Editor's note
Enterprise IT deployments are increasingly complex -- as they span on-premises data centers and multiple cloud platforms -- and involve a mix of containers and microservices to support distributed application architectures.
IT ops teams must maintain visibility into these modern and dynamic architectures, and it's not enough to monitor key metrics in isolation. Instead, they need a holistic view of infrastructure resources, complete with dependency mapping, automated root cause analysis and predictive insights. These goals can be achieved with an AIOps monitoring strategy, but the technology is still maturing.
Use this guide to explore the top software, services and hardware performance-tracking challenges enterprises face today and how AIOps monitoring tools can address them.
1Challenges with modern IT monitoring tools
IT teams must carefully weigh the tradeoffs of different app and infrastructure monitoring tools, including those that maintain static vs. dynamic thresholds or those that take a reactive vs. proactive approach. Does the deployment require customized tools that can link infrastructure behavior to app performance and the end-user experience? Explore these challenges -- and more -- when it's time to select and implement IT monitoring tool sets.
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Monitoring thresholds determine IT performance alerts
An IT monitoring strategy depends on the applications and systems it governs. Static and dynamic thresholds each have benefits and drawbacks, but it's possible to find a balance. Read Now
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Combine reactive, proactive monitoring for optimal IT visibility
IT monitoring tools can be either proactive or reactive in nature. But, despite their differences in function, cost and required resources, these two types of tools both have a place in modern IT environments. Read Now
2Distributed monitoring for distributed apps
Distributed applications, including those that span container, cloud and microservices architectures, introduce novel monitoring requirements -- and hurdles -- for IT operations admins and engineers. Learn how to adapt monitoring strategies to suit these distributed environments and how to ensure monitoring tools don't disrupt the very systems and workloads they're intended to track.
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Distributed tracing gives microservices monitoring more clarity
When you have users interacting with multiple services with each action, finding the cause of a problem becomes a difficult hunt. Distributed tracing helps highlight the issues. Read Now
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Monitoring distributed systems means first, do no harm
SRE veterans who work with large, complex, latency-sensitive infrastructures say some monitoring tools can hurt the systems they're meant to help. Read Now
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Predictive IT analytics improves distributed application monitoring
Data analysis on app performance isn't an instantaneous process, but it's worth the wait given the time it will save IT admins in problem-solving in the future. Read Now
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Apply AI to container monitoring and management -- piece by piece
While the application of AI to container monitoring and management is possible, it first requires certain operations practices and carefully integrated tool sets. Read Now
3The basics of AIOps
Through an ability to automate root cause analysis, correlate events and predict future trends and issues, AIOps monitoring tools can quickly become a go-to in an IT admin's toolkit. But, before adoption, admins need to get a handle on the key characteristics of AIOps initiatives and tools. Understand the prominent AIOps use cases, where they fit within a CI/CD pipeline, and the technical and organizational challenges these tools introduce.
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Get started with AIOps tools
Instead of admins doing all the tedious work to resolve issues reactively, AIOps tools promise predictive analytics, health assessments and preventative action suggestions. Read Now
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AIOps tools supplement -- not supplant -- DevOps pipelines
While the line between DevOps and AIOps often seems blurred, the two disciplines aren't synonymous. Instead, they present some key differences in terms of required skill sets and tools. Read Now
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Artificial intelligence for IT operations pays off -- with time
IT professionals say AIOps holds great potential to optimize day-to-day operations tasks. First, though, teams must lay a foundation of data, consistency and trust. Read Now
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5 critical features that put the 'AI' in AIOps tools
Don't fall victim to AI-washing in the IT systems management market. Instead, know what to look for in a truly 'intelligent' operations platform -- starting with these 5 capabilities. Read Now
4AIOps monitoring strategies and tools
The application of AI to an IT monitoring strategy can take many forms. AI alongside log analysis, for example, enables teams to detect potential security vulnerabilities in near-real time and with fewer false alarms. In addition, AI within monitoring tools turns raw data into actionable steps to streamline network operations.
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AIOps monitoring arms IT staff with broader, deeper insights
Conventional monitoring gives ops teams critical visibility into the health of their IT systems, but with limited scope. Through an AIOps tool, they can significantly broaden their view. Read Now
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Log management systems benefit greatly from AI
Organizations with massive volumes of IT operational data need log management tools that can quickly and adeptly process it. AI embedded into tools might be the answer. Read Now
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Log analytics tools gain application performance support skills
Log analytics tools are boosting real-time capabilities to monitor application performance, and users are in the market for tools that best slice, dice and store log data. Read Now
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Machine learning network monitoring shows AIOps' promise
Machine learning network monitoring tools highlight the promise of artificial intelligence for IT operations, helping networking pros contextualize data and turn it into action. Read Now