AWS Knowledge
Monitoring and Logging for Amazon EKS Clusters
Piyush Kalra
Oct 11, 2024
The cloud is just not an easy environment to deal with, more so when it comes to dealing with Amazon EKS clusters. Unless you are a DevOps engineer, cloud architect or cloud engineer, there is one thing that you need to know - these clusters must be monitored to ensure that they are working as intended and are safe. Wherever there is a cloud infrastructure supporting the applications, their monitoring and logging is critical for maintaining application availability at about 90% and security at over 95%. They allow you to see the current state of matters, help you diagnose problems, and enhance security by detecting outliers.
When it comes to Amazon EKS cluster, these tasks become even more important because of their level of abstraction and size. So in this guide, several aspects of EKS will be discussed, the importance of monitoring it and what tools, tips and tricks, to use in order to maximize the benefits that the cloud has to offer.
What is Amazon EKS?
(Image Source: AWS Cloud)
Amazon EKS is a managed service that makes it easy to run Kubernetes applications without the need to install and operate your control plane or nodes. It handles the heavy lifting and allows developers to concentrate on application building and security.
Key Components of EKS Clusters
For proper logging and monitoring of Amazon EKS clusters, having knowledge of the main components of EKS is important. Let’s start easy and break it down:
Control Plane: The Control Plane is the brain of your EKS Cluster, controls everything and has the following as its main features:
API Server: This is the cluster’s management interface and API requests.
High Availability: Automatically scales up to multiple AWS Availability Zones for fault tolerance and thereby increasing uptime.
Managed Service: The management of scaling, patching, and maintenance is done by AWS enabling developers to concentrate on deploying applications.
Worker Nodes: These are EC2 instances that run your Kubernetes pods, with major features including:
Scalability: Able to increase or reduce node size as required in order to manage and/or minimize resource use and costs.
Container logs Management: Run the tools required by Kubernetes for proper application handling.
Networking Components: EKS clusters can't work without network, and correct network configuration allows internal cluster communication with a high level of security:
Virtual Private Cloud (VPC): Provides network security and isolation to your EKS cluster.
Load Balancing: A Network Load Balancer is applied to instruct how to direct the incoming traffic.
Security Groups: These work as firewalls and restrict access to worker nodes thereby controlling the amount of traffic coming to these nodes.The Critical Importance of Monitoring in EKS
Why Monitor EKS Clusters?
Keeping an eye on your EKS clusters is crucial for optimizing performance monitoring, troubleshooting issues, and bolstering your system's security posture.
Performance Optimization: The overall system performance should be constantly monitored as this can help in the proper functioning of the applications, minimizing the time in which transactions are accomplished, and effectively managing high volumes of transactions. For instance, Prometheus can be used to monitor resource consumption and spectrum level limits.
Troubleshooting Capabilities: This is offered to those who make program monitoring activities because a problem can be subjected to a problem domain where the relevant organization has been presented with data in order to assess and fix the situation as soon as possible, thus reducing the overall service latency. For instance, Visualizing system metrics using Grafana dashboards can help troubleshoot system issues quickly and also reduce system downtime.
Improving security and safety: Finding potentially dangerous activity and taking action to secure your system is aided by monitoring. Suspicious activity must be restricted within acceptable parameters as soon as practical. Look at, say, AWS CloudTrail which allows you to follow API requests made.
Key Metrics to Monitor
These particular integrations with EKS clusters have to be continuously monitored since they illustrate the functionality and overall condition of the resource.
Cluster Health Metrics
CPU Usage: Shows how much processing power is getting consumed on your nodes.
Memory Usage: Plays a role in ensuring that memory is efficiently used and also operates to mitigate the chances of out of memory errors.
Application Performance Metrics
Response Time: The response time takes a closer look at the time an application is expected to respond after communications have been initiated, which helps assess if the application has delays at certain points or not.
Error Rates: Measures the impact of errors for assessing the strategy and pinpointing areas that need attention.
Networking Metrics
Latency: Measures time it takes for a data request to be accomplished and how long it will take more to meet the demand.
Throughput: Monitors the amount of data being manipulated, therefore establishing the level of activity in the system.
Effective Logging Strategies for EKS Clusters
Types of Logs in EKS
Logging in EKS includes recording different logs which offer a useful insight to the overall use of your cluster.
Control Plane Logs: logs of API calls and other control plane activity that gives more details on the operation and the security events in the cluster.
Application Logs: Created by the applications running inside your pods, these logs assist in diagnosing the problems associated with the applications performance.
