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GoodData this week unfurled a data-as-a-service platform that employs Docker containers and microservices running on Kubernetes clusters to dynamically scale analytics up and down on demand.
The GoodData.CloudNative (GoodData.CN) platform heralds a new cloud-native era that enables easier embedding of analytics within applications. Key to that is a well-defined set of application programming interfaces (APIs), said Roman Stanek, CEO of GoodData. “It makes analytics much more flexible,” he said.
Initially available for free via a community edition of the platform that comes in the form of a single Docker container image, GoodData also plans to make GoodData.CN available in Freemium, Growth, and Enterprise editions that come with additional capabilities, along with support from GoodData.
Deploy anywhere
Most existing analytics applications are based on monolithic architectures originally created for desktop PCs. These are not designed to dynamically scale up and down on demand. GoodData.CN takes advantage of the orchestration capabilities of Kubernetes to provide application developers with as much compute and storage resources as they can afford to consume, either via a public cloud or in an on-premises IT environment.
The ability to deploy GoodData.CN anywhere is crucial because multiple centers of data gravity will always exist in the enterprise, noted Stanek. It’s unlikely any major enterprise is ever going to be able to standardize on a single data warehouse or data lake, he said.
The GoodData.CM platform provides all the metadata capabilities required to maintain a single source of truth across what are rapidly becoming highly federated environments, noted Stanek.
A programmable API also makes it feasible to deploy a headless data-as-a-service platform for processing analytics that can be readily accessed and consumed as a service by multiple applications. Previously, individual developers had to take the time and effort to embed analytics capabilities directly within their application, noted Stanek. The GoodData.CM platform makes applications more efficient and, as a consequence, smaller. That is because more analytics processing is offloaded to the headless platform, added Stanek.
Employ microservices
Pressure to embed analytics in every application is mounting as end users seek to make faster and better fact-based decisions. Rather than having to move data into a separate application to analyze it, Stanek said the GoodData.CN platform makes it simpler to infuse real-time analytics within an application.
The need to embed analytics within applications is becoming more pronounced with the acceleration of various digital business transformation initiatives. The expectation is that next-generation applications will all provide some type of embedded analytics capability that enables end users to make better decisions in the moment versus long waits for a report prepared by a business analyst, Stanek said. In many cases, the query that was launched by a business analyst is no longer especially relevant by the time that a report can be delivered.
GoodData is not likely the last provider of software that will be going cloud-native. A microservices-based application makes it easier to add new features and capabilities to software by ripping and replacing containers. It also makes applications more resilient. That is because, should any microservice become unavailable for any reason, calls are dynamically rerouted to other microservices to ensure redundancy.
Most software developers are rapidly moving down the path to microservices as an alternative to monolithic applications that may be easier to build but that are increasingly viewed as being inflexible.
In the case of GoodData, it’s not clear to what degree they may be ahead of rivals making similar transitions. However, enterprise IT organizations should expect in the months ahead a wave of headless services based on microservices architectures that will change the way data is consumed and managed.
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