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Author: Elon Li (Software Engineer at PingCAP)

Transcreator: Ran HuangEditor: Tom Dewan

Previous articles in this series:

In our last article, we learned how to implement a component control loop in TiDB Operator. This time, I’ll move on to a new but important topic: backup and restore.

Backup and restore are two of the most important and frequently used operations when you maintain a database. To ensure data safety, database maintainers usually need a set of scripts that automatically back up the data and recover the dataset when data is corrupted. A well-designed backup and restore platform should allow you to:

  • Choose different data sources and target storage.
  • Execute backup jobs on scheduled time.
  • Maintain the backup and restore history for auditing.
  • Clean up obsolete backup files to save storage space.

TiDB Operator provides CustomResourceDefinitions (CRDs) for all these requirements. In this post, I’ll walk you through the core design logic of TiDB Operator’s backup and restore features, leaving out the trivial implementation details. Let’s get started.


TiDB Operator performs ad-hoc backup, restore, and scheduled backup via custom resources (CRs) such as BackupRestore, and BackupSchedule, so we implement three corresponding controllers to execute the control loops.

When a user needs to start a backup job, they can create a YAML file as follows and submit it to Kubernetes. For example:

# An example backup job
kind: Backup
  name: demo-backup-gcp
  namespace: test1
    cluster: mycluster
    projectId: gcp
    location: us-west2
    bucket: backup
    prefix: test1-demo1
    secretName: gcp-secret

When the backup controller receives an event that creates the Backup resource, it creates a job to do the configured backup operation. In the case above, it backs up data in the mycluster database in the test1 namespace and stores the data in the GCP storage specified in the gcs field.

In the following sections, I’ll explain the internal logic of the three controllers.

The backup controller

The backup controller manages the Backup CR. Based on the configuration in the spec field, the controller uses BR or Dumpling to perform the backup task and deletes the corresponding backup file when the user deletes the Backup CR.

Similar to that of other controllers, the core of the backup controller is a control loop, which listens to the Backup CR events (create, update, and delete) and runs the required operations.

In this section, I’ll skip the generic control loop logic and focus on the core backup logic.

Core logic

The core logic of the backup controller is implemented in the syncBackupJob function in the pkg/backup/backup/backup_manager.go file. The actual code processes many corner cases; to facilitate understanding, we removed the unimportant details, so you may see some function signatures are inconsistent. The core logic code is as follows:

if err := JobLister.Jobs(ns).Get(backupJobName); err == nil {
    return nil
} else if !errors.IsNotFound(err) {
    return err
if backup.Spec.BR == nil {
    // create Job Spec which will use Dumpling to do the work
    job = bm.makeExportJob(backup)
} else {
    // create Job Spec which will use BR to do the work
    job = bm.makeBackupJob(backup)
if err := bm.deps.JobControl.CreateJob(backup, job); err != nil {
    // update Backup.Status with error message

In the code block above, backup is the Go struct converted from the Backup YAML created by the user. We use a ValidateBackup function to check the validity of the fields in backup.

Because the backup task is executed as a Kubernetes-native job and because the controller must ensure idempotency—duplicated executions don’t affect the end result—it is possible that a job already exists. Therefore, we try to find if there is an existing backup job in the same namespace:

  • If a job is found, the if statement returns nil and stops processing the current backup object.
  • If a job is not found, the controller proceeds to the next step.

Next, the controller decides whether to use BR or Dumpling to perform the backup task and executes the corresponding function to create the Job spec. In this step, if you have configured the br field, the controller chooses BR; otherwise, it goes with Dumpling.

Finally, the controller uses CreateJob to create the job object and executes the backup operation in the job Pod.

