You’ll also want to drill down into performance data across several dimensions to determine the root cause of problems and address bottlenecks. It’s important to continuously monitor system performance because it is often most affected during bursts of activity or periods of peak demand. The performance of the server you’re running on underlies and determines application performance. For web applications, slow page load times will lead users to abandon the page, some never to return. Performance impacts user experience and, therefore, impacts earnings. If you suspect an outage is due to changes made by a person or automated tool, this is the first place to look. You can find a record of all the changes made using the AWS API or console through the CloudTrail audit log. For example, a misconfigured security group could make your instance unreachable, or an auto-scaling script could accidentally remove too many instances and make your service unavailable. Sometimes, especially in large teams, people can make changes that can impact service availability. You can aggregate these logs to Amazon CloudWatch Logs by installing their agent, or you can use syslog to forward the logs to some other central location. You might see problems with boot up or kernel errors. You can find these errors listed inside your system log file, which is often in /var/log/syslog or /var/log/messages. System errors can also cause your instance to become unavailable or fail a status check. A good monitoring system will store metrics from the instance and can show you an increase in its resource usage until eventually hitting a ceiling and becoming unavailable. In this case, you’ll need to do a hard reboot, which risks losing the system state. If a server does not even have enough memory to support an incoming SSH connection, you will not be able to access it through a remote terminal. For example, web servers can become unresponsive when they lack sufficient CPU or memory to respond before timing out. Servers can become unavailable when the resources that they need to support clients are exhausted. The best practice is to set a status check alarm to notify you when a status check fails. Instance status checks monitor conditions that you need to fix yourself, including exhausted memory and corrupt file system. System status checks monitor conditions that require AWS’s involvement to fix, including loss of network connectivity and hardware issues. They come in two flavors: system status checks and instance status checks. A better health indicator will say if instances are responding to requests in an expected time and without errors.Īmazon performs status checks on all EC2 servers by default. ![]() Amazon has the ability to track if each instance is in the running state, as shown in the screenshot below. If you have several instances in your production cluster, you should be aware of whether each instance is healthy or not. Outages can cause degraded user experience and, potentially, lost revenue. You need to know quickly when there’s an outage in your production servers. Similar to our review of Amazon RDS top metrics, here are the top indicators you should monitor for insights into availability, performance, and cost. Despite EC2’s resilience and elasticity, there are still ongoing objectives that require close tracking of capacity, predictability, and interdependence with other services and infrastructure. However, monitoring all the metrics for a production compute cluster still remains a significant challenge. Companies like Stormpath and Tapjoy rely on EC2 to run their production systems in an efficient and reliable way. Amazon EC2 provides the foundation for many organizations’ cloud strategies, enabling teams to allocate compute resources rapidly and easily meet demand at both high and low points for truly web-scale performance. Amazon’s Elastic Compute Cloud (EC2) is one of the most popular products on Amazon Web Services (AWS), used by 84% of companies on AWS according to 2nd Watch’s AWS Scorecard.
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