The need to explain why one has to consider mining their logs is no longer relevant with so many advantages of log analytics. If you are still thinking whether mining your machine logs is important, read these two documents from Harbor Research: The Internet of Things, Machines and Data Analyticsor Product Analytics & Intelligence or just google and you will get compelling reasons. The focus of this blog is the next step, which is after you have decided that analyzing log data from connected devices is indeed useful.
Any data analytics project that involves mining log data has the following stages:
So, an in-house project will involve multiple people with various skills to build the required platform and applications and can take months to complete. We built our core technology - SCALAR, our machine log analytics language - SPL and the visual data preparation and transformation tool - Glassbeam Studio exactly to solve this issue and dramatically improve time to value by factor of 100! You can know more about our Patented Language here and about Glassbeam Studio here.
While Glassbeam Analytics has always been a Software-as-a-Service offering from inception, however, we had many customers who wanted to maximize their existing investments in other data store technologies and wanted to use our technology as a platform instead of a software service. They loved our data preparation and transformation capabilities, ease of handling complex, multi-structured logs, and our Rules Engine, but wanted to build applications on their existing data stores.
So, we have customers who love out SaaS offerings and we also have an option for those who want to build their own applications on their data stores and only use the data preparation and transformation capabilities of Glassbeam Analytics. We also have an option for those who want to use our data store but want to build their own custom applications using the exposed APIs.
Here’s the comparative summary of the three offerings:
|SaaS Offering||Data Transformation and Preparation Platform including data store||Data Transformation and Preparation Platform only|
|Data Preparation||Data preparation and transformation as a service||Data preparation and transformation as a tool||Data preparation and transformation as a tool|
|Hosting||Hosted infrastructure management as a service||Infrastructure managed by Glassbeam on the cloud or managed by the customer on premise||Infrastructure managed by the customer|
|Access Control||In-built authentication and access control||In-built authentication and access control||Authentication and access control need to be built by the customer|
|In-Built Applications||In-built applications for support, Product management, Engineering and Sales||In-built applications optional||No In-built applications|
|Data Store||Data Store transparent to the user||Data exposed through APIs to build applications||Parsed/transformed data exposed through Kafka message bus. Kafka consumers have to be developed by the customer depending on the data store they plan to use|
|Custom Apps||Custom app development as a service||Custom app development will be the responsibility of the customer||App development will be the responsibility of the customer based on the data store they choose|
Glassbeam now provides multiple options to use its machine data analytics platform making ‘build versus buy’ a non-issue. We heard our customers and we now bring to them everything that Glassbeam has to offer in a way that works best for our customers.