fast growth by tremendous demand for cloud computing services. Cloud, which is highly scalable and offers low investment and high computational capabilities to end us...
The Internet of Things. Cloud. Big Data. Real-Time Analytics. To those who do not quite understand what these phrases mean (and let’s be honest, that’s likely to be a large portion of the world), words like “IoT” and “Big Data” are just buzzwords. The truth is, the Internet of Things encompasses much more than jargon and predictions of connected devices. According to Parker Trewin, Senior Director of Content and Communications of Aria Systems, “IoT is big news because it ups the ante: Reach out ...
At DevOps Summit NY there’s been a whole lot of talk about not just DevOps, but containers, IoT, and microservices. Sessions focused not just on the cultural shift needed to grow at scale with a DevOps approach, but also made sure to include the network ”plumbing” needed to ensure success as applications decompose into the microservice architectures enabling rapid growth and support for the Internet of (Every)Things.
Our guest on the podcast this week is Adrian Cockcroft, Technology Fellow at Battery Ventures. We discuss what makes Docker and Netflix highly successful, especially through their use of well-designed IT architecture and DevOps.
Explosive growth in connected devices. Enormous amounts of data for collection and analysis. Critical use of data for split-second decision making and actionable information. All three are factors in making the Internet of Things a reality. Yet, any one factor would have an IT organization pondering its infrastructure strategy. How should your organization enhance its IT framework to enable an Internet of Things implementation? In his session at @ThingsExpo, James Kirkland, Red Hat's Chief Arch...
This week, I joined SOASTA as Senior Vice President of Performance Analytics. Given my background in cloud computing and distributed systems operations — you may have read my blogs on CNET or GigaOm — this may surprise you, but I want to explain why this is the perfect time to take on this opportunity with this team. In fact, that’s probably the best way to break this down. To explain why I’d leave the world of infrastructure and code for the world of data and analytics, let’s explore the timing...
Digital Transformation is the ultimate goal of cloud computing and related initiatives. The phrase is certainly not a precise one, and as subject to hand-waving and distortion as any high-falutin' terminology in the world of information technology. Yet it is an excellent choice of words to describe what enterprise IT—and by extension, organizations in general—should be working to achieve. Digital Transformation means: handling all the data types being found and created in the organizat...
Public Cloud IaaS started its life in the developer and startup communities and has grown rapidly to a $20B+ industry, but it still pales in comparison to how much is spent worldwide on IT: $3.6 trillion. In fact, there are 8.6 million data centers worldwide, the reality is many small and medium sized business have server closets and colocation footprints filled with servers and storage gear. While on-premise environment virtualization may have peaked at 75%, the Public Cloud has lagged in adop...
SYS-CON Events announced today that HPM Networks will exhibit at the 17th International Cloud Expo®, which will take place on November 3–5, 2015, at the Santa Clara Convention Center in Santa Clara, CA. For 20 years, HPM Networks has been integrating technology solutions that solve complex business challenges. HPM Networks has designed solutions for both SMB and enterprise customers throughout the San Francisco Bay Area.
MuleSoft has announced the findings of its 2015 Connectivity Benchmark Report on the adoption and business impact of APIs. The findings suggest traditional businesses are quickly evolving into "composable enterprises" built out of hundreds of connected software services, applications and devices. Most are embracing the Internet of Things (IoT) and microservices technologies like Docker. A majority are integrating wearables, like smart watches, and more than half plan to generate revenue with ...
Rapid innovation, changing business landscapes, and new IT demands force businesses to make changes quickly. The DevOps approach is a way to increase business agility through collaboration, communication, and integration across different teams in the IT organization. In his session at DevOps Summit, Chris Van Tuin, Chief Technologist for the Western US at Red Hat, will discuss: The acceleration of application delivery for the business with DevOps
Growth hacking is common for startups to make unheard-of progress in building their business. Career Hacks can help Geek Girls and those who support them (yes, that's you too, Dad!) to excel in this typically male-dominated world. Get ready to learn the facts: Is there a bias against women in the tech / developer communities? Why are women 50% of the workforce, but hold only 24% of the STEM or IT positions? Some beginnings of what to do about it! In her Opening Keynote at 16th Cloud Expo, S...