JNDI & connection pooling functionality

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Ajay Babu

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Sep 8, 2025, 2:24:45 PM (12 days ago) Sep 8
to Nussknacker
Hi,

1.Is the implementation of EagerService and ServiceInvoker common for both Flink and the Lite engine?
2.I see both Kafka source and sink running on the same cluster. If I need to connect to a source in a different cluster, do I need to implement a custom source?
3.Is there any expected release date for NunSnaker 1.19?
4.In the cloud version, I can see admin login and can create integrations. Is this functionality available only in the Enterprise version?
5.Is it possible to implement a connection pool and JNDI in the Lite engine and use them commonly across all jobs?

Thanks,
Ajay Babu Maguluri.

Arkadiusz Burdach

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Sep 8, 2025, 10:26:25 PM (12 days ago) Sep 8
to Ajay Babu, Nussknacker, enter...@nussknacker.io
Hi,


On 8.09.2025 20:24, Ajay Babu wrote:
Hi,

1.Is the implementation of EagerService and ServiceInvoker common for both Flink and the Lite engine?
Yes

2.I see both Kafka source and sink running on the same cluster. If I need to connect to a source in a different cluster, do I need to implement a custom source?
By "cluster" do you mean Kafka cluster? If you want to consume events from other Kafka cluster then you produce, you need to configure another "kafka" component provider, (providerType = kafka), see https://nussknacker.io/documentation/docs/configuration/model/ModelConfiguration/#components-configuration . I guess that >1 "kafka" component provider configuration will work only for Flink engine, but I'm not sure.

3.Is there any expected release date for NunSnaker 1.19?
I don't have information in this subject. I'll try to get this information and come back to you with it.

4.In the cloud version, I can see admin login and can create integrations. Is this functionality available only in the Enterprise version?
Yes

5.Is it possible to implement a connection pool and JNDI in the Lite engine and use them commonly across all jobs?
Do you run Lite engine on K8s setup? For K8s setup, every job is a separate K8s deployment so they can't share resources across multiple jobs.

Thanks,
Ajay Babu Maguluri.
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