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Cassandra-on-Kubernetes-A-Beginners-Guide blog
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commit d59bbab0240852d0681c2bbfbdeeb0a43f6b43b4
Author: mck <m...@apache.org>
AuthorDate: Tue Sep 7 18:10:35 2021 +0200
ninja-fix: date and apostrophe on Cassandra-on-Kubernetes-A-Beginners-Guide
blog
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-= Cassandra on Kubernetes: A Beginner's Guide
-:page-layout: single-post
-:page-role: blog-post
-:page-post-date: August 27, 2020
-:page-post-author: The Apache Cassandra Community
-:description: The Apache Cassandra Community
-:keywords:
-
-Kubernetes is a hot technology, and while it seems like everyone is using it
for automating deployment, scaling, and management of containerized
applications, you’ll still face fundamental issues as you try to grow from a
beginner to an intermediate Kubernetes Operator. One of these hurdles is the
storage and control of data.
-
-=== Where and how to store Kubernetes data
-Kubernetes is an amazingly flexible and robust way to host stateless
computation, but the data layer isn’t a straightforward solution. Traditionally
computation would happen within a cluster, with every container in that cluster
requesting and updating data from a traditionally stored database.
-
-Running applications in Kubernetes with databases external to Kubernetes
creates a mismatched architecture. This situation has limited developer
productivity, duplicative stacks for monitoring applications and database
infrastructure, and increased cloud computing costs.
-
-=== What is Cassandra?
-Apache Cassandra is an open source NoSQL distributed database trusted by
thousands of companies for scalability and high availability without
compromising performance. Linear scalability and proven fault tolerance on
commodity hardware or cloud infrastructure make it the perfect platform for
mission-critical data. The latest version of Apache Cassandra
-
-Cassandra merges the ease-of-use of NoSQL with the reliability of a mature
open source project. Most importantly, for real-world applications, it’s
designed with distributed architectures in mind.
-
-"Distributed" means Cassandra can run on multiple machines while appearing to
users as a unified whole. There is little point in running Cassandra as a
single node, although it is constructive to help you get up to speed on how it
works. But to get the maximum benefit out of Cassandra, you would run it on
multiple machines.
-
-=== Apache Cassandra and Kubernetes
-Kubernetes has emerged as the leading orchestration platform for deploying and
managing containerized systems in the cloud. Since managing infrastructure has
been standardizing around Kubernetes, many organizations are looking at the
data plane as something that should be managed under the same umbrella.
-
-Kubernetes simplifies distributed systems lifecycle management. It’s natural
to use Kubernetes to build your flexible, distributed database with Cassandra.
-
-=== The Challenge of Kubernetes: Complexity
-Kubernetes enables you to auto-scale whole containers: providing resources and
spinning up new instances, along with load balancing, but without careful
management: rather than removing the complexity of managing loads and
containers, Kubernetes can increase the complexity of a system, making it even
harder to manage.
-
-Running Cassandra on Kubernetes can be difficult. Kubernetes has only a
limited understanding or insight into database functionality. It is blind to
key operational requirements of the database that’s in use and it requires
significant effort to script and leverage existing Kubernetes functionality to
run a production-grade Cassandra deployment.
-
-To reduce those complexities, the Apache Cassandra community built
https://github.com/datastax/cass-operator[Cass Operator,window=_blank], which
is installed via Helm (see below). Operators take the process of describing
many of the lower-level Kubernetes components and instead provide a more
straightforward, logical interface for describing an application. They provide
a translation layer between what Kubernetes needs to maintain services and the
actual implementation by the database.
-
-There are multiple Kubernetes operators to try and solve the same problem,
including those from
https://www.instaclustr.com/products/cassandra-kubernetes-operator/[Instaclustr,window=_blank]
and https://github.com/sky-uk/cassandra-operator[Sky UK,window=_blank], but
the Cassandra community has coalesced around Cass Operator and is
https://cassandra.apache.org/blog/Cassandra-and-Kubernetes-SIG-Update-2.html[merging
features from other operators, such as CassKop], which Orange developed.
