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Published: Apr 24, 2024 License: MIT Imports: 29 Imported by: 1

README

A brief* overview of Scanner and Fixer and how to control them

First and foremost: most code in this folder is disabled by default dynamic config, and it should be considered beta-like quality in general. Understand what you are enabling before enabling it, and run it at your own risk. It is shared primarily so others can learn from and leverage what we have already encountered, if they end up needing it or something similar.

Any actually recommended fixing processes will be explicitly called out in release notes or similar. This document is not recommending any, merely describing.

There are a variety of problems with the Scanner and Fixer related code, so please do not take this document as a sign that it is a structure we want to keep. It has just been confusing enough that it took substantial time to understand, and now some of that effort is written down to save people the full effort in the future.

What is this folder for

This folder as a whole contains a variety of data-cleanup workflows.

Stuff like:

  • Find old, unnecessary data and delete it.
  • Find data caused by old bugs and fix it.
  • Clean up and remove abandoned tasklists so they do not continue taking up space.

As a general rule, these all scan the full database (for one kind of data), check some data, and clean it up if necessary.
How their code does that varies quite a bit, however.

E.g. the "history scavenger" finds old branches of history that lost their CAS race to update the workflow's official history. It is not possible to guarantee that these are cleaned up while a workflow runs, because any cleanup could have failed.
Instead, the history scavenger periodically walks through the whole database and looks for these orphaned history branches, and deletes them.

The most complex of these processes are based around Scanner and Fixer, and so this readme is almost exclusively written for them.
For others, just read their code, it's probably faster than reading any doc about their code.

Basic structure of Scanner and Fixer workflows

  • "Invariants" define Check and Fix methods that make sure our invariants hold, and fixes them if they did not for some reason.
    • These are in the common/reconciliation/invariant folder, e.g. concreteExecutionExists.go checks (Check) that a current execution record points to a concrete record that exists. If it does not, it deletes the current record (the Fix).
    • Some of these have a paired "invariant collection" which is currently a 1:1 relationship, and is used elsewhere to refer to the invariants by a name where it isn't unique per data-type (e.g. timer only has one).
    • These are often bundled together in an InvariantManager, which runs multiple and aggregates the results.
    • Invariants are almost exclusively used by Scanner and Fixer. One is also used as part of replication processing, in ndc/history_resender.go. That use is essentially completely unrelated to Scanner or Fixer, and is ignored for this doc.
  • Scanner runs only the Check, and pushes all failing checks to the blobstore.
    • It gets its core data through an Iterator, whose implementation depends on your datastore.
    • On each Iterator item, it runs through its list of Invariants (via an InvariantManager).
    • Per item, the aggregated result from the InvariantManager is collected, and pushed to a blob-store.
  • Fixer runs only Fix, on the downloaded results from the most-recent Scanner.
    • Structurally it's extremely similar to Scanner, but it calls Fix instead, and it gets its data from a different Iterator (this one iterates over the scanner results in your blobstore).
    • All configured invariants run, not just the ones that failed Check previously.
    • Because only Fix is called, invariants should likely Check first internally.
  • ^ The workflows that run Scanner and Fixer are started at service startup if enabled, and are run as continuous every-minute crons that essentially never expire.
    • Each scanner / fixer type uses its own tasklist, and these workers are only started if enabled.
      • This effectively means that enabling one works immediately after a service start, but disabling only pauses, which may be undesirable if they are resumed after a lengthy delay.
      • Because these are crons, only the original start arguments are retained, not new ones if changes are made.
      • Manually cancel or terminate the cron workflows if you change relevant fields, and (re)start a worker to start the new versions.
    • Each workflow that runs processes only one data-source, primarily via its Iterator.
      • This means all invariants within a scanner/fixer run handle the same type of data.
  • The bulk of all ^ this is plugged together by *shardscanner.ScannerConfig instances, which contain everything that customizes each particular kind of scanner/fixer, which is stored in / retrieved from the context by the workflow's type as a key.
    • E.g. see the concrete_execution.go config.
    • The workflow type (registered function name) is in there, as are the start args, some high level dynamic config to control the scanner/fixer workflows (enabled, concurrency, etc), and "hooks" for both scanner and fixer.
    • The workflows largely do not care about this config, they just run the same activities each time and let the activities figure out what to do.
    • Activities get their config and other dependencies from Get{Scanner,Fixer}Context), which contain this config.
  • Hooks (fields in the ScannerConfig) are where much of the non-workflow behavior comes from.
    • E.g. the concrete scanner hooks bundle up a "manager" (InvariantManager), "iterator" (walks the datasource and yields individual items to check), and "custom config" (dynamic config to control which invariants are enabled) as part of the create*Hooks funcs in concrete_exeuction.go.
  • And so, ultimately the workflows essentially take this config and create a Scanner or Fixer out of them (in activities), as you can see in e.g. the scanner workflow.
    • It reads some config through an activity (which gets its per-workflow-type context).
      • This is used to decide parallelism / pass additional args to the scan activities.
    • The scanShardActivity (in shardscanner/activities.go essentially iterates over shards, and runs scanShard on each one, which creates a NewScanner that gets its config and behavior from args / environment / hooks.
    • Fixer is very similar, except it also queries the previous Scanner run to get the list of blobstore files that it needs to process.

