Alexis Kestler
The rapid adoption of cloud computing has fundamentally changed how IT infrastructure is deployed and managed. According to Gartner, the worldwide public cloud services market is forecast to grow 17% in 2022 to total $591.8 billion. As more workloads move to the cloud, monitoring and observability have become critical.
In this comprehensive guide, we will provide an overview of monitoring approaches for cloud infrastructure and applications.
Why Cloud Monitoring Matters
Monitoring provides visibility into the health and performance of cloud environments. With proper monitoring, teams can:
- Quickly detect and troubleshoot issues before they cause downtime
- Optimize resource utilization to reduce costs
- Gain insights to improve architectures and deployments
- Correlate metrics for faster root cause analysis
- Set up alerts to be proactively notified of problems
Without monitoring, cloud users are "flying blind" and lack awareness of what is happening across dynamic, distributed cloud environments. As complexity increases, monitoring becomes even more crucial.
Cloud Infrastructure Monitoring
Monitoring for cloud infrastructure focuses on the foundational components like virtual machines, servers, databases, networking, storage, and more.
Key things to monitor for cloud infrastructure:
- Compute – CPU, memory, disk utilization for VMs and containers
- Network – Bandwidth, latency, errors, VPN tunnels
- Storage – Capacity, IOPS, latency, errors
- Databases – Connections, operations, cache hit rate
- Security – Unauthorized requests, DDoS attacks, suspicious activity
- Costs – Overall spending and resource consumption
Understanding typical baseline metrics allows teams to set thresholds and get alerts for abnormal activity. Dashboards provide at-a-glance views into the health of core infrastructure.
When issues arise, infrastructure monitoring data helps pinpoint where bottlenecks exist. For example, correlating VM CPU usage with database operations can identify when databases are overloaded.
Cloud Application Monitoring
While infrastructure monitoring focuses on components, application monitoring looks at the software workflows from the end user perspective. Key aspects include:
APM – Application performance monitoring tracks response times, latency, and errors for services and APIs. This helps identify performance bottlenecks.
Logging – Centralized logs allow tracing application workflows and debugging issues. Logs provide insights into application usage and errors.
Synthetic monitoring – Simulating user transactions from various geographic regions tests availability and performance of critical business workflows. Alerts notify teams of degradations.
User experience – Front-end performance metrics measure page load speeds, Javascript errors, and other user-centric KPIs that impact customer experience.
Taken together, these capabilities allow comprehensive monitoring of cloud-native applications and microservices environments. Teams gain visibility into all layers of complex, distributed architectures.
Cloud Monitoring Tools
Many tools exist for monitoring cloud environments. Here are some popular options:
CloudWatch
Amazon CloudWatch is the native monitoring tool for AWS. It collects metrics, logs, and events from AWS services. With CloudWatch, you can:
- Create custom dashboards and charts for AWS resources
- Set alarms and alerts based on thresholds
- Integrate with notification services like SNS
- Analyze log data in CloudWatch Logs
- Trace requests across resources with X-Ray
CloudWatch provides a convenient way to monitor AWS environments. The default metrics are useful but provide only basic visibility – more advanced capabilities require additional configuration.
Datadog
Datadog is a hosted monitoring and analytics platform that supports extensive cloud integrations. Key features:
- Over 250 pre-built integrations for cloud providers, databases, tools, etc.
- Infrastructure and application monitoring capabilities
- Customizable dashboards with anomaly detection
- Advanced analytics and forecasting
- Robust alerting options including on-call scheduling
- Distributed tracing and log management
Datadog provides strong out-of-the-box visibility and analysis across diverse environments in a user-friendly interface. More advanced features require higher service tiers.
Prometheus
Prometheus is a popular open source monitoring tool optimized for containers and microservices. Key aspects:
- Pull-based scraping to collect metrics from hosts and exporter targets
- Powerful multi-dimensional query language to analyze metrics
- Built-in alerting and notifications
- Highly scalable, flexible architecture
- Ecosystem of integrations for pulling metrics
- Dashboards via Grafana for visualization
Prometheus excels at infrastructure monitoring and provides extensive capabilities for free. It requires more manual configuration than commercial tools.
Grafana
While not a full monitoring platform, Grafana is the leading open source tool for building dashboards and visualizing monitoring data from various sources.
- Connect to Prometheus, InfluxDB, Graphite, cloud providers, databases, and other sources
- Build interactive dashboards with graphs, gauges, heat maps and more
- Wide range of charting options including histograms, bar charts, geomaps, etc.
- Clickable metrics and annotations provide insights into spikes
- Flexible templating and variables for dynamic dashboards
- Open source and available via hosted Grafana Cloud
Grafana enables creating polished, shareable dashboards to visualize monitoring data from diverse sources. It complements tools like Prometheus with world-class visualizations.
Best Practices for Cloud Monitoring
Here are a few key best practices:
Leverage service integrations – Use native monitoring capabilities for cloud services whenever possible. AWS CloudWatch, Azure Monitor, and Google Cloud Monitoring provide out-of-the-box visibility.
Monitor across all layers – Use a combination of tools to get infrastructure metrics, application performance data, logging, tracing, and synthetic tests.
Custom dashboards – Build custom dashboards tailored to your apps and services vs generic ones. Focus on business-critical workflows.
Set alerts wisely – Set critical, warning, and info alerts based on your SLAs. Use multiple notification channels.
Retain key metrics – Determine metrics retention periods based on storage limits and analytics needs.
Automate dashboarding – Use annotation and templating capabilities to build dashboards programmatically vs manual point-and-click.
Trends and forecasts – Leverage tools with advanced analytics for usage forecasts, anomaly detection, and correlation.
Wrapping Up
As cloud adoption accelerates, having visibility through robust monitoring and observability will be key to delivering great customer experiences. Organizations should invest in the right combination of tools and follow cloud monitoring best practices. With the proper foundations in place, devops teams can move faster with confidence.
