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A Kubernetes reconciliation loop is a continuously repeating control process: it reads a resource’s desired state from the Kubernetes API, observes what is actually running, and takes the smallest actions needed to make reality converge on that specification. Controllers implement this pattern for built-in and custom resources. An operator is a controller pattern that adds custom resources and application-specific operational knowledge. “Agent” is not a standardized Kubernetes primitive, so it should be used only for a separately defined helper process or automation client.
What a reconciliation loop does
Kubernetes is declarative. A user, deployment tool, or another controller describes an outcome—such as a desired replica count, a configured service, or a database cluster represented by a custom resource. Kubernetes stores that desired state in its API. The cluster also has an observed state: which Pods exist, which nodes are available, which external systems respond, and which configuration has actually been applied.
The reconciliation loop continuously reduces the difference between those two states. It does not normally execute a one-time script and stop. Instead, it reacts to changes, checks the current situation, performs a bounded set of changes, records what happened, and waits for another event or a scheduled retry. If a node fails, a Pod is deleted, or a user edits the specification, another pass can restore the declared outcome.
- Desired state: the specification stored in the Kubernetes API, including fields such as a replica count, image, selector, or custom-resource configuration.
- Observed state: what the controller can currently see in the API, its cache, and any systems it is responsible for checking.
- Reconciliation action: a create, update, delete, external API call, or status update that narrows the difference.
- Convergence: repeated passes eventually leave the system matching the specification, assuming dependencies become available and the desired state is valid.
Kubernetes defines a controller as a reconciliation loop that reads a resource’s desired state from the Kubernetes API and acts to bring the cluster’s actual state closer to it. This definition is broader than any particular implementation language or framework.
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Controllers: the general Kubernetes mechanism
Built-in controllers
Core Kubernetes behavior is implemented by built-in controllers that run in the kube-controller-manager component. These controllers manage built-in API resources and coordinate common tasks such as maintaining workload replicas or associating related resources. They use the same control-loop idea as custom code: observe, compare, act, and repeat.
Custom controllers
A custom controller can run as a separate workload in the cluster or outside it, provided it can authenticate to the Kubernetes API. It may manage a built-in resource, a custom resource, or a system outside Kubernetes. For example, a controller might watch a Deployment and ensure a matching configuration object exists, or it might watch a custom resource and call an external service when its specification changes.
“Controller” describes the role and behavior, not a particular packaging model. A controller can be small and focused on one resource kind or coordinate several related kinds. Its ownership should be explicit: operators need to know which controller is allowed to create, update, or delete each object.
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What happens during one reconciliation pass
The exact implementation differs, but a typical controller follows this sequence.
- An object changes. A user creates or edits a watched object, another controller changes a related object, or an external event causes the controller to refresh its view.
- An event becomes a request. A watch mechanism turns the event into a reconcile request, commonly represented by a namespace/name key rather than a full object snapshot. The key identifies what should be re-read.
- The reconciler reads current data. It obtains the latest object and related resources from the API or an informer/cache. It must not assume that the event payload is still current, because several changes may have occurred before the worker handles the request.
- Desired and observed states are compared. The code determines which resources, fields, owner references, or external settings are missing or incorrect.
- Only necessary changes are applied. The controller creates, updates, or deletes resources, or performs an external operation. A well-designed pass does not rewrite unchanged objects or repeat expensive side effects unnecessarily.
- Status is reported. The controller updates status fields or conditions with useful information such as readiness, progress, failure, or the reason a dependency is unavailable.
- The request finishes or is requeued. On success, the queue item can be considered complete. If work must be attempted later, the controller returns an error or explicitly requests a later retry, depending on its framework and policy.
Because events can be coalesced, duplicated, delayed, or delivered while another pass is running, the request should be treated as a prompt to inspect current state—not as an instruction to apply a specific historical change.
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Why idempotence and retries matter
Reconciliation is designed for eventual correction, which means transient failures are expected. An API call can time out after the remote system accepted it; a dependent resource can be created between two reads; or a node can disappear during an update. The controller will often retry, so running the same logic more than once must be safe.
Idempotent logic produces the same intended result when applied repeatedly. Typical techniques include using deterministic names, checking whether a resource already exists before creating it, calculating a complete desired object before updating, and treating an already-completed external operation as success. Avoid blindly appending list entries or issuing irreversible actions on every pass.
