When deployed in Kubernetes, Cassandra needs an underlying data store that won’t disappear whenever the pod is rescheduled or destroyed. Cassandra offers tunable consistency – eventual and string consistency – to meet this need.
To get started, use the Cassandra operator – a helm chart that lets you deploy the Cassandra cluster and its related tools in one shot. Then, discover what makes it a good fit for Kubernetes.
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Scalability
Cassandra is an extremely scalable database system that can easily manage a huge amount of data. This feature makes it a perfect choice for companies that experience seasonal peaks, such as those that conduct online shopping. It can handle the sudden influx of visitors without shutting down and redeploying applications. It also enables businesses to reduce cloud computing costs using only the needed resources.
It is a fault-tolerant system because of its data replication feature. This capability enables it to store the same data at multiple locations or nodes, ensuring it is highly available. If one of these locations or nodes experiences a failure, the remaining sites can still retrieve the information. This self-healing is critical for e-commerce applications, where every visitor counts.
In addition, the scalability of Cassandra Kubernetes is a result of its container-based architecture. This eliminates the need for a dedicated server to run a Cassandra instance and ensures the cluster has adequate resources to handle the load. You can scale your Cassandra instances vertically and horizontally and configure dedicated node pools. The apigee-data-node-pool has a default replica count of three, which can be adjusted by changing the value in the config file.
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Reliability
The reliability of Apache Cassandra is a key feature that helps companies like Apple, Netflix, CapitalOne, and McDonald’s keep their data accurate. It distributes data across multiple nodes and uses a masterless system, so one failed node does not affect overall performance. It also performs live backups, so you can get back up and running quickly if one or more of your data centers is down.
However, deploying and running Cassandra on Kubernetes can be complex. You must understand how to deploy the database in a multi-datacenter setup, configure your replication settings, and optimize read performance. In addition, you must be familiar with the CQL Query Language.
Fortunately, several tools now make it easier to run Cassandra on Kubernetes. These include the open-source Cassandra operator and the management API sidecar.
These tools allow you to install a Cassandra container image in a Kubernetes cluster and then create PersistentVolumes for the container. To do this, you must have at least 10 GB of storage on the host machine where the containers will be running. Then, you can use a YAML file to specify the Cassandra image and location of the PersistentVolumes.
These tools are designed to automate the deployment and maintenance of Cassandra on Kubernetes, but you must still be familiar with the operating system requirements and database functions. You should also know how to monitor and troubleshoot Cassandra using cqlsh, the command-line shell.
Security
Cassandra uses a distributed database architecture and uses replication to store data across multiple data centers. This enables users to recover data from a failed node or site without downtime. Cassandra is a great choice for businesses that experience seasonal traffic surges and e-commerce websites.
To prevent data loss, a Cassandra cluster has several layers of security. It uses SSL encryption to secure communications between a client and a database and between the nodes in the cluster. It also allows for independent configuration of node-to-node and client-to-node encryption. The encryption feature ensures that data in flight is not exposed to hackers.
The database also has a cache to improve read performance. It stores some data in RAM, known as MemTable, and saves the rest to disk as SSTable.
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Performance
Cassandra is a distributed database, meaning multiple copies of data are stored across the cluster. This allows it to handle a high level of concurrent read and write requests. In addition, if a node fails, other nodes will continue to function and replicate the data from the failed node to the remaining ones. This prevents data loss and enables the database to recover quickly.
Bringing Cassandra into Kubernetes requires an underlying database that can handle the ephemerality of pods. Without losing data, it must survive multiple pod deletions, reschedules, and replacements. Luckily, there are several options available to meet these needs. The goal is to deploy Cassandra as a single helm chart, which can be done with various open-source and commercial solutions.
One option is to use the open-source K8ssandra operator. This cloud-native distribution of Apache Cassandra provides a complete suite of operational tools. It includes dashboards, metrics, data anti-entropy services, and backup tools. Additionally, it includes a tool to deploy and wire together the components of a Cassandra cluster. It also simplifies the deployment of Cassandra within Kubernetes, freeing teams from performing the tedious plumbing work.