Last but not least: there are other workflows in this folder which do not follow these patterns!

Hopefully that made sense.

Config

Scanners and fixers are generally disabled by default, as they can consume substantial resources and may delete or modify data to correct issues.
Because of this, you generally need to modify your dynamic config to run them.

At the time of writing, you can enable these with config like the following.

Enable scanner workflows (these are per data source / per record type, like "concrete executions" and "timers"):

worker.executionsScannerEnabled:
  - value: true        # default false
worker.currentExecutionsScannerEnabled:
  - value: true        # default false
worker.timersScannerEnabled:
  - value: true        # default false
worker.historyScannerEnabled:
  - value: true        # default false
worker.taskListScannerEnabled:
  - value: true        # default true, only used on sql stores

Enable scanner invariants (currently each one only supports one data source / record type, but there may be multiple invariants for the data source):

# concretes
worker.executionsScannerInvariantCollectionStale:
  - value: true         # default false
worker.executionsScannerInvariantCollectionMutableState:
  - value: true         # default true
worker.executionsScannerInvariantCollectionHistory:
  - value: true         # default true

# timer invariant is implied as there is only one.
# to enable it, enable the workflow.

# currents, NONE OF THESE WORK because of type mismatch
worker.currentExecutionsScannerInvariantCollectionHistory:
  - value: true         # default true
worker.currentExecutionsInvariantCollectionMutableState:
  - value: true         # default true

Enable fixer workflows (also one per type):

worker.concreteExecutionFixerEnabled:
  - value: true       # default false
worker.currentExecutionFixerEnabled:
  - value: true       # default false
worker.timersFixerEnabled:
  - value: true       # default false

Enable fixer to run on a domain (required to do anything to a domain's data, which also means nothing will be fixed without this):

worker.currentExecutionFixerDomainAllow:
  - value: true         # default false
    constraints: {domainName: "your-domain"}  # for example, or have no constraints to enable for all domains
worker.concreteExecutionFixerDomainAllow:
  - value: true         # default false
worker.timersFixerDomainAllow:
  - value: true         # default false

Enable fixer invariants:

# concretes
worker.executionsFixerInvariantCollectionStale:
  - value: true         # default false
worker.executionsFixerInvariantCollectionMutableState:
  - value: true         # default true
worker.executionsFixerInvariantCollectionHistory:
  - value: true         # default true

# timer invariant is enabled if timer-fixer is enabled, as there is only one

# current execution fixer has never worked and does not currently support dynamic config

Verifying locally

There are a few ways to run local clusters and make changes and test things out, but this is the way I did things when reading and changing this code:

  1. Run the default docker-compose cluster (docker-compose.yml)
  2. Make your config/code/etc changes locally for scanner / fixer.
  3. make cadence-server to ensure it builds
  4. ./cadence-server start --services worker to start up a worker that will connect to your docker-compose cluster.
  5. Browse history via the web UI, usually http://localhost:8088/domains/cadence-system/workflows

The default docker-compose setup starts a worker instance, but due to the default dynamic config setup where all but worker.taskListScannerEnabled are disabled, the in-docker worker will not run (most) scanner/fixer tasklists and will not steal any tasks from a local worker.

So you can often simply run it without any changes, start up your local (customized) worker service outside of docker, and everything will Just Work™.

This way you can leverage the normal docker-compose yaml files with minimal effort, use the web UI to observe the results, and rapidly change/rebuild/rerun/debug/etc without needing to deal with docker.

If you do need to debug the tasklist scanner, I would recommend making a custom build, and modifying the docker-compose file to use your build. Details on that are below, but they are not necessary for other scanners/fixers.

