As modern software development shifts toward microservices and cloud-native architectures, effective database management is critical for supporting these complex, distributed systems and driving application success. The emergence of orchestration solutions like Kubernetes has streamlined database deployment and management. MySQL is a popular relational database management system, and deploying it on Kubernetes environments can provide a highly scalable and adaptable solution for managing complicated workloads.
In this blog, we will provide a step-by-step guide for setting up MySQL on Kubernetes, its management, day 2 operations, best practices, and much more.
What is MySQL?
MySQL is an open source relational database management system that has long been used as the foundation of many web applications. It manages data using SQL. Well known for its reliability, user-friendliness, quick, and robust support for data-driven applications of all types. MySQL allows individuals to store, manage, and access data efficiently. It’s a go-to choice for a wide range of applications for both small and large-scale operations.
Benefits of MySQL
MySQL is a widely used open-source relational database management system (RDBMS) known for its versatility and robust features. Here are the key benefits of using MySQL:
- Scalability: MySQL can handle massive datasets making it suitable for both small applications and large enterprise systems.
- High Performance: MySQL is optimized for speed, capable of executing thousands of queries per second. Benchmarks show that it can outperform other databases like SQL Server and Oracle in certain scenarios, especially with read-heavy workloads.
- Reliability: MySQL supports ACID compliance (atomicity, consistency, isolation, and durability), ensuring data integrity even in high-transaction environments.
- Security Features: MySQL includes advanced security measures such as user authentication, SSL support, and data encryption, making it a secure choice for managing sensitive information.
- Cross-Platform Compatibility: MySQL can run on various operating systems, including Windows, Linux, and macOS, providing flexibility in deployment options.
What is Kubernetes?
Kubernetes is an open source container orchestration platform that simplifies the deployment, scaling, and management of containerized applications. Originally developed by Google and now maintained by the Cloud Native Computing Foundation (CNCF), Kubernetes allows users to manage workloads across various environments, including on-premises, public, and hybrid clouds.
Kubernetes simplifies complex application management and enables essential features such as autoscaling, load balancing, and self-healing, which ensure high availability and optimal resource utilization. Its flexibility makes it a popular choice for supporting microservices architectures.
By orchestrating containers efficiently, Kubernetes allows developers to focus on building software rather than managing infrastructure, ultimately enhancing productivity and operational efficiency.
Benefits of Kubernetes
Kubernetes offers powerful features that streamline application management. Here are some key benefits:
- Scalability: Kubernetes allows applications to automatically scale by adjusting their instances based on traffic. It supports both Horizontal Pod Autoscaling (HPA) based on resource metrics and Vertical Pod Autoscaling (VPA) for dynamic resource allocation.
- High Availability & Resilience: Leverages ReplicaSets and health probes (liveness, readiness, startup) to maintain the desired state. Implements automatic pod rescheduling and container restarts based on defined health checks and resource constraints.
- Portability & Flexibility: Kubernetes maximizes flexibility by providing support for different environments to run applications across cloud platforms (AWS, Azure, GCP), on-premises data centers, or hybrid setups.
- Automated Deployments & Rollbacks: Kubernetes streamlines software updates with automated deployments and rolling updates, allowing easy rollbacks if issues arise. Kubernetes can be configured to automatically roll back deployments if certain health checks fail during the update process, enhancing application stability without manual intervention.
Why Deploy MySQL on Kubernetes?
Using MySQL on Kubernetes provides flexibility and scalability for container orchestration. When businesses use Kubernetes to deploy MySQL, they can fasten the deployment process, assure high availability, and optimize resource allocation across the cluster for optimal performance.
Benefits of Running MySQL on Kubernetes
Here are some key benefits that illustrate how MySQL could leverage Kubernetes to ensure optimal performance for applications:
Scalability
MySQL on Kubernetes supports scaling through StatefulSets and horizontal scaling by utilizing read replicas. Kubernetes simplifies the management of these replicas, automates connection pooling configurations, and provides load balancing through Services. Additionally, Custom Resource Definitions (CRDs) implemented via operators facilitate the automation of intricate scaling tasks.
