Build vs. buy dilemma in machine data analytics

Aug 29, 2013

Over the last few years of Glassbeam evolution, I have seen many of our customers and prospects grappling with the question of “build vs buy” when it comes to deploying a machine data analytics solution. It is no doubt intuitive for a product company to start thinking about building this as an in-house solution. Why? Because it is their products, log data, formats, and they know the best on what value they want to derive out of that. However, many of these home grown projects start with a big promise and deliver very little in the long term.

Why dynamic columns make sense for glassbeam architecture

Aug 14, 2013

Glassbeam Engineering is working heads down on our next-gen architecture using Cassandra and related column family structures. There are many reasons for this evolution, but one of the key drivers is a compelling support use case. Here is some background for this topic.

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

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.

Glassbeam scalar – the new platform to analyze data from the internet of things.

Oct 22, 2013

It’s been over year since the team at Glassbeam set out to build the next generation platform to analyze machine data generated by the "Internet of Things"( MORE BY HARBOR RESEARCH ON THE INTERNET OF THINGS HERE). And now, it is time to show the world the capabilities of this unique platform and solution set. READ MORE ABOUT "WHY GLASSBEAM?".

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

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.

Big data: search vs. analysis

Oct 11, 2013

Early on in my career at SGI we built some interesting data management tools and data warehouses for processing world wide business data and BILL INMON was my hero(I am sure he was the hero for a lot of data geeks back then!).

This recent article on BIG DATA: SEARCH VS. ANALYSIS by him, is a great validation of the need for structure for analysis.

Log analysis on the cloud

Oct 03, 2013

Splunk is now going where their customers want them to go – to the CLOUD with an enterprise offering! Glassbeam has been offering an enterprise log analysis solution on the cloud for fortune 500 companies for a few years now, to analyze the data from their devices. Splunk’s log analysis is focused on Enterprise IT for the most part while Glassbeam has focused on Enterprise business users in support, engineering and service/sales.

Troubleshooting troubles! – part 2

Jul 16, 2013

Basic troubleshooting and Automation

In the previous blog, we looked at some of the steps commonly followed during troubleshooting and also how even though the specifics are different the overall approach is similar.

While looking at finding solutions to enable support, we need to remember that all support problems cannot be treated the same way. If we look at support issues, they are typically broken down into different levels, depending on the complexity of the problem. Most organizations have 3 to 4 levels – L1 – L3 or L4.

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.

Troubleshooting troubles! – part 1

Jun 19, 2013

Troubleshooting troubles!

This is a 4 part series focusing on the use case and possible solution for supporting support engineers.

The problem statement