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What are the best practices for selecting and deploying AI-based system monitoring tools?

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System monitoring is a vital task for ensuring the performance, availability, and security of your IT infrastructure. However, traditional system monitoring tools may not be able to cope with the complexity, scale, and dynamism of modern environments. That's why many organizations are turning to AI-based system monitoring tools that can leverage machine learning, analytics, and automation to provide deeper insights, faster detection, and smarter actions.

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1 What is AI-based system monitoring?

AI-based system monitoring is the application of artificial intelligence (AI) techniques, such as machine learning, natural language processing, and computer vision, to system monitoring tasks, such as data collection, analysis, visualization, alerting, and remediation. AI-based system monitoring tools can learn from historical and real-time data, identify patterns and anomalies, generate meaningful and contextual alerts, and automate or recommend actions to resolve issues. AI-based system monitoring tools can also integrate with other tools and platforms, such as cloud services, DevOps tools, and chatbots, to enhance collaboration and communication.

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Sagar Navroop

? Architect | ??????????-?????????????? | Technologist
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Selecting and deploying AI-based system monitoring tools requires strategic considerations. Prioritize tools offering anomaly detection, predictive analytics, and automation. If using an AWS Ecosystem; leverage CloudWatch with its AI-powered features like Anomaly Detection and Contributor Insights. Integrate Lambda for automated responses. Implement telemetry through services like AWS X-Ray for distributed tracing. Establish clear KPIs aligned with business objectives. Regularly update models and algorithms to adapt to evolving system behaviors. Leverage Amazon Lookout for Metrics for advanced anomaly detection. Continuously refine configurations based on insights from CloudTrail, Config for for auditing and compliance needs.

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2 Why use AI-based system monitoring tools?

AI-based system monitoring tools can offer numerous advantages over traditional system monitoring tools, such as improved accuracy, scalability, and efficiency. These tools can reduce false positives and false negatives by applying advanced algorithms and models to filter out noise and focus on relevant signals. They can also handle large volumes and varieties of data from different sources and systems, and automate repetitive tasks. Furthermore, AI-based system monitoring tools can provide deeper insights into the root causes, impacts, and trends of system issues, as well as suggest possible solutions and improvements. Lastly, these tools can shorten the time to detect and resolve issues by alerting the right people at the right time, and executing or facilitating actions through integrations and workflows.

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Prashant Chaudhary

Engineering Manager | Paytm | Payment Gateway | Fintech | Ex - Honeywell | CDAC
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Let's consider an example to illustrate this point. Imagine a network monitoring scenario where a traditional tool sets a fixed threshold for network traffic. If the threshold is set too low, the tool might trigger alarms for minor fluctuations in traffic that don't necessarily indicate a problem. Conversely, if the threshold is set too high, it might overlook significant issues that fall within the normal range.

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3 How to select AI-based system monitoring tools?

When selecting the right AI-based system monitoring tool for your organization, you need to consider several factors such as your goals and requirements, environment and context, resources and capabilities, as well as preferences and expectations. Additionally, you should evaluate the various tools based on criteria such as data sources and types, data quality and reliability, data analysis and modeling, data visualization and presentation, data alerting and notification, and data remediation and optimization. For instance, the tool should be able to collect various data sources and types while providing accurate, complete, and consistent data. Furthermore, it should have advanced algorithms and models to analyze the data as well as generate clear dashboards, reports, and charts. It should also be able to send timely alerts and notifications that are relevant and actionable. Finally, it should be able to execute actions to resolve or prevent issues while optimizing system performance.

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Asif Shafi

Senior Automation Engineer at General Dynamics Mission Systems
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Please include types of platforms to be monitored. For example Syslog, SNMP, and performance counters for Microsoft platforms. AI could assist with pinpointing and rectifying a problem inside a complicated heterogeneous application systems.

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4 How to deploy AI-based system monitoring tools?

Deploying an AI-based system monitoring tool requires careful planning, testing, and evaluation to ensure a smooth and successful transition. To do this, you must define your objectives and metrics, prepare your data and infrastructure, test the tool in a controlled environment, train your team and stakeholders on how to use it, and deploy it gradually and iteratively. Before deploying the tool, you should ensure that your objectives and metrics align with your business goals and strategies. You should also backup your data and systems, create a contingency plan, monitor the tool's performance, accuracy, and reliability during testing, provide documentation and support for your team and stakeholders, evaluate the tool's impact in production, and make adjustments as needed.

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5 How to optimize your AI-based system monitoring tool?

Deploying an AI-based system monitoring tool is not a one-time event, but an ongoing process that requires continuous optimization and improvement. To ensure that your system monitoring objectives and metrics remain relevant and aligned, you should review them regularly and update them as necessary. Additionally, you should update your system monitoring data and infrastructure periodically to ensure compatibility and comprehensiveness. As technology advances, you should upgrade your AI-based system monitoring tool to take advantage of new capabilities and enhancements. To ensure that your system monitoring team and stakeholders are leveraging the tool's functions and benefits, you should provide them with training opportunities. Finally, soliciting feedback from your system monitoring team and stakeholders on how to improve the AI-based system monitoring tool is essential for optimization and improvement plans.

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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What are the best practices for selecting and deploying AI-based system monitoring tools?

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1 What is AI-based system monitoring?

2 Why use AI-based system monitoring tools?

3 How to select AI-based system monitoring tools?

4 How to deploy AI-based system monitoring tools?

5 How to optimize your AI-based system monitoring tool?

6 Here’s what else to consider

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