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Agent Troubleshooting

Logging Mode Options

In the normal logging mode, the Nobl9 Agent only writes events at startup and when errors are encountered. If you have no SLOs, you will only see the startup events. If no errors are returned, this means you have successfully connected to Nobl9.

After adding your first SLO, you will only see a new log message if there is an error. In most cases, these logs can help you diagnose the issue. Note that problems are usually related to the firewall, authentication, or the query.

For debugging purposes, the Agent allows you to enable verbose logging. This means that all logs related to all operations that happen when you execute commands in the Agent will be displayed in the output. You can enable this option as follows:

  • Kubernetes: If the Agent is already deployed in your Kubernetes cluster, add args: ["--debug"] to the YAML configuration file on the level of your container:

    spec:
    containers:
    - name: agent-container
    image: nobl9/agent:latest
    resources:
    requests:
    memory: "350Mi"
    cpu: "0.1"
    args: ["--debug"]
  • Docker: When you invoke the Agent with docker run, add --debug at the end of all the statements that are given in the UI:

    docker run -d --restart on-failure \
    --name nobl9-agent-nobl9-dev-datadog-month-test \
    -e N9_CLIENT_ID="unique_client_id" \
    -e N9_CLIENT_SECRET="unique_client_secret" \
    -e DD_API_KEY="<DATADOG_API_KEY>" \
    -e DD_APPLICATION_KEY="<DATADOG_APPLICATION_KEY>" \
    telegraf --debug \
    nobl9/agent:latest

Troubleshooting

Missing Data

If data appears to be missing, check whether your Agent is running. An Agent that runs on your desktop will stop running and sending data when your machine is sleeping.

Data Backlog

Our users often ask how Nobl9 handles data backlog in various cases. Below, you can find several possible data backlog scenarios and solutions that will help you address them.

Backlogging impact on the Nobl9 Agent

Backlogging issue (for instance, network issues) differs between the data sources available through Nobl9. In general, if the Nobl9 Agent can't reach the N9 data intake, it caches using the FIFO (First In, First Out) method and retries to connect indefinitely.

If the connection outage lasts longer, it may exhaust the Agent's cache. It is also worth noting that the cache is user-configurable by how much memory is allocated to the container.

note

With the Agent version 0.44.0, you can enable Agent's timestamps cache persistence to prevent such situations. Refer to Agent persistence for more details.

Data outage in the Data Source

If the data source is out, Nobl9 won't get data, which might impact your Error budget.

If the Agent keeps running, it will try to catch up after reconnecting (i.e., varying by data source). If the Agent restarts, then it's possible it would stop retrying.

Nobl9 integration mechanism that queries APIs or metrics systems is naturally susceptible to outages between the Agent and the metrics system or between the Agent and Nobl9. These outages may also include the outage of the metrics system itself.

tip

Remember that SLOs are always approximations of the SLI metric and are not ideal reflections of this metric.

Query Errors

Nobl9 is designed to accept single metric values back from queries. If you see a query error, check that what is being returned by that query is a single metric value.

note

Splunk queries may behave differently; see the documentation for more details).