Kubernetes is a production-ready, open-source platform designed with Google’s accumulated experience in container orchestration, combined with best-of-breed ideas from the community. It is designed to automate deploying, scaling, and operating application containers.
With the increasing adoption of containers and microservices in enterprises, monitoring utilities have to handle more services and server instances than ever before. Although the infrastructure landscape has changed, operations teams still need to monitor the same metrics on CPU, RAM, File System, Network utilization, and the availability of service endpoints. In this post, we take look at some of the best monitoring tools available for Kubernetes.
Datadog allows you to collect metrics, events, and service states from Kubernetes service in real-time. You can then, visualize and correlate the data with beautiful graphs, and set flexible alerting conditions without running any storage or monitoring infrastructure yourself.
Key Features :
Datadog seamlessly aggregates metrics and events across the full DevOps stack
Ability to monitor, troubleshoot, and optimize application performance
Option to search, filter, and analyze logs for troubleshooting
Datadog offers real-time dashboards, high-resolution metrics, and events for manipulation and graphing
Datadog alerts on any metric, for a single host or for an entire cluster. Get notifications via e-mail, PagerDuty, Slack, and other channels
Datadog includes full API access to bring observability to all your apps and infrastructure
If you’re looking for a quick start on a basic understanding of Kubernetes concepts, please refer to earlier posts for understanding on Kubernetes & how to create, deploy & rollout updates to the cluster.
Sumo Logic App for Kubernetes allows you to monitor Kubernetes deployments. Preconfigured dashboards present resource-related metrics at the Kubernetes pod, cluster, and namespace level; and provide operational insight into Kubernetes components, including nodes, the API Server, the Controller Manager, the Kube System, and the Scheduler.
Key Features:
Assess the health of Kubernetes-built applications and manage the environment from a simple GUI interface.
Full-stack visibility into applications, including Kubernetes container orchestration.
App installs instantly as a stand-alone tool in a data center or as part of cloud architecture and integrates with Sumo Logic apps for all major cloud hosting platforms, including AWS, Google Cloud, and Microsoft Azure.
New Relic Infrastructure on-host integration for Kubernetes, provides deep monitoring of the container orchestration layer. It collects metrics that monitor data and metadata for nodes, Namespaces, Deployments, ReplicaSets, Pods, and containers, so you can fully monitor your frontend and backend applications and hosts running in your Kubernetes clusters.
Key Features:
A comprehensive view of the health of your servers and hosts as well as the applications and services
Cloud-ready out-of-the-box integrations let you view and report data from various services
Detailed views of the processes running within containers and track container versions.
Full visibility into how your host is performing, sorted by the host traits you care about. Infrastructure collects and displays health metrics such as CPU, Load, Memory, etc. at the host level, as well as individual Process, Network, and Storage levels.
Tag-driven alerting and dashboarding
Powerful search allows you to find vulnerable packages and other inventory items
To activate on-host integration, deploy the newrelic-infra agent onto a Kubernetes cluster. Check out the documentation on Kubernetes integration here.
Be it traditional or microservice-based applications running on Kubernetes. AppDynamics for Kubernetes offers a unified solution to deliver flawless application experiences.
Key Features:
Visibility into Kubernetes by leveraging labels like Namespace, Pods, ReplicaSets, Deployment, or any other Kubernetes label. Organize, group, query, or filter Kubernetes objects or performance metrics based on labels
Consistent visibility into Kubernetes clusters deployed across on-premises or hybrid environments
Quickly triage the root cause via stack-ranked order of potential root causes
Isolate the performance issues in different environments and their impact on business in real-time.
To install AppDynamics for Kubernetes visibility follow these steps :
Install a Standalone Machine Agent in a Kubernetes node.
Install an APM Agent inside each container in a pod that needs to be monitored.
The Standalone Machine Agent then collects hardware metrics for each monitored container, as well as Machine and Server metrics for the host, and forwards the metrics to the Controller.
Linkerd is a service sidecar and service mesh for Kubernetes and other frameworks. It gives you runtime debugging, observability, reliability, and security–all without requiring any changes to your code.
Linkerd has three basic components: User interface, data plane, and control plane. Linkerd works by installing ultralight proxies into each pod of a service. These proxies become part of a data plane that reports telemetry data to and receives signals from, a control plane.
Key Features:
Automatically instruments metrics such as request volume, success rates, and latency distributions.
Provides real-time streams of requests for all incoming and outgoing traffic.
Linkerd control plane must be installed first and then add the data plane proxies for respective services. Check out Documentation for more details on how to install/configure for Kubernetes.
Check out a detailed article on Linkerd Service Mesh on why do we need it and more here.
Turbonomic uses a patented analysis engine to provide visibility and control across the entire stack in order to assure the performance of running micro-services in Kubernetes Pods, as well as the efficiency of the underlying infrastructure.
