Kubernetes Application Performance Monitoring Tools
Olabanji Ayodele
Olabanji Ayodele
July 21, 2020
/
6 minutes read

Kubernetes Application Performance Monitoring Tools

In recent years, the Kubernetes platform has witnessed steady growth and transformation, becoming a top standard for the management and orchestration of application containers. Practically all the key stakeholders in the cloud-native application industry have shown massive support for Kubernetes as a standard in the industry.

Today, the deployment of Kubernetes by most companies often seek to attain a similar goal - maximizing the benefits of running containerized apps, through the usage of automation, orchestration, and more.

While Kubernetes shines at abstracting away much of the work linked to managing containerized workloads, it also presents some difficulties. These challenges lead to the creation of Application Performance Monitoring Tools to monitor and maintain the performance of deployed Kubernetes environments. These tools come in different varieties and can also assist in troubleshooting issues when they arise.

What are the best Kubernetes Application Performance Monitoring Tools?

Developing a personalized monitoring solution can be a great option if the resources and time are available, but this is not the case for many organizations. The Kubernetes Application Performance Monitoring Tools come as commercial or open-source tools to help with monitoring and management. The use of SaaS monitoring solutions allows them carryout effective management and monitoring of these systems with a focus on the creation of value. Due to the seemingly complex nature of Kubernetes and large-scale usage by several organizations, there are various functionalities offered by these monitoring tools. Some notable features include data collectors, metrics, tackle logs, and more.

Some of the top Kubernetes Application Performance Monitoring Tools include:

Datadog

The Datadog platform offers an APM solution with functionalities to extract logs, events, service states, and metrics from Kubernetes. Datadog allows users to optimize, troubleshoot, and monitor application performance. Datadog provides dashboards and high-resolution metrics, as well as events for graphing and manipulation. Users can also set up and receive alerts notifications on a variety of channels.

Key Advantages:

  • Easy installation
  • Easy access to metrics history
  • Excellent APM integration
  • Exceptional downtime management for various resources

Cons:

  • Complex logs integration
  • No custom query language

Elastic Stack (ELK)

The Elastic Stack platform offers another excellent open-source monitoring solution for log management. It can be engaged for a variety of Kubernetes demands, as it is already a popular choice for many monitoring purposes. In guaranteeing a comprehensive logging pipeline, the platform features four tools that include:

  • Beats – Beats is a lightweight data shipper that provides services for sending logs and metrics to Elasticsearch.
  • Elasticsearch – This tool is a full-text search and analytics engine with storage for Kubernetes logs.
  • Kibana – offers functionalities that cover visualization and reporting.
  • Logstash – is a log aggregator that captures logs and delivers to the elasticsearch platform.

Elastic Stack also comes with Docker monitoring beats alongside auto-discovery. The Beats gathers Docker logs and Kubernetes, metadata, and metrics, thus aiding performance monitoring at system and application level.

Key Advantages:

  • Easy deployment and running in Kubernetes environment
  • Efficient Log Storage solution
  • Excellent analytics abilities
  • Large community Support

Cons:

  • Overall architecture and query mechanisms are complex
  • Difficult to scale

Grafana

Grafana offers an open-source platform with functionalities to handle analysis, data visualization, metrics, and monitoring. Grafana’s ability to link with several databases makes it stands out from other visualization tools. For monitoring Kubernetes, Grafana makes a popular combination for use alongside Graphite, InfluxDB, or Prometheus. The platform also features annotations, inbuilt alert systems, cross-organizational collaboration, data-source specific queries, etc. Users can create detailed monitoring dashboards with a large selection of graphs options covering bar graphs, Geo maps, heatmaps, histograms, and more. There are several off-the-shelf Kubernetes monitoring dashboards available for use.

Key Advantages:

  • Excellent developer community
  • The simultaneous query for several entities
  • Compatible with many data sources
  • Easy setup and usage.
  • Excellent reporting and visualization functions
  • Support for Elasticsearch and Prometheus backends

Cons:

  • No customization is available for Kubernetes log handling.

