Monitoring Performance Efficiency
After implementing an architecture, monitor its performance so that any issues are remediated before customers are aware of them. Use monitoring metrics to raise alarms when thresholds are breached. The alarms potentially also trigger automated action to work around any badly performing components.
Active and Passive
Monitoring solutions fall into two types: active monitoring and passive monitoring. Active and passive monitoring complement each other to give a full view of how a workload is performing.
Active monitoring simulates user activity in scripted user journeys across critical paths in the product. Active monitoring needs to be continuously performed in order to test the performance and availability of a workload. Active monitoring complements passive monitoring by being continuous, lightweight, and predictable. When it runs across all environments (especially pre-production environments), it is used to identify problems or performance issues before they affect end users.
Passive monitoring is commonly used with web-based workloads. Passive monitoring collects performance metrics from the browser, (Non-web-based workloads also use a similar approach). Collect metrics across all users (or a subset of users), geographies, browsers, and device types, then use passive monitoring to understand the following issues:
User experience performance
Passive monitoring provides metrics on what the users are experiencing, which gives a continuous view into how production is working, as well as a view into the impact of changes over time.
Geographic performance variability
If a workload has a global footprint and users access the application from all around the world, using passive monitoring enables users to spot a performance problem affecting other users in a specific geography.
The impact of API use
Modern workloads use internal API’s and third-party API’s. Passive monitoring provides visibility into the use of API’s so performance bottlenecks originating from third-party API providers are identified.
Monitoring of cloud environments consists of five distinct phases:
- Generation – scope of monitoring, metrics, and thresholds.
- Aggregation – creating a complete view from multiple sources.
- Real-time processing and alarming – recognizing and responding.
- Storage – data management and retention policies.
- Analytics – dashboards, reporting, and insights.
Devek is used to set up systems to collect and track metrics, collect and monitor log files, and set alarms. Monitor cloud compute instances, database instances, custom metrics generated by deployed applications and services, and any log files these applications generate. Use dashboards to gain system-wide visibility into resource utilization, application performance, and operational health. Use these insights to react quickly and keep applications running smoothly. Dashboards enable users to create reusable graphs of cloud resources and custom metrics to monitor operational status and identify issues at a glance.
Ensuring few false positives is key to an effective monitoring solution. Automated triggers avoid human error and reduce the time it takes to fix problems. Plan for game days, where simulations are conducted in the production environment, to test the alarm solution and ensure that it correctly recognizes issues.
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