Dynamic Kubelet Configuration


A proposal for making it possible to (re)configure Kubelets in a live cluster by providing config via the API server. Some subordinate items include local checkpointing of Kubelet configuration and the ability for the Kubelet to read config from a file on disk, rather than from command line flags.


The Kubelet is currently configured via command-line flags. This is painful for a number of reasons: - It makes it difficult to change the way Kubelets are configured in a running cluster, because it is often tedious to change the Kubelet startup configuration (without adding your own configuration management system e.g. Ansible, Salt, Puppet). - It makes it difficult to manage different Kubelet configurations for different nodes, e.g. if you want to canary a new config or slowly flip the switch on a new feature. - The current lack of versioned Kubelet configuration means that any time we change Kubelet flags, we risk breaking someone’s setup.

Example Use Cases

  • Staged rollout of configuration changes, including tuning adjustments and enabling new Kubelet features.
  • Streamline cluster bootstrap. The Kubeadm folks want to plug in to dynamic config, for example: kubernetes/kubeadm#28.
  • Making it easier to run tests with different Kubelet configurations, because tests can modify Kubelet configuration on the fly.

Primary Goals of the Design

Kubernetes should:

  • Provide a versioned object to represent the Kubelet configuration.
  • Provide the ability to specify a dynamic configuration source for each node.
  • Provide a way to share the same configuration source between nodes.
  • Protect against bad configuration pushes.
  • Recommend, but not mandate, the basics of a workflow for updating configuration.

Additionally, we should:

  • Add Kubelet support for consuming configuration via a file on disk. This aids work towards deprecating flags in favor of on-disk configuration.
  • Make it possible to opt-out of remote configuration as an extra layer of protection. This should probably be a flag, rather than a dynamic field, as it would otherwise be too easy to accidentally turn off dynamic config with a config push.


Two really important questions: 1. How should one organize and represent configuration in a cluster? 2. How should one orchestrate changes to that configuration?

This doc primarily focuses on (1) and the downstream (API server -> Kubelet) aspects of (2).

Organization of the Kubelet’s Configuration Type

In general, components should expose their configuration types from their own source trees. The types are currently in the alpha componentconfig API group, and should be broken out into the trees of their individual components. PR #42759 reorganized the Kubelet’s tree to facilitate this. PR #44252 initiates the decomposition of the type.

Components with several same-configured instances, like the Kubelet, should be able to share configuration sources. A 1:N mapping of config-object:instances is much more efficient than requiring a config object per-instance. As one example, we removed the HostNameOverride and NodeIP fields from the configuration type because these cannot be shared between Nodes - #40117.

Components that currently take command line flags should not just map these flags directly into their configuration types. We should, in general, think about which parameters make sense to configure dynamically, which can be shared between instances, and which are so low-level that they shouldn’t really be exposed on the component’s interface in the first place. Thus, the Kubelet’s flags should be kept separate from configuration - #40117.

The Kubelet’s current configuration type is an unreadable monolith. We should decompose it into sub-objects for convenience of composition and management. An example grouping is in PR #44252.

Representing and Referencing Configuration

Cluster-level object

  • The Kubelet’s configuration should be:
    • Structured into sub-categories, so that it is readable.
    • A bundled payload, so that all Kubelet parameters roll out to a given Node in unison.
  • The Kubelet’s configuration should be stored in the Data of a ConfigMap object. Each value should be a YAML or JSON blob, and should be associated with the correct key.
    • Note that today, there is only a single KubeletConfiguration object (required under the kubelet key).
  • The ConfigMap containing the desired configuration should be specified via the Node object corresponding to the Kubelet. The Node will have a new spec subfield, configSource, which is a new type, NodeConfigSource (described below).

ConfigMap object containing the Kubelet’s configuration:

kind: ConfigMap
  name: my-kubelet-config
  kubelet: "{JSON blob}"


There are two types of configuration that are stored on disk: - cached configurations from a remote source, e.g. ConfigMaps from etcd. - the local “init” configuration, e.g. the set of config files the node is provisioned with.

The Kubelet should accept a --dynamic-config-dir flag, which specifies a directory for storing all of the information necessary for dynamic configuration from remote sources; e.g. the cached configurations, which configuration is currently in use, which configurations are known to be bad, etc. - When the Kubelet downloads a ConfigMap, it will checkpoint a serialization of the ConfigMap object to a file at {dynamic-config-dir}/checkpoints/{UID}. - We checkpoint the entire object, rather than unpacking the contents to disk, because the former is less complex and reduces chance for errors during the checkpoint process.