Docker-compose changes (tasklist scanner only)

There are a few ways to achieve this, but I like modifying the docker-compose*.yaml file to use a custom local build, and just changing its dynamic config to disable the tasklist scanner.

To do that, see the docker/README.md file for instructions. Personally I prefer making a unique auto-setup tag so it does not replace any non-customized docker-compose runs in the future. E.g.:

services:
  # ...
  cadence:
    image: ubercadence/server:my-auto-setup  # use your new tag
    # ...
    environment:
      # note this env var, it is the file you need to change
      - "DYNAMIC_CONFIG_FILE_PATH=config/dynamicconfig/development.yaml"

And just make a build after changing the dynamic config file. This will copy the file into the docker image, and any local changes won't affect the running container.

worker.taskListScannerEnabled:
  - value: false        # default true, only used on sql stores

Just set ^ this, and make sure the others are not explicitly enabled as they are disabled by default, and you're likely done.

Other things to change outside docker
  • Config, as running the server locally will generally use the config/dynamicconfig/development.yaml file, so you likely want to change that one to enable your code.
  • Data, to give your invariant / scanner something to notice
    • Running some workflows and then deleting / modifying the data by hand in the database is fairly simple.
  • Your invariants, to prevent prematurely purging any manual data changes you made.
    • I'm fond of this trick:
      func (i *invariant) Check(...) {
          x := true    // go vet doesn't currently complain
          if x {       // about dead code with this.  handy!
              return CheckResult{Failed} // fake failure, so all records go to fixer
          }
          // ... the rest of your normal code, unchanged
      }
      func (i *invariant) Fix(...) {
          // print the fix rather than doing it, so the next runs try too.
          // or do the `if x {` trick here too
      }
      
  • Your IDE, to launch with only the worker, as other services are not necessary and it will just slow down startup/shutdown.
    • Just make sure you have start --services worker in its start-args.
Running it all and checking the results

Add some breakpoints or print statements, run it and see what happens :)

If Scanner found anything interesting, you should now have a /tmp/blobstore folder with files like {uuid()}_0.corrupted. These uuids are random, and the _0.corrupted suffix marks them as page 0 (out of N), and that they refer to corrupted entries. You'll have one uuid per Scanner shard (configurable, for concurrency) that found issues, and multiple pages per shard if the results exceeded the paging size limit.

If Fixer found anything, /tmp/blobstore should now have {uuid()}_0.skipped and/or {uuid()}_0.fixed files. These uuids are also random, and do not refer to the Scanner file that their data came from, and the uuid and paging patterns are the same as Scanner.

You may also have *.failed files, following the same pattern. Similarly, these are cases where an invariant returned a Failure result (they can come from scanner or fixer). Only *.corrupted files from scanner will be processed by fixer, however.

Note that *.failed files can contain invariant results of all statuses, as the status of a record trends towards "failed", and only the final status is recorded. For details, see the behavior in the InvariantManger.

You can also see the results in the scanner and fixer workflows in the UI. In particular:

  • Scanner:
    • Each scanner type has a unique ID, like concreteExecutionsScannerWFID = "cadence-sys-executions-scanner".
    • Check the activities to see how many corruptions were found per shard
    • Query its aggregate_report (works in UI, others require arguments and you currently need to use the CLI) to get overall counts.
    • The activities return results with UUIDs and page numbers. These are the UUIDs and page ranges for files in /tmp/blobstore, so you can look up specific detailed results.
      • Otherwise tbh I grab a known workflow ID and grep the most-recent batch of files for it.
  • Fixer:
    • Check the recent fixer workflows for fix results.
      • If it has completed already, it is likely not the most-recent or the currently running one. Check older ones until you find some with more than ~ a dozen events, as those are no-ops.
    • The activities accept UUIDs and page ranges from scanner (these match the return values in scanner, and refer to the scan-result files in /tmp/blobstore), and return the same kind of structure (new random UUIDs, new page ranges, referring to new files in /tmp/blobstore).
      • Again, I would also recommend just grepping for known IDs that should have been processed.

If you are not printing or debugging whatever info you are looking for, check the contents of these files to verify they're doing what you expect!

An example working scanner/fixer setup, visible in /tmp/blobstore files

This is the new "stale" invariant working in its concrete execution scanner -> the concrete execution fixer also working, with faked results to simplify testing. I also ran all the other concrete invariants because I was curious.

