The Key Differences Between Pairs of Similar AWS Services (Part 1)
In the ever-evolving landscape of cloud computing, Amazon Web Services (AWS) offers a comprehensive suite of services designed to meet a wide range of business needs. However, navigating the AWS ecosystem can be challenging, particularly when confronted with services that seem to share similarities that blur the lines between their use cases. In this article, we delve into the nuanced differences that set apart pairs of seemingly similar AWS services. By gaining a deeper understanding of these distinctions, users can make informed decisions, optimize their cloud infrastructure to suit their specific requirements and ultimately harness the full potential of AWS at optimal cost.
Goals
For this part of the series, we will clarify the key differences between:
- EC2 Instance Store and Elastic Block Store
- CloudTrail and CloudWatch
In subsequent parts, we will consider the key differences between:
- Amazon ElastiCache and CloudFront
- AWS Trusted Advisor and AWS Personal Health Dashboard
- Amazon Elastic Bean Stalk and Amazon CloudFormation
- Amazon’s security services
EC2 Instance Store and Elastic Block Store (EBS)
In my cloud journey, I became quite familiar with the AWS Elastic Block Store before I eventually learned about the EC2 Instance Store. AWS Elastic Block Store (EBS) and EC2 Instance Store are storage options available for Amazon Elastic Compute Cloud (EC2) instances, but they have several key differences:
Persistence
EBS volumes are network-attached virtual hard disks that provide durable, block-level storage. In contrast, EC2 Instance Store volumes, also known as temporary storage, are directly attached to the physical host of the EC2 Instance and as such, data stored here are non-persistent through instance stops, termination, or hardware failure.
Data on EBS volumes persists even if the associated EC2 Instance is stopped or terminated. However, this must be enabled by setting the DeleteOnTermination attribute of the EC2 Instance’s configuration to False (True by default).
To prevent unintentional data loss, it is best practice to frequently take snapshots of your EBS volumes — a task you can automate with AWS Backup. EC2 Instance Store can neither create snapshots by itself nor work with AWS Backup.
Also, several EBS volumes can be attached to an Instance, and they can be removed from one Instance and reattached to another. Multi-Attach allows you to mount an EBS volume on multiple Instances concurrently, but this feature is subject to the volume and Instance type used.
Performance
EBS volumes offer consistent and predictable performance characteristics. You can choose between different volume types optimized for specific workloads, such as General Purpose SSD (gp2 and gp3), Provisioned IOPS SSD (io1 and io2), Throughput Optimized HDD (st1), Cold HDD (sc1), and Magnetic (standard). These storage options vary in performance and price, allowing you to optimize for your application needs. EC2 Instance Store volumes typically provide high, but variable performance which depends on the instance type and the specific instance store volume attached.
Availability and Redundancy
EBS volumes are replicated in multiple devices within an Availability Zone to ensure redundancy beyond the failure of a single device, and can also be snapshotted for backup and disaster recovery purposes. It is important to note that they must be in the same Availability Zone as the EC2 Instance(s) they are attached to. In contrast, EC2 Instance Store volumes are limited to a single device in an Availability Zone with no built-in mechanism for redundancy or snapshots.
EC2 Instance Store volumes are located on the same physical server hosting the respective EC2 instance.
Size and Scalability
EBS volumes can be created with sizes ranging from a few gigabytes to multiple terabytes. You can resize EBS volumes as needed (but not automatically by default), making them suitable for a wide range of workloads. Though EC2 Instance Store volume size and type are fixed and depend on the selected instance type, they cannot be resized.
Click the link below to learn how to use AWS Step Functions and AWS Systems Manager to automate resizing an Amazon EBS volume.
Use Cases
In terms of use cases, Amazon EBS is ideal for applications requiring data persistence, encryption, durability, and consistent performance. It is commonly used for databases, root volumes, and shared storage.
EC2 Instance Store is well-suited for stateless applications, temporary data, or caching where data loss is tolerable. It can provide high-speed storage for temporary processing tasks.
In summary
The choice between Amazon EBS and Amazon EC2 Instance Store depends on your specific application requirements. If you need durable, scalable, and highly available storage with consistent performance, EBS is the better option. On the other hand, if you have stateless, temporary workloads with high-performance demands, an EC2 instance store may be more suitable, but be prepared for potential data loss in case of instance failures.
CloudTrail and CloudWatch
Amazon CloudTrail and Amazon CloudWatch are two AWS services that appear similar. Both monitor, maintain event history and store logs in S3 buckets making it challenging to distinguish them. So let us point out their key differences:
Primary Purposes
Amazon CloudTrail is primarily used to track user activity and API usage. It is focused on providing audit and compliance logging. It keeps a record of all the API calls made on your AWS account, including the details of who (user or account) made the call, the actions taken, and when they were executed. This service is essential for security and compliance auditing. Amazon CloudWatch, on the other hand, is designed to monitor the performance and health of AWS resources and applications. It collects and visualizes metrics, creates alarms, and enables automated actions based on predefined thresholds.
Use Cases
The common use cases of Amazon CloudTrail include security monitoring, compliance auditing, and investigating security incidents. It helps in tracking changes to AWS resources. CloudWatch revolves around monitoring the health and operational performance of AWS resources and applications, resource optimization, alerting or auto-scaling based on set thresholds.
Data Type
CloudTrail logs are in the form of JSON files that provide details of every API call on AWS resources, making them suitable for forensic analysis. These logs allow you to trace every action taken on your AWS resources and therefore are used for security analysis and compliance reporting. Amazon CloudWatch, in contrast, focuses on real-time monitoring and metric analysis. It captures numerical metrics like CPU utilization, disk space usage, and network traffic, along with application logs. CloudWatch aggregates metrics at set intervals for AWS resources to provide a comprehensive view of their health and performance over time.
Alerting and Automation
CloudTrail records activities, but does not offer built-in alerting or automated responses (except when integrated with CloudWatch). It is used primarily for retrospective analysis and auditing. CloudWatch, on the other hand, allows you to set up alarms based on metric thresholds. When an alarm is triggered, you can configure actions like sending notifications, scaling resources, or running AWS Lambda functions, enabling real-time alerting and automation.
In summary
While CloudTrail and CloudWatch share similarities, they play distinct roles in the AWS ecosystem. CloudTrail is dedicated to tracking and logging AWS API actions, primarily for security and compliance needs. In contrast, CloudWatch is predominantly employed for real-time monitoring, alerting, and enhancing the performance of AWS resources and applications. Depending on your requirements, you might utilize both services concurrently to achieve a thorough understanding of your AWS environment.
Conclusion
In this particular part of the series, we clarified the key disparities between EC2 Instance Store and Elastic Block Store, as well as between CloudTrail and CloudWatch. By shedding light on these differences, we aim to empower AWS users to make more informed choices that align with their specific requirements and objectives, ensuring efficient utilization of AWS services.
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