The Kubelet should also accept a --init-config-dir flag, which specifies a directory containing a local set of “init” configuration files the node was provisioned with. The Kubelet will substitute these files for the built-in KubeletConfiguration defaults (and also for the existing command-line flags that map to KubeletConfiguration fields).

Orchestration of configuration

There are a lot of opinions around how to orchestrate configuration in a cluster. The following items form the basis of a robust solution:

Robust Kubelet behavior

To make config updates robust, the Kubelet should be able to locally and automatically recover from bad config pushes. We should strive to avoid requiring operator intervention, though this may not be possible in all scenarios.

Recovery involves: - Checkpointing configuration on-disk, so prior versions are locally available for rollback. - Tracking a last-known-good (LKG) configuration, which will be the rollback target if the current configuration turns out to be bad. - Tracking bad configurations, so the Kubelet can avoid using known-bad configurations across restarts. - Detecting whether a crash-loop correlates with a new configuration, marking these configurations bad, and rolling back to the last-known-good when this happens.

Finding and checkpointing intended configuration

The Kubelet finds its intended configuration by looking for the ConfigMap referenced via it’s Node’s optional spec.configSource field. This field will be a new type:

type NodeConfigSource struct {
  ConfigMapRef *ObjectReference

For now, this type just contains an ObjectReference that points to a ConfigMap. The spec.configSource field will be of type *NodeConfigSource, because it is optional.

The spec.configSource field can be considered “correct,” “empty,” or “invalid.” The field is “empty” if and only if it is nil. The field is “correct” if and only if it is neither “empty” nor “invalid.” The field is “invalid” if it fails to meet any of the following criteria: - Exactly one subfield of NodeConfigSource must be non-nil. - All information contained in the non-nil subfield must meet the requirements of that subfield.

The requirements of the ConfigMapRef subfield are as follows: - All of ConfigMapRef.UID, ConfigMapRef.Namespace, and ConfigMapRef.Namemust be non-empty. - Both ConfigMapRef.UID and the ConfigMapRef.Namespace-ConfigMapRef.Name pair must unambiguously refer to the same object. - The referenced object must exist. - The referenced object must be a ConfigMap.

The Kubelet must have permission to read ConfigMaps in the namespace that contains the referenced ConfigMap.

If the spec.configSource is empty, the Kubelet will use its “init” configuration or built-in defaults (including values from flags that currently map to configuration) if the “init” config is also absent.

If the spec.configSource is invalid (or if some other issue prevents syncing configuration with what is specified on the Node): - If the Kubelet is in its startup sequence, it will defer to its LKG configuration and report the failure to determine the desired configuration via a NodeCondition (discussed later) when the status sync loop starts. - If the failure to determine desired configuration occurs as part of the configuration sync-loop operation of a live Kubelet, the failure will be reported in a NodeCondition (discussed later), but the Kubelet will not change its configuration. This is to prevent disrupting live Kubelets in the event of user error.

If the spec.configSource is correct and using ConfigMapRef, the Kubelet checkpoints this ConfigMap to the dynamic-config-dir, as specified above in the Representing and Referencing Configuration section.

The Kubelet serializes a “current” and “last-known-good” NodeConfigSource to disk to track which configuration it is currently using, and which to roll back to in the event of a failure. If either of these files is empty, the Kubelet interprets this as “use the local config,” whether that means the combination of built-in defaults and flags, or the “init” config.

The Kubelet detects new configuration by watching the Node object for changes to the spec.configSource field. When the Kubelet detects new configuration, it checkpoints it as necessary, saves the new NodeConfigSource to the “current” file, and calls os.Exit(0). This relies on the process manager (e.g. systemd) to restart the Kubelet. When the Kubelet restarts, it will attempt to load the new configuration.

Metrics for Bad Configuration

These are metrics we can use to detect bad configuration. Some are perfect indicators (validation) and some are imperfect (P(ThinkBad == ActuallyBad) < 1).

Perfect Metrics: - KubeletConfiguration cannot be deserialized - KubeletConfiguration fails a validation step

Imperfect Metrics: - Kubelet restarts occur above a frequency threshold when using a given configuration, before that configuration is out of a “trial period.”

