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5 Ways AIOps Helps IT Teams

Phil Tee

In our digital world, it is impossible to reduce downtime and cut through alert noise without the proper tools. The pressure to avoid outages to maintain and improve customer experience has never been higher, and if you think old tools can handle the needs of today, think again.

AIOps leverages the power of artificial intelligence (AI) and machine learning (ML) to improve performance and availability.

Still not convinced on the value an AIOps platform offers? Consider this: one minute of downtime at Amazon costs the company roughly $220,000 in revenue. With that kind of money on the line, SRE and DevOps teams forced to manage availability by writing rules and querying logs manually are set up to fail — and failure is costly. AIOps is the necessary lift your monitoring tools need to improve performance and cut out the toil for DevOps and IT teams.

Here are five ways AIOps does exactly that:

1. Reduce noise

If your team has thousands of alerts coming in daily, there is no way to differentiate between which need immediate attention and those that can wait. Instead, when DevOps and IT teams are faced with an outage they find themselves bogged down in huges data sets as they attempt to find the incident. Legacy tools simply aren’t built for observability and the critical task of automating root cause and simply are not scalable enough for the high load of data they must process.

On the other hand , AIOps platforms thrive in this high data load environment.

AIOps (the key here: AI) solutions are built to look for anomalies and start remediating immediately, meaning DevOps and IT teams don’t have to hunt down the issue among thousands of alerts. AIOps is so powerful that it can even find the root cause before a customer even realizes the service is down!

2. Detect early

AIOps brings advanced capabilities to pinpoint which events or logs might be the issue to investigate early signs of a problem with anomaly detection.

Even better, AIOps platforms have no dependence upon rules. Instead, alerts and incidents evolve in real time, supported by deep metrication of your environment. This means that you do not have to wait for all the rules to be met, saving you costly (remember the price of downtime at Amazon) minutes as you tackle issues in the services you own.

3. Identify cause

These days, engineers regularly upgrade platforms, and systems are continuously changing. With an IT culture focused on constant change, it is difficult to know where to look first when things go wrong.

If the house is on fire, where do you point the firehose?

AIOps tells you exactly where to focus your efforts. AIOps platforms automatically add context to alerts and change records to show where issues are. These tools can easily identify patterns in data that a human would miss and help you diagnose and alert your team as it happens.

4. Automate responses

What is the quickest way to avoid alert fatigue and boost job satisfaction? AIOps.

If DevOps teams are spending all of their time manually sorting through alerts, there is little time for them to do what they enjoy: building and innovating. AIOps tools use AI and ML to automatically resolve an incident once detected or route the issue to the correct team to remedy it.

Not only do AIOps tools free up time and maintain job fulfillment for your team, but when a notification is sent to the IT team, you know that it’s mission-critical.

5. Trust one system

The number of different tools DevOps teams are expected to manage is overwhelming. But, choosing the right AIOps platform can replace other tools without losing capabilities. If you want quality incident management, invest in a quality AIOps platform. With flexible integrations, adaptable APIs and collaborative, automated incident management all within the same AIOps tool, you can manage an outage from start to finish without leaving the platform.

Of course, there are many more use cases for AIOps platforms. The impact AIOps has on every aspect of a business, from customer experience to employee satisfaction and revenue, is beyond what anyone could have predicted when Gartner introduced the term five years ago. It is why AIOps is the lift that will allow organizations to keep up as the digital transformation continues and changes.

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5 Ways AIOps Helps IT Teams

Phil Tee

In our digital world, it is impossible to reduce downtime and cut through alert noise without the proper tools. The pressure to avoid outages to maintain and improve customer experience has never been higher, and if you think old tools can handle the needs of today, think again.

AIOps leverages the power of artificial intelligence (AI) and machine learning (ML) to improve performance and availability.

Still not convinced on the value an AIOps platform offers? Consider this: one minute of downtime at Amazon costs the company roughly $220,000 in revenue. With that kind of money on the line, SRE and DevOps teams forced to manage availability by writing rules and querying logs manually are set up to fail — and failure is costly. AIOps is the necessary lift your monitoring tools need to improve performance and cut out the toil for DevOps and IT teams.

Here are five ways AIOps does exactly that:

1. Reduce noise

If your team has thousands of alerts coming in daily, there is no way to differentiate between which need immediate attention and those that can wait. Instead, when DevOps and IT teams are faced with an outage they find themselves bogged down in huges data sets as they attempt to find the incident. Legacy tools simply aren’t built for observability and the critical task of automating root cause and simply are not scalable enough for the high load of data they must process.

On the other hand , AIOps platforms thrive in this high data load environment.

AIOps (the key here: AI) solutions are built to look for anomalies and start remediating immediately, meaning DevOps and IT teams don’t have to hunt down the issue among thousands of alerts. AIOps is so powerful that it can even find the root cause before a customer even realizes the service is down!

2. Detect early

AIOps brings advanced capabilities to pinpoint which events or logs might be the issue to investigate early signs of a problem with anomaly detection.

Even better, AIOps platforms have no dependence upon rules. Instead, alerts and incidents evolve in real time, supported by deep metrication of your environment. This means that you do not have to wait for all the rules to be met, saving you costly (remember the price of downtime at Amazon) minutes as you tackle issues in the services you own.

3. Identify cause

These days, engineers regularly upgrade platforms, and systems are continuously changing. With an IT culture focused on constant change, it is difficult to know where to look first when things go wrong.

If the house is on fire, where do you point the firehose?

AIOps tells you exactly where to focus your efforts. AIOps platforms automatically add context to alerts and change records to show where issues are. These tools can easily identify patterns in data that a human would miss and help you diagnose and alert your team as it happens.

4. Automate responses

What is the quickest way to avoid alert fatigue and boost job satisfaction? AIOps.

If DevOps teams are spending all of their time manually sorting through alerts, there is little time for them to do what they enjoy: building and innovating. AIOps tools use AI and ML to automatically resolve an incident once detected or route the issue to the correct team to remedy it.

Not only do AIOps tools free up time and maintain job fulfillment for your team, but when a notification is sent to the IT team, you know that it’s mission-critical.

5. Trust one system

The number of different tools DevOps teams are expected to manage is overwhelming. But, choosing the right AIOps platform can replace other tools without losing capabilities. If you want quality incident management, invest in a quality AIOps platform. With flexible integrations, adaptable APIs and collaborative, automated incident management all within the same AIOps tool, you can manage an outage from start to finish without leaving the platform.

Of course, there are many more use cases for AIOps platforms. The impact AIOps has on every aspect of a business, from customer experience to employee satisfaction and revenue, is beyond what anyone could have predicted when Gartner introduced the term five years ago. It is why AIOps is the lift that will allow organizations to keep up as the digital transformation continues and changes.

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AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...

An overwhelming majority of IT leaders (95%) believe the upcoming wave of AI-powered digital transformation is set to be the most impactful and intensive seen thus far, according to The Science of Productivity: AI, Adoption, And Employee Experience, a new report from Nexthink ...

Overall outage frequency and the general level of reported severity continue to decline, according to the Outage Analysis 2025 from Uptime Institute. However, cyber security incidents are on the rise and often have severe, lasting impacts ...