High Availability
Kubernetes improves MySQL’s high availability (HA) features by utilizing pod disruption budgets, anti-affinity rules, and topology spread constraints. StatefulSets provide consistent network identities and facilitate ordered deployment and scaling, ensuring that MySQL instances are managed effectively. Persistent volumes play a crucial role in preserving data durability. Additionally, operators can automate failover processes by overseeing MySQL’s replication, promoting replicas to primary status, and updating service endpoints accordingly.
Resource Efficiency
Kubernetes offers precise management of MySQL resource allocation through the use of resource quotas and limits. Quality of Service (QoS) classes ensure that essential database pods are prioritized during scheduling, while Storage classes facilitate dynamic volume provisioning tailored to specific performance requirements, such as IOPS and throughput.
Ease of Management
MySQL instances can be managed using Infrastructure-as-Code practices through Kubernetes manifests and Helm charts. Additionally, you can streamline management by utilizing MySQL-specific operators that extend the Kubernetes API to facilitate database-native operations such as backup scheduling, point-in-time recovery, major version upgrades, and connection pooling configurations.
How to Set Up MySQL on Kubernetes
Deploying MySQL on Kubernetes involves creating several resources, such as Deployments, Persistent Volumes, and Services. There are different operators with varying functionality, management, and scalability that we can use to deploy MySQL. In this demo, we will be using Vitess Operator. Let’s look at the various prerequisites that are required to set up MySQL on a Kubernetes cluster.
Prerequisites
- A running Kubernetes cluster
- kubectl CLI configured with cluster access
- Persistent storage provider configured (e.g., CSI driver)
- Install the MySQL client locally
- Install vtctldclient locally
With these prerequisites, you are ready to deploy MySQL on Kubernetes.
Choosing the Right Kubernetes Distribution
MySQL can run on any CNCF-certified Kubernetes distribution, but its deployment depends on your infrastructure and business requirements. It supports major Kubernetes distributions, including EKS, GKE, AKS, and self-managed Kubernetes clusters.
Running MySQL on Kubernetes
By leveraging Kubernetes’ orchestration capabilities, teams can simplify the deployment and management of MySQL instances while ensuring high availability and performance by carefully considering the following factors.
Proper Worker Configuration
To optimize MySQL’s performance on Kubernetes, it is essential to configure worker nodes appropriately. MySQL can be resource-intensive, particularly in terms of memory and CPU usage. Therefore, provisioning nodes with sufficient resources is crucial. Consider the following best practices:
- Taints and Tolerations: Use taints and tolerations to schedule MySQL pods on nodes that are specifically optimized for database workloads.
- Pod Affinity: Implement pod affinity rules to distribute MySQL instances across different fault domains, enhancing resilience against node failures.
Reliable Container Storage and Data Management
MySQL requires a robust storage solution to manage its persistent data effectively. Portworx offers an ideal environment for stateful applications like MySQL. Key features include:
- Dynamic Storage Provisioning: Portworx allows for the automatic provisioning of storage volumes based on the needs of the MySQL deployment.
- Database-Optimized Storage Classes: With Portworx, you can create storage classes tailored for MySQL workloads, ensuring optimal performance through I/O profiles and SSD utilization.
Data Security
Databases like MySQL handle sensitive information so built-in security features such as SSL encryption for data in transit and user authentication will only give your application basic security. Portworx enhances data security by providing the following:
- Granular Access Controls: Implement Role-Based Access Control (RBAC) at the storage level with Portworx to manage who can access or modify data.
- Integration with Key Management Systems: For organizations requiring stringent compliance measures, Portworx integrates with external key management systems to manage encryption keys securely.
- Encryption at rest: Data encryption is critical and the basic features provided by MySQL are not enough to secure your data. Portworx’s encryption features utilizing the AES-256 cipher help safeguard your data.
