MACHINE DATA ANALYTICS

Glassbeam begins where splunk ends – going beyond operational intelligence with iot logs

SRIKANTH DESIKAN
Dec 10, 2013

Splunk announced today that it acquired Cloudmeter to enhance its capability to analyze machine data. While tools like Splunk have tremendous value for internal data centers, companies are starting to embark on more complex Big Data projects with multi-structured machine logs. The rapidly exploding market of physically connected devices and the machine data generated by the “Internet of Things” is driving the need to leverage this data beyond simple troubleshooting needs.

Designing for the internet of things using cassandra

ASHOK AGARWAL
Sep 25, 2013

I like the word “ontology”. It has a nice ring to it. Wikipedia defines Ontology as “knowledge as a set of concepts within a domain, and the relationships among those concepts”. When applied to machine data analytics (“domain”), we see that unless we isolate concepts and understand the relationships, we cannot obtain “knowledge”.

Glassbeam for medical – analyzing mri machine logs

Vivek Sundaram
Sep 18, 2013

The advent of complex medical devices has triggered a renaissance of sorts and imposed a new set of demands on the healthcare industry. Intelligent medical equipment now connect to a central location, enabling key stakeholders to glean insights from historical data collected over time.

The intersection of machine data analytics and the internet of things

SRIKANTH DESIKAN
Sep 08, 2013

The ability to gather and harness data from machines and devices connected to the net is increasingly becoming a source of competitive advantage for those who have been thinking ahead. GE is widely cited, with their INDUSTRIAL INTERNET initiative. Cisco has been talking about INTERNET OF EVERYTHING for a while. At Glassbeam, we have been focusing on the infrastructure required to process and analyze machine data for over 3 years now.

An auto-tuning parser for data from the internet of things (iot)

ASHOK AGARWAL
Nov 15, 2013

We have established beyond a reasonable doubt that knowledge comes from structure. Therefore, parsing IoT logs to create structure is a must do for making sense of this data. Remember the definition of big data – volume, variety and velocity. If you combine that with the business requirement of near real-time analytics, you are looking at a need for high data ingestion speeds. However, the issue is not of ingestion speeds but the total cost of ownership (TCO) for providing that.

Scaling machine data analytics for the internet of things – introducing glassbeam scalar

PUNEET PANDIT
Oct 21, 2013

from: Puneet Pandit, CEO, Glassbeam.

It’s a new era…

Welcome to the Internet of Things – where every connected physical device will generate volumes of machine data. And the key to extracting the intelligence and meaning locked inside this data will lie in a highly scalable platform and a set of applications. At Glassbeam, today marks the launch of that that truly next generation platform purpose-built for machine data analytics – Glassbeam SCALAR.

Search vs. Analysis on log data

Pramod Sridharamurthy
May 23, 2013

Search as the starting point is a great way to start any analytics with Machine log data. As a user, initially you don’t know what you are searching for and hence searching for “needle in a hay stack” is easy, because all you need to do is type needle! Yes, you will get a lot of results back which then needs to be filtered/ranked and presented in a meaningful way, but open source search engines, that allow full text search of any document like SOLR/Lucene, provide a good starting point for search implementation.

Part 4 – Beyond internal support teams – reaching end customers

Pramod Sridharamurthy
Aug 14, 2013

In the last 3 blogs on the topic of “Troubleshooting troubles”, we looked at how troubleshooting steps can be generalized and how a holistic approach can be arrived at building tools/systems/processes that can significantly enhance the productivity of a support group.

To search or not to search on machine data

Pramod Sridharamurthy
May 24, 2013

Search as the starting point is a great way to start any analytics with Machine data. As a user, initially you don’t know what you are searching for and hence searching for “needle in a hay stack” is easy, because all you need to do is type needle! Yes, you will get a lot of results back which then needs to be filtered/ranked and presented in a meaningful way, but open source search engines, that allow full text search of any document like SOLR/Lucene, provide a good starting point for search implementation.

Know your products and your customers

Mar 19, 2013

Sometimes its the small data hidden inside the Big Data that ends up making a huge impact on the business. Often we find our customers using Glassbeam machine data analytics to find all sorts of information about their customers that they could never have known if not for their machine data logs.

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