We should absolutely use the perfect metrics we have available. These immediately tell us when we have bad configuration. Adding a user-defined trial period, within which restarts above a user-defined frequency can be treated as crash-loops caused by the current configuration, adds some protection against more complex configuration mishaps.

More advanced error detection is probably best left to an out-of-band component, like the Node Problem Detector. We shouldn’t go overboard attempting to make the Kubelet too smart.

Tracking LKG (last-known-good) configuration

The Kubelet tracks its “last-known-good” configuration by saving the relevant NodeConfigSource to a file, just as it does for its “current” configuration. If this file is empty, the Kubelet should treat the “init” config or combination of built-in defaults and flags as it’s last-known-good config.

Any configuration retrieved from the API server must persist beyond a trial period before it can be considered LKG. This trial period will be called ConfigTrialDuration, will be a Duration as defined by k8s.io/apimachinery/pkg/apis/meta/v1/duration.go, and will be a parameter of the KubeletConfiguration. The trial period on a given configuration is the trial period used for that configuration (as opposed to, say, using the trial period set on the previous configuration). This is useful if you have, for example, a configuration you want to roll out with a longer trial period for additional caution.

Similarly, the number of restarts tolerated during the trial period is exposed to the user via the CrashLoopThreshold field of the KubeletConfiguration. This field has a minimum of 0 and a maximum of 10. The maximum of 10 is an arbitrary threshold to prevent unbounded growth of the startups-tracking file (discussed later). We implicitly allow one more restart than the user-provided threshold, because one restart is necessary to begin using a new configuration.

The “init” configuration will be automatically considered good. If a node is provisioned with an init configuration, it MUST be a valid configuration. The Kubelet will always attempt to deserialize the init configuration and validate it on startup, regardless of whether a remote configuration exists. If this fails, the Kubelet will refuse to start. Similarly, the Kubelet will refuse to start if the sum total of built-in defaults and flag values that still map to configuration is invalid. This is to make invalid node provisioning extremely obvious.

It is very important to be strict about the validity of the init and default configurations, because these are the baseline last-known-good configurations. If either configuration turns out to be bad, there is nothing to fall back to. We presume a user provisions nodes with an init configuration when the Kubelet defaults are inappropriate for their use case. It would thus be inappropriate to fall back to the Kubelet defaults if the init configuration exists.

As the init configuration and the built-in defaults are automatically considered good, intentionally setting spec.configSource on the Node to its empty default will reset the last-known-good back to whichever local config is in use.

Rolling back to the LKG config

When a configuration correlates too strongly with a crash loop, the Kubelet will “roll-back” to its last-known-good configuration. This process involves three components: 1. The Kubelet must choose to use its LKG configuration instead of its intended current configuration. 2. The Kubelet must remember which configuration was bad, so it doesn’t roll forward to that configuration again. 3. The Kubelet must report that it rolled back to LKG due to the belief that it had a bad configuration.

Regarding (2), when the Kubelet detects a bad configuration, it will add an entry to a “bad configs” file in the dynamic-config-dir, mapping the namespace and name of the ConfigMap to the time at which it was determined to be a bad config and the reason it was marked bad. The Kubelet will not roll forward to any of these configurations again unless their entries are removed from this file. For example, the contents of this file might look like (shown here with a reason matching what would be reported in a NodeCondition:

  "{uid}": {
    "time": "RFC 3339 formatted timestamp", 
    "reason": "failed to validate current (UID: {UID})"

Regarding (1), the Kubelet will check the “bad configs” file on startup. It will use the “last-known-good” config if the “current” config referenced is listed in the “bad configs” file.

Regarding (3), the Kubelet should report via the Node’s status: - That it is using LKG. - The configuration LKG refers to. - The supposedly bad configuration that the Kubelet decided to avoid. - The reason it thinks the configuration is bad.

Tracking restart frequency against the current configuration

Every time the Kubelet starts up, it will append the startup time to a “startups” file in the dynamic-config-dir. This file is a JSON list of string RFC3339-formatted timestamps. On Kubelet startup, if the time elapsed since the last modification to the “current” file does not exceed ConfigTrialDuration, the Kubelet will count the number of timestamps in the “startups” file that occur after the last modification to “current.” If this number exceeds the CrashLoopThreshold, the configuration will be marked bad and considered the cause of the crash-loop. The Kubelet will then roll back to its LKG configuration. We use “exceeds” as the trigger, because the Kubelet must be able to restart once to adopt a new configuration.