Data Protection & Disaster Recovery
A robust disaster recovery strategy is essential for maintaining zero application downtime when running MySQL on Kubernetes. Portworx provides powerful tools for data protection and disaster recovery:
- Automated Backups: With Portworx, you can schedule automated backups of your MySQL databases to ensure that data can be restored quickly in case of failure.
- Cross-Cluster Replication: Portworx supports cross-cluster replication, allowing you to replicate your MySQL data across different Kubernetes clusters for enhanced availability.
MySQL Deployment Strategies on Kubernetes
Deploying MySQL instances on the Kubernetes platform has transformed how we think about database management. Whether you’re managing a high-availability multi-node cluster or a single-node MySQL instance, Kubernetes offers built-in resources and strategies for ensuring smooth operation. Let’s look at some crucial strategies for ensuring the MySQL setup grows in a Kubernetes environment.
Single-node MySQL Deployment
This deployment strategy is ideal for development or testing environments, small applications, or scenarios where high availability is not a priority. In this method, MySQL is put in a single pod, which reduces complexity while utilizing Kubernetes’ scalability as required. It provides simple management and quick setup, but it costs high availability and redundancy.
Multi-node MySQL Cluster Deployment
When production environments require high availability and enhanced read scalability, a multi-node cluster deployment is the best option. This strategy involves setting up a primary MySQL server that has write access and one or more read replicas. This allows distributing workload over many pods ensuring high availability and fault tolerance. It requires more resources and thoughtful handling to avoid conflicts.
Using StatefulSets for MySQL
StatefulSets are ideal for deploying stateful applications like MySQL because they provide stable, unique network identities, data consistency, and persistent storage across pod rescheduling. StatefulSets simplifies MySQL cluster management by handling pod scaling and storage provisioning, making it a robust choice for production environments. Their stable replication and smooth failover mechanisms make them ideal for multi-node MySQL deployments.
Configuring Persistent Storage
MySQL databases require persistent storage to ensure data integrity during pod restarts or rescheduling. Kubernetes typically manages persistent storage using Persistent Volumes (PVs) and Persistent Volume Claims (PVCs). PVs provide long-term storage for PostgreSQL data, independent of the pod lifecycle, retaining data across pod rescheduling or failures. PVCs link these volumes to PostgreSQL pods, ensuring that each instance can access its storage consistently and maintaining data reliability and durability in dynamic environments.
Pod Affinity and Anti-Affinity Rules
Managing performance and resilience in Kubernetes involves the strategic placement and configuration of pods. Affinity rules position MySQL pods close to application pods, helping reduce network latency and accelerating database query processing. Conversely, anti-affinity rules ensure that MySQL pods are distributed across different nodes, minimizing the impact of potential failures and optimizing resource utilization. This dual strategy not only enhances performance by lowering latency but also boosts availability and resilience, ensuring that the system remains robust and scalable under varying load conditions.
Benefits of MySQL on Kubernetes
Running MySQL on Kubernetes merges MySQL’s reliability with Kubernetes’ scalability and automation features. This configuration enables dynamic resource adjustments based on workload demands, optimizing resource use and lowering costs. Kubernetes enhances high availability with self-healing and failover mechanisms, ensuring quick pod restarts on healthy nodes to minimize downtime. Moreover, this integration simplifies updates with minimal disruption and offers portability across cloud and on-premises environments, making MySQL database management more flexible and efficient for modern containerized applications.
How to Configure MySQL on Kubernetes
Here are some of the important configurations to help you optimize your MySQL deployment on Kubernetes.
MySQL Configuration Options
The Vitess operator and MySQL can be installed by cloning the Vitess repository and following the below steps. We have used the latest stable version, Vitess-21.0 in this demo.
