IT Alert Noise Reduction with AIOps

One of the core value propositions of AIOps platforms is to increase IT efficiency & productivity by applying AI & ML techniques to perform Alert Noise Reduction. This in turn, translates to direct cost reduction due to savings in IT man-hours. In this approach, the AIOps platform becomes like a gatekeeper for all the IT alerts/events. It can help effectively reduce and correlate such events to send meaningful incidents to NOC or Service Desk.

Let us understand some of the typical challenges with IT alerts/events in modern IT environments.

Challenges with IT Alerts/Events

• Exponentially increasing alert volume – with the increase of tools and hybrid environments
• Most alerts are repetitive in nature – Example: CPU high, timeout error, unavailable error etc.
• Every alert must be processed by NOC or Service Desk team – most are not actionable or ephemeral – hurts productivity
• Raw alerts/events miss a required application or serviceability context

IT Alert Noise Reduction Benefits

• Incident volume reduction (Typically 60% or more)
• Cost savings (Typically 40% or more)
• Decreased time to resolution (MTTR reduction – Typically 50% or more)
• Improved IT productivity and efficiency

Now, let us shift gears a little bit and think about IT logs. Many of the challenges that we saw with IT alerts exist with IT logs as well.

Challenges with IT Logs

• Exponentially increasing IT log volume
• Many IT logs are redundant
• Many IT logs are unwanted or unnecessary
• Raw IT logs miss context for timely insights
• Unable to leverage cost-effective cloud object stores for archival

These are the numbers from a recent ESG survey for log management in a large enterprise for a 3-year period.

These numbers are staggering and indicate a real problem that needs to be solved and is as important as solving the alert noise reduction problem.

IT Log Noise Reduction with AIOps

IT logs can also be effectively reduced with AIOps, but legacy event correlation platforms or traditional AIOps do not fit the bill as they are black-boxed to solve only core use cases and cannot effectively handle IT logs.

Additionally, domain-centric AIOps platforms focus only on a certain domain like applications or infrastructure, network or cloud, and they cannot do a good job working with cross-domain data, whether IT alerts or IT logs.

Only a modern data fabric-driven and distributive messaging technology-based AIOps platform built with microservices architecture can solve this log noise reduction problem at scale.

cfxCloud is the only modern AIOps platform built with the world’s first Robotic Data Automation Fabric(TM) that can unify AIOps, Observability and, Automation to enable customers to handle unending complexity with IT logs, in addition to IT alerts/events.

Log noise reduction works by ingesting all of your IT logs from your hybrid cloud environments and intelligently reducing the log noise by applying AI/ML techniques. It also sends filtered and relevant logs to IT destinations or sinks of your choice, typically Cloud Data warehouses like Snowflake, AWS Redshift, Google BigQuery, Data lakes, or SIEM platforms like Splunk, Elasticsearch, Qradar, etc.

Log Noise Reduction Benefits

Benefits from log noise reduction are quite compelling and translate to significant TCO savings for most IT organizations.

Continuing from above mentioned large enterprise scenario, we could potentially see the following benefits when log noise reduction is applied.

It is not just us talking about log noise reduction in AIOps, but Gartner has very well articulated the application of AIOps in various stages of IT, and we can see Log File Analytics as a key use case in the DevOps stage.

Go Beyond Log Noise Reduction with Log Intelligence

In our AIOps platform, we go beyond log noise reduction. We recognize that our customers need to be empowered with more capabilities to effectively handle the daunting challenges of log management. With our AIOps Log Intelligence, customers can send log data from all of their hybrid data sources and achieve the following at scale:

1. Log Data Reduction and Routing: Filter unwanted, redundant and sample data. Send important events to SIEM/Analytics/Data lake of your choice. Trigger outputs.
2. Log Data Enrichment: DNS/Geo-IP lookups, CMDB lookup & enrichment, Full-stack context, cross-domain data
3. Log Data Archival: Raw, untampered data to any AWS S3 compatible object storage, Azure Blob Storage, Google Cloud Storage, Snowflake, and more
4. Log Data Replay: Replay data from archival storage into SIEM/analytics tools – during security investigations/audits
5. Log Data Analytics: Establish patterns, trends, anomaly detection
6. Log Data Shaping/Transformation: You can shape or transform your data to meet standard formats, make them API-compatible or be readily consumable by destinations or sinks.

I will discuss each of the six outcomes mentioned above that we can achieve with our AIOps solution using our Log Intelligence service in upcoming blogs. Stay tuned.

Getting Started with AIOps Log Intelligence on cfxCloud

If you are interested in reducing your IT log volume, you can get started easily with our Log Intelligence service on cfxCloud.