Amazon Web Services (AWS) is the most popular cloud infrastructure vendor. In the fourth quarter of 2022, its market share sat at 32%, with Microsoft Azure following at a distant 23%. But despite its popularity, AWS is complex. It's easy to overlook AWS mistakes that can have significant repercussions, from security breaches to downtime to increased costs.
In this article, we'll explore 5 of the most common AWS mistakes that you should be aware of when you set up, maintain, and optimize any AWS service.
AWS security groups are virtual firewalls that have defined rules to control the inbound and outbound traffic of your instances. When properly configured, a security group provides granular control over who can access your instances.
On the flip side, misconfiguring a security group exposes those instances to unauthorized access and other risks. Common ways to misconfigure a security group include:
- Overly permissive IP ranges, such as
0.0.0.0/0 (which includes all possible IP addresses). If you don't restrict who can access your resources, anyone who's somewhat technically savvy on the internet can access them.
- Unnecessary ports. The more ports you open, the bigger the attack surface for bad actors. Make sure you open only the required ports for your apps and services, and limit access to those ports through only the necessary IP ranges.
- Outdated security groups. As your infrastructure changes over time, you have to keep your security groups up to date. To maintain a secure environment, update the security group rules when you add new services, apps, or IP addresses.
2. Improper IAM Management
Identity and Access Management (IAM) in AWS should follow the principle of least privilege, which gives someone access with only the minimum necessary resources and authorizations for them to perform their function properly (sometimes this means giving them access only temporarily).
Other AWS IAM mistakes include improperly handling access keys to programmatically access AWS resources, not regularly rotating those keys, not having multi-factor authentication enabled for sensitive accounts, having unused or unnecessary IAM users or roles, and not using Organizations and Service Control Policies (SCPs) across multiple AWS accounts.
3. No Auto Scaling
AWS Auto Scaling is a helpful feature that automatically adjusts capacity for consistent performance at the lowest possible cost. It's particularly helpful for apps with variable or unpredictable workloads. Use auto scaling to avoid using either not enough or too many resources. The former leads to poor performance, the latter to unnecessary costs.
Auto scaling is available at no additional charge. You just need to figure out which resources would benefit from it on the basis of their usage patterns and workload variability. Then you define a scaling policy, decide which metrics you want to watch using CloudWatch, and configure the templates for instance launch and configuration.
4. Poor Data Backup and Recovery
It's not because your data is in the cloud that you can't lose it. Human error, malicious activity, and application bugs are all risks that can lead to data loss. It's crucial to have a robust data backup and recovery process in place.
When you've defined your backup frequency and retention policies, use AWS services like AWS Backup, Amazon S3 Backups, and Amazon Glacier to automate backups and store them in a cost-effective way. Every once in a while, test your recovery processes too, to make sure they work.
Another important tip is to enable cross-region replication, so your backups are replicated across AWS regions and you are protected against regional outages or disasters. Encrypt these backups with the AWS Key Management Service (KMS) to stay compliant with regulatory requirements.
5. Insufficient Monitoring and Logging
Although much of AWS runs automatically, you still want to keep an eye on what's going on. Otherwise, you may miss performance issues, security breaches, and other operational problems. AWS has various monitoring services like Amazon CloudWatch, AWS CloudTrail, and AWS Config. These tools track and analyze different aspects of your cloud infrastructure.
Best practices for AWS monitoring and logging includes: Collecting a wide range of metrics so you have a comprehensive view of your infrastructure and applications, storing logs for as long as needed for analysis and compliance purposes, using log analysis tools to identify patterns and uncover problems, and setting up alarms or notifications to quickly identify potential issues.
