While most businesses know they should be making use of big data technologies in some way, it’s often difficult to know how you should get started. After all, there are a lot of decisions to be made about which stack to use, what hardware configurations to use, and how to monitor and service a large-scale big data setup. Often times, companies will take on the challenge of setting up Hadoop or Spark themselves, only to realize later on that their setup is brittle and difficult to monitor and maintain.
The Evolving Story
One key development in big data technology over the past few years has been improvements in containerization and virtualization technology. In the past few years as analytics software has matured, DevOps technology has been undergoing a revolution as well. The end result is that it’s now both easy and efficient for you to get a managed big data solution based on state-of-the art containerization tools such as Docker and Kubernetes.
The latest wave in big data and analytics is Big Data as a Service (BDaaS) – big data analytics managed as a service. While most people tend to think about managing their own big data analytics engine, there are a few reasons to prefer using a third-party Docker-based service. Using Docker, you’re assured of getting a properly configured container that scales to whatever sizes you need. And by outsourcing the management of your cluster to experts, you can focus on the core expertise of your company.
The Latest Technologies
With Docker, you get a standardized, repeatable build process wrapped up in its own runtime, a container. Analytics technologies are notorious for requiring a lot of tweaking for performance: many development weeks have been wasted managing kernel settings, and tuning config parameters in a Spark cluster trying to get things to work. With a pre-built Docker file, you’re guaranteed to get a container that works right out of the gate, configured by data architects and data scientists who now how to get the most out of the technology you choose.
Big data analytics also require the ability to scale up to whatever size your data requires. With Docker, you’re able to take a single pre-configured container and launch as many instances of it as your cluster requires. Because Docker ensures that each container is identically configured and networked, you’re able to scale your analytics cluster to match your organization’s needs.
Docker allows you to build a scalable architecture out of container building blocks, but it takes cutting-edge tools to manage large groups of containers. Google built the open-source project Kubernetes to manage its billions of containers using the latest developments in DevOps. Kubernetes is a container orchestration tool that allows you to declaratively describe how your architecture should look. From there, Kubernetes handles the heavy lifting of managing the lifecycle of individual containers. From the user perspective, you simply say you’d like a 100-instance Hadoop cluster. Kubernetes takes care of the rest.
Used in combination with Docker, Kubernetes is designed to handle enterprise-level analytics concerns for the world’s largest data sets. With Docker and Kubernetes as the basis of your analytics stack, you can use any analytics engine, such as Hadoop or Spark, and be sure you’re getting the most out of these technologies.
The Reliable Provider
CloudPlex is a DevOps-as-a-service company that manages launching, orchestrating, and monitoring everything from applications to analytics engines. CloudPlex was designed with modern Docker-based applications in mind, and allows you to select from several pre-built containers crafted by data architects and data scientists who understand Big Data. Right off the bat you can choose from several pre-built containers, such as Hadoop, Spark, Kafka, Cassandra, etc., and different distributions, such as Apache, Cloudera, or Hortonworks.
CloudPlex uses policy-based auto-scaling, and uses Kubernetes under the hood for orchestration, so you can be confident your app will scale gracefully from ten containers to ten thousand, empowering you to accelerate your growth. CloudPlex also offers high availability options, where the platform detects the failure and replaces the failed instances with new instances, minimizing the impact on your business apps.