General guidance around Bigtable performance

Question

I'm using a single node Bigtable cluster for my sample application running on GKE. Autoscaling feature has been incorporated within the client code. Sometimes I experience slowness (>80ms) for the GET calls. In order to investigate it further, I need some clarity around the following Bigtable behaviour.

1. I have cached the Bigtable table object to ensure faster GET calls. Is the table object persistent on GKE? I have learned that objects are not persistent on Cloud Function. Do we expect any similar behaviour on GKE?
2. I'm using service account authentication but how frequently auth tokens get refreshed? I have seen frequent refresh logs for gRPC Java client. I think Bigtable won't be able to serve the requests over this token refreshing period (4-5 seconds).
3. What if client machine/instance doesn't scale enough? Will it cause slowness for GET calls?
4. Bigtable client libraries use connection pooling. How frequently connections/channels close itself? I have learned that connections are closed after minutes of inactivity (>15 minutes or so).
5. I'm planning to read only needed columns instead of entire row. This can be achieved by specifying the rowkey as well as column qualifier filter. Can I expect some performance improvement by not reading the entire row?

Answer 1

According to GCP official docs you can get here the cause of slower performance of Bigtable. I would like to suggest you to go through the docs that might be helpful. Also you can see Troubleshooting performance issues.