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Failure categories
- Transient errors: temporary API unavailability, a starting Pod, or a remote service timeout. Return an error or requeue so the system can try again.
- Permanent specification errors: an invalid value or unsupported combination in the desired state. Set a failure condition with an actionable reason; repeated retries will not repair an invalid specification.
- Dependency failures: a referenced Secret, Service, namespace, or external object is absent. Report the dependency and retry when a watch or later event indicates it may now exist.
- Concurrency conflicts: another writer changed the object between read and update. Re-read the latest version and recompute the change rather than overwriting unrelated fields.
Status and conditions should distinguish these cases. A condition that says an object is waiting for a dependency gives users a different response from one that says configuration is invalid. Controllers should also avoid treating status writes as proof that the underlying work succeeded; status is an observation, not a substitute for verification.
Controller, operator, and agent: precise distinctions
| Term | What it means | Typical state it watches | Operational knowledge | API surface |
|---|---|---|---|---|
| Controller | A Kubernetes control-loop implementation that observes state and takes corrective action. | Built-in resources, custom resources, or external systems. | General resource-management rules. | Existing Kubernetes kinds, custom kinds, or both. |
| Operator | A specialized controller pattern that uses Kubernetes principles and usually one or more custom resources. | Application-specific custom resources plus dependent Kubernetes objects and services. | Domain procedures such as installation, backups, upgrades, schema changes, and recovery. | CRDs define the user-facing API; the controller implements its behavior. |
| Agent | An auxiliary process or automation client; the word has no single standardized Kubernetes primitive. | Whatever its implementation is configured to inspect, potentially Kubernetes or an external system. | Task-specific observation or action; reconciliation ownership must be explicitly defined. | May call the Kubernetes API, use another API, or communicate with a controller. |
Use controller when describing the broad control-loop role. Use operator when the component exposes custom resources and embeds application operations that a generic controller could not know. Do not assume that a process called an agent owns reconciliation. If an agent changes resources, document whether it is the source of truth, a helper invoked by a controller, or an external automation client that can race with the controller.
How an operator uses a CRD
1. Define the application API
A CustomResourceDefinition (CRD) adds a new resource kind to the Kubernetes API. Its schema describes the fields users can set in spec, validation rules, versions, and the status shape exposed by the operator. A resource might declare a database version, storage policy, members, or backup settings. The CRD is an API contract, not the reconciliation logic itself.
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2. Create a custom resource
A user creates an instance of the CRD. That object becomes the desired state for one application deployment or service. The operator watches instances of that kind and may also watch dependent Deployments, StatefulSets, Services, Secrets, Jobs, or other resources.
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The reconcile function translates the custom resource into concrete actions. It may create or update workloads, configure networking, create credentials, initialize storage, or call an external control plane. Ownership references and labels help the operator find the objects it manages and respond when they change.
4. Perform application operations
The operator’s distinguishing value is operational knowledge. It can encode safe sequencing for an upgrade, a backup schedule, a schema migration, failover, or recovery. These procedures must still be modeled as repeatable checks and transitions; putting a long imperative script in a reconcile method without checkpoints makes retries dangerous.
5. Publish conditions and outputs
The operator updates status with readiness, observed versions, failure reasons, and other facts that users and automation can consume. A custom resource should make it possible to tell whether the requested application state is ready, progressing, degraded, or blocked.
Events, watches, queues, and dependency graphs
Most controllers watch a primary resource and one or more related resources. A change to a dependent object must map back to the primary object that owns the desired outcome. For example, if an operator creates a Deployment for each custom resource, a Deployment update should enqueue the corresponding custom-resource key.
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The worker queue separates event delivery from reconciliation. Bursts of changes can be merged into fewer requests, and workers can process independent keys concurrently while serializing work for the same key according to the controller’s design. The reconciler still reads current state on every pass; it should never rely on queue ordering to provide a complete history.
Dependency graphs should be deliberate. Watch only resources that can change the outcome, establish a clear mapping from dependent objects to owners, and avoid cycles in which two controllers continually rewrite each other’s fields. If an external system cannot emit watch events, use a bounded requeue or another polling strategy and expose the last successful observation in status.
Implementing a controller or operator
Operator SDK documents a workflow for Go, Ansible, and Helm projects. The names of generated files and commands vary by SDK release, but the design sequence is stable:
- Choose the ownership boundary. Decide which resource is the primary API, which objects are dependent, and whether an external system is in scope.
