Amazon Web Services is a comprehensive, well-supported cloud service that is continuously growing and evolving. As cloud technology continues to boom, enterprises all across the globe are increasingly depending on cloud service providers to manage their workloads, data, and applications.
With digital transformation at its peak more so now, the organizations are increasingly transitioning their IT infrastructure to the cloud and AWS remains the most sought-after service with its diverse product portfolio.
Since Amazon Web Services (AWS) has emerged as the dominant player with a 30% market share, the need of the hour for organizations has shifted to prioritizing security which means investing in an AWS monitoring solution that complements existing AWS security tools, satisfies the requirements of the AWS shared responsibility model and enables best practices for AWS monitoring.
The need for AWS monitoring ensures security, high performance, and proper resource allocation.
Before delving deeper into the best practices for AWS monitoring, we should first be aware of the key metrics that need to be monitored. The below metrics provide a foundation for understanding the performance and availability of your deployed applications.
Some Important Metrics to Watch
- CPU Utilization: It measures the percentage of allocated compute units currently being used. If you see degraded application performance alongside continuously high levels of CPU usage then the CPU may be a resource bottleneck. Tracking CPU utilization across, as part of your AWS monitoring module, can also help you determine if your instances are over or undersized for your workload.
- Application StatusCheck: These checks provide visibility into your application health, and also help you determine whether the source of an issue lies with the instance itself or the underlying infrastructure that supports the instance.
- Latency:High latency can indicate issues with network connections, backend hosts, or web server dependencies that can have a negative impact on your application performance.
- Memory Utilization: Tracking memory utilization can help you determine if you’ve adequately scaled your IT infrastructure. If memory utilization is consistently high, you may need to update your task definitions to either increase or remove the hard limit so that your tasks continue to run.
- Disk Utilization: Tracking disk utilization can help you determine the disk capacity on a node’s storage volume, which can be set up differently depending on whether you are deploying pods. Like memory utilization, if there is low disk space on a node’s volume, Kubernetes will attempt to free up resources by evicting pods.
- Swap Usage: Swap Usage measures the amount of disk used to hold data that should be in memory. You should track this metric closely because high swap usage defeats the purpose of in-memory caching and can significantly degrade application performance.
Now that we are aware of the key metrics to be monitored, it is important to understand the best practices around AWS monitoring to employ better risk management and use its output to foresee and prevent potential problems.
Some of the Best Practices for AWS Monitoring
Automation is a game-changer, use it where ever possible:
For IT teams working to maintain their AWS environment and manage multitude of resources within a complex enterprise IT infrastructure, automated responses to alerts become important. Dynamic Automation in AWS monitoring will help organizations to:
- Improve cloud productivity via dynamic configuration of services, such as increasing memory or storage capacity.
- Avoid delays in issue resolution when the human response to an alert is hindered by access and permission restrictions.
- Focus on remediating more critical issues by having minor tasks automated.
Resolve problems before they become critical at the organizational level:
It has been often been observed that the engineering team tends to solve the problem via a temporary patch for the system and postponing the implementation for an appropriate fix.
This practice might have a serious downside since a minor unresolved issue may be a sign of an underlying IT infrastructure problem, eventually resulting in critical errors. It could also potentially create multiple layers of unmaintainable technical debt, leaving the team unable to quickly respond to issues, eventually leading to a negative impact on the end-customer experience.
That is where the dynamic AWS monitoring approach pitches in to provide timely proactive solutions.
Creating predefined policies to determine priority levels:
Predefined policies that regulates events and alerts created by AWS-based services will give full control of your deployed AWS environment applications. Keeping your IT management from being loaded with notifications and having almost 0 perpetual time to respond.
Having said that, priority levels will help you build a more sophisticated alerts processing system. With the right AWS monitoring solution in place, you can respond to these problems according to their priority level.
Establishing Efficient AWS Monitoring for your business needs
With Motadata NMS, get improved visibility with AWS monitoring product solution. You can monitor the performance of AWS hosted applications, get a drill down into each and every transaction, extract critical code-level details to resolve performance issues for your distributed AWS applications.
The solution helps to evaluate, monitor, and manage business-critical cloud-based (public and private) services, applications, and infrastructure on a constant basis. The proactive cloud monitoring module including AWS monitoring instance yields metrics such as response time, availability, and frequency of use, etc. to make sure that the cloud infrastructure performs at acceptable levels, all the time.
To know more about how Motadata’s cloud monitoring platform provides a complete picture of the overall health of your cloud environment including all the nodes, users, and transactions from one dashboard, request a demo.