Jaeger

Jaeger, an open-source tool released by Uber Technologies, provides a free request tracing tool to monitor and troubleshoot multipart distributed systems such as Kubernetes. The Jaeger tool allows users to perform distributed context propagations, distributed transaction monitoring, performance optimization, service dependency, and root cause analysis. The platform also features support for OpenTracing-based solutions like C++, Java, Go, Node, Phyton, and other data sources, like Kafka, Elasticsearch, Cassandra, and memory. In the deployment of Jaeger, users can employ the DaemonSet configuration or the Jaeger Operator.

Key Advantages:

  • Several instrumentations option
  • Easy Deployment
  • Modern user interface

Cons:

  • Complex User Interface
  • Limited backend integration

While the use of OpenTracing usually requires changes to the code, in Kubernetes environment, it can be avoided using Service Mesh technology. With Service Mesh, the tracing headers can be automatically injected to requests from sidecar containers. While Service Mesh comes with its own complexities, it could significantly simplify the insertion of OpenTacing into the application stack.

Kubernetes Dashboard

This tool is a web-based platform for managing Kubernetes clusters. The Kubernetes Dashboard makes use of an add-on that offers a simple approach to managing, monitoring, and troubleshooting the Kubernetes application. Users can engage the Kubernetes Dashboard in accessing metrics connected to CPU and memory usage stats across all nodes. The platform also allows for monitoring the well-being of workloads like cron jobs, deployments, pods, replica sets, and more. Kubernetes Dashboard can be installed easily using the off-the-shelf YAML files.

Key Advantages:

  • Easy installation
  • A component of the Kubernetes environment

Cons:

  • Overall features are limited

New Relic

The New Relic platform provides features for Kubernetes integration that gives users an impressive view of applications, hosts, servers, and services. Users can also capture metadata and data for containers, deployments, namespaces, nodes, pods, and replica sets. Additionally, the New Relic platform also delivers robust searching capabilities, along with tag-driven alerts and dashboards.

Key Advantages:

  • APM Integration
  • Visualization for cluster health

    Cons:

  • Complex onboarding

Prometheus

Prometheus, developed by SoundCloud, is amongst the most common open-source platforms for monitoring Kubernetes. Popular as an accessible time-series database, Prometheus stands out from others by offering a robust multidimensional data model alongside PromQL. Additionally, Prometheus uses the pull model approach with a real-time alert system that is inbuilt. As an open-source platform, Prometheus features a large support community involved in driving innovation. Kubernetes and Prometheus can run efficiently via the Prometheus Operator.

Key Advantages:

  • Easy integration with Kubernetes-native and Grafana
  • It has a built-in alert system.
  • Large community Support
  • Reliable and Functional even with outages

Cons:

  • No dashboard and prolonged storage solution
  • No authentication or authorization
  • Scaling challenges

Sematext

The Sematext provides an integrated solution for monitoring both microservice- and traditional-based apps on Kubernetes. It also adds other functionalities like capturing logs, events, and metrics, all with instantaneous access to live data. These data can further be analyzed, structured, and visualized. Sematext also lets users build reports on log analytics, create customized monitoring dashboards and notifications, and alerts for metrics and logs. These functionalities make it easy to find faulty pods quickly. While handling both log and monitoring processes, the Sematext platform does not require running any monitoring or storage infrastructure. Sematext can also be optimized with DaemonSet, Elasticsearch API, Helm chart, and Kubernetes Operator.

Key Advantages:

  • Auto-discovery
  • Customizable monitoring dashboards
  • Easy installation

Cons

  • Multiple Clusters
  • Manual Configuration

Conclusion

Application Performance Monitoring is not a simple task, but gaining a proper understanding of the possible challenges emanating from Kubernetes monitoring makes the first phase. Knowing the key metrics and importance of monitoring would help you define the best approach and suitable monitoring tools to keep track of your systems.

Selecting an Application Performance Monitoring tool is mostly dependent on individual monitoring demands and use cases. With the benefit of having large support communities, more open-source solutions are driven to enhance present answers. But SaaS solutions are generally created by experts who offer support and primarily eliminate the need to handle the Kubernetes monitoring tools yourself.

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