SUPPORT ANALYTICS

New analyst coverage reflecting exciting developments

DEVANG MEHTA
Aug 20, 2015

It’s a busy summer at Glassbeam – we’re entering new verticals and also rolling out some game-changing product features. We constantly talk to industry analysts to keep them abreast of key developments at Glassbeam, and as a result of these conversations a couple of important Analyst coverage reports have been published in recent times.

Geting the most out of akka clusters

SURAJ ATREYA
Aug 14, 2015

Anyone serious about distributed systems or building one, commonly encounters issues such as replication, consistency, availability and partition tolerance (CAP) [1]. In a real life scenario, partition tolerance is inevitable. So the system must be able to handle partition tolerance when there are network outages. Therefore, ‘P’ in the CAP is a must for any distributed system. This has been backed by Peter Deutsch in his (EIGHT FALLACIES OF DISTRIBUTED COMPUTING).

Elastically adding and removing nodes using akka cluster

SURAJ ATREYA
Aug 07, 2015

This post explores a pull-based master/worker architecture – one that is suitable for anyone who is looking to elastically provision nodes when the load is higher than normal and under-provision when the load is below normal. In this post, the master accepts RSS links from frontend which can be a user submitting links and worker accept one RSS link and extract information such as article’s published date, title and a brief description. All this information is indexed into ELASTICSEARCH.

IOT analytics a critical success factor in today’s "big storage"

DEVANG MEHTA
Jul 08, 2015

The pervasiveness of big data has led to an equally significant expansion of what can be called “big storage.” Whether you’re a cloud service provider or an enterprise, managing that big data requires highly complex and sophisticated storage systems. Failure of these systems is not an option.

Storage system providers have turned to IoT analytics both to help ensure optimal performance and to gain a deeper understanding of how customers are using their solutions.

We need to resolve what “resolution” means

DEVANG MEHTA
Apr 02, 2015

In my last BLOG, I discussed three levels of analysis and each type’s benefits to teams, these were proactive, predictive and prescriptive analytics. Predictive and prescriptive, in particular, demonstrate how the enormous potential of big data combined with today’s advanced analytics can contribute to an organization’s success.

Multiple levels of insights courtesty iot analytics

DEVANG MEHTA
Mar 26, 2015

Today’s new and powerful information platforms collect, distill, analyze and present massive amounts of operational data in formats that are easy for the most junior customer service person to understand. In a typical scenario, these platforms apply rules to incoming machine data and enable proactive actions, such as opening up a customer case, dispatching a part and/or alerting a field service team to take preventive action. The customer gets his problem solved and the customer service team is satisfied they have successfully dealt with a problem. Everyone is happy.

Integrating failure analysis into regular support operations

CARLOS QUEZADA
Jan 09, 2015

Our first post for 2015 focuses on integrating failure analysis with the goal of making support operations more productive.

Lets’ take a use case of a hardware vendor that has a chassis based product that has multiple blades as well as an additional card used as the overall controller for the chassis. This Management card is important because it controls power for each blade as well as the fans for cooling.

Why phone-home makes strategic sense?

PUNEET PANDIT
May 31, 2014

I have come across many sales situations where customers are unsure or wary of asking their customers to send regular feeds of the machine-generated data (logs). This feature is known as phone-home or call-home. The fact is that all high technology devices, systems and networks are constantly generating all kinds of log data (syslogs, configs, stats, static etc). This is now called the Internet of Things (IoT) phenomenon.

Predicting system failures to improve customer satisfaction

MOHAMMED GULLER
May 14, 2014

Companies like Amazon, Google, and Netflix have done an amazing job of providing a great customer experience. For example, when you use Google’s search engine, it quickly figures out if you are just researching a topic or planning to a buy a product/service. Accordingly, it tailors content to show you relevant ads or chooses not to display any. Similarly, when you buy a product on Amazon, it displays other products that may be of interest to you. Netflix offers suggestions of movies you may enjoy based on your viewing behavior. How do they do this?

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.

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