Project: Crossplane (Orchestration & Management / Scheduling & Orchestration)
File: guide-observability.md

Observability is crucial to Crossplane users; both those operating Crossplane and those using Crossplane to operate their infrastructure. Crossplane currently approaches observability via Kubernetes events and structured logs. In short, a non-admin user and an admin user should both be able to debug any issues only by inspecting logs and events. There should be no need to rebuild the Crossplane binary or to reach out to a Crossplane developer. A user should be able to: Debug an issue without rebuilding the Crossplane binary Understand an issue without contacting a cluster admin Ask a cluster admin to check the logs for more details about the reason the issue happened, if the details are not part of the error message A cluster admin should be able to: Debug an issue without rebuilding the Crossplane binary Debug an issue only by looking at the logs Debug an issue without needing to contact a Crossplane developer Error reporting in the logs is mostly intended for consumption by Crossplane cluster admins. A cluster admin should be able to debug any issue by inspecting the logs, without needing to add more logs themselves or contact a Crossplane developer. This means that logs should contain: Error messages, at either the info or debug level as contextually appropriate Any context leading up to an error, typically at debug level, so that the errors can be debugged Error reporting as Kubernetes events is primarily aimed toward end-users of Crossplane who are not cluster admins. Crossplane typically runs as a Kubernetes pod, and thus it is unlikely that most users of Crossplane will have access to its logs. [Events], on the other hand, are available as top-level Kubernetes objects, and show up the objects they relate to when running `kubectl describe`. Events should be recorded in the following cases: A significant operation is taken on a resource The state of a resource is changed An error occurs Events should not be recorded if nothing happens or changes, with the exception of repeated errors. The events recorded in these cases can be thought of as forming an event log of things that happen for the resources that Crossplane manages. Each event should refer back to the relevant controller and resource, and use other fields of the Event kind as appropriate. More details about examples of how to interact with events can be found in the guide to [debugging an application cluster]. There are many ways to report errors, such as: Metrics Events Logging Tracing It can be confusing to figure out which one is appropriate in a given situation. This section will try to offer advice and a mindset that can be used to help make this decision. Let's set the context by listing the different user scenarios where error reporting may be

Here are the typical scenarios as we imagine them: A person using a system needs to figure out why things aren't working as expected, and whether they made a mistake that they can correct. A person operating a service needs to monitor the service's health, both now and historically. A person debugging a problem which happened in a live environment (often an operator of the system) needs information to figure out what happened. A person developing the software wants to observe what is happening. A person debugging the software in a development environment (typically a developer of the system) wants to debug a problem (there is a lot of overlap between this and the live environment debugging scenario). The goal is to satisfy the users in all of the scenarios. We'll refer to the scenarios by number. The short version is: we should do whatever satisfies all of the scenarios. Logging and events are the recommendations for satisfying the scenarios, although they don't cover scenario 2. The longer version is: Scenario 1 is best served by events in the context of Crossplane, since the users may not have access to read logs or metrics, and even if they did, it would be hard to relate them back to the event the user is trying to understand. Scenario 2 is best served by metrics, because they can be aggregated and understood as a whole. And because they can be used to track things over time. Scenario 3 is best served by either logging that contains all the information about and leading up to the event. Request-tracing systems are also useful for this scenario. Scenario 4 is usually logs, maybe at a more verbose level than normal. But it could be an attached debugger or some other type of tool. It could also be a test suite. Scenario 5 is usually either logs, up to the highest imaginable verbosity, or an attached debugging session. If there's a gap in reporting, it could involve adding some print statements to get more logging. As for the question of how to decide whether to log or not, we believe it helps to try to visualize which of the scenarios the error or information in question will be used for. We recommend starting with reporting as much information as possible, but with configurable runtime behavior so that, for example, debugging logs don't show up in production normally. For the question of what constitutes an error, errors should be actionable by a human. See the [Dave Cheney article] on this topic for some more discussion. An error message is good if it communicates what went wrong where it went wrong for which inputs and if it is concise without redundancies and at best displayable in one line. The general goal of an error message is to be actionable for the user who is trying to avoid the error in the

