Organizations are increasingly expanding their Kubernetes footprint by deploying microservices to incrementally innovate and deliver business value faster. This growth places increased reliance on the network, giving platform teams exponentially complex challenges in monitoring network performance and traffic patterns in EKS. As a result, organizations struggle to maintain operational efficiency as their container environments scale, often delaying application delivery and increasing operational costs.
Today, I’m excited to announce Container Network Observability in Amazon Elastic Kubernetes Service (Amazon EKS), a comprehensive set of network observability features in Amazon EKS that you can use to better measure your network performance in your system and dynamically visualize the landscape and behavior of network traffic in EKS.
Here’s a quick look at Container Network Observability in Amazon EKS:
Container Network Observability in EKS addresses observability challenges by providing enhanced visibility of workload traffic. It offers performance insights into network flows within the cluster and those with cluster-external destinations. This makes your EKS cluster network environment more observable while providing built-in capabilities for more precise troubleshooting and investigative efforts.
Getting started with Container Network Observability in EKS
I can enable this new feature for a new or existing EKS cluster. For a new EKS cluster, during the Configure observability setup, I navigate to the Configure network observability section. Here, I select Edit container network observability. I can see there are three included features: Service map, Flow table, and Performance metric endpoint, which are enabled by Amazon CloudWatch Network Flow Monitor.
On the next page, I need to install the AWS Network Flow Monitor Agent.
After it’s enabled, I can navigate to my EKS cluster and select Monitor cluster.
This will bring me to my cluster observability dashboard. Then, I select the Network tab.
Comprehensive observability features
Container Network Observability in EKS provides several key features, including performance metrics, service map, and flow table with three views: AWS service view, cluster view, and external view.
With Performance metrics, you can now scrape network-related system metrics for pods and worker nodes directly from the Network Flow Monitor agent and send them to your preferred monitoring destination. Available metrics include ingress/egress flow counts, packet counts, bytes transferred, and various allowance exceeded counters for bandwidth, packets per second, and connection tracking limits. The following screenshot shows an example of how you can use Amazon Managed Grafana to visualize the performance metrics scraped using Prometheus.
With the Service map feature, you can dynamically visualize intercommunication between workloads in your cluster, making it straightforward to understand your application topology with a quick look. The service map helps you quickly identify performance issues by highlighting key metrics such as retransmissions, retransmission timeouts, and data transferred for network flows between communicating pods.
Let me show you how this works with a sample e-commerce application. The service map provides both high-level and detailed views of your microservices architecture. In this e-commerce example, we can see three core microservices working together: the GraphQL service acts as an API gateway, orchestrating requests between the frontend and backend services.
When a customer browses products or places an order, the GraphQL service coordinates communication with both the products service (for catalog data, pricing, and inventory) and the orders service (for order processing and management). This architecture allows each service to scale independently while maintaining clear separation of concerns.
For deeper troubleshooting, you can expand the view to see individual pod instances and their communication patterns. The detailed view reveals the complexity of microservices communication. Here, you can see multiple pod instances for each service and the network of connections between them.
This granular visibility is crucial for identifying issues like uneven load distribution, pod-to-pod communication bottlenecks, or when specific pod instances are experiencing higher latency. For example, if one GraphQL pod is making disproportionately more calls to a particular products pod, you can quickly spot this pattern and investigate potential causes.
Use the Flow table to monitor the top talkers across Kubernetes workloads in your cluster from three different perspectives, each providing unique insights into your network traffic patterns.
Flow table – Monitor the top talkers across Kubernetes workloads in your cluster from three different perspectives, each providing unique insights into your network traffic patterns:
- AWS service view shows which workloads generate the most traffic to Amazon Web Services (AWS) services such as Amazon DynamoDB and Amazon Simple Storage Service (Amazon S3), so you can optimize data access patterns and identify potential cost optimization opportunities.
- The Cluster view reveals the heaviest communicators within your cluster (east-west traffic), which means you can spot chatty microservices that might benefit from optimization or colocation strategies
- External viewidentifies workloads with the highest traffic to destinations outside AWS (internet or on premises), which is useful for security monitoring and bandwidth management.
The flow table provides detailed metrics and filtering capabilities to analyze network traffic patterns. In this example, we can see the flow table displaying cluster view traffic between our e-commerce services. The table shows that the orders pod is communicating with multiple products pods, transferring amounts of data. This pattern suggests the orders service is making frequent product lookups during order processing.
The filtering capabilities are useful for troubleshooting, for example, to focus on traffic from a specific orders pod. This granular filtering helps you quickly isolate communication patterns when investigating performance issues. For instance, if customers are experiencing slow checkout times, you can filter to see if the orders service is making too many calls to the products service, or if there are network bottlenecks between specific pod instances.
Additional things to know
Here are key points to note about Container Network Observability in EKS:
- Pricing – For network monitoring, you pay standard Amazon CloudWatch Network Flow Monitor pricing.
- Availability – Container Network Observability in EKS is available in all commercial AWS regions where Amazon CloudWatch Network Flow Monitor is available.
- Export metrics to your preferred monitoring solution – Metrics are available in OpenMetrics format, compatible with Prometheus and Grafana. For configuration details, refer to Network Flow Monitor documentation.
Get started with Container Network Observability in Amazon EKS today to improve network observability in your cluster.
Happy building!
— Donnie