Create Job

The actual backup job is created by two functions: makeExportJob and makeBackupJob. I’ll take makeBackupJob as an example and explain its core code (which is simplified below):

tc := bm.deps.TiDBClusterLister.TidbClusters(backupNamespace).Get(backup.Spec.BR.Cluster)
envVars := backuputil.GenerateTidbPasswordEnv(ns, name, backup, bm)
envVars = append(envVars, backuputil.GenerateStorageCertEnv(ns, backup, bm))
args := []string{"backup", fmt.Sprintf("--namespace=%s", ns), fmt.Sprintf("--backupName=%s", name)}
podSpec := &corev1.PodTemplateSpec{
    Spec: corev1.PodSpec{
        InitContainers: []corev1.Container{{
            Image:   "pingcap/br",
            Command: []string{"/bin/sh", "-c"},
            Args:    []string{fmt.Sprintf("cp /br %s/br; echo 'BR copy finished'", util.BRBinPath)},
        Containers: []corev1.Container{{
            Image:           "pingcap/tidb-backup-manager",
            Args:            args,
            Env:             util.AppendEnvIfPresent(envVars, "TZ"),
        Volumes:          volumes,
job := &batchv1.Job{
    Spec: batchv1.JobSpec{
        Template:     *podSpec,

In the code above, the controller:

  1. Obtains the TidbCluster resources according to the backup information.
  2. Sets the environment variables and command-line arguments.
  3. Constructs a job using pingcap/tidb-backup-manager as the image to perform the backup task. In this process, the pingcap/br image is used as the init container so that BR is copied to the actual working container.
  4. Executes the backup-manager logic after the job is created.

The makeExportJob function takes similar steps, except that it uses Dumpling rather than BR.

Clean backup files

After a user deletes the Backup resource, the backup controller deletes the backup files and releases the storage space.

As mentioned in the previous section, the backup controller creates a job when it receives the create event. Meanwhile, the controller adds a string ( to finalizers of the Backup resource, which signals that the resource needs special treatment when deleted. When a user deletes the Backup resource, the API server sets a value for the metadata.deletionTimestamp field. The backup controller then checks the clean policy of the Backup resource. If the clean policy isn’t Retain, the controller creates a clean job to delete the backup files and reclaim the storage space.

The restore controller

Restoration is the reverse process of backup, and their core logic is similar.

The restore controller checks the validity of the Restore field and then calls the makeImportJob function (using TiDB Lightning) or the makeRestoreJob function (using BR) to create the restore job. The restore job also uses the backup-manager as a basic image.

The backupschedule controller

To ensure data safety, we usually need to automatically back up important data on a scheduled basis. The backupschedule controller implements such functionality.

A user can schedule a backup job in Cron format and configure backup details similar to ad-hoc backup. After the configuration is submitted to the API server, TiDB Operator runs a scheduled backup with this configuration.

To avoid taking up a lot of storage, a user can also decide on the maximum number of copies to save or the maximum time to keep them. TiDB Operator deletes the outdated backup files.

The design logic of the backupschedule controller uses the existing functionality of the backup controller and encapsulates an abstraction layer for scheduled execution. When TiDB Operator runs a scheduled backup task, the backupschedule controller simply creates a Backup resource and has the backup controller do the rest.

You may have noticed that this design is similar to the relationship between CronJob and the Job controller. In fact, the implementation of the backupschedule controller is borrowed from CronJob, especially the logic that determines the next execution time.

Core logic

The core logic of the backupschedule controller is implemented in the Sync function in the pkg/backup/backupschedule/backup_schedule_manager.go file. The main logic is as follows. For implementation details, you can refer to the source code.

func (bm *backupScheduleManager) Sync(bs *v1alpha1.BackupSchedule) error {
    defer bm.backupGC(bs)
    if err := bm.canPerformNextBackup(bs); err != nil { 
        return err 
    scheduledTime, err := getLastScheduledTime(bs,
    if err := bm.deleteLastBackupJob(bs); err != nil { 
        return nil 
    backup, err := createBackup(bm.deps.BackupControl, bs, *scheduledTime)
    bs.Status.LastBackup = backup.GetName()
    bs.Status.LastBackupTime = &metav1.Time{Time: *scheduledTime}
    bs.Status.AllBackupCleanTime = nil
    return nil

The code first calls the canPerformNextBackup function to determine if a new Backup resource should be created to perform a new backup task. If the previous backup has completed or the previous backup has failed, the function agrees to execute the next backup; otherwise, the request is rejected.