- Scaffold the project. Select the implementation type and create the project structure with the SDK or your chosen controller framework.
- Define and validate the CRD, if needed. Specify versions, required fields, defaults, validation, printer columns, and status conditions. A controller for built-in resources can skip this step.
- Register watches. Watch the primary object and map relevant dependent-object events back to it. Keep the mapping deterministic.
- Implement observe-and-act logic. Read current objects, calculate the desired result, apply only necessary changes, and make every operation safe to repeat.
- Handle deletion and cleanup. Decide whether dependents should be garbage-collected, retained, or removed through a finalization workflow. External resources need an explicit cleanup policy.
- Update status carefully. Use conditions with stable types and reasons. Do not report ready until the underlying resource has been verified.
- Generate and deploy manifests. Produce RBAC permissions, CRDs, controller deployment manifests, and any admission or conversion components required by the design.
- Test retries and partial progress. Simulate missing dependencies, API conflicts, restarts, duplicate events, and failures after an external call but before status is written.
Controller-runtime is commonly used in Go projects to provide event-to-request handling and worker-queue foundations. Whether you use it, another framework, or a different language, the same requirements remain: current reads, explicit ownership, idempotent writes, bounded retries, and observable status.
Choosing between a controller, an operator, and an agent
Choose a controller when
- You are enforcing behavior for an existing Kubernetes kind.
- The desired state fits the standard Kubernetes API and does not need a new user-facing resource.
- The logic is generic resource management rather than application lifecycle expertise.
Choose an operator when
- Users need an application-specific API with fields and validation that built-in kinds cannot express.
- The component must encode installation, upgrades, backups, failover, recovery, or another domain procedure.
- A custom resource should be the durable source of desired state and status should expose application readiness.
Use an agent only with an explicit contract
- Define whether the agent is read-only, advisory, or authorized to mutate resources.
- Specify who wins if the agent and a controller write the same field.
- Give it bounded retries, authentication limits, and a way to report failures.
- Do not call it a Kubernetes controller unless it actually owns a reconciliation loop.
Common failure modes and fixes
The controller keeps recreating or rewriting objects
Usually the desired-object calculation is not deterministic, defaulted fields are compared incorrectly, or another writer owns the same fields. Normalize values, use field ownership deliberately, and update only the fields your controller owns.
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Events arrive but nothing changes
Check that the watch is registered, the event maps to the correct primary key, RBAC permits the required reads and writes, and the reconciler is reading the current object rather than stale assumptions. Inspect queue and reconcile errors as well as the resource’s conditions.
Retries create duplicate external resources
Persist a deterministic external identifier or use an idempotency key when the external API supports one. After a timeout, query the external system before creating anything again. Treat “already exists” as a state to reconcile, not automatically as a fatal error.
Status says ready while the service is unusable
Separate object creation from readiness verification. Check the signal that proves the application is usable, record the observed version or endpoint, and set a progressing or degraded condition until that check succeeds.
Two controllers fight over the same field
Assign one owner for each mutable field or resource. Use labels, annotations, and ownership references to make boundaries visible. If coordination is unavoidable, define a shared protocol rather than relying on update order.
Reconciliation never settles
Compare the complete intended state with what is actually stored, including defaults and server-generated values. Look for a controller that changes a field another controller immediately changes back, an unstable name or ordering calculation, or a status update that incorrectly triggers its own work.
Design checklist
- Is the desired state represented by the right built-in resource or CRD?
- Can every reconcile pass safely run twice, after a timeout, or after a process restart?
- Are primary and dependent resources, ownership, and watches documented?
- Does the controller read current state before acting?
- Are transient, permanent, dependency, and conflict failures distinguishable?
- Do status conditions explain what users should do next?
- Are external calls bounded, authenticated, observable, and protected against duplicate effects?
- Is deletion behavior explicit for both Kubernetes and external resources?
- Can operators inspect logs, events, conditions, and the last observed version?
- Is the word “agent” avoided unless its authority and relationship to reconciliation are clear?
Key takeaway
Reconciliation is Kubernetes’ core way of turning declarative intent into a continuously corrected system. Controllers provide the general loop; operators extend it with CRDs and application lifecycle expertise; agents are merely a descriptive category for auxiliary automation unless a design gives them a defined ownership role. Reliable implementations read current state, make idempotent changes, report meaningful conditions, and treat retries and partial failure as normal operating conditions.
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