Kubernetes and Mesos are container orchestration engines that run cloud applications and services, such as those available through AWS or Azure.
Your choice of container orchestration engine depends on various considerations, including the size and scope of your application, budget constraints, and goals.
Apache Mesos may be the perfect fit if your primary concerns include flexibility and massive scale; its use by companies like Twitter, Airbnb, and eBay demonstrates this fact.
Overview of Kubernetes
Kubernetes is an open-source and extensible platform for managing containerized applications and services. The system offers declarative configuration and automation with support from an established ecosystem - making it popular with web-scale companies looking to automate containerized workloads such as automatic container scheduling, self-healing capabilities, and automated rollouts and rollbacks.
Kubernetes clusters consist of worker nodes - virtual or physical servers that serve as nodes in a cluster - interconnected via network and running the control plane components that manage containers and orchestrate resource utilization.
Clusters also utilize a network proxy called Kube-proxy that connects applications running on its nodes to each other, maintains rules regarding inside/outside cluster networking, and provides fault tolerance and high availability.
Kubernetes offers several advantages when used for container management, such as portability and flexibility, support for various platforms and libraries, and robust security capabilities - these benefits make Kubernetes a go-to choice among businesses of all sizes across industries.
Kubernetes can protect containerized applications from malware with automatic scanning that identifies viruses and malicious code in containers. Furthermore, users can create quarantines for specific container types or set a default policy across all containers.
Overview of Apache Mesos
Apache Mesos is a cluster manager designed for container orchestration. It supports Docker and native containerization methods and integrates seamlessly with machine learning/big data tools like Cassandra, Kafka, and Spark.
Mesos API provides developers with an efficient means of building applications across multiple clusters. It has been carefully designed to support a range of framework languages and driver-based framework APIs.
Provides a fault-tolerant architecture that enables upgrades on both masters and slaves without cluster downtime and supports notifications when failure or leader elections have taken place so that frameworks can take appropriate actions accordingly.
Mesos stands apart from many other cluster managers by using an agile allocation system that distributes resources such as CPU and memory evenly across frameworks according to organizational policies, such as fair sharing or strict priority.
Frameworks register executors and launch tasks through a Mesos master, which maintains records on which executors are running which tasks and can use this information for service discovery purposes.
Example: A framework could give its executor addresses to a service discovery system, which uses them to set up DNS entries or configure proxies to reach their task. This feature is similar to service discovery found in other systems.
Docker Images support launching tasks and executors through their API; however, the API only offers support for specific options; we plan to expand it further in future releases.
Scheduling engines (commonly called schedulers) are responsible for allocating workloads among frameworks on a cluster, managing resource pools, and overseeing tasks while executing commands to run these workloads.
Scheduling engines can use suppression to save on resources. When other schedulers need no new tasks or operations, a scheduler can remain suppressed until tasks or operations are offered up for launch or against other schedulers. This helps save on resource consumption.
Schedulers should decline offers they cannot accept before attempting to reutilize them, ensuring fewer offers from other schedulers and better resource allocation for their workloads.
Strengths & weaknesses of Kubernetes and Mesos
Kubernetes and Mesos are two container orchestration platforms that enable businesses to quickly deploy, scale, and operate multiple application containers across clusters of nodes. Both platforms are deployed across most cloud providers and used by developers, IT system administrators, DevOps engineers, and DevOps engineers for building microservice architecture in private, public, or hybrid clouds.
Kubernetes is an exceptional solution for managing large, scalable, resilient applications with zero downtime. It automates container deployment, scaling, and de-scaling and offers a centralized platform for load-balancing containers. Furthermore, Kubernetes features numerous security measures to ensure services run in a secure environment.
Kubernetes stands out as an open-source platform, available from a wide range of vendors with an active community supporting it. Many popular cloud providers, including Google Cloud Platform (GCP), also support Kubernetes.
Mesos is a highly scalable and flexible infrastructure management platform capable of supporting thousands of nodes at the same time. Companies like Twitter, Airbnb, and Yelp use Mesos for this reason.
Mesos' versatility and expansive capabilities may limit its use by smaller organizations due to its steep learning curve for new users, thus making the system less accessible.
But its strengths outweigh these drawbacks; it supports many different kinds of container engines and can be easily managed through a web interface, with comprehensive security features to support any size workload.
Mesos provides stateful services with a built-in persistence mechanism that enables them to store data locally on agents' storage devices for persistence. This mechanism helps store logs or data that don't fit within one container.
This system also features an API called the Container Object Storage Interface, a standard layer for storing and managing container objects. Based on CSI standards, this API can be implemented by various open-source and commercial storage systems.
No matter which platform you select, it is imperative that your clusters can be managed effectively to increase reliability and performance, enhance security posture, reduce downtime, and gain key business insights.
Comparison between features of Kubernetes & Mesos
Kubernetes is the industry standard open-source system for orchestrating containerized applications. Though widely utilized by cloud providers and large enterprises alike, Kubernetes remains controversial, with some opposing its usage and providing it as the perfect infrastructure solution. Although Kubernetes enjoys wide use, some voices voice concerns regarding it needing to be more popular or implemented too quickly.
Kubernetes has gained popularity due to its expansive built-in features that simplify application deployment in production environments. Furthermore, Kubernetes can autoscale containers and nodes automatically; its load balancing support even works to balance the load evenly across nodes.
Additionally, it supports multiple cloud platforms - an essential feature for developers who need their applications running across several cloud providers without modifying any code.
Kubernetes stands out as a unique system due to its self-healing abilities. This means it can detect non-working containers and replace them if necessary, providing another central plus point.
DevOps teams appreciate Kubernetes because of its capacity to scale applications automatically. Traditional DevOps methods could make matching capacity with user traffic challenging; with Kubernetes, this problem has been eliminated.
Pods are one of the most popular deployment models in Kubernetes. A pod comprises several containers with a common namespace and is launched simultaneously on multiple nodes.
Launching containers in a cluster has two options: using a container or directly from the primary node. Mesos frameworks offer built-in support for using containerised to launch pods directly; Docker EE and DC/OS also support this through their compose executor projects.
Containerizers are services that perform container execution and manage their state on nodes, an essential element of container clusters that allow each underlying node to maintain a consistent state for all running containers and services.
Kubernetes offers the Pod as the core unit for deployment, comprising multiple containers that logically belong together. This method has proven popular in Kubernetes and Mesos, Marathon, and DC/OS environments.
Dynamic disk provisioning is another essential feature of Kubernetes and Mesos. Through dynamic disk provisioning, users can easily resize disk resources by dynamically distributing them among nodes according to statistics from their containerized application.
FAQ Section
Kubernetes has a steeper learning curve but provides more advanced features, while Mesos offers simplicity and ease of use for managing distributed systems.
Kubernetes has a larger user base and ecosystem, making it more mature with a wide range of integrations and tools available for deployment and management.
Kubernetes has strong support for hybrid cloud deployments, enabling consistent management and deployment across on-premises and cloud environments.
Both platforms are capable of scaling applications, but Kubernetes has native scaling features and autoscaling capabilities that make it easier to scale applications dynamically.