``` git clone https://github.com/vitessio/vitess cd vitess/examples/operator git checkout release-21.0 ```
Install Vitess operator
``` kubectl apply -f operator.yaml customresourcedefinition.apiextensions.k8s.io/etcdlockservers.planetscale.com created customresourcedefinition.apiextensions.k8s.io/vitessbackups.planetscale.com created customresourcedefinition.apiextensions.k8s.io/vitessbackupschedules.planetscale.com created customresourcedefinition.apiextensions.k8s.io/vitessbackupstorages.planetscale.com created customresourcedefinition.apiextensions.k8s.io/vitesscells.planetscale.com created customresourcedefinition.apiextensions.k8s.io/vitessclusters.planetscale.com created customresourcedefinition.apiextensions.k8s.io/vitesskeyspaces.planetscale.com created customresourcedefinition.apiextensions.k8s.io/vitessshards.planetscale.com created serviceaccount/vitess-operator created role.rbac.authorization.k8s.io/vitess-operator created rolebinding.rbac.authorization.k8s.io/vitess-operator created priorityclass.scheduling.k8s.io/vitess created priorityclass.scheduling.k8s.io/vitess-operator-control-plane created deployment.apps/vitess-operator created ```
As a part of operator installation, a `vitess-operator deployment`, `replicaset`, `role`, `rolebinding`, `serviceaccount` are created in the `default` namespace. Further, we will deploy the Vitess cluster, which deploys MySQL as a part of the Vitess cluster itself. Vitess manages the MySQL instances and abstracts them into a distributed database system.
The Vitess operator official guide provides the sample configuration in 101_initial_cluster.yaml file for deploying MySQL cluster using the default storageClass.
```kubectl apply -f 101_initial_cluster.yaml vitesscluster.planetscale.com/example configured secret/example-cluster-config configured ```
List the pods created to verify the deployment was successful.
```kubectl get pods NAME READY STATUS RESTARTS AGE example-commerce-x-x-zone1-vtorc-c13ef6ff-69bf74845b-22dpn 1/1 Running 0 5h28m example-etcd-faf13de3-1 1/1 Running 0 5h28m example-etcd-faf13de3-2 1/1 Running 0 5h28m example-etcd-faf13de3-3 1/1 Running 0 5h28m example-vttablet-zone1-2469782763-bfadd780 3/3 Running 1 (5h26m ago) 5h28m example-vttablet-zone1-2548885007-46a852d0 3/3 Running 1 (5h27m ago) 5h28m example-zone1-vtadmin-c03d7eae-664c7568d6-59hv6 2/2 Running 0 5h28m example-zone1-vtctld-1d4dcad0-7674ffbdfd-mrsnj 1/1 Running 0 5h28m example-zone1-vtgate-bc6cde92-79564bb58d-h25cl 1/1 Running 0 5h28m vitess-operator-7cc877ccc5-c8jnx 1/1 Running 0 5h56m ```
You should see the `vitess-operator-xxxxx` pod created for the deployment. We will explain further parts in the coming sections.
Setting Up MySQL Credentials
Vitess has its own mechanism for managing users and their permissions. It is done through the VTGate. VTGate supports multiple types of authentication. This example uses static file-based authentication as mentioned in 101_initial_cluster.yaml. The configured secret users.json provides credentials and init_db.sql has a MySQL initialization script. You can check the full configuration of init_db.sql in 101_initial_cluster.yaml as shown below.
```
apiVersion: v1
kind: Secret
metadata:
name: example-cluster-config
Namespace: default
type: Opaque
stringData:
users.json: |
{
"user": [{
"UserData": "user",
"Password": "password"
}]
}
init_db.sql: |
```
This would create a secret with an `example-cluster-config` name in the `default` namespace along with a few others which are used for managing and connecting to the Vitess cluster, to discover the services in the zone dynamically and web interface configuration.
