Splunk this week revealed at its .conf18 conference that it has created a beta version of a Splunk Developer Cloud platform based on Kubernetes to both foster the development of microservices-based applications and make functions within the core Splunk platform readily accessible to other applications.
In addition, Splunk announced that version 7.2 of the Splunk operational analytics platform now can be deployed using Docker containers.
Jon Rooney, vice president of product marketing, says Splunk Developer Cloud is being made available as a managed Splunk service at least through its beta period, adding Splunk may later decide to take advantage of the inherent portability of Kubernetes to make Splunk Developer Cloud available in an on-premises environment or even across multiple clouds.
Rooney says Splunk doesn’t intend to convert its entire monolithic application into a set of microservices. But The company will make it possible for developers to embed a search or analytics function within their applications. In that context, use of Splunk will become more pervasive as part of a larger Splunk Next initiative that includes support in beta support for a Splunk Data Stream Processor, which enables Splunk to access and analyze data in near real-time. As part of that initiative, Rooney says Splunk is now being a lot more open about its product road maps to encourage organizations to co-develop applications and technologies that leverage core Splunk functions.
In addition, Rooney notes Splunk will make available machine learning algorithms in the form of toolkits that developers can optionally employ.
Splunk Developer Cloud represents a major expansion of the application development strategy for Splunk. Instead of focusing on enabling developers to build applications on top of an instance of the Splunk platform, developers now will be able to invoke Splunk services via documented application programming interfaces (APIs), says Rooney. That approach will enable developers to focus more of their efforts on developing business logic that differentiates their application, rather than replicating a function that Splunk now makes easily accessible.
In addition, Rooney says Splunk expects that developers will leverage Splunk Developer Cloud to build applications in vertical industry segments where Splunk has either no expertise or may not be large enough for Splunk to serve.
Meanwhile, Docker support for Splunk Enterprise 7.2, now generally available, is meant to assist organizations that are looking to lift and shift Splunk applications into the cloud. Splunk recommends running Splunk Enterprise 7.2 on a bare-metal server as best practice. But as many organizations start to eliminate data centers in favor of public clouds, there’s a need to provide an easier way to migrate those workloads using Docker containers versus requiring organizations to refactor Splunk Enterprise to run on a different class of virtual machines.
Overall, Splunk made it apparent this week that its ambition extends to everything from internet of things (IoT) environments to augmented reality applications that are informed to one degree or another by Splunk analytics. The challenge facing Splunk now is recruiting the developer community required to turn those ambitions into reality.