After deciding to execute the backup task, the controller call getLastScheduledTime to get the next backup execution time. getLastScheduledTime calculates the last Cron time just before the current time, based on the current time and the Cron settings. getLastScheduledTime also handles a lot of boundary conditions; you can check the source code if you’re interested to know more.

When the controller gets the backup time, it calls the createBackup function to create the Backup resource, thus leaving the actual backup operation to the backup controller.


To adapt TiDB Operator to the Kubernetes execution environment, we abstracted a backup-manager on top of BR, Dumpling, and TiDB Lightning. The backup-manager provides a uniform encapsulation of entry parameters for the tools. When each controller creates a job resource, it uses the backup-manager as an image. The backup-manager starts the corresponding tools to perform backup or restore tasks with the container start parameters and the Backup/Restore resource specs. Moreover, the backup-manager syncs the status of the Backup and Restore resources and updates their progress.

Backup/restore using BR

This section explains how the backup-manager implements the main logic of backup and restore. When the backup controller calls the makeBackupJob function to create a backup job, the Job controller starts a Pod to run the task, using the backup-manager as the image. The first container start parameter passed to makeBackupJob is backup; the backup processing logic is located in cmd/backup-manager/app/cmd/backup.go.

Similar to controllers, when the Pod is started, the backup-manager constructs a series of common Kubernetes client objects, such as Informer, Lister, and Updater. Then it calls the ProcessBackup function and performs the backup. The simplified main logic is as follows:

    backup, err := bm.backupLister.Backups(bm.Namespace).Get(bm.ResourceName)
    if backup.Spec.From == nil {
        return bm.performBackup(ctx, backup.DeepCopy(), nil)
func (bm *Manager) performBackup(ctx context.Context, backup *v1alpha1.Backup, db *sql.DB) error {
    // update status to BackupRunning
    backupFullPath, err := util.GetStoragePath(backup)
    backupErr := bm.backupData(ctx, backup)
    // update status to BackupComplete
func (bo *Options) backupData(ctx context.Context, backup *v1alpha1.Backup) error {
    clusterNamespace := backup.Spec.BR.ClusterNamespace
    args := make([]string, 0)
    args = append(args, fmt.Sprintf("--pd=%s-pd.%s:2379", backup.Spec.BR.Cluster, clusterNamespace))
    dataArgs, err := constructOptions(backup)
    args = append(args, dataArgs...)
    fullArgs := []string{"backup", backupType}
    fullArgs = append(fullArgs, args...)
    klog.Infof("Running br command with args: %v", fullArgs)
    bin := path.Join(util.BRBinPath, "br")
    cmd := exec.CommandContext(ctx, bin, fullArgs...)
    // parse error messages

ProcessBackup runs on a simple logic:

  1. It obtains the Backup object in the corresponding namespace and calls performBackup.
  2. The performBackup function gets the backup storage path and calls the backupData function. We support three backup paths: s3gcs, and locallocal refers to the local path mounted by persistent volumes (PVs).
  3. backupData uses BR to perform the backup. This function combines the command-line parameters BR needs and uses backup as the command to run the BR binary and parse error messages.

After the backup command runs successfully, the backup task is complete.

Import/export using Dumpling and TiDB Lightning

Import and export are similar to backup and restore using BR, except that the tools involved are Dumpling and TiDB Lightning. You can check the previous section for details.


When the backup controller creates a job to execute the clean command, the backup-manager executes the clean logic to delete the corresponding backup files. In cmd/backup-manager/app/cmd/clean.go, the clean logic calls the ProcessCleanBackup function to start the clean process.

After a series of checks, the controller calls cleanBRRemoteBackupData or cleanRemoteBackupData to delete the BR or Dumpling backup files from remote storage.


In this post, we talked about the design and implementation of TiDB Operator’s backup and restore features. When a user creates a backup or restore task, the corresponding backup, restore, or backupschedule controller calls the backup-manager to run the actual operations. The backupschedule controller encapsulates the timing task logic based on the backup controller, while the backup-manager encapsulates the specific tools into a unified portal for each controller to call.

If you are interested in learning more about TiDB Operator, feel free to join our Slack channel or join our discussions at pingcap/tidb-operator.

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