How to run MongoDB on Kubernetes?

Jan 16,2023 by Meghali Gupta
mongodb kubernetes
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As enterprises move to cloud computing and containers become more popular in software development, Kubernetes lets users deploy, scale, and manage containers easily. This platform makes it effortless to run and manage applications throughout their life cycle.

Though it’s always been a challenge to run databases and stateful applications in Kubernetes, it’s even more difficult to manage them in a production setting. Every enterprise needs a qualified operator to deploy and manage its databases efficiently. 

A production-grade operator has the necessary skills and experience to run databases effectively, ensuring they are always available and perform at optimal levels. It manages its life cycle on Kubernetes so that its data is protected and always available when needed.

This blog will teach you about MongoDB and how to deploy and manage MongoDB on Kubernetes.

What is MongoDB?

MongoDB

MongoDB is a powerful NoSQL database that uses flexible JSON-like documents with optional schemas. This means that fields can vary from document to document, and data structure can be changed over time. To make the smooth working of data, the document model used by MongoDB maps to the objects in your application code.

With MongoDB, you can meet the needs of today’s businesses by creating rich, scalable applications.  It is developed by MongoDB Inc. and is classified as a cross-platform document-oriented database program.

MongoDB is excellent for storing and querying large amounts of unstructured data. It’s frequently used in real-time analytics, big data, and other performance-intensive tasks because it can handle large data sets effortlessly. In addition, it provides a lot of features such as indexing, sharding, and aggregation. These make MongoDB very powerful and ideal for high-performance use cases.

MongoDB also supports automatic sharding, which allows horizontal database scaling by distributing data across multiple servers. Additionally, it can be used as a replica set, providing automatic failover and data redundancy in the event of failure.

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How to run MongoDB on Kubernetes?

Running MongoDB on Kubernetes involves several steps; here is a complete guide on how to run MongoDB on Kubernetes:

Step 1: Create and provision a Kubernetes 

The first step in the process of running MongoDB on Kubernetes is to create a cluster of Kubernetes. By using a tool like minikube, Google Kubernetes Engine (GKE), or Amazon Elastic Kubernetes Service (EKS). This will provide the necessary infrastructure for running MongoDB.

Step 2: Define a MongoDB Deployment

Next, you will need to create a deployment that defines how many replicas of MongoDB you want to run, what image to use, and how to configure the container. This is typically done using a Kubernetes YAML file. You can use the official MongoDB image from Docker Hub or the MongoDB Enterprise Kubernetes Operator.

Step 3: Create a Kubernetes Service

To access the MongoDB replicas from outside the cluster, you must create a service that acts as a load balancer. This is typically done using another YAML file.

Step 4: Configuration of Persistent Storage

MongoDB requires persistent storage for its data. You can use Kubernetes StatefulSets to create and manage MongoDB pods with persistent storage. You can configure a storage class or use a cloud provider’s storage service to create a persistent volume for the MongoDB pods.

Step 5: Deploy the MongoDB pods

Once you have your deployment and service defined, you can use the kubectl command-line tool to create and manage your MongoDB pods.

Step 6: Escalate your deployment

If you need to scale up or down your MongoDB deployment, you can do it using the kubectl command.

Step 7: Monitoring

It’s important to monitor your MongoDB deployment and to be aware of the performance metrics of your pods and the resources they are using. You can use tools such as Prometheus and Grafana to monitor and visualize your MongoDB deployment.

Step 8: Backup and Restore

To ensure the safety of your data and to be able to recover from failures, it’s important to have a backup and restore strategy. You can use the MongoDB Enterprise Kubernetes Operator to automate the backup and restore process.

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It’s important to note that MongoDB is a complex system, and there are several ways to run MongoDB on Kubernetes. 

For more detailed instructions, follow MongoDB’s official documentation on how to run MongoDB on Kubernetes and consult with MongoDB experts if you encounter any issues.

