Best Practices for Practitioners: AWS Network Monitoring
Overview Monitoring your AWS environment is crucial for maintaining optimal performance, ensuring security, and managing costs effectively. LM Envision provides a comprehensive, automated monitoring solution that seamlessly integrates with AWS, enabling real-time visibility into infrastructure health, performance metrics, and billing data. With features like automated discovery, customizable dashboards, and intelligent alerting, organizations can proactively address issues before they impact operations. By leveraging LogicMonitor’s AWS monitoring capabilities, businesses can enhance scalability, improve security, and optimize cloud expenditures with minimal manual intervention. Key Principles Comprehensive Visibility: Monitor all AWS services and resources to maintain a holistic view of your infrastructure. Automation: Utilize automated discovery and monitoring to reduce manual efforts and minimize errors. Cost Management: Implement billing monitoring to track and optimize AWS expenditures that can lead to cost-savings. Scalability: Ensure monitoring solutions can scale with your AWS environment's growth. Security: Adhere to best practices for role and policy management to maintain a secure monitoring setup. AWS Monitoring Features and Methods Setting Up AWS Monitoring Add AWS Account to LogicMonitor: Navigate to Resources > Add > Cloud and SaaS > Amazon Web Services. Provide necessary credentials and configurations. IAM Role and Policy Creation: Create an IAM policy and role in AWS with permissions required by LogicMonitor. This allows secure access to your AWS resources. Monitoring Organizational Units AWS Organizational Unit Monitoring: Configure LM Envision to monitor AWS accounts organized under Organizational Units (OUs). This setup provides consolidated monitoring across multiple accounts. Automating Role and Policy Creation Using AWS CloudFormation StackSets: Automate the creation of IAM roles and policies across multiple AWS accounts using StackSets, ensuring consistent and efficient deployment. Billing Management and Cost Optimization AWS Billing Monitoring Setup: Configure LogicMonitor to collect billing data from AWS, enabling tracking of costs and usage patterns. Monitor CloudWatch API Usage: Keep track of CloudWatch API requests to manage and optimize associated costs. Set Up Billing Alerts: Configure alerts for unexpected cost increases to enable prompt investigation and action. Analyze Cost Trends: Leverage LogicMonitor dashboards to analyze spending trends and identify inefficiencies. Implement Cost Optimization Strategies: Use AWS cost allocation tags, rightsizing recommendations, and Reserved Instances planning to reduce overall cloud costs. Best Practices for AWS Monitoring Efficient Data Collection Optimize Polling Intervals: Adjust polling intervals based on the criticality of resources to balance between data freshness and cost. Use Tag-Based Filtering: Leverage AWS tags to include or exclude resources from monitoring, focusing on critical components and reducing unnecessary data collection. Alert Configuration Set Appropriate Alert Thresholds: Define thresholds that align with your operational requirements to minimize false positives and alert fatigue. Implement Escalation Chains: Establish clear escalation paths to ensure timely response to critical alerts. Dashboard Customization Create Custom Dashboards: Develop dashboards tailored to your organization's needs, providing visibility into key metrics and facilitating proactive management. Utilize Pre-Built Dashboards: Leverage LogicMonitor's out-of-the-box dashboards for quick deployment and insights. Cost Management Monitor CloudWatch API Usage: Keep track of CloudWatch API requests to manage and optimize associated costs. Set Up Billing Alerts: Configure alerts for unexpected cost increases to enable prompt investigation and action. Implementation Checklist ✅ Navigate to the LM Envision portal and add your AWS account using secure credentials. ✅ Configure necessary IAM roles and policies to provide LogicMonitor with the required permissions for monitoring AWS resources. ✅ Ensure auto-discovery is enabled to detect all AWS services and instances for continuous monitoring. ✅ If using AWS Organizations, set up monitoring to capture insights across multiple AWS accounts. ✅ Integrate AWS billing data into LogicMonitor to track spending patterns, identify anomalies, and optimize costs. ✅ Adjust polling intervals, use tag-based filtering, and focus on critical resources to balance cost and performance. ✅ Configure appropriate alert thresholds and define escalation paths for critical issues. ✅ Develop real-time dashboards to visualize performance, costs, and potential issues in AWS infrastructure. ✅ Regularly review and manage CloudWatch API requests to control monitoring-related costs. ✅ Review AWS