Resource Metrics

Overview

Details of specific measurements used to assess and quantify the resource utilization of LILT applications. These metrics provide insights into the performance, capacity, and scalability requirements of the applications. They include parameters such as CPU utilization, memory consumption, disk size and concurrent user sessions. By establishing baseline measurements and setting thresholds, usage-sizing metrics help identify normal operating levels and define boundaries for resource usage. These metrics enable proactive capacity planning, resource optimization, and the ability to detect anomalies or performance bottlenecks. The table below is meant to be a reference guide, and not an exact match to your individual environment, as each installation may choose to enable or disable specific services.

Usage-Sizing Metrics

App Name	Min Recommended vCPUs	Max Recommended vCPUs	Min Recommended Memory (GB)	Max Recommended Memory (GB)
Front	0.5	2	4	8
Beehive	0.1	4	4	4
Converter	1	12	26	28
QA	0.5	1	3	4
Search	0.05	n/a	21	22
TM	4	12	30	32
TB	1	n/a	30	30
Indexer	0.05	n/a	21	22
Lexicon	4	8	30	30
Watchdog	0.1	n/a	2	3
Segment	0.5	2	4	4
File-translation	3	6	14	15
Job	0.5	1	2	3.5
Tag	0.5	1	2	3.5
Linguist	0.5	1	1	2
Auditlog	0.5	1	2	3.5
Assignment	1	2	4	4
Workflow	1	2	2	2
File-job	2	4	16	16
memory	1	2	4	4.6
notification	0.5	n/a	2	4
auth	0.1	2	0.128	1
core-api	0.1	2	0.128	1
configuration-api	0.1	2	0.128	1
events-consumer	0.1	2	0.128	1
login	0.1	2	0.128	1
manager-ui	0.1	2	0.128	1
plugin-api	0.1	2	0.128	1
token-proxy	0.1	2	0.128	1
webhooks	0.1	2	0.128	1
webhooks-consumer	0.1	2	0.128	1
monitor	0.1	2	0.128	1
updatev3	1	4	80	80
Langid	0.5	1	1.5	1.5
update-managerv3	0.25	0.5	1	1
Routing	0.5	3	1.5	1.5
batchv3	0.25	0.5	1	1
batch-tb	2	7	22	30
llm-inference	1	15	4	30
Localpv	0.1	2	0.128	1
nginx-ingress	0.1	0.128	n/a	n/a
isitiod	0.5	0.5	2	2
istio-ingressgateway	0.1	2	0.128	1
kiali	0.01	0.01	0.064	1
redis	0.2	0.6	4	10
rabbitmq	1	2	4	4
mysql	0.5	n/a	4	8
mongoDB	0.5	0.5	0.5	0.5
minIO	0.1	0.5	1	1.5
clickhouse	0.5	n/a	1	16
elasticsearch***	1	2	4	4
batch-worker-gpuv3 ****	1	2	12	12
translatev3 ****	1	2	25	39
Total*	50 vCPUs	160 vCPUs	630 GB RAM	728 GB RAM
Total*	1 TB Disk**8 GPU

*The following specifications are recommended for installing LILT on bare-metal hardware to support the given applications. It is important to note that these specifications may need to be adjusted based on the specific load requirements.

**To efficiently handle parallel batch requests, it is recommended to have the same number of GPUs as the number of required concurrent batch requests. This enables the system to effectively distribute the workload and process multiple requests simultaneously, leveraging the processing power of each GPU to improve throughput.

Resource Metrics

Overview

Usage-Sizing Metrics

*The following specifications are recommended for installing LILT on bare-metal hardware to support the given applications. It is important to note that these specifications may need to be adjusted based on the specific load requirements.

*** These values are doubled, because there are two replicas

**** These pods run on the GPU node

n/a marked services have no maximum limit and can use the available resources on the node

​Overview

​Usage-Sizing Metrics

*The following specifications are recommended for installing LILT on bare-metal hardware to support the given applications. It is important to note that these specifications may need to be adjusted based on the specific load requirements.

*** These values are doubled, because there are two replicas

**** These pods run on the GPU node

n/a marked services have no maximum limit and can use the available resources on the node

Overview

Usage-Sizing Metrics