Open Source Solutions to run MongoDB on Kubernetes

There are several open-source solutions available to run MongoDB on Kubernetes. Some of the common and renowned open-source options include – 

MongoDB Enterprise Kubernetes Operator

MongoDB Inc created this operator of Kubernetes. The purpose of this operator is to make it easy to deploy, manage, and scale MongoDB clusters on Kubernetes. It provides features such as backup and restores, automatic failover, and scaling.

Helm Charts

For Kubernetes, Helm is a package manager allowing you to install and manage applications on a Kubernetes cluster conveniently. Several Helm charts are available for MongoDB, making it easy to deploy MongoDB on a Kubernetes cluster.

StatefulSets

It is a Kubernetes resource that makes it easy to manage stateful applications on a Kubernetes cluster. You can use this solution to create and manage MongoDB pods with persistent storage, which makes it easy to deploy MongoDB on a Kubernetes cluster.

Custom YAML files

You can also use custom YAML files to deploy MongoDB on a Kubernetes cluster. It allows you to have complete access to your MongoDB deployment configuration and make any customizations you require.

Open Source MongoDB Operator

This open-source operator allows you to deploy and manage MongoDB clusters on Kubernetes. The features provided by this operator include automatic failover, backup and restore, and scaling.

OperatorHub.io

OperatorHub.io is a central repository or platform for discovering and deploying Kubernetes Operators. Here, Kubernetes Operators stands for software extensions to Kubernetes. They make it convenient to manage applications, such as databases, message queues, and other services, on top of Kubernetes. 

It allows users to browse and deploy Operators from a curated catalog, and to submit their Operators for inclusion in the catalog.

Each of these solutions has its pros and cons, and the best choice for you will rely on your particular use case and requirements. It is substantial to thoroughly evaluate each option and consult with experts if you encounter any issues.

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Mongodb Sharding Kubernetes

MongoDB’s sharding capabilities in a Kubernetes environment facilitate horizontal scaling and efficient data distribution across multiple instances. Leveraging Kubernetes orchestration, MongoDB’s sharding feature enables the division of data across nodes, allowing for seamless scaling as data volumes grow. This setup optimizes performance and resilience, supporting applications’ evolving demands within Kubernetes clusters by dynamically managing and balancing data across the sharded MongoDB deployment.

Scaling Mongodb Kubernetes

Scaling MongoDB in a Kubernetes environment involves adjusting resources to accommodate varying workloads and data growth. Kubernetes offers flexibility by allowing horizontal and vertical scaling of MongoDB instances. Horizontal scaling involves adding more MongoDB pods to distribute the load, while vertical scaling adjusts the resources within each pod, such as CPU and memory. This dynamic scaling capability within Kubernetes ensures MongoDB databases can efficiently handle increased demands, maintaining performance and reliability as application requirements evolve.

MongoDB Deployments in a Kubernetes Environment:

 

Aspect Description
Deployment Using StatefulSets or Operator-based deployments for MongoDB instances
Scaling Horizontal scaling via replica sets or sharding to distribute data across multiple pods
Storage PersistentVolumes (PV) for data storage, often backed by cloud-based or on-premises storage solutions
Configuration ConfigMaps or Helm charts to manage MongoDB configurations, including authentication, authorization, and parameters
Networking Service objects for inter-pod communication and access, optionally using LoadBalancers or Ingress for external access
High Availability Replica sets for ensuring high availability and fault tolerance among MongoDB instances
Monitoring Integration with monitoring tools like Prometheus, Grafana, or MongoDB-specific monitoring solutions
Backup & Restore Scheduled backups using tools like Velero, Mongodump, or MongoDB Atlas Backup for data protection and recovery
Upgrades Rolling updates with minimal downtime, managed via Kubernetes rolling updates or Operator-based approaches

Conclusion

This blog post summarized and highlighted how to deploy MongoDB on Kubernetes and manage it. This is an important technical decision that might impact various business metrics, so choosing the right solution to deploy and manage MongoDB is crucial

An important thing to remember when choosing a database solution is that it should provide a way to deploy the database and enable your teams to execute various management and maintenance tasks without drowning in MongoDB complexity.

At Cyfuture cloud, we provide complete assistance in the deployment and management process of MongoDB on Kubernetes.

 

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