LOG FILE ANALYSIS

What’s On the Chief Data Officers’ Table to Wrestle Data Preparation

The need for proper tool to organize and understand the underlying patterns in machine data exists. From what we’ve been hearing, that’s gripping the Chief Data Officer’s mind. Why?

Introducing glassbeam studio

I am delighted to announce the release of Glassbeam Studio – the industry’s first Data Transformation and Preparation tool for complex machine data.

According to Gartner, by 2018, data discovery and data management evolution will drive most organizations to augment centralized architectures with decentralized approaches. Most business users and analysts will have access to self-service tools to prepare data for analysis.

IOT analytics to drive ev charging station infrastructure growth

We live in anxious times. People are anxious about moving their careers forward, spending enough time with their families, maintaining a healthy diet and more. Happily, the arrival of viable electric cars has alleviated one anxiety we share – namely, polluting the environment with car emissions.

Geting the most out of akka clusters

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

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.

We need to resolve what “resolution” means

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.

Expanding our offering inside salesforce.com

In a PREVIOUS BLOG POST we wrote of Glassbeam’s robust SSO integration with Salesforce.com that helps a user view IOT Analytics along with their CRM data through one interface. Recently, Glassbeam recently won a deal with a major company in the Converged Infrastructure space. This company interacts a fair bit with it’s customers (especially for support issues) through Salesforce.com’s Portal. When our customer has a support issue, they raise a ticket inside Salesforce.com and attach an associated log files (sometimes these are large log files).

Machine logs analytics – next frontier for data center infrastructure management (dcim)

There are few detractors when it comes to the value of DCIM for an Infrastrucutre-as-a-Service (IaaS) provider. But as the data centers become more dynamic and heterogeneous, these tools will need to adept. As CDW, a leading DCIM vendor PREDICTS that cross vendor visibility and heterogeneous platform will challenge the effectiveness of these tools.

Glassbeam for root cause analysis

As a Solutions Architect at Glassbeam, I come across many pre-sales situations during a demo, when I’m asked to showcase our functionality to perform a root cause analysis. So, here is a good example that I’ve pretty much standardized for such situations. It sure is a compelling value proposition of the Glassbeam Explorer application.

Why phone-home makes strategic sense?

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.

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