Best Practices for Server Monitoring
Based upon the cloud server and monitoring tool, the server monitoring technique differs. As an organization grows and the number of deployments and modules increases, it needs to set up a server monitoring solution that collects data from the various cloud-based endpoints. There are five steps involved in the practice of monitoring servers.
1. Agentless Vs. Agent-based monitoring: Before any monitoring solution starts monitoring the system and evaluating the metrics, it needs the basic configurations to set up. One of the initial steps of configuring the system is bifurcating the devices based on agents: Agent-based devices and agent-less devices.
– Agentless Monitoring: Agentless monitoring only needs to deploy the software on the remote data collector. The data collector communicates with the target systems at various ports. The collector may need to be installed with admin accesses to access the remote systems. Agentless monitoring comes with its own limitations as not all applications and operating systems support it.
– Agent-based Monitoring: Agent-based monitoring requires an agent to be deployed on each server. Agent-based monitoring is much more secure compare to agentless monitoring. The agent handles all the security aspects and controls all the communications. As it is configured to the application/operating system, it does not need any external firewall rules to be deployed. The agent-based monitoring comes with broader and deeper monitoring solutions.
2. Prioritize the metrics: It is important to identify the metrics that need to be monitored. One should prioritize the metrics that help track the servers and provide important insights into the server’s behavior. The choice of metrics depends on the kind of infrastructure the organization has and the kind of services the organization uses. For example, an application server will need metrics like server availability and response time, while a monitoring tool for a web server will measure the capacity and speed.
3. Set the threshold value for the metrics: Once the metrics are prioritized and monitored, the next step should be to set the threshold values for the same. A baseline value and a specific range should be set according to the type of the metrics. Based on these baseline values, the upcoming server performance can be monitored.
4. Data Collection and Analysis: The server monitoring tool must be configured to seamlessly collect the data from the cloud endpoints. The server monitoring tool monitors the activities taking place across the server with the help of log files. Log files have the data about the failed operations and user activities. Furthermore, metrics such as network connectivity and CPU performance can be monitored with the help of log files. In addition, log files also help secure the server as they contain information about the security events.
5. Alert System: Since the server is being monitored and metrics are being measured, the next step should be setting up an alert when a specific threshold meets. An alert system that sends notifications to the admin team whenever any metrics reach threshold value or in case of any security breach.
6. Setting up Response: Since the admin team is notified about the failure, it is time to take action against it. The monitoring solution should help do root cause analysis from the available data and resolve the issues. Before that, a policy needs to be configured. A policy that sets the procedure for responding to the alerts. Investigate the security alerts, solutions for the operational failures, types of alerts, response actions, and priority. These can be part of the policy while configuring the go-to action procedure.
With these practices, IT organizations can monitor the server and ensure smooth transactions across the server, user experience, and secure the server from the data breach. AIOps, provided by Motadata, being one such intelligent monitoring tool, offers monitoring solutions with cutting-edge technologies like Artificial Intelligence and Machine Learning. AIOps forecast the potential errors, check on the server’s health, notify the admin team, and help resolve the same before they cause any potential damage. The blend of AI and ML makes it one smart monitoring tool that offers one unified dashboard with smart widgets and real-time data of the measured metrics. Overall, it is essential to monitor the server when your entire business and the transactions rely on the server’s health.