Dead-end states

We may use imperfect indicators to detect bad configuration. It is possible for a crash-loop unrelated to the current configuration to cause that configuration to be marked bad. This becomes evident when the Kubelet rolls back to the LKG configuration and continues to crash. In this scenario, an out-of-band node repair is required to revive the Kubelet. Since the current configuration was not, in fact, the cause of the issue, the component in charge of node repair should also reset that belief by removing the entry for the current configuration from the “bad configs” file.

How to version “bad configs” and “startups” tracking files

Having unversioned types for persisted data presents an upgrade risk; if a new Kubelet expects a different data format, the new Kubelet may fail. We need a versioning mechanism for these files to protect against this.

We have at least these two options: - Define a versioned API group, similar to how we have a versioned KubeletConfiguration object, for these data-tracking types. - Alternatively, store these files under a directory that contains the Kubelet’s version string in its name.

There are tradeoffs between these approaches:

Theoretical kubelet version pros: 1. Config marked bad due to a bug in an old Kubelet won’t be considered bad by the new Kubelet that contains the bug fix, e.g. incorrect bad-config information won’t leak across Kubelet upgrades. 2. If you have to roll back the Kubelet version while the current config is still in its trial period, config marked bad by a new Kubelet due to a bug or crash-loop won’t all-of-a-sudden look bad to an old Kubelet that used to accept it. 3. We never worry about whether a new Kubelet is compatible with a given schema for this tracking state, because the state is always local to a given Kubelet version.

Pros in practice: 1. In practice, you probably moved away from the config your old Kubelet marked bad. It is not unreasonable, however, that the ConfigMap behind the old config still exists in your cluster, and you would like to roll this config out now that you have a new Kubelet. In this case, it’s nice not to have to delete and recreate the same ConfigMap (config source objects are checkpointed by UID, re-creation gets you a new UID) just to roll it out. In practice, this is probably a rare scenario because users shouldn’t initiate a Kubelet upgrade until they are sure the current config is stable. 2. This is a worse information leak than the previous scenario. A new Kubelet that crash-loops might mark the current config bad (or simply record enough startups that the old Kubelet will mark it bad), and then you won’t be able to roll back to the same Kubelet + config combination as before because the old Kubelet will now reject the current config. In practice, this is probably a rare scenario because users shouldn’t initiate a Kubelet upgrade until they are sure the current config is stable. 3. This is nice in practice: it also allows us to make what would be breaking changes (if we used apimachinery) across Kubelet versions, which means we can more easily iterate on the Kubelet’s behavior in the face of bad config.

Theoretical kubelet version cons: 1. Different Kubelet versions can’t make use of each-other’s bad-config information. Thus if you initiate a Kubelet upgrade on a cluster where the Kubelets are currently using the last-known-good config because the current config is bad, the new Kubelets will have to rediscover that the current config is bad. 2. Different Kubelet versions can’t make use of each-other’s startup count. Thus if you initiate a Kubelet upgrade on a cluster where the Kubelets are currently using the last-known-good config because the current config caused a crash-loop, the new Kubelets will have to rediscover that the current config is bad by crash-looping. 3. The Kubelet has to make sure it properly namespaces this state under a versioned directory name.

Cons in practice: 1. This scenario is certainly possible, but except for the crash-loop case, it is unlikely to cause serious issues, as all other “bad config” cases are discovered almost immediately during loading/parsing/validating the config. In general, we should recommend that Kubelet version upgrades only be performed when the ConfigOK condition is True anyway, so this should be a rare scenario. 2. This is slightly worse than Con 1, because a Kubelet crash-loop will be more likely to disrupt Kubelet version upgrades, e.g. causing an automatic rollback. As above, however, we should recommend that Kubelet version upgrades only be performed when the ConfigOK condition is True, in which case this should be a rare scenario. 3. This isn’t particularly difficult to do, but it is additional code.

Most of the pros and cons aren’t particularly strong either way; the scenarios should be rare in practice given good operational procedures. The remaining pros/cons come down to which versioning scheme is nicer from a development perspective. Namespacing under a versioned directory is fairly easy to do and allows us to iterate quickly and safely across Kubelet versions.

