[Fleet] Add source information to configuration settings

[julesmcrt]

Previous PR before packages got moved around : #19832

TL;DR

Know which source is setting a configuration parameter

Future consequences

When using the .Set() method to change a configuration setting in the agent, you must now add a model.Source parameter, keeping in mind the following hierarchy between them:
CLI > Remote Config > Agent Runtime > Env Var > File > Unknown > Default

You could also use the .SetWithoutSource() method, it will then assume SourceUnknown

If you want to override a setting (e.g. for a unit test), you can now call .Set() specifying a source higher in the hierarchy, then use the .UnsetForSource() method ; the applied setting will fallback to its previous value

What do the sources correspond to?

1. Default is the lowest in the hierarchy, also Go fallback state (empty string). Also used when calling .SetDefault()
2. Unknown is used by the .SetWithoutSource() method, you should avoid using it on purpose
3. File corresponds to the datadog.yaml configuration file
4. Env Var corresponds to the environment variables
5. Agent Runtime is used when the agent itself changes values for its configuration, not to be confused with runtime settings
6. Remote Config is used to remotely change the behaviour of the agent
7. CLI is used when a user manually enters commands

What does this PR do?

1. Move the Source type from the settings package to model (Viper wrapper)
2. Add one Viper instance per source, and edit the .Set() method to include a source parameter
3. Add a .SetWithoutSource() as a legacy way to change a setting without specifying a source
4. Add the different sources to the inventories payload

Motivation

For Fleet Automation, we want to display the configuration of the agent and the source of every setting.
Use case: a customer doesn't understand why when he changed a setting in the datadog.yaml file it didn't have any effect on the agent (because he had forgotten to unset an ENV VAR).

Additional Notes

A lot of the changes are moving .Set() calls to .SetWithoutSource(), the more impactful changes are in the following files:

1. pkg/config/model/viper.go
2. Adding the sources to the Agent inventories payload
3. comp/remote-config/rcclient/rcclient.go

More detailed explanations

Because Viper doesn't support multiple sources of setting, the workaround is to spawn one instance of Viper per configuration source. Everytime a setting is changed, we check the value of every instance and the value of the highest source is applied to the "main" Viper instance.

Only the Set core concept is changed, the Get behavior do not change

Possible Drawbacks / Trade-offs

1. The new Viper instances will require more computing for the Agent
2. The inventories payload will be heavier, REDAPL agreed for the storage aspect

Describe how to test/QA your changes

• Ensure that functions which change agent configuration settings still behave as expected
• Use different sources to change settings and ensure that the hierarchy is always respected
• Check CPU & memory usage, especially if you use Runtime Settings or Remote Config

Reviewer's Checklist

• If known, an appropriate milestone has been selected; otherwise the Triage milestone is set.
• Use the major_change label if your change either has a major impact on the code base, is impacting multiple teams or is changing important well-established internals of the Agent. This label will be use during QA to make sure each team pay extra attention to the changed behavior. For any customer facing change use a releasenote.
• A release note has been added or the changelog/no-changelog label has been applied.
• Changed code has automated tests for its functionality.
• Adequate QA/testing plan information is provided if the qa/skip-qa label is not applied.
• At least one team/.. label has been applied, indicating the team(s) that should QA this change.
• If applicable, docs team has been notified or an issue has been opened on the documentation repo.
• If applicable, the need-change/operator and need-change/helm labels have been applied.
• If applicable, the k8s/<min-version> label, indicating the lowest Kubernetes version compatible with this feature.
• If applicable, the config template has been updated.

[pr-commenter]

Bloop Bleep... Dogbot Here

Regression Detector Results

Run ID: 81956b41-e370-4435-ae36-bc22042f4b18
Baseline: d969bdc
Comparison: d1946d9
Total datadog-agent CPUs: 7

Explanation

A regression test is an integrated performance test for datadog-agent in a repeatable rig, with varying configuration for datadog-agent. What follows is a statistical summary of a brief datadog-agent run for each configuration across SHAs given above. The goal of these tests are to determine quickly if datadog-agent performance is changed and to what degree by a pull request.

Because a target's optimization goal performance in each experiment will vary somewhat each time it is run, we can only estimate mean differences in optimization goal relative to the baseline target. We express these differences as a percentage change relative to the baseline target, denoted "Δ mean %". These estimates are made to a precision that balances accuracy and cost control. We represent this precision as a 90.00% confidence interval denoted "Δ mean % CI": there is a 90.00% chance that the true value of "Δ mean %" is in that interval.

