Data Grid Operator 8.5 Release Notes
Get release information for Data Grid Operator 8.5
Abstract
Red Hat Data Grid
Data Grid is a high-performance, distributed in-memory data store.
- Schemaless data structure
- Flexibility to store different objects as key-value pairs.
- Grid-based data storage
- Designed to distribute and replicate data across clusters.
- Elastic scaling
- Dynamically adjust the number of nodes to meet demand without service disruption.
- Data interoperability
- Store, retrieve, and query data in the grid from different endpoints.
Data Grid documentation
Documentation for Data Grid is available on the Red Hat customer portal.
Data Grid downloads
Access the Data Grid Software Downloads on the Red Hat customer portal.
You must have a Red Hat account to access and download Data Grid software.
Making open source more inclusive
Red Hat is committed to replacing problematic language in our code, documentation, and web properties. We are beginning with these four terms: master, slave, blacklist, and whitelist. Because of the enormity of this endeavor, these changes will be implemented gradually over several upcoming releases. For more details, see our CTO Chris Wright’s message.
Chapter 1. Data Grid Operator 8.5
Get version details for Data Grid Operator 8.5 and information about issues.
1.1. Data Grid Operator 8.5.6
What is new in 8.5.6.
The 8.5.6 release includes only bug fixes. For more information, see Fixed in Data Grid Operator 8.5.6.
1.2. Data Grid Operator 8.5.4
What is new in 8.5.4.
Setting CPU and memory limits in Batch CR
With this update, you can limit the number of CPU requests and memory allocation in a Batch Custom Resource (CR). For example:
apiVersion: infinispan.org/v2alpha1 kind: Batch metadata: name: exampleBatch spec: cluster: infinispan configMap: mybatch-config-map container: cpu: "2000m:1000m" memory: "2Gi:1Gi"
apiVersion: infinispan.org/v2alpha1
kind: Batch
metadata:
name: exampleBatch
spec:
cluster: infinispan
configMap: mybatch-config-map
container:
cpu: "2000m:1000m"
memory: "2Gi:1Gi"
Customizing log display in log traces
You can now customize the log display for Data Grid log traces by defining the spec.logging.pattern
field in your Infinispan
CR.
If you do not define a custom pattern, the default format is the following:
%d{HH:mm:ss,SSS} %-5p (%t) [%c] %m%throwable%n
%d{HH:mm:ss,SSS} %-5p (%t) [%c] %m%throwable%n
For more information, see Adjusting log pattern.
Support for auto scaling with HorizontalPodAutoscaler
StatefulSets or Deployments can now be automatically scaled up or down based on specified metrics by defining a HorizontalPodAutoscaler
resource in the same namespace as the Infinispan CR.
For more information, see Auto Scaling.
1.3. Data Grid Operator 8.5.3
What’s new in 8.5.3.
Automatic reloading of SSL/TLS certificates
Starting with Data Grid 8.5.1, Data Grid monitors keystore files for changes and automatically reloads them, without requiring a server or client restart, when certificates are renewed.
Therefore, with Data Grid Operator 8.5.3, StatefulSet
rolling update is not triggered on key or truststore update in a server when managing Data Grid 8.5.1 Operands because it is not required.
1.4. Data Grid Operator 8.5.0
What’s new in 8.5.0.
Ability to configure InitContainer
resource
You can now configure the InitContainer
resource. Previously, if a LimitRange
was in effect for the deployment namespace, then the InitContainer
would be restricted to these resource values causing issues such as OutOfMemoryError. You can configure InitContainer resource configuration in the Data Grid CR as follows:
spec: dependencies: initContainer: cpu: "2000m:1000m" memory: "2Gi:1Gi"
spec:
dependencies:
initContainer:
cpu: "2000m:1000m"
memory: "2Gi:1Gi"
Ability to define Batch
resource CPU and memory request/limits
You can now define CPU and memory request/limits for Batch Job created by the Operator. You can define the resource request/limits in the Batch CR as follows:
apiVersion: infinispan.org/v2alpha1 kind: Batch metadata: name: mybatch spec: cluster: infinispan configMap: mybatch-config-map container: cpu: "2000m:1000m" memory: "2Gi:1Gi"
apiVersion: infinispan.org/v2alpha1
kind: Batch
metadata:
name: mybatch
spec:
cluster: infinispan
configMap: mybatch-config-map
container:
cpu: "2000m:1000m"
memory: "2Gi:1Gi"
TLSv1.3 encryption for cross-site encryption
The default encryption protocol for cross-site is now TLSv1.3 instead of TLSv1.2.
Ability to define TopologyPodConstraints
and Tolerations
in StatefulSet
You can now configure more advanced high availability configurations by defining TopologyPodConstraints
and Tolerations
in spec.statefulSet
.