recommendations for rightsizing instances, using Reserved Instances, and applying cost-saving measures. Conclusion Implementing AWS monitoring provides organizations with a powerful, automated approach to managing cloud performance, security, and costs. By following best practices such as optimizing data collection, configuring effective alerts, and leveraging cost monitoring features, businesses can maintain a well-managed, highly efficient AWS environment. With LM Envision’s advanced analytics and automation, teams can shift from reactive troubleshooting to proactive cloud optimization, ensuring better resource utilization and long-term cost savings. Embracing a structured monitoring strategy enables businesses to scale confidently while maintaining control over their cloud infrastructure. Additional Resources Introduction to Cloud Monitoring AWS Monitoring Setup AWS Organizational Unit Monitoring Setup Using StackSets to Automate Role and Policy Creation AWS Billing Monitoring Setup CloudWatch Costs Associated with Monitoring
Cloudwatch custom datasource metric path including wildvalue
Hi, I have created a cloudwatch custom datasource to pull custom metrics from cloudwatch by following this document - https://www.logicmonitor.com/support/lm-cloud/getting-started-lm-cloud/5-adding-monitoring-custom-aws-cloudwatch-metrics We got a scenario where we are pulling custom metric for a AMQ broker in cloudwatch. So we created a datasource for that, While creating datapoints (where metric path is specified) we like to include wildvalue in that. metric path we looking to create - pulling CPU utilization metric for different brokers. Where ##wildvalue## is placed with Broker Name. AWS/AmazonMQ>Broker:##wildvalue##-1>CpuUtilization>Average AWS/AmazonMQ>Broker:##wildvalue##-2>CpuUtilization>Average When wildvalue is replaced with Broker Name - “prod-1”.. Metric path should look like below. AWS/AmazonMQ>Broker:prod-1-1>CpuUtilization>Average AWS/AmazonMQ>Broker:prod-1-2>CpuUtilization>Average By this way we can reduce number of datapoints created a datasource, also we can use that datasource for multiple devices. So could someone please provide suggestion on this. Thanks.,Linux details for EC2 hosts
Linux details for EC2 hosts such as Kernel version, etc are not displayed, as the Linux_SSH datasource specifically excludes these. I can understand that for some hardware specific properties/info, but it would be useful to have the patch release, etc. of the kernel regardless of being a VM/EC2 in AWS. Is there another datasource or property source I should be using for this info?AWS Gateway Load Balancer monitoring functionality must be added.
Hi LM I had a request from one of our clients to set up monitoring and alerting for the gateway loadbalancers, but I couldn't find any documentation on that, and according to LM support, the functionality isn't currently available. I'd like to request you to please integrate this functionality as soon as you can. Please refer the aws GWLB's documentation below. https://aws.amazon.com/elasticloadbalancing/gateway-load-balancer/LogicMonitor has expanded its relationship with AWS for unified monitoring and cloud coverage.
LogicMonitor has expanded our alliance with AWS, this lets IT and CloudOps teams confidently migrate with reduced risk, and oversee their post-migration estate on a unified platform. In addition to our partnership upgrade, our AWS monitoring capabilities have been significantly upgraded as well. Here are some of the highlights we announced at the AWS New York Summit. Fast and easy to get started Control cloud costs Migrate confidently Scaling and adapting to your AWS deployment Read the full article here.Monitoring Ec2 instances
Hi All, I have been going through the documentation and it suggests that when we are setting up monitoring for ec2 with autoscaling we should select netscan frequency of 10 minutes. This is the minimum time we can configure and new device may take upto 15 minutes to be monitored. My question is is there a way if a new instance is launched we can bring that into monitoring less than 10 or 5 minutes.How many collectors do you have?
Hello, Our Logic Monitor environment is overloaded. What is the best practices to expand? We have currenty 64 collectors “All the same size” and our internal LM Support for the collectors is requesting 52 new collectors!! They are taking the approach to create collectors all the same size for 10,000 instances. I was thinking about other routes 1. bigger collectors if possible for 30,000 instances each may be... 2. minimize the number of instances by cleaning up what is not needed but I am not sure anybody will know We have an AZURE Collector VZPOHIALGCMON01 with 82,305 instances !!! I reviewed this Collector Capacity | LogicMonitor and apparenlty we could expand another way than the one selected !!! Any thoughts on this? Thanks, Dom