-
-As with any Kubernetes operator, the goal is to create a robot that makes it
easier to set up, maintain, and scale complex configurations of containers in
Kubernetes.
-
-=== How to simplify deployment: Apache Cassandra as a Helm Chart
-Helm is a package manager for Kubernetes. Helm is the Kubernetes’ equivalent
of yum or apt. Helm deploys charts, which you can think of like a packaged
application. It is a collection of all your versioned, pre-configured
application resources, which can be deployed as one unit.
-
-The goal when adopting Cassandra on Kubernetes should be to deploy it as a
single helm chart. There are many
https://bitnami.com/stack/cassandra/helm[options here from multiple
vendors,window=_blank], and the open source K8ssandra project is one of many
but in active development having reached v1.3, which supports the new Apache
Cassandra 4.0 GA.
-
-=== What is K8ssandra?
-https://k8ssandra.io[K8ssandra,window=_blank] is a cloud native, open source
distribution of Apache Cassandra that runs on Kubernetes. Accompanying
Cassandra is a suite of tools to ease and automate operational tasks, which
includes metrics, data anti-entropy services for running repairs, and backup
tooling. As part of K8ssandra’s installation process, all of these components
are installed and wired together and frees your teams from performing the
tedious plumbing of components.
-
-Apache Cassandra can be deployed in many environments, including bare-metal
hosts, virtual machines, and container platforms. Each deployment type has its
pros and cons, but in all cases automation is leveraged to ensure that all
nodes are configured homogeneously and without failure.
-
-=== Operator Problems
-Site reliability engineering (SRE) expertise remains an essential resource for
running distributed workloads. Challenges such as configuring throttles and
scheduling backups, and managing edge case failures, for example concurrent
socket problems, are all things that are not currently covered by automation.
-
-While the tools available from multiple vendors for Kubernetes can simplify
the process for deploying new workloads, you will still need a team that is
excited to increase their Kubernetes expertise.
-
-The particular tools you choose for solving the ‘data on Kubernetes’ problem
will be your own, but the good news is that there are viable solutions from
both the open source community around Apache Cassandra, and even fully-featured
SaaS products that will spin up your cluster and handle data problems for you.
+= Cassandra on Kubernetes: A Beginners Guide
+:page-layout: single-post
+:page-role: blog-post
+:page-post-date: September 4, 2021
+:page-post-author: The Apache Cassandra Community
+:description: The Apache Cassandra Community
+:keywords:
+
+Kubernetes is a hot technology, and while it seems like everyone is using it
for automating deployment, scaling, and management of containerized
applications, you’ll still face fundamental issues as you try to grow from a
beginner to an intermediate Kubernetes Operator. One of these hurdles is the
storage and control of data.
+
+=== Where and how to store Kubernetes data
+Kubernetes is an amazingly flexible and robust way to host stateless
computation, but the data layer isn’t a straightforward solution. Traditionally
computation would happen within a cluster, with every container in that cluster
requesting and updating data from a traditionally stored database.
+
+Running applications in Kubernetes with databases external to Kubernetes
creates a mismatched architecture. This situation has limited developer
productivity, duplicative stacks for monitoring applications and database
infrastructure, and increased cloud computing costs.
+
+=== What is Cassandra?
+Apache Cassandra is an open source NoSQL distributed database trusted by
thousands of companies for scalability and high availability without
compromising performance. Linear scalability and proven fault tolerance on
commodity hardware or cloud infrastructure make it the perfect platform for
mission-critical data. The latest version of Apache Cassandra
+
+Cassandra merges the ease-of-use of NoSQL with the reliability of a mature
open source project. Most importantly, for real-world applications, it’s
designed with distributed architectures in mind.
+
+"Distributed" means Cassandra can run on multiple machines while appearing to
users as a unified whole. There is little point in running Cassandra as a
single node, although it is constructive to help you get up to speed on how it
works. But to get the maximum benefit out of Cassandra, you would run it on
multiple machines.