This doc proposes namespacing under a versioned directory.

Reporting Configuration Status

Succinct messages related to the state of Node configuration should be reported in a NodeCondition, in status.conditions. These should inform users which ConfigMap the Kubelet is using, and if the Kubelet has detected any issues with the configuration. The Kubelet should report this condition during startup, after attempting to validate configuration but before actually using it, so that the chance of a bad configuration inhibiting status reporting is minimized.

All NodeConditions contain the fields: lastHeartbeatTime:Time, lastTransitionTime:Time, message:string, reason:string, status:string(True|False|Unknown), and type:string.

These are some brief descriptions of how these fields should be interpreted for node-configuration related conditions: - lastHeartbeatTime: The last time the Kubelet updated the condition. The Kubelet will typically do this whenever it is restarted, because that is when configuration changes occur. The Kubelet will update this on restart regardless of whether the configuration, or the condition, has changed. - lastTransitionTime: The last time this condition changed. The Kubelet will not update this unless it intends to set a different condition than is currently set. - message: Think of this as the “effect” of the reason. - reason: Think of this as the “cause” of the message. - status: True if the currently set configuration is considered OK, False if it is known not to be. Unknown is used when the Kubelet cannot determine the user’s desired configuration. - type: ConfigOK will always be used for these conditions.

The following list of example conditions, sans type, lastHeartbeatTime, and lastTransitionTime, can be used to get a feel for the relationship between message, reason, and status:

Config is OK:

message: "using current (UID: {cur-UID})"
reason: "all checks passed"
status: "True"

No remote config specified:

message: "using current (init)"
reason: "current is set to the local default, and an init config was provided"
status: "True"

No remote config specified, no local init config provided:

message: "using current (default)"
reason: "current is set to the local default, and no init config was provided"
status: "True"

If Node.spec.configSource is invalid during Kubelet startup:

message: "using last-known-good (init)"
reason: "failed to sync, desired config unclear, cause: invalid NodeConfigSource, exactly one subfield must be non-nil, but all were nil"
status: "Unknown"

Validation of a configuration fails:

message: "using last known good: (UID: {lkg-UID})"
reason: "failed to validate current (UID: {cur-UID})"
status: "False"

The same text as the reason, along with more details on the precise nature of the error, will be printed in the Kubelet log.

Operational Considerations

Rollout workflow

Kubernetes does not have the concepts of immutable, or even undeleteable API objects. This makes it easy to “shoot yourself in the foot” by modifying or deleting a ConfigMap. This results in undefined behavior, because the assumption is that these ConfigMaps are not mutated once deployed. For example, this design includes no method for invalidating the Kubelet’s local cache of configurations, so there is no concept of eventually consistent results from edits or deletes of a ConfigMap. You may, in such a scenario, end up with partially consistent results or no results at all.

Thus, we recommend that rollout workflow consist only of creating new ConfigMap objects and updating the spec.configSource field on each Node to point to that new object. This results in a controlled rollout with well-defined behavior.

There is discussion in #10179 regarding ways to prevent unintentional mutation and deletion of objects.

Additional concerns not-yet-addressed

Monitoring configuration status

  • A way to query/monitor the config in-use on a given node. Today this is possible via the configz endpoint, but this is just for debugging, not production use. There are a number of other potential solutions, e.g. exposing live config via Prometheus.


  • A specific orchestration solution for rolling out kubelet configuration. There are several factors to think about, including these general rollout considerations:
    • Selecting the objects that the new config should be rolled out to (Today it is probably okay to roll out Node config with the intention that the nodes are eventually homogeneously configured across the cluster. But what if a user intentionally wants different sets of nodes to be configured differently? A cluster running multiple separate applications, for example.).
    • Specifying the desired end-state of the rollout.
    • Specifying the rate at which to roll out.
    • Detecting problems with the rollout and automatically stopping bad rollouts.
    • Specifying how risk-averse to be when deciding to stop a rollout.
    • Recording a history of rollouts so that it is possible to roll back to previous versions.
    • Properly handling objects that are added or removed while a configuration rollout is in process. For example, Nodes might be added or removed due to an autoscaling feature, etc.
    • Reconciling configuration with objects added after the completion of a rollout, e.g. new Nodes.
    • Pausing/resuming a rollout.