Cloud Monitoring for Performance and Security

Cloud Monitoring Through Logs and Alerts

Log Monitoring and Analysis

Logging has been an essential part of resolving application and infrastructure problems. It generates a detailed list of events occurring in your application and can help trace the cause of a problem providing the context in which it happened. The more relevant data you log, the better you can troubleshoot when a problem arises.

As log files grow in size, it can become difficult to search through all of them. Commercial tools such as Splunk or open-source options like the ELK stack (Elasticsearch, Logstash, and Kibana) can be used to collect, search, and visualize log data. Analyzing log data in the light of information from external monitoring adds to its value and significance.

Alert Management

Reporting problems is the core competency of a monitoring solution. By automating alerts, your team can quickly respond to such reported events.

However, not all alerts carry the same degree of urgency. Low severity alerts need not interrupt anyone’s work but can be recorded in the monitoring system for reference or investigation at a later time. Events such as a delay in application response time need immediate attention and can be configured to trigger high severity alerts that receive special treatment. An important step in cloud monitoring, therefore, is setting up alerting thresholds correctly.

Monitoring in DevOps Lifecycle

Continuous monitoring is as much an integral part of DevOps implementation as continuous integration and delivery. Monitoring both pre-production and production environments enable teams to build faster, test earlier, and release frequently while improving quality and reducing costs.

Proactive monitoring, also known as synthetic monitoring, involves stimulating user interaction with applications, APIs, or web services to study what a real user would face in reality. Monitors can be run from different geographic locations, browsers, or devices to collect performance feedback.

Real-time user monitoring (RUM), on the other hand, captures the actual transaction between the user and the application. It is a passive monitoring technique to observe systems in the background, tracking responsiveness, functionality, and availability.

Agile teams wanting to shift their focus to prevention rather than detection, use synthetic monitoring tools to identify and fix performance deviations before real users experience them. Log and event management in the CI/CD pipeline will enable your team to monitor application behavior before releasing it to production. Clubbing data from synthetic monitoring with RUM data provides full visibility into the user experience.