+
+=== Apache Cassandra and Kubernetes
+Kubernetes has emerged as the leading orchestration platform for deploying and
managing containerized systems in the cloud. Since managing infrastructure has
been standardizing around Kubernetes, many organizations are looking at the
data plane as something that should be managed under the same umbrella.
+
+Kubernetes simplifies distributed systems lifecycle management. It’s natural
to use Kubernetes to build your flexible, distributed database with Cassandra.
+
+=== The Challenge of Kubernetes: Complexity
+Kubernetes enables you to auto-scale whole containers: providing resources and
spinning up new instances, along with load balancing, but without careful
management: rather than removing the complexity of managing loads and
containers, Kubernetes can increase the complexity of a system, making it even
harder to manage.
+
+Running Cassandra on Kubernetes can be difficult. Kubernetes has only a
limited understanding or insight into database functionality. It is blind to
key operational requirements of the database that’s in use and it requires
significant effort to script and leverage existing Kubernetes functionality to
run a production-grade Cassandra deployment.
+
+To reduce those complexities, the Apache Cassandra community built
https://github.com/datastax/cass-operator[Cass Operator,window=_blank], which
is installed via Helm (see below). Operators take the process of describing
many of the lower-level Kubernetes components and instead provide a more
straightforward, logical interface for describing an application. They provide
a translation layer between what Kubernetes needs to maintain services and the
actual implementation by the database.
+
+There are multiple Kubernetes operators to try and solve the same problem,
including those from
https://www.instaclustr.com/products/cassandra-kubernetes-operator/[Instaclustr,window=_blank]
and https://github.com/sky-uk/cassandra-operator[Sky UK,window=_blank], but
the Cassandra community has coalesced around Cass Operator and is
https://cassandra.apache.org/blog/Cassandra-and-Kubernetes-SIG-Update-2.html[merging
features from other operators, such as CassKop], which Orange developed.
+
+As with any Kubernetes operator, the goal is to create a robot that makes it
easier to set up, maintain, and scale complex configurations of containers in
Kubernetes.
+
+=== How to simplify deployment: Apache Cassandra as a Helm Chart
+Helm is a package manager for Kubernetes. Helm is the Kubernetes’ equivalent
of yum or apt. Helm deploys charts, which you can think of like a packaged
application. It is a collection of all your versioned, pre-configured
application resources, which can be deployed as one unit.
+
+The goal when adopting Cassandra on Kubernetes should be to deploy it as a
single helm chart. There are many
https://bitnami.com/stack/cassandra/helm[options here from multiple
vendors,window=_blank], and the open source K8ssandra project is one of many
but in active development having reached v1.3, which supports the new Apache
Cassandra 4.0 GA.
+
+=== What is K8ssandra?
+https://k8ssandra.io[K8ssandra,window=_blank] is a cloud native, open source
distribution of Apache Cassandra that runs on Kubernetes. Accompanying
Cassandra is a suite of tools to ease and automate operational tasks, which
includes metrics, data anti-entropy services for running repairs, and backup
tooling. As part of K8ssandra’s installation process, all of these components
are installed and wired together and frees your teams from performing the
tedious plumbing of components.
+
+Apache Cassandra can be deployed in many environments, including bare-metal
hosts, virtual machines, and container platforms. Each deployment type has its
pros and cons, but in all cases automation is leveraged to ensure that all
nodes are configured homogeneously and without failure.
+
+=== Operator Problems
+Site reliability engineering (SRE) expertise remains an essential resource for
running distributed workloads. Challenges such as configuring throttles and
scheduling backups, and managing edge case failures, for example concurrent
socket problems, are all things that are not currently covered by automation.
+
+While the tools available from multiple vendors for Kubernetes can simplify
the process for deploying new workloads, you will still need a team that is
excited to increase their Kubernetes expertise.
+
+The particular tools you choose for solving the ‘data on Kubernetes’ problem
will be your own, but the good news is that there are viable solutions from
both the open source community around Apache Cassandra, and even fully-featured
SaaS products that will spin up your cluster and handle data problems for you.
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