Check the secrets created:
``` kubectl get secret NAME TYPE DATA AGE example-cluster-config Opaque 3 16m example-zone1-vtadmin-clusterconfig-a6b6280c Opaque 1 16m example-zone1-vtadmin-discovery-26fba126 Opaque 1 16m example-zone1-vtadmin-webconfig-1c814ad7 Opaque 1 16m ```
Configuring MySQL Heap Size
MySQL heap size controls memory allocation for MySQL server, which is used for working memory, buffer cache, and query operations. For optimal performance, it is recommended to set the heap size to 30-50% of available memory. Heap size in Vitess configuration is defined as `mysqld` resources under `shardTemplate` in 101_initial_cluster.yaml.
```
mysqld:
# Heap Size: Control memory allocation for MySQL server (mysqld)
resources:
limits:
memory: 1024Mi
requests:
cpu: 100m # CPU request for mysqld
memory: 512Mi
```
Configuring Shards and Replicas
Vitess supports horizontal scaling through shards and replicas, allowing users to distribute data across multiple nodes and make it fault-tolerant.
Configuring Shards: Shards are configured under `keyspaces`, named `commerce` in 101_initial_cluster.yaml. Additionally, each shard has 2 replicas which ensure the high availability, redundancy and improved read performance. Replicas and Shards are carefully allocated with heap size, explained above, for reliability and efficiency.
```
partitionings:
- equal:
parts: 1
```
A shard is a subset of a keyspace (logical database), designed to distribute data across multiple MySQL instances for horizontal scaling. With `parts: 1`, all the data in the `commerce` keyspace is stored in a single shard.
Shard-Specific Configurations:
When shards are created, databaseInitScriptSecret (init_db.sql, also a part of 101_initial_cluster.yaml) script is run in the shard to set up Vitess metadata tables, initial user and privileges. This is defined in the `shardTemplate`.
Configuring Replicas: The replicas in MySQL mirror the primary data in shard for read-only access and redundancy. Replicas allow high availability, distribute read traffic, and help in backups and analytics without affecting primary data.
Replica configured in 101_initial_cluster.yaml
```yaml tabletPools: - cell: zone1 type: replica replicas: 2 ```
Using `replicas: 2`, two replicas are defined for each shard.
Replica-Specific Configurations:
To allocate the resources appropriately, memory and CPU requests/limits are defined for `vttablet` and `mysqld` in 101_initial_cluster.yaml. Each replica uses 10Gi of persistent volume created with dataVolumeClaimTemplate for storing data.
```yaml
vttablet:
extraFlags:
db_charset: utf8mb4
resources:
limits:
memory: 256Mi
requests:
cpu: 100m
memory: 256Mi
mysqld:
resources:
limits:
memory: 1024Mi
requests:
cpu: 100m
memory: 512Mi
dataVolumeClaimTemplate:
accessModes: ["ReadWriteOnce"]
resources:
requests:
storage: 10Gi
```
Data is stored in a single shard in the `commerce` keyspace, which has 2 read-only replicas in the `zone1` cell which provides load balancing for read-only queries and redundancy. If the primary shard fails, one of the two replicas is promoted as primary, avoiding failover and maintaining availability.
However, this configuration is not scalable horizontally, since we have defined only one shard. To distribute the data in multiple shards, i.e. horizontally, increase the value of the `parts` in the partitioning section.
Configuring Network Settings
For ease of use, Vitess provides a script to port forward from Kubernetes to your local machine. This script also recommends setting up aliases for MySQL and `vtctldclient`:
``` ./pf.sh & alias vtctldclient="vtctldclient --server=localhost:15999" alias mysql="mysql -h 127.0.0.1 -P 15306 -u user" ```
pf.sh file is also available in the cloned repository.
Make sure you are on the branch specific to the Vitess version you have installed.
Once the port forward starts, the VTAdmin UI will be available at http://localhost:14000/
You can check the number of shards and replicas by logging into vtctld pod and running the following command.
```kubectl exec -it example-zone1-vtctld-1d4dcad0-7674ffbdfd-mrsnj -- bash```
Run the following command in the pod.
