1. PaaS model. We have a team responsible for the deployment and self-service tooling, as well as SME for both development and Cassandra operations. End users consume the service, and are responsible for app development and operations. Larger apps have separate teams for this, smaller apps have a single text for both
2. Homegrown with custom agent piping stats to a Cassandra cluster. Grafana with custom http reader to read metrics from homegrown API. If it would have existed when we first did this, we probably would have worked in Prometheus. 3. Yes. ELK and/or Splunk 4. Used homegrown repair mechanism before 2.2. Now use reaper. PaaS consumers responsible for configuring repairs. 5. No. Need to get better here, but "real" AI seems to be a.bew trend we have seen talked about on this list. On Thu, Mar 28, 2019, 5:03 AM Kenneth Brotman <kenbrot...@yahoo.com.invalid> wrote: > I’m looking to get a better feel for how people use Cassandra in > practice. I thought others would benefit as well so may I ask you the > following five questions: > > > > 1. Do the same people where you work operate the cluster and write > the code to develop the application? > > > > 2. Do you have a metrics stack that allows you to see graphs of > various metrics with all the nodes displayed together? > > > > 3. Do you have a log stack that allows you to see the logs for all > the nodes together? > > > > 4. Do you regularly repair your clusters - such as by using Reaper? > > > > 5. Do you use artificial intelligence to help manage your clusters? > > > > > > Thank you for taking your time to share this information! > > > > Kenneth Brotman >
