IT Operations

Reading Between the Log Lines: 4 Customer Challenges and How to Solve Them

July 13, 2017 | Zev Schonberg
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With analysts like Gartner, predicting that the number of devices connected to the internet – currently at around 8 billion – will more than double to 20 billion by 2020 , it’s clear that for pretty much any business, government or institution, properly managing one’s digital ecosystem, is critical for survival.

One of the main challenges in this area is uncovering potential issues before they impact the broader system and any end-u

sers. The sheer volume and velocity of data being generated from so many devices and applications, guarantees that uncovering problems and their causes, is like finding a needle in the haystack…..and even worse, not even knowing whether to look for the figurative needle, or something else entirely.

In this blog post, we’ll be taking a look at four specific scenarios where enterprises around the globe are successfully managing these IT and cyber security challenges (Yes...by using Loom!..but please focus on the methodology).

 

Knowing the Unknowns – Discovering Problems You Never Heard of

A large European telecom using OpenSIPS and Asterisk (both open source tools and infrastructure for the telecom industry) was struggling with manual configuration of static thresholds in their existing log management solution. While their DevOps could easily look for known issues, they had no way to detect incidents that had never occurred before. In their own words, they were seeking a platform that would help them “know the unknowns”. By utilizing the dynamic baseline capabilities in Loom, they successfully uncovered multiple, unknown issues (e.g. No fail-over gateways left) and were able to proactively troubleshoot before their customers’ voice, video, and IM services were affected.

 

Understanding the Domino Effect for Better Troubleshooting

Getting an alert that your system is experiencing some issue is no doubt important, but without visibility into underlying causes, these alerts can be a real tease. For example, when the IT team for a major, fast-food chain in the US would receive an exception such as the “existing connection was forcibly closed by the remote host”, it would take their team considerable time and effort to identify and resolve the issue. And hungry customers would go elsewhere. But with Loom’s smart correlation engine guiding them directly to the root cause of the error, IT no longer just received an isolated alert, but rather could see any and all correlated events occurring in their POS ecosystem.

 

Detecting Issues Before the Customer Does

The NOC team for a large, online forum in the APAC region was charged with keeping performance issues and website downtime to an absolute minimum. In the past, detecting potential problems before they impacted users would literally keep them up at night. Our mission was to allow them to filter out all the noisy alerts and focus on finding real issues, large and small. Recently, a new behavior popped up that highlighted a Solr server configuration issue that could affect search functionality on their site. Loom allowed them to identify and address the issue, well before it affected any end users.

 

The Bottom (Log) Line

In our digital reality, keeping customers happy requires every IT leader to ensure that the myriad systems IT departments use to support their products and platforms, are all running smoothly. And being able to tap into the rich source of information that hides in the log files, is the key for every organization to succeed.

Did your organization face similar issues? What was your methods of detection and resolution? Feel free to share with us your thoughts.

 


 

Enter Loom Systems

Loom is an AI-powered log analysis solution that gives a heads up when there may be a problem within a digital system. Loom connects to a business’ digital assets, continually monitors and learns about them by reading their logs and detects when something is likely to deviate from the norm.

Tags: IT Operations Monitoring Logging log-analytics

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