Set memory limits for agents' Openshift deployments

[lbarcziova]

No description provided.

[gemini-code-assist]

Code Review

This pull request adds memory limits to the OpenShift deployments for various agents, which is a good step towards better resource management. My review focuses on enhancing this by following Kubernetes best practices for resource allocation. I've suggested adding CPU limits (which were mentioned in the original TODO) and also setting CPU and memory requests. This will ensure the pods have a higher Quality of Service (QoS) class, are scheduled more reliably, and don't negatively impact other workloads on the same nodes. The specific CPU values in my suggestions are placeholders and should be tuned based on application profiling.

[gemini-code-assist]

While setting a memory limit is a good improvement, it's highly recommended to also set CPU limits as well as requests for both CPU and memory. This ensures predictable performance and resource allocation. The TODO that was removed also mentioned CPU limits.

Setting requests is important for Kubernetes to schedule the pod appropriately, and it provides a higher Quality of Service (QoS) class. Setting CPU limits prevents the container from consuming excessive CPU and impacting other applications.

Consider defining the full set of resource constraints. The CPU values here are placeholders and should be adjusted based on profiling.

        resources:
          requests:
            memory: 4Gi
            cpu: "1"
          limits:
            memory: 4Gi
            cpu: "2"

[gemini-code-assist]

While setting a memory limit is a good improvement, it's highly recommended to also set CPU limits as well as requests for both CPU and memory. This ensures predictable performance and resource allocation. The TODO that was removed also mentioned CPU limits.

Setting requests is important for Kubernetes to schedule the pod appropriately, and it provides a higher Quality of Service (QoS) class. Setting CPU limits prevents the container from consuming excessive CPU and impacting other applications.

Consider defining the full set of resource constraints. The CPU values here are placeholders and should be adjusted based on profiling.

        resources:
          requests:
            memory: 4Gi
            cpu: "1"
          limits:
            memory: 4Gi
            cpu: "2"

[gemini-code-assist]

While setting a memory limit is a good improvement, it's highly recommended to also set CPU limits as well as requests for both CPU and memory. This ensures predictable performance and resource allocation. The TODO that was removed also mentioned CPU limits.

Setting requests is important for Kubernetes to schedule the pod appropriately, and it provides a higher Quality of Service (QoS) class. Setting CPU limits prevents the container from consuming excessive CPU and impacting other applications.

Consider defining the full set of resource constraints. The CPU values here are placeholders and should be adjusted based on profiling.

        resources:
          requests:
            memory: 1Gi
            cpu: "500m"
          limits:
            memory: 1Gi
            cpu: "1"

[gemini-code-assist]

While setting a memory limit is a good improvement, it's highly recommended to also set CPU limits as well as requests for both CPU and memory. This ensures predictable performance and resource allocation. The TODO that was removed also mentioned CPU limits.

Setting requests is important for Kubernetes to schedule the pod appropriately, and it provides a higher Quality of Service (QoS) class. Setting CPU limits prevents the container from consuming excessive CPU and impacting other applications.

Consider defining the full set of resource constraints. The CPU values here are placeholders and should be adjusted based on profiling.

        resources:
          requests:
            memory: 1Gi
            cpu: "500m"
          limits:
            memory: 1Gi
            cpu: "1"

[gemini-code-assist]

While setting a memory limit is a good improvement, it's highly recommended to also set CPU limits as well as requests for both CPU and memory. This ensures predictable performance and resource allocation. The TODO that was removed also mentioned CPU limits.

Setting requests is important for Kubernetes to schedule the pod appropriately, and it provides a higher Quality of Service (QoS) class. Setting CPU limits prevents the container from consuming excessive CPU and impacting other applications.

Consider defining the full set of resource constraints. The CPU values here are placeholders and should be adjusted based on profiling.

        resources:
          requests:
            memory: 1Gi
            cpu: "500m"
          limits:
            memory: 1Gi
            cpu: "1"