We decide whether a change in performance is a "regression" -- a change worth investigating further -- if both of the following two criteria are true:

1. The estimated |Δ mean %| ≥ 5.00%. This criterion intends to answer the question "Does the estimated change in mean optimization goal performance have a meaningful impact on your customers?". We assume that when |Δ mean %| < 5.00%, the impact on your customers is not meaningful. We also assume that a performance change in optimization goal is worth investigating whether it is an increase or decrease, so long as the magnitude of the change is sufficiently large.

2. Zero is not in the 90.00% confidence interval "Δ mean % CI" about "Δ mean %". This statement is equivalent to saying that there is at least a 90.00% chance that the mean difference in optimization goal is not zero. This criterion intends to answer the question, "Is there a statistically significant difference in mean optimization goal performance?". It also means there is no more than a 10.00% chance this criterion reports a statistically significant difference when the true difference in mean optimization goal is zero -- a "false positive". We assume you are willing to accept a 10.00% chance of inaccurately detecting a change in performance when no true difference exists.

The table below, if present, lists those experiments that have experienced a statistically significant change in mean optimization goal performance between baseline and comparison SHAs with 90.00% confidence OR have been detected as newly erratic. Negative values of "Δ mean %" mean that baseline is faster, whereas positive values of "Δ mean %" mean that comparison is faster. Results that do not exhibit more than a ±5.00% change in their mean optimization goal are discarded. An experiment is erratic if its coefficient of variation is greater than 0.1. The abbreviated table will be omitted if no interesting change is observed.

No interesting changes in experiment optimization goals with confidence ≥ 90.00% and |Δ mean %| ≥ 5.00%.

Fine details of change detection per experiment.

experiment	goal	Δ mean %	Δ mean % CI	confidence
otel_to_otel_logs	ingress throughput	+1.93	[+0.33, +3.53]	95.22%
process_agent_standard_check_with_stats	egress throughput	+0.69	[-1.34, +2.72]	42.43%
file_to_blackhole	egress throughput	+0.39	[-0.05, +0.84]	85.42%
file_tree	egress throughput	+0.25	[-1.62, +2.12]	17.35%
process_agent_standard_check	egress throughput	+0.06	[-3.49, +3.60]	2.15%
dogstatsd_string_interner_8MiB_100k	ingress throughput	+0.02	[-0.02, +0.07]	68.27%
trace_agent_msgpack	ingress throughput	+0.02	[-0.11, +0.14]	18.39%
idle	egress throughput	+0.01	[-2.44, +2.47]	0.66%
uds_dogstatsd_to_api	ingress throughput	+0.01	[-0.16, +0.18]	7.52%
dogstatsd_string_interner_128MiB_1k	ingress throughput	+0.00	[-0.14, +0.14]	1.83%
dogstatsd_string_interner_8MiB_100	ingress throughput	+0.00	[-0.13, +0.13]	1.46%
dogstatsd_string_interner_64MiB_1k	ingress throughput	+0.00	[-0.13, +0.13]	1.05%
dogstatsd_string_interner_64MiB_100	ingress throughput	-0.00	[-0.14, +0.14]	0.10%
dogstatsd_string_interner_128MiB_100	ingress throughput	-0.00	[-0.14, +0.14]	1.04%
dogstatsd_string_interner_8MiB_50k	ingress throughput	-0.01	[-0.05, +0.03]	26.10%
dogstatsd_string_interner_8MiB_10k	ingress throughput	-0.02	[-0.05, +0.02]	47.33%
trace_agent_json	ingress throughput	-0.02	[-0.15, +0.12]	16.05%
dogstatsd_string_interner_8MiB_1k	ingress throughput	-0.02	[-0.12, +0.08]	23.09%
process_agent_real_time_mode	egress throughput	-0.03	[-2.55, +2.49]	1.47%
tcp_dd_logs_filter_exclude	ingress throughput	-0.04	[-0.11, +0.04]	59.36%
tcp_syslog_to_blackhole	ingress throughput	-0.69	[-0.82, -0.55]	100.00%

[chouquette]

LGTM for agent-platform owned files

[songy23]

LGTM on changes to OTel

[sarah-witt]

Looks good for platform integrations!

[dustmop]

Looks good for Agent Shared Components