Modernizing IT Operations with AIOps

Sudheesh SubhashCEO, NetServ.

There comes a time when companies need to modernize their IT operations (ITOps). To do this effectively, they need to identify the challenges and pain points their ITOps present. If they implement full-stack observability, it’s relatively easy to unravel all the problematic aspects that affect the business.

What common problems do companies face on a daily basis? High-volume volumes and lengthy service interruptions that frustrate customers and employees often occur in companies with outdated systems. In addition, redundant tools can impede mission-critical business operations.

As a business leader or head of ITOps, you may have experienced the above. Undoubtedly, these issues are a cause for concern, and you’ll want to find a way to modernize your systems to stay competitive and relevant. Below, we reveal how AIOps can help your enterprise IT environment and upgrade it.

Common issues you may be dealing with

The following issues can affect your IT productivity and operational efficiency goals:

• Longer service interruptions.

• Too many redundant tools.

• Too many calls.

• No single pane of glass management.

• No key performance indicators (KPI) reporting.

• No proactive or predictive analytics.

What is AIOps?

AIOps stands for “artificial intelligence for IT operations”. AIOps platforms leverage big data, AI and machine learning for advanced analytics to automate and improve your ITOps. AIOps platforms allow simultaneous use of multiple data sources (domain-centric monitoring tools, logging tools, etc.) to improve IT operations.

In a nutshell, AIOps aims to improve data quality so that ITOps teams can utilize various use cases relevant to their practices. In addition, AIOps detects anomalies and provides contextual insights that can benefit companies by enabling them to implement new capabilities based on data and RCA faster.

Why do companies need AIOps?

AIOps platforms can significantly improve IT operational efficiency. This can include application operations, DevOps, DevSecOps, infrastructure operations, and service management. Additionally, AIOps can give companies the ability to ingest data from multiple sources such as domain-centric IT monitoring tools such as application performance monitoring (APM), network performance monitoring (NPM), logging tools and other monitoring tools.

When implementing IT monitoring tools consisting of infrastructure, application performance monitoring (APM), and network performance monitoring (NPM), it pays to apply AI/ML algorithms. These algorithms use real-time and historical data for event correlation, proactive remediation, predictive problem management, and faster RCA.

However, it is best not to rely solely on domain-centric tools, as each domain-centric tool offers its own dedicated view, making it difficult to isolate problems and identify root causes while prolonging troubleshooting times. problems.

This is where domain-independent AIOps comes in as it can solve common problems much more efficiently by eliminating noise found in observability data, detecting anomalies and creating actionable incidents. Some other side benefits are that it reduces case volumes and increases ITOps team bandwidth.

How to start the change

Start by implementing a monitoring strategy and ensure you have the most critical domain-centric IT infrastructure available. This infrastructure can include, at a minimum, your company’s application, data center, and end-user monitoring tools.

Regardless of whether or not you have a monitoring strategy, go ahead with your observability maturity assessment or IT monitoring tools assessment, as this can help you identify gaps and limitations of your toolset in its current state and create your roadmap and proper monitoring strategy to achieve your business objectives.

What to know about adopting AIOps

Current corporate IT monitoring methodologies follow the reactive/responsive model. When they try to modernize their current monitoring stack, it’s uncertain if they make much progress, which largely depends on other priorities.

When they try to change their tools, they may run into various problems. This can include integration challenges and alerting issues that cause various mishaps resulting from data provided to the response team.

AIOps is an emerging technology and adoption rates are low because companies do not have a clear strategy that allows them to move from a reactive to an autonomous observability model.

Implementing managed AIOps

As AIOps can bring tangible benefits to the table, consider what this means for your company. Also, consider the steps you need to take for a satisfactory result.

Deploying domain-independent AIOps does not involve any changes or agent installations in your current environment. The data just needs to be sent to the domain independent AIOps tool and then a machine learning algorithm can be applied to enrich the data by removing noise and duplication.

This further enhances data analysis to correlate events from multiple domains or sources, anomaly detection, diagnostic information, and proactive RCA to improve MTTR, automated remediation and task automation – and drive ITOps for autonomous observability.

When implemented, domain agnostic tools will be integrated with existing tools. Now, you can gain access to up-to-date reporting capabilities, advanced presentation capabilities, and transparent ML. It is also unnecessary to learn new tools or initiate configuration changes in your current environment. Depending on your requirements, a managed service provider (MSP) can help you achieve your business goals.

When researching potential managed AIOps vendors to partner with, there are a few things to keep in mind:

1. Make sure the vendor is partnering with one of the leading AIOps vendor platforms.

2. The partner must have a clear strategy to guide you in AIOps, as well as the ability to manage distributed infrastructure, resources, support for hybrid or multi-cloud applications and tools.

3. The partner must adhere to industry-leading security and compliance practices and have clear expectations and SLA requirements, such as performance agreements, issue handling and termination procedures.

Conclusion

If you want to modernize your existing IT operations, consider AIOps. It can help you more efficiently collect and analyze data through robust automation-driven platforms.


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