Containers
Tag: ADOT
Scale your Amazon ECS using different AWS native services!
Containers accelerate application development and enhance deployment consistency across environments, thus enabling organizations to improve productivity and agility. AWS container services such as Amazon Elastic Container Service (Amazon ECS) make it easier to manage your application so you can focus on innovation and your business needs. Customer experience is the most important yardstick by which […]
Diving into Container Insights cost optimizations for Amazon EKS
Introduction Amazon CloudWatch Container Insights allows you to collect, aggregate, and analyze metrics, logs, and traces for your container-based applications and infrastructure on AWS. Container Insights captures metrics for various resources, such as CPU, memory, disk, and network, along with diagnostic data like container restart failures, which enables you to efficiently isolate and resolve problems. […]
Metrics and traces collection from Amazon ECS using AWS Distro for OpenTelemetry with dynamic service discovery
An earlier blog published last year (Part 1 in the series), Metrics collection from Amazon ECS using Amazon Managed Service for Prometheus, demonstrated how to deploy Prometheus server on an Amazon ECS cluster, dynamically discover the services to collect metrics from, and send metrics to Amazon Managed Service for Prometheus for subsequent query and visualization. […]
Metrics and traces collection using Amazon EKS add-ons for AWS Distro for OpenTelemetry
Introduction Amazon Elastic Kubernetes Service (Amazon EKS) is a managed service that offloads from its users the onerous task of managing the Kubernetes control plane. It gives users the flexibility to install tools they need to manage their application workloads on the data plane. However, many customers want us to manage some of these tools […]
Introducing Amazon CloudWatch Container Insights for Amazon EKS Fargate using AWS Distro for OpenTelemetry
Introduction Amazon CloudWatch Container Insights helps customers collect, aggregate, and summarize metrics and logs from containerized applications and microservices. Metrics data is collected as performance log events using the embedded metric format. These performance log events use a structured JSON schema that enables high-cardinality data to be ingested and stored at scale. From this data, […]