I made a change like this:

func (c *staleWorkflowCheck) Check(
	ctx context.Context,
	execution interface{},
) CheckResult {
	x := true
	if x {
		return CheckResult{
			CheckResultType: CheckResultTypeCorrupted,
			InvariantName:   c.Name(),
			Info:            "fake corrupt",
		}
	}
	_, result := c.check(ctx, execution)
	return result
}

so the Check call would always fail, and the Fix call would run the real check.

And added dynamic config like this:

# enable these invariants
worker.executionsScannerInvariantCollectionStale:
  - value: true         # default false
worker.executionsScannerInvariantCollectionMutableState:
  - value: true         # default true
worker.executionsScannerInvariantCollectionHistory:
  - value: true         # default true
worker.executionsFixerInvariantCollectionStale:
  - value: true         # default false
worker.executionsFixerInvariantCollectionMutableState:
  - value: true         # default true
worker.executionsFixerInvariantCollectionHistory:
  - value: true         # default true

# these invariants are all run by the concrete execution scanner/fixer
worker.executionsScannerEnabled:  # note slightly different name
  - value: true         # default false
worker.concreteExecutionFixerEnabled:
  - value: true         # default false
worker.concreteExecutionFixerDomainAllow:
  - value: true         # default false

After a scanner and fixer run, /tmp/blobstore contained *.corrupted and *.skipped files. The *.corrupted files contained data like this:

{
  "Input": {
    "Execution": { ... },
    "Result": {
      "CheckResultType": "corrupted",
      "DeterminingInvariantType": "stale_workflow",
      "CheckResults": [
        {
          "CheckResultType": "healthy",
          "InvariantName": "history_exists",
          "Info": "",
          "InfoDetails": ""
        },
        {
          "CheckResultType": "healthy",
          "InvariantName": "open_current_execution",
          "Info": "",
          "InfoDetails": ""
        },
        {
          "CheckResultType": "corrupted",
          "InvariantName": "stale_workflow",
          "Info": "fake corrupt",
          "InfoDetails": ""
        }
      ]
    }
  },
  "Result": {
    "FixResultType": "skipped",
    "DeterminingInvariantName": null,
    "FixResults": null
  }
}

You can see the two healthy invariants, and the one I faked.

When fixer then ran I got this in a *.skipped file:

{
  "Execution": { ... },
  "Input": {
    "Execution": { ... },
    "Result": {
      "CheckResultType": "corrupted",
      "DeterminingInvariantType": "stale_workflow",
      "CheckResults": [
        {
          "CheckResultType": "healthy",
          "InvariantName": "history_exists",
          "Info": "",
          "InfoDetails": ""
        },
        {
          "CheckResultType": "healthy",
          "InvariantName": "open_current_execution",
          "Info": "",
          "InfoDetails": ""
        },
        {
          "CheckResultType": "corrupted",
          "InvariantName": "stale_workflow",
          "Info": "fake corrupt",
          "InfoDetails": ""
        }
      ]
    }
  },
  "Result": {
    "FixResultType": "skipped",
    "DeterminingInvariantName": null,
    "FixResults": [
      {
        "FixResultType": "skipped",
        "InvariantName": "history_exists",
        "CheckResult": {
          "CheckResultType": "healthy",
          "InvariantName": "history_exists",
          "Info": "",
          "InfoDetails": ""
        },
        "Info": "skipped fix because execution was healthy",
        "InfoDetails": ""
      },
      {
        "FixResultType": "skipped",
        "InvariantName": "open_current_execution",
        "CheckResult": {
          "CheckResultType": "healthy",
          "InvariantName": "open_current_execution",
          "Info": "",
          "InfoDetails": ""
        },
        "Info": "skipped fix because execution was healthy",
        "InfoDetails": ""
      },
      {
        "FixResultType": "skipped",
        "InvariantName": "stale_workflow",
        "CheckResult": {
          "CheckResultType": "",
          "InvariantName": "",
          "Info": "",
          "InfoDetails": ""
        },
        "Info": "no need to fix: completed workflow still within retention + 10-day buffer",
        "InfoDetails": "completed workflow still within retention + 10-day buffer, closed 2023-09-20 20:26:04.924876012 -0500 CDT and allowed to exist until 2023-10-07"
      }
    ]
  }
}

Notice that all three invariants ran in the fixer (all three were enabled), and all three fixes were skipped because they did not find any problems.

If I had also faked the stale workflow invariant Fix, you would see a FixResultType of "fixed" on that invariant in fixer, and a file named *.fixed rather than *.skipped.