Example
kind: Infinispan ... spec: scheduling: affinity: ... tolerations: ... topologySpreadConstraints: ...
kind: Infinispan
...
spec:
scheduling:
affinity:
...
tolerations:
...
topologySpreadConstraints:
...
Cache service type removed
RHDG 8.5 removes the Cache service type cache. Instead, use the DataGrid
service type to automate complex operations such as cluster upgrades and data migration.
Cloud events removed
RHDG 8.5 removes cloud events integration.
1.5. Data Grid Operator 8.5.x release information
The following table provides detailed version information for Data Grid Operator.
Data Grid Operator versions do not always directly correspond to Data Grid versions because the release schedule is different.
Data Grid Operator version | Data Grid version | Operand versions | Features |
8.5.6 | 8.5.3 |
8.5.3-1 | Includes several bug fixes. |
8.5.5 | 8.5.2 |
8.5.2-2 | Includes several bug fixes. |
8.5.4 | 8.5.2 |
8.5.2-1 | Includes several bug fixes. |
8.5.3 | 8.5.1 |
8.5.1-1 | Includes several bug fixes. |
8.5.2 | 8.5.0 |
8.5.0-3 | Includes several bug fixes. |
8.5.1 | 8.5.0 |
8.5.0-2 | Includes several bug fixes. |
8.5.0 | 8.5.0 |
8.5.0-1 | Includes several bug fixes. |
Chapter 2. Known and fixed issues
Learn about known issues for Data Grid Operator and find out which issues are fixed.
2.1. Known issues with Data Grid Operator deployments
This release does not include any known issues that affect Data Grid clusters that you manage with Data Grid Operator. For complete details about Data Grid, see the Data Grid 8.5 release notes.
2.2. Fixed in Data Grid Operator 8.5.6
Data Grid Operator 8.5.6 includes the following notable fixes:
- JDG-7503 Exception when retrieving logs with Service Mesh
2.3. Fixed in Data Grid Operator 8.5.4
Data Grid Operator 8.5.4 includes the following notable fixes:
2.4. Fixed in Data Grid Operator 8.5.3
Data Grid Operator 8.5.3 includes the following notable fixes:
- JDG-6764 Updates to spec.image on existing Infinispan CR have no effect
2.5. Fixed in Data Grid Operator 8.5.0
Data Grid Operator 8.5.0 includes the following notable fixes:
- JDG-5000 Gossip router pod generates lot of SSLHandshake warn messages
- JDG-7063 Nil pointer error on upgrade from dropped Operand version
- JDG-7032 Operator generates truststore from certificates using outdated algorithms
- JDG-7093 Operator may not reconcile Data Grid cluster properly after upgrade
- JDG-5989 Operator Configuration spec.autoscale should not be possible with a Data Grid service
Chapter 3. Data Grid on OpenShift
3.1. Data Grid 8.5 images
Data Grid 8.5 includes two container images, the Data Grid Operator image and Data Grid Server image.
Data Grid images are hosted on the Red Hat Container Registry, where you can find health indexes for the images along with information about each tagged version.
Custom Data Grid Deployments
Red Hat does not support customization of any 8.5 images from the Red Hat Container Registry through the Source-to-Image (S2I) process or ConfigMap
API.
As a result it is not possible to use custom:
- Discovery protocols
-
JGroups
SYM_ENCRYPT
orASYM_ENCRYPT
encryption mechanisms
3.2. Embedded caches on OpenShift
Using embedded Data Grid caches in applications running on OpenShift, which was referred to as Library Mode in previous releases, is intended for specific uses only:
- Using local or distributed caching in custom Java applications to retain full control of the cache lifecycle. Additionally, when using features that are available only with embedded Data Grid such as distributed streams.
-
Reducing network latency to improve the speed of cache operations.
The Hot Rod protocol provides near-cache capabilities that achieve equivalent performance to a standard client-server architecture.
Requirements
Embedding Data Grid in applications running on OpenShift requires you to use a discovery mechanism so Data Grid nodes can form clusters to replicate and distribute data.
Red Hat supports only DNS_PING as the cluster discovery mechanism.
DNS_PING exposes a port named ping
that Data Grid nodes use to perform discovery and join clusters. TCP is the only supported protocol for the ping
port, as in the following example for a pod on OpenShift:
spec: ... ports: - name: ping port: 8888 protocol: TCP targetPort: 8888
spec:
...
ports:
- name: ping
port: 8888
protocol: TCP
targetPort: 8888
Limitations
Embedding Data Grid in applications running on OpenShift also has some specific limitations:
- Persistent cache stores are not currently supported.
- UDP is not supported with embedded Data Grid.
Custom caching services
Red Hat highly discourages embedding Data Grid to build custom caching servers to handle remote client requests. To benefit from regular, automatic updates with performance improvements and fix security issues, you should create Data Grid clusters with the Data Grid Operator instead.