Chapter 1. Overview of AMQ Streams

AMQ Streams simplifies the process of running Apache Kafka in an OpenShift cluster.

1.1. Kafka capabilities

The underlying data stream-processing capabilities and component architecture of Kafka can deliver:

  • Microservices and other applications to share data with extremely high throughput and low latency
  • Message ordering guarantees
  • Message rewind/replay from data storage to reconstruct an application state
  • Message compaction to remove old records when using a key-value log
  • Horizontal scalability in a cluster configuration
  • Replication of data to control fault tolerance
  • Retention of high volumes of data for immediate access

1.2. Kafka use cases

Kafka’s capabilities make it suitable for:

  • Event-driven architectures
  • Event sourcing to capture changes to the state of an application as a log of events
  • Message brokering
  • Website activity tracking
  • Operational monitoring through metrics
  • Log collection and aggregation
  • Commit logs for distributed systems
  • Stream processing so that applications can respond to data in real time

1.3. How AMQ Streams supports Kafka

AMQ Streams provides container images and Operators for running Kafka on OpenShift. AMQ Streams Operators are fundamental to the running of AMQ Streams. The Operators provided with AMQ Streams are purpose-built with specialist operational knowledge to effectively manage Kafka.

Operators simplify the process of:

  • Deploying and running Kafka clusters
  • Deploying and running Kafka components
  • Configuring access to Kafka
  • Securing access to Kafka
  • Upgrading Kafka
  • Managing brokers
  • Creating and managing topics
  • Creating and managing users

1.4. Operators

AMQ Streams provides Operators for managing a Kafka cluster running within an OpenShift cluster.

Cluster Operator
Deploys and manages Apache Kafka clusters, Kafka Connect, Kafka MirrorMaker, Kafka Bridge, Kafka Exporter, and the Entity Operator
Entity Operator
Comprises the Topic Operator and User Operator
Topic Operator
Manages Kafka topics
User Operator
Manages Kafka users

The Cluster Operator can deploy the Topic Operator and User Operator as part of an Entity Operator configuration at the same time as a Kafka cluster.

Operators within the AMQ Streams architecture

Operators

1.5. AMQ Streams installation methods

There are two ways to install AMQ Streams on OpenShift.

Installation methodDescriptionSupported versions

Installation artifacts (YAML files)

Download the amq-streams-x.y.z-ocp-install-examples.zip file from the AMQ Streams download site. Next, deploy the YAML installation artifacts to your OpenShift cluster using oc. You start by deploying the Cluster Operator from install/cluster-operator to a single namespace, multiple namespaces, or all namespaces.

OpenShift 3.11 and later

OperatorHub

Use the AMQ Streams Operator in the OperatorHub to deploy the Cluster Operator to a single namespace or all namespaces.

OpenShift 4.x only

For the greatest flexibility, choose the installation artifacts method. Choose the OperatorHub method if you want to install AMQ Streams to OpenShift 4 in a standard configuration using the OpenShift 4 web console. The OperatorHub also allows you to take advantage of automatic updates.

In the case of both methods, the Cluster Operator is deployed to your OpenShift cluster, ready for you to deploy the other components of AMQ Streams, starting with a Kafka cluster, using the YAML example files provided.

AMQ Streams installation artifacts

The AMQ Streams installation artifacts contain various YAML files that can be deployed to OpenShift, using oc, to create custom resources, including:

  • Deployments
  • Custom resource definitions (CRDs)
  • Roles and role bindings
  • Service accounts

YAML installation files are provided for the Cluster Operator, Topic Operator, User Operator, and the Strimzi Admin role.

OperatorHub

In OpenShift 4, the Operator Lifecycle Manager (OLM) helps cluster administrators to install, update, and manage the lifecycle of all Operators and their associated services running across their clusters. The OLM is part of the Operator Framework, an open source toolkit designed to manage Kubernetes-native applications (Operators) in an effective, automated, and scalable way.

The OperatorHub is part of the OpenShift 4 web console. Cluster administrators can use it to discover, install, and upgrade Operators. Operators can be pulled from the OperatorHub, installed on the OpenShift cluster to a single (project) namespace or all (projects) namespaces, and managed by the OLM. Engineering teams can then independently manage the software in development, test, and production environments using the OLM.

Note

The OperatorHub is not available in versions of OpenShift earlier than version 4.

AMQ Streams Operator

The AMQ Streams Operator is available to install from the OperatorHub. Once installed, the AMQ Streams Operator deploys the Cluster Operator to your OpenShift cluster, along with the necessary CRDs and role-based access control (RBAC) resources.

Additional resources

Installing AMQ Streams using the installation artifacts:

Installing AMQ Streams from the OperatorHub:

1.6. Document Conventions

Replaceables

In this document, replaceable text is styled in monospace and italics.

For example, in the following code, you will want to replace my-namespace with the name of your namespace: 

sed -i 's/namespace: .*/namespace: my-namespace/' install/cluster-operator/*RoleBinding*.yaml