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5 AWS Monitoring Best Practices You Must Know

May 6, 2021

Topics: Cloud Insights AWSElementary

What are AWS Monitoring Best Practices?

AWS monitoring best practices were developed to help you ensure that your resources and applications are operating efficiently, your costs are optimized, and your data remains secure. These practices incorporate a range of tools and techniques to grant you real-time, continuous visibility into your operations.

AWS monitoring best practices include:

    1. Use Automation Where Possible
    2. Create Policies to Define Priority Levels
    3. Resolve Problems Early On
    4. Use the Cloud to Your Advantage
    5. Use NetApp Cloud Insights

AWS Monitoring Strategy

Effective AWS monitoring strategies rely on centralized and actionable insights. These require aggregation of data from across your resources and system components and real-time analytics. Once collected, strategies need to be able to direct appropriate action to resolve issues. Ideally, they can also provide insights for optimization.

In AWS, there are multiple ways to aggregate your monitoring data but if you want to use native tools, CloudWatch is one of your central sources for information. This service can ingest metrics and log data from your various sources in AWS and on-premises.

CloudWatch includes features for event monitoring, log and data analysis, alerting, automated response, and data visualization. Additionally, an anomaly detection feature was recently added to the service that uses machine learning analysis of historical data to determine an expected baseline for performance. If your data deviates from this baseline, you’re alerted.

You can access data directly from CloudWatch, or you can ingest it with third-party tools for more in-depth analysis and more elaborate automation. You can also combine CloudWatch with other AWS services, such as Lambda or Simple Notification Service (SNS). You can then use these integrations respectively to perform automated responses or remotely alert teams.

5 AWS Monitoring Best Practices

While you should also investigate best practices for the specific services you’re using, the following practices are a good place to start. These general best practices can help you develop an effective monitoring strategy and learn how to best leverage your system data.

Use Automation Where Possible

The scale and distribution of cloud resources makes it difficult or impossible to perform monitoring manually. Instead, effective monitoring relies on automation to surface relevant issues and threats which teams can then address. You can also use automation to handle routine and low-level issues that can be reliably managed with scripted responses.

For example, automatically throttling traffic for users who are sending too many requests too quickly. You can also use automation to distribute higher-level knowledge across your team. For example, a security engineer can create an automation runbook (or script) that walks lower-level responders through appropriate measures.

Related content: read our guide to aws monitoring tools (coming soon)

Create Policies to Define Priority Levels

As part of your automation and your distribution of human resources, you need to prioritize issues or types of issues. For example, if resources hosting mission-critical applications fail it is more important than if an email server is slower than expected. Prioritization helps you ensure that higher impact events or indicators are reported to your IT teams before lower impact ones.

This prioritization can help you more efficiently assign resources to respond to issues. It can also help you reduce or avoid system damage, data loss, or loss of revenue. With prioritization, you can help ensure that your response teams are not overwhelmed with alerts, increasing their ability to respond effectively.

Resolve Problems Early On

The sooner you can resolve issues discovered in your systems the better off you are. This doesn’t mean that every issue is urgent, but it does mean you shouldn’t ignore issues. Small decreases in performance, delayed patch updates, or glitchy applications can all compound into more serious issues if left unresolved. These small issues can also be indicators for larger issues, such as resource misconfigurations or poor quality control.

If possible, you should also consider taking this a step further and proactively searching for issues. While some defects may be harmless, others can create significant vulnerabilities in your systems. It is better that you find these issues before your users or cyberattackers do.

Use the Cloud to Your Advantage

The cloud provides a highly flexible environment that allows a lot of experimentation with resource configurations and deployments. Because of this, gaining an optimal balance between performance and security in the cloud can be challenging. However, you can use this flexibility to your advantage.

If you are not getting the performance you expect, you can try creating test deployments with your target applications or workloads. Once staged, you can use monitoring to track how configuration or resource changes affect your performance without risking your production services. Additionally, because the cloud is scalable, you can start small with these tests while also evaluating how well configurations perform with maximum traffic, CPU use, or memory use.

Use NetApp Cloud Insights

To monitor workloads on the cloud, you need a robust monitoring tool. NetApp Cloud Insights is an infrastructure monitoring tool that gives you visibility into your complete AWS infrastructure. With Cloud Insights, you can monitor, troubleshoot and optimize all your resources - including other public clouds and your on-premise data centers.

Cloud Insights helps you find problems fast before they impact your business. Optimize usage so you can defer spend, do more with your limited budgets, detect ransomware attacks before it’s too late and easily report on data access for security compliance auditing.

In particular, NetApp Cloud Insights lets you automatically build topologies, correlate metrics, detect greedy or degraded resources, and alert on anomalous user behavior. This means better visibility and more effective monitoring efforts.

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