Node Logs: Node logs are related to the operating system and the Kubernetes activities of the worker nodes which is used in the diagnosis of the host related problems.
Best Practices for Logging in EKS
These are the practices that should be implemented to strengthen the effectiveness of the logging procedure.
Choosing the Right Logging Tools
Use logging tools such as Amazon CloudWatch logs insights and Fluent Bit to record and retrieve your logs without destroying them. Make sure that the systems in use cannot impede your growth and performance capabilities.
Log Retention Policies
The policies determining the duration of the log files are necessary to assist in storing the critical but needed information to analyze the log size.
Data and Analysis Log Structure
Place log files in specific formats that enable one to look for certain areas or sections without any unnecessary delays. This makes the whole process of looking for log data and identifying performance holes faster and less inaccurate.
Tools for Monitoring and Logging in EKS
AWS Native Tools
AWS offers a great number of native instruments for round-the-clock monitoring and logging of EKS clusters.
Amazon CloudWatch Container Insights
(Image Source: Amazon CloudWatch)
Amazon CloudWatch Container Insights is a fully managed service that provides a solution for the collection, aggregation, and summarization of available metrics and logs of the customer’s containers. Through Container Insights, an Amazon EKS customer is able to monitor, troubleshoot, and set cloudwatch alarms on their Amazon EKS clusters. It allows performance monitoring of an EKS cluster for operations such as CPU and memory usage, network usage, and disk I/O. It also gives information and insights concerning the operational status of the clusters and avert issues that would be of major impact on the applications being run.
AWS X-Ray
X-Ray can be referred to as a distributed tracing service whose main purpose is to provide an understanding of application performance, as well as spotting the source of the problem. It allows for end-to-end visibility of requests flowing through an EKS cluster so that their journey may be tracked, hence knowing the effect to the users.
(Image Source: AWS X-Ray)
Service maps in X-Ray allow a user to see within the application, its structure and how the different services are related, and where the delays are. This accelerates the speed with which problems are identified, improves the speed of resolving the problems, and optimizes the cluster to perform better.
Third-Party Tools
Extend log management and monitoring using third party tools designed for Kubernetes specific environments.
Prometheus and Grafana
Prometheus captures system metrics in real-time while the information is visualized and presented with Grafana interactive dashboards. Together, these tools provide great information about your EKS clusters.
ELK Stack (Elasticsearch, Logstash, Kibana)
ELK Stack combines and helps to manage logs so it provides a complete log and data visualization solution.
Cost Management in Monitoring and Logging
Understanding Costs Associated with Monitoring
There are costs for monitoring and logging due to data ingestion, storage, and processing. Keeping in mind the nature of these costs assists in budget optimization.
Breakdown of Potential Costs
Data Ingestion: Costs incurred in the capturing and the forwarding of logs.
Storage: Charges made against the retention of the logs and the metrics with time.
Processing: Costs incurred in the process of querying the log data and analyzing the data.
Strategies to Optimize Costs
The existing monitoring and logging activities can be carried out at a lower cost by putting in place proper cost management practices:
Log Filtering Techniques
Source filtering techniques can discourage the ingestion of unnecessary logs, hence significantly cutting down on both ingestion and storage costs. Log levels should be applied such as; DEBUG, INFO, ERROR etc so that only the crucial messages are recorded while the rest are ignored.
Retention Policies
Retention periods should be designed in accordance with the analysis requirements, such that critical logs are kept longer and the less important ones are kept shorter duration periods in order to contain costs associated with storage. Cost effective long term retention should be sought for i.e. with tiered storage like AWS S3 or others.
Conclusion
Lastly, monitoring and logging are important practices for the maintenance and security of Amazon EKS clusters. With the help of the techniques and tools illustrated in this guide, DevOps engineers, cloud architects, and cloud engineers can improve their clusters' performance, resolve issues quickly, and reduce expenses. Take a look at the tools and practices discussed to improve your cloud operations.
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FAQs
What are the benefits of using Amazon CloudWatch logs for EKS monitoring?
CloudWatch is an effective and competitive metric and logging tool, which enables the user to monitor the performance and status of their clusters in real-time.
Which third-party tools are popular for EKS monitoring and logging?
Prometheus together with Grafana and the ELK Stack successfully gained popularity due to its powerful data collection, data visualization and data interpretation capacity.
How can I reduce costs associated with EKS logging?
Adopting log filtering techniques and the establishment of suitable retention policies will considerably lower data collection and storage costs.