Key Features:
Provides Rescheduler capability (continuous placement for Pods)
Continuous scaling for applications and the underlying cluster.
Full-Stack Visibility from on-prem DataCenter to major public cloud providers.
Combining real-time performance monitoring and analysis engine, Turbonomic is able to provide right-sizing information for each individual pod as well as the entire IT stack.
If you’re looking for a quick start on a basic understanding of Kubernetes concepts, please refer to earlier posts for understanding on Kubernetes & how to create, deploy & rollout updates to the cluster.
Replex gives you a complete picture of your container environment no matter whether private/public cloud or physical infrastructure. It includes the following
Discover workload distributions
Analyze container efficiencies
Identify where your applications are running in real-time
Key Features:
Deep insights into containers and orchestrators
Container workload analyses
Full insights into cost distributions of applications and teams
With Instana, you can automatically detect the containers running in the service and the platforms running on the containers, deploying additional sensors to gather performance metrics of the full application stack.
Key Features:
Automatic discovery and monitoring of all infrastructure components ensures full-stack accuracy at all times
Automatic deployment and upgrade of infrastructure monitoring sensors
Automatic tag and label correlation enriches the monitoring data making it easier
Automatically identify root cause at any layer of your technology stack.
Do check out Container monitoring documentation for details on how to view real-time insights into metadata, configuration, metrics, etc.,
Weave Scope is a visualization and monitoring tool for Docker and Kubernetes. For Microservices-based architecture, Weave scope would be useful in visualizing network bottlenecks, troubleshooting CPU consumption, and troubleshooting memory leaks. It provides a top-down view into your app as well as your entire infrastructure and allows you to diagnose any problems with your distributed containerized app, in real-time, as it is deployed to a cloud provider.
Key Features
Drill down Views: For an app that is running in Kubernetes, Scope displays Pods, Replica Sets, Deployments, and related Services on clusters. So for containerized microservices running in the cloud, you can view Processes, Containers, Orchestrators, and Hosts.
Real-time Contextual metrics: By clicking on a node you can get a detailed panel with additional metrics on the node. From the detailed panel, you can drill down on processes inside your container to the hosts that your containers run on.
Troubleshoot / Manage Containers: On clicking of a container, pod or host, you can view the controls pane from there you can pause, restart, stop and delete without having to leave the Scope browser window. If further troubleshooting is required, terminal windows can be launched from any container or host so that you can interact with your app and run any UNIX command to diagnose issues.
Search: Weave supports simple operands so that for example, you can find processes consuming a certain amount of memory or nodes using too much CPU.
Filtering options: Nodes can be filtered by CPU and Memory usage so that you can easily find containers using the most resources. If you are running an app in Kubernetes then your app can be filtered by namespace and by container state whether running or stopped or contained and uncontained.
Graphic / Table Mode: Views can be presented in Graphic as well as Table Mode. The graphical mode is more useful in cases where you want to have a quick visual overview of your app. Tablet mode is for viewing data like resources being consumed by processes, containers, and hosts, etc.,
Sematext is a log management and monitoring solution that offers full-stack visibility into containers and container orchestrators. It collects Kubernetes and container logs, metrics, and events for all the containers running in your Kubernetes cluster, including system-component containers from the kube-system namespace.
With Sematext it’s easy to structure and make sense of data, build analytics reports. It features real-time anomaly detection and alerting to immediately pinpoint problematic pods. With metrics and log correlations, you can easily pivot between spikes in metrics and error logs while troubleshooting production issues.
Key features:
Easy installation as Helm chart, DaemonSet, or Kubernetes Operator
Native monitoring and log collection agents that capture and process Docker and Kubernetes data
Automatic label and tag correlation to enrich data and make it easily searchable for both troubleshooting and business analytics with the ability to add custom labels and tags for even more fine-grained data correlation
Automatically discovers any newly launched containers without manual intervention
Secure and reliable data transfer to avoid data loss
Out-of-the-box dashboards and alerts covering general Kubernetes use-cases with the ability to add custom charts, dashboards, and events for your specific needs
Pick the right solution – key capabilities to watch out for
Aggregate metrics, events, and labels from Kubernetes
Support for any deployment style (Local, hosted, or hybrid) and ability to collect and report following Host /Pod/Container/Control Plane metrics
Resource utilization (for each container can consume)
CPU Usage
Node CPU capacity
Memory Usage
Node Memory capacity
Requests
Limits
Filesystem Usage
Disk I/O (per node)
Network Throughput
Application metrics – Support to monitor applications running on Kubernetes
I hope this listing of 10 BEST monitoring tools would help you to choose the best monitoring solution for the Kubernetes environment. Also If I have missed out on anything, do let me know.
With the increasing adoption of containers and microservices in the enterprises, monitoring utilities have to handle more services and server instances than ever before.In this post,we take look at some of the monitor tools available for Kubernetes.
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Karthik
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