An example bad scanner/fixer setup

This is the current-execution scanner working -> the current-execution fixer misbehaving and using the wrong type, and creating *.failed files, as of commit eb55629d.

I faked the current execution invariant to always say "corrupt" in Check, and panic in Fix, and enabled the current execution scanner and fixer in dynamic config, and ran the worker.

First, the scanner run creates *.corrupted files with entries like this:

{
  "Input": {
    "Execution": { ... },
    "Result": {
      "CheckResultType": "corrupted",
      "DeterminingInvariantType": "concrete_execution_exists",
      "CheckResults": [
        {
          "CheckResultType": "corrupted",
          "InvariantName": "concrete_execution_exists",
          "Info": "execution is open without having concrete execution",
          "InfoDetails": "concrete execution not found. WorkflowId: e905c98f-108a-4191-9ef2-ca07a1361f9c, RunId: 6bc5386b-c043-4eb1-a332-c3bb7b5188f0"
        }
      ]
    }
  },
  "Result": {
    "FixResultType": "skipped",
    "DeterminingInvariantName": null,
    "FixResults": null
  }
}

This shows that it identified my "always corrupt" results correctly, in the concrete_execution_exists invariant.

This is later consumed by the current execution fixer, which produces *.failed files with contents like this:

{
  "Execution": { ... },
  "Input": {
    "Execution": { ... },
    "Result": {
      "CheckResultType": "corrupted",
      "DeterminingInvariantType": "concrete_execution_exists",
      "CheckResults": [
        {
          "CheckResultType": "corrupted",
          "InvariantName": "concrete_execution_exists",
          "Info": "execution is open without having concrete execution",
          "InfoDetails": "concrete execution not found. WorkflowId: e905c98f-108a-4191-9ef2-ca07a1361f9c, RunId: 6bc5386b-c043-4eb1-a332-c3bb7b5188f0"
        }
      ]
    }
  },
  "Result": {
    "FixResultType": "failed",
    "DeterminingInvariantName": "history_exists",
    "FixResults": [
      {
        "FixResultType": "failed",
        "InvariantName": "history_exists",
        "CheckResult": {
          "CheckResultType": "failed",
          "InvariantName": "history_exists",
          "Info": "failed to check: expected concrete execution",
          "InfoDetails": ""
        },
        "Info": "failed fix because check failed",
        "InfoDetails": ""
      },
      {
        "FixResultType": "failed",
        "InvariantName": "open_current_execution",
        "CheckResult": {
          "CheckResultType": "failed",
          "InvariantName": "open_current_execution",
          "Info": "failed to check: expected concrete execution",
          "InfoDetails": ""
        },
        "Info": "failed fix because check failed",
        "InfoDetails": ""
      }
    ]
  }
}

You can see scanner's data as the input-result, and completely different invariants running and failing as the fixer result.

Thoughts and prayers

Most notably:

  • The current implementation is extremely difficult to extend externally, as the code depends heavily on constants that cannot be added to or changed.
    • Changing this likely requires rewriting a significant amount of the code, but does seem worth doing.
    • Future versions really should try to fix this. Custom database plugins may have unique problems and need unique scan/fix tools, and those are unlikely to be open-source friendly and useful to run on every database.
  • The current-execution fixer has never been run successfully anywhere. Beware drawing any conclusions from its code or config.
    • The scanner appears to work, and the invariant seems correct, but the fixer was written to use the concrete execution invariants, and that has caused it to always fail when run.
    • This might be fixed and (optionally) enabled or deleted in the future.
  • Current, concrete, and timer scan/fix code is very similar but not identical.
    • Maybe this is good, maybe not, but it can be confusing. Read carefully.
  • Config keys, configurability, all things config-like vary widely between scan/fix implementations.
    • Copy/paste, don't guess. And verify it before calling it "done".
  • The current "scan everything, then fix everything" structure is problematically slow on large clusters, and quite resource-wasteful due to doing everything at least 2x.
    • Generally speaking it's probably not a bad thing to slow it down and re-check, but large clusters can take weeks before fixer starts. That's horrible for verifying fixes, or addressing any issues quickly.
  • Queries feel like an odd way to pass data from scanner to fixer.
    • I suspect they were done to avoid returning too much data, violating a blob-size limit constraint. This... might be valid? The data it actually uses is saved by fixer's querying activity though, so it is still bound by that limit.
    • Due to results being spread between many activities and many queries, overviews are hard to get. We could instead push it all to a new blobstore file, for human use.
  • There's a lot of indirection in general for unknown reasons, and that makes control-flow extremely hard to figure out.
    • Possibly it was intended for more flexibility than it has seen, possibly it would simply benefit from some modernizing (instance fields rather than background activity context), possibly it's a functional-like lament about the lack of generics in Go when it was written, I'm really not sure.

