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AIOps

Stream Your Data Using Loom's Source Types- Announcing Streaming 2.0!

November 29, 2017 | Orr Semmel
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source types

 

We are super excited to share that we've just released our new feature, Streaming 2.0, and oh, the surprises this entails!

In a nutshell, Our new Streaming 2.0 is all about an Advanced AI Data Structure for Precision Log Analysis. It enables more precise log analysis in Enterprise IT environments, ultimately reducing the manual work needed to optimize the product by up to 80%.

If you want to get the highlight version, you can find it here.

What's in it for you?

A few features we are so very proud about are:

1. New Data Architecture:

 

source types

 

• Every event streamed to Loom is now mapped to a “Source Type” (each type of log/technology will have its own "source type", e.g. Apache Tomcat, IIS access log, etc.).

• Once a “Source Type” is mapped – no additional work is needed for this particular source.

• A source type contains all the relevant information in order for Loom to analyze properly the event:

• The proper schema

• Properties classification (ARC, Meter, Gauge, etc.)

• Replacements (regular expressions for patterning)

• Keywords for lexical analysis

• Loom supports a repository of source types and of course, all sources that we encountered during the POC will be already covered so there will be very little work left to be done in terms of lift-up (if they are aware of additional source they want to stream they can let us know in advance and we will be able to prepare the system to support it, which is not possible with the current version).

 

Bottom line: 

Reduces Loom’s lift-up time by ~80% 

Extract more value from Loom as it becomes easier to manipulate the data and configure the system

Automatically mapped event to source type

Automatically mapped event to source type- source types goes way beyond parsing the data and really fine tunes the anomaly detection to the data you are streaming.

 

2. Better options to structure the data - as a huge organization with a complex infrastructure they will enjoy better flexibility in structuring the data (splitting sources according to their desired logical separation) and will be able to do so in a much easier way. Current version requires more manual work and might be more limited in terms of the ability to split and analyze the data.

data inputs

 

3. Improved integration with notification systems:

 

notifications1

 

• Enhancement of the Slack and email notification sent by Loom to be significantly clearer and understandable (adding contextual information, adding the graph of the anomaly).

 

set notification

 

• Actionable Slack and email notifications (ability to mute, raise or remove an incident directly from Slack or Email)

• More granular user preferences for email and slack notification (subscribe to specific type of alerts, specific applications, allows the admin to subscribe other users to alerts)

 

4. Additional enhancements:

 

• Script-less mapping of sources to a source type, application, and service

• Create custom alerts using the filters on the analytics screen so almost no syntax is now required!

• More granular feedback options (mainly mute & raise specific dominant patterns)

 

That's it folks. We have so may super exciting new features up our sleeves and can't wait for your feedback on our new thing!

 

Loom Systems delivers an AI-powered log analysis solution to predict and prevent problems in the digital business. Loom collects logs and metrics from the entire IT stack, continually monitors them, and gives a heads-up when something is likely to deviate from the norm. When it does, Loom sends out an alert and recommended resolution so DevOps and IT managers can proactively attend to the issue before anything goes down. Schedule Your Live Demo here!

Tags: AIOps AI streaming 2.0

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