``` vtctldclient --server <vtctld_host>:15999 GetTablets zone1-2469782763 commerce - replica 10.244.2.10:15000 10.244.2.10:3306 [] <null> zone1-2548885007 commerce - primary 10.244.1.8:15000 10.244.1.8:3306 [] 2024-11-18T06:55:36Z ```
The output should look similar to the above if you have only one shard. Notice the primary and replica in the output. Each shard should have a primary tablet (replica) and replicas represent one or more tablets (replica). Further, you can utilize the locally installed MySQL and `vtctldclient` to create schema and connect to MySQL. Refer to this official documentation here.
Monitoring MySQL on Kubernetes
Monitoring MySQL with Vitess is crucial for maintaining MySQL performance and scalability in large, sharded environments. It enables visibility into resource utilization, query performance, and cluster health, ensuring smooth operations and proactive issue resolution. Vitess components can be accessed by pointing your browser to http://
- Scaling Insights: Monitor QPS, replication lag, and shard load for horizontal scaling.
- Performance Metrics: Track query execution, VTGate routing, and tablet health.
- Health Monitoring: Identify unhealthy tablets, replication issues, or cluster bottlenecks.
- Resource Optimization: Monitor memory, CPU, and disk usage to optimize resources.
- Cluster Overview: Gain shard-level insights and component statuses for VTGate, VTTablet, and VTAdmin.
Vitess Monitoring Documentation can be referred here.
Day 2 Operations for MySQL on Kubernetes
For databases like MySQL, a strategic approach is necessary to address potential failures and enhance overall operations, ensuring that the database remains reliable, efficient, and resilient during Day 2 operations.
Handling Node Failures
Portworx offers robust storage solutions that enable automatic failover and high availability for MySQL clusters. With Portworx’s capabilities, data is synchronously replicated across nodes, allowing for seamless recovery from node failures. You can configure a storageClass as shown below.
``` apiVersion: storage.k8s.io/v1 kind: StorageClass metadata: name: portworx-mysql-sc provisioner: pxd.portworx.com parameters: io_profile: db_remote repl: "3" io_priority: "high" allowVolumeExpansion: true reclaimPolicy: Delete volumeBindingMode: Immediate ```
This way, you can ensure that your MySQL service can quickly resume operations with minimal downtime and data loss, maintaining business continuity even in the face of unforeseen incidents.
Scaling MySQL Cluster
As the demand for data grows, scaling your MySQL cluster becomes essential to accommodate increasing workloads without downtime. Portworx features like Autopilot can easily help you automate the resize of Persistent Volume Claims (PVCs) when they approach capacity limits or expand storage pools to meet heightened usage demands. For detailed guidance on managing these scaling operations effectively, refer to Portworx’s resources on scaling MySQL on Kubernetes.
How to Secure MySQL on Kubernetes
To secure MySQL on Kubernetes, a multi-layered approach that combines network isolation, encryption, and access control is essential for protecting the database.
- Network Policies: Implementing Network Policies defines rules that restrict which pods can communicate with MySQL instances, effectively limiting exposure to potential threats and ensuring that only trusted services can access the database.
- Securing Communication with TLS: TLS for data in transit ensures that sensitive information is encrypted, preventing eavesdropping and tampering during communication between clients and the MySQL server.
- Role-Based Access Control (RBAC): RBAC allows for precise management of permissions within the Kubernetes cluster, ensuring that only authorized users can access the MySQL database and perform actions, minimizing the risk of unauthorized access and enhancing overall security.
Securing Data at Rest
Portworx offers robust capabilities for securing data at rest, primarily through its encryption features. Utilizing the AES-256 cipher in xts-plain64 mode, Portworx ensures that all data stored within volumes is protected against unauthorized access.
Additionally, Portworx integrates seamlessly with various secret management solutions, such as Kubernetes Secrets and cloud provider key management services, allowing for secure storage of encryption keys. Users can easily enable encryption at the Persistent Volume Claim (PVC) level through annotations and storage class configurations.