Overall it seems like it probably deserves a rewrite, though some of the parts are pretty clearly reusable (invariants, iterators, etc).


[*]: may not actually be brief

Documentation

Index

Constants

This section is empty.

Variables

This section is empty.

Functions

func CheckDataCorruptionWorkflow added in v0.24.0

func CheckDataCorruptionWorkflow(ctx workflow.Context, fixList []entity.Execution) error

CheckDataCorruptionWorkflow is invoked by remote cluster via signals

func EmitResultMetricsActivity added in v0.24.0

func EmitResultMetricsActivity(ctx context.Context, fixResults []invariant.FixResult) error

func ExecutionFixerActivity added in v0.24.0

func ExecutionFixerActivity(ctx context.Context, fixList []entity.Execution) ([]invariant.FixResult, error)

func HistoryScannerWorkflow added in v0.9.3

func HistoryScannerWorkflow(
	ctx workflow.Context,
) error

HistoryScannerWorkflow is the workflow that runs the history scanner background daemon

func HistoryScavengerActivity added in v0.9.3

func HistoryScavengerActivity(
	activityCtx context.Context,
) (history.ScavengerHeartbeatDetails, error)

HistoryScavengerActivity is the activity that runs history scavenger

func NewScannerContext added in v0.18.1

func NewScannerContext(ctx context.Context, workflowName string, scannerContext scannerContext) context.Context

NewScannerContext provides context to be used as background activity context it uses typed, private key to reduce access scope

func TaskListScannerWorkflow

func TaskListScannerWorkflow(
	ctx workflow.Context,
) error

TaskListScannerWorkflow is the workflow that runs the task-list scanner background daemon

func TaskListScavengerActivity

func TaskListScavengerActivity(
	activityCtx context.Context,
) error

TaskListScavengerActivity is the activity that runs task list scavenger

Types

type BootstrapParams

type BootstrapParams struct {
	// Config contains the configuration for scanner
	Config Config
	// TallyScope is an instance of tally metrics scope
	TallyScope tally.Scope
}

BootstrapParams contains the set of params needed to bootstrap the scanner sub-system

type Config

type Config struct {
	// ScannerPersistenceMaxQPS the max rate of calls to persistence
	// Right now is being used by historyScanner to determine the rate of persistence API calls
	ScannerPersistenceMaxQPS dynamicconfig.IntPropertyFn
	// TaskListScannerEnabled indicates if taskList scanner should be started as part of scanner
	TaskListScannerEnabled dynamicconfig.BoolPropertyFn
	// TaskListScannerOptions contains options for TaskListScanner
	TaskListScannerOptions tasklist.Options
	// Persistence contains the persistence configuration
	Persistence *config.Persistence
	// ClusterMetadata contains the metadata for this cluster
	ClusterMetadata cluster.Metadata
	// HistoryScannerEnabled indicates if history scanner should be started as part of scanner
	HistoryScannerEnabled dynamicconfig.BoolPropertyFn
	// ShardScanners is a list of shard scanner configs
	ShardScanners              []*shardscanner.ScannerConfig
	MaxWorkflowRetentionInDays dynamicconfig.IntPropertyFn
}

Config defines the configuration for scanner

type Scanner

type Scanner struct {
	// contains filtered or unexported fields
}

Scanner is the background sub-system that does full scans of database tables to cleanup resources, monitor anomalies and emit stats for analytics

func New

func New(
	resource resource.Resource,
	params *BootstrapParams,
) *Scanner

New returns a new instance of scanner daemon Scanner is the background sub-system that does full scans of database tables in an attempt to cleanup resources, monitor system anamolies and emit stats for analysis and alerting

func NewDataCorruptionWorkflowWorker added in v0.24.0

func NewDataCorruptionWorkflowWorker(
	resource resource.Resource,
	params *BootstrapParams,
) *Scanner

func (*Scanner) Start

func (s *Scanner) Start() error

Start starts the scanner

func (*Scanner) StartDataCorruptionWorkflowWorker added in v0.24.0

func (s *Scanner) StartDataCorruptionWorkflowWorker() error

Directories

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