Louis-Victor Jadavji (or "LV") is a recognized leader in the cloud services industry. He's helped 50+ digital native companies like ModusBox, Later, and NS1 choose the right cloud stack for their applications. His work has been featured in Forbes (30 Under 30 All-Star), HuffPost, The New York Times, The Globe and Mail, and Inc. Magazine.
Kubernetes, also known as K8s, is a container orchestration engine built by Google to manage their container deployments and released as open-source in 2014. It automates the deployment, scaling, and management of containerized applications.
Kubernetes helps enterprises speed up their development and deployment processes and efficiently utilize resources. However, Kubernetes is a very large, complex distributed system with many components to monitor and manage.
Ops teams can monitor Kubernetes with the help of open-source monitoring tools such as Prometheus, Jaeger, Grafana, etc., and vendor-provided tools such as AppDynamics, Datadog, and Instana.
In this guide, we cover the following topics:
Enterprises used to run multiple applications on the same physical servers, causing resource allocation problems. One application would take up most of the resources, causing performance issues for other applications. In addition, running multiple applications on a single server did not work for the applications that had to meet specific compliance standards. Organizations used to run applications on different physical servers, which could lead to underutilized resources.
Virtualization allowed multiple Virtual Machines (VMs) to run on a single physical server and solve these issues. As a result, boundaries were created between applications wherein another application does not freely access information of one application, and applications can be added or updated easily, reducing hardware costs and increasing scalability. Containers were introduced to share resources but have separate file systems.
In a microservices-first world, enterprises tend to deploy large applications in multiple containers that run across multiple clusters. Coordinating these containers and virtual machines is complex in large distributed applications.
Kubernetes is an open-source container orchestration software. It controls how to run containers and where to run them. It helps run containers and workloads by tackling operational complexities such as scaling up or scaling down different containers and the virtual machines on which the containers are deployed. The basic functional unit of Kubernetes is called a “pod,” and containers are grouped into these pods. Containers and pods can be scaled up or down to the desired state. In addition, the lifecycle is managed to keep the applications up and running.
Scalability: With the help of configuration management tools in Kubernetes, it’s easy to scale the containers and the clusters on which they are running.
Efficiency: Kubernetes helps you use resources efficiently by automating the distribution of applications across different clusters.
High Availability: Kubernetes helps you restart failed containers or replace them by killing them when they don’t respond to user-defined health checks and helps you maintain a highly available service.
Speed and Agility: Kubernetes provides a way to potentially orchestrate and manage container resources from a single control plane, thereby keeping the core promise of containers: speed and agility.
Load Balancing: Kubernetes can distribute the incoming traffic by exposing a container using either the DNS name or IP address, thereby balancing the load.
Components of Kubernetes
Kubernetes clusters contain the following three components:
Let’s dive in a bit deeper into the components of the control plane:
Nodes have the following components:
Source: Above Image is from Kubernetes
There are several tools in the market that provide monitoring applications that run on the Kubernetes cluster. Below are some of the open-source tools and vendor-provided tools.
Kubernetes dashboard is a web-based Kubernetes user interface. The dashboard can be used to deploy containerized applications to a Kubernetes cluster.
The Elastic Stack (also known as “ELK Stack”) is a popular collection of four open-source log management and monitoring solutions – Elasticsearch, Logstash, Kibana, and Beats. It is used for Kubernetes monitoring as well.
Jaeger is an open-source distributed tracing system inspired by Dapper and OpenZipkin that was developed by Uber.
Prometheus was originally built at SoundCloud in 2012 before being released as an open-source project. It joined CNCF as only the second hosted project after Kubernetes.
Grafana offers open-source software that allows you to query, visualize, alert, and explore metrics, logs, and traces from different systems.
Datadog is an Application Performance Monitoring tool (or “APM” for short) that gives visibility into Kubernetes applications by monitoring, troubleshooting, and optimizing application performance.
Dynatrace provides APM tooling by supporting multiple languages, application architectures, cloud, on-premises or hybrid, enterprise applications, SaaS monitoring, etc.
New Relic is an APM tool that features Kubernetes integration and provides visibility to performance across the entire application environment.
AppDynamics APM by Cisco provides a global view across the application landscape that runs on a container or Kubernetes cluster.
Instana provides Kubernetes and container monitoring.
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