MySQL Backup and Restore Strategies
Effective backup and restore strategies are crucial to ensure data integrity and availability for MySQL databases running on Kubernetes. Capitalizing on Portworx’s capabilities can substantially enhance these processes. Here are some key approaches to consider:
Snapshot and Restore
Portworx provides an efficient snapshot and restore capability that enables point-in-time backups of MySQL databases. These snapshots are lightweight, can be taken almost instantly, without affecting performance, and allow for quick restoration in case of data corruption or failures.
Using Volume Snapshots
Portworx integrates with Kubernetes’ native VolumeSnapshot API to create and manage snapshots of persistent volumes used by MySQL. This ensures consistent backups and easy restoration of databases to previous states. Volume snapshots can be stored across different storage backends for flexibility.
Automating Backups
Portworx allows MySQL backup automation with scheduled policies, ensuring regular, hands-free backups. It supports incremental backups to optimize storage and bandwidth usage, making the process efficient. You can create on-demand snapshots of your MySQL volumes using PX-Backup or through native Portworx Enterprise commands. Refer to our documentation on creating cloud backups.
Best Practices for Running MySQL on Kubernetes
By leveraging cloud-native architecture with Kubernetes, it has transformed the deployment and management of containerized applications including databases like MySQL. However, operating MySQL in Kubernetes environments to realize its full potential requires careful implementation and adherence to best practices to address challenges.
Regular Updates and Patching
Regular updates and patching ensure that you have access to the latest features, performance improvements, and security fixes, as well as the ability to leverage the latest Kubernetes features and security enhancements.
It is recommended to establish automated update processes using tools such as Helm charts or Operators. These tools can handle rolling updates while minimizing downtime. Kubernetes gets rapid development, demanding updates to its components, including the API server, kubelet, etcd, to ensure compatibility with the MySQL deployment model.
Resource Quotas and Limits
Proper resource management is critical to ensuring the reliability and performance of a Kubernetes cluster running MySQL pods. Setting CPU and memory quotas and limits for MySQL pods ensures that it has the resources it needs while preventing it from consuming too many resources, which could impact performance. Tools such as Prometheus, Grafana, or Kubernetes Metrics Server also help in monitoring resource consumption.
Effective Use of Namespaces
Namespaces in Kubernetes offer a method for organizing and isolating MySQL workloads, thereby simplifying the management of multi-tenant environments or the separation of environments such as development, staging, and production. When running MySQL instances, consider using these recommended practices:
- Use namespaces to differentiate between distinct MySQL instances or environments (e.g., development, staging, production).
- Set resource quotas at the namespace level to prevent MySQL instances from using all of the cluster resources.
- Utilize network policies within namespaces to regulate the passage of traffic to and from MySQL pods, thereby improving security.
Keeping Configuration Consistent
Ensuring consistent configurations throughout the MySQL deployment provides error-free operations, seamless scaling, and replicability.
- When managing MySQL configuration files and sensitive data in Kubernetes, make sure to save them in the Kubernetes ConfigMaps and Secrets. This approach ensures their encryption while at rest.
- Use version management tools to handle Kubernetes manifests, Helm charts, or custom operators like Git.
- Conduct periodic audits on the deployed MySQL setup to ensure it meets consistent organizational or business guidelines and adheres to Kubernetes and security requirements.
Following these best practices and standards will result in a robust, secure, and efficient MySQL implementation in the Kubernetes environment. Remember that these practices and recommendations can be tailored to unique objectives and use cases.
Get Started Running Data and MySQL on Kubernetes
Running MySQL on Kubernetes can unlock greater flexibility and data resiliency, but it requires the right storage solution. Container-native storage and database platform solutions like Portworx are purpose-built for Kubernetes environments. To simplify database and storage operations on Kubernetes, get started and try Portworx for free