Examples for bad error messages: `cannot resolve package dependencies: Invalid Semantic Version` `cannot parse file foo.yaml: failed to parse YAML of file foo.yaml` Examples for how to improve them: `cannot resolve package dependencies in crossplane.yaml: invalid Semantic Version "main" on package "provider-kubernetes"` `failed to load OCI image provider-gcp/v0.42.0: failed to unpack layer: cannot parse file: failed to parse YAML of file foo.yaml: unexpected indention in line 4`. General rules: follow the pattern `generic error cause: more details: even more details`. put values into quotes (`%q` in Golang), with the following exceptions where quotes don't add to readability: resource names with namespace or resource type (e.g. `default/foo` or `providers/foo`), resource names alone are quoted kinds (e.g. `cannot find provider "provider-kubernetes"`; here, the kind provider is without quotes, the provider name is with) filenames with extensions and/or path (e.g. `cannot parse foo.yaml`). add a context of e.g. filenames, object names, or values which are wrong (and the values are known to be insensitive). Which context is added by which functions depends on the level of abstraction of the code at hand: the package loader will know the OCI image name, the YAML parser might only see a byte slice. The former adds the image name as context, some layer in-between adds the filename and the YAML parser adds the line and column in the byte stream. Filenames should be relative to the logical working directory of the context at hand (e.g. a package root, current working directory, workspace root). Ensure that the context is clear in the error message (e.g. `failed to load package "provider-kubernetes": failed to parse apis/xrd.yaml`). add a context just once. Rule of thumb: if a function gets a parameter, it will also include it in the error messages, so the caller does not have to. E.g. a function getting a filename as input will include the filename in errors it returns. don't return multi-line errors. aggregate errors if there is clear use for the user, but not in general, i.e. fail fast is the default. Aggregate through `kerrors.NewAggregate`. When the number of aggregated errors is unbounded, return a subset, e.g. the first 3. E.g.: `cannot parse workspace: failed to parse foo.yaml, bar.yaml, abc.yaml, and 17 more files` don't include sensitive information like tokens into error messages, not even in debug mode. These are usually considered insensitive: field names, file paths, resources, kinds, object names, namespaces, labels, enum values, numbers, booleans. use error message constants, e.g. `errSomethingWentWrong` for messages without interpolation, and `errFmtSomethingWentWrong` for those with interpolation. use [wrapping errors] and github.com/crossplane/crossplane-runtime/pkg/errors in general. error messages must be deterministic. Use sorting in loops over maps or sort returned errors to ensure determinism. Background: one never knows how an error is displayed. Not being deterministic can lead to hot-loops with constant API updates, e.g. of a

error messages are good candidates to be included in condition or event messages. Crossplane provides two observability libraries as part of crossplane-runtime: [`event`] emits Kubernetes events. [`logging`] produces structured logs. Refer to its package documentation for additional context on its API choices. Keep the following in mind when using the above libraries: [Do] [not] use package level loggers or event recorders. Instantiate them in `main()` and plumb them down to where they're needed. Each [`Reconciler`] implementation should use its own `logging.Logger` and `event.Recorder`. Implementations are strongly encouraged to default to using `logging.NewNopLogger()` and `event.NewNopRecorder()`, and accept a functional loggers and recorder via variadic options. See for example the [managed resource reconciler]. Each controller should use its name as its event recorder's name, and include its name under the `controller` structured logging key. The controllers name should be of the form `controllertype/resourcekind`, for example `managed/cloudsqlinstance` or `stacks/stackdefinition`. Controller names should always be lowercase. Logs and events should typically be emitted by the `Reconcile` method of the `Reconciler` implementation; not by functions called by `Reconcile`. Author the methods orchestrated by `Reconcile` as if they were a library; prefer surfacing useful information for the `Reconciler` to log (for example by [wrapping errors]) over plumbing loggers and event recorders down to increasingly deeper layers of code. Almost nothing is worth logging at info level. When deciding which logging level to use, consider a production deployment of Crossplane reconciling tens or hundreds of managed resources. If in doubt, pick debug. You can easily increase the log level later if it proves warranted. The above is true even for errors; consider the audience. Is this an error only the Crossplane cluster operator can fix? Does it indicate a significant degradation of Crossplane's functionality? If so, log it at info. If the error pertains to a single Crossplane resource emit an event instead. Always log errors under the structured logging key `error` (e.g. `log.Debug("boom!, "error", err)`). Many logging implementations (including Crossplane's) add context like stack traces for this key. Emit events liberally; they're rate limited and deduplicated. Follow [API conventions] when emitting events; ensure event reasons are unique and `CamelCase`. Consider emitting events and logs when a terminal condition is encountered (e.g. `Reconcile` returns) over logging logic flow. i.e. Prefer one log line that reads "encountered an error fooing the bar" over two log lines that read "about to foo the bar" and "encountered an error". Recall that if the audience is a developer debugging Crossplane they will be provided a stack trace with file and line context when an error is logged. Consider including the `reconcile.Request`, and the resource's UID and resource version (not API version) under the keys `request`, `uid`, and `version`. Doing so allows log readers to determine what specific version of a resource the log pertains to. Finally, when in doubt, aim for consistency with existing Crossplane controller implementations. <!-- Named Links -->