EXPECT_EQ(feed2, control_inputs[1]);

  // Export to a graph def so we can import a graph with control dependencies
  TF_DeleteBuffer(graph_def);
  graph_def = TF_NewBuffer();
  TF_GraphToGraphDef(graph, graph_def, s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);

  // Import again, with remapped control dependency, into the same graph
  TF_DeleteImportGraphDefOptions(opts);
  opts = TF_NewImportGraphDefOptions();

### Transition Status

However, for the vast majority of issues, we aim to empower individuals to first resolve conflicts themselves, asking for help when needed, and only after that fails to escalate further. This approach gives people more control over the outcome of their dispute. 

If you are experiencing or witnessing conflict, we ask you to use the following escalation strategy to address the conflict:

	"acl",
	"cors",
	"delete",
	"encryption",
	"legal-hold",
	"lifecycle",
	"location",
	"logging",
	"notification",
	"partNumber",
	"policy",
	"requestPayment",
	"response-cache-control",
	"response-content-disposition",
	"response-content-encoding",
	"response-content-language",
	"response-content-type",
	"response-expires",
	"retention",
	"select",
	"select-type",
	"tagging",

# Using MinIO with Veeam

When using Veeam Backup and Replication, you can use S3 compatible object storage such as MinIO as a capacity tier for backups.  This disaggregates storage for the Veeam infrastructure and allows you to retain control of your data. With the ease of use of setup and administration of MinIO, it allows a Veeam backup admin to easily deploy their own object store for capacity tiering.

## Prerequisites

in one bucket. For example, you could store `spark.csv` (version `ede336f2`) and `spark.csv` (version `fae684da`) in a single bucket. Versioning protects you from unintended overwrites, deletions, protect objects with retention policies.

To control data retention and storage usage, use object versioning with [object lifecycle management](https://github.com/minio/minio/blob/master/docs/bucket/lifecycle/README.md).  If you have an object expiration lifecycle policy in your non-versioned bucket...

crawler2.setBackground(true);

String sessionId1 = crawler1.execute();
String sessionId2 = crawler2.execute();

crawler1.awaitTermination();
crawler2.awaitTermination();
```

### Custom Interval Control

```java
// Configure politeness policy
container.singleton("intervalController", DefaultIntervalController.class, controller -> {
    controller.setDelayMillisForWaitingNewUrl(5000);

// Scanning stops unrecoverably at EOF, the first I/O error, or a token too
// large to fit in the [Scanner.Buffer]. When a scan stops, the reader may have
// advanced arbitrarily far past the last token. Programs that need more
// control over error handling or large tokens, or must run sequential scans
// on a reader, should use [bufio.Reader] instead.
type Scanner struct {
	r            io.Reader // The reader provided by the client.

github.com/envoyproxy/go-control-plane v0.13.4 h1:zEqyPVyku6IvWCFwux4x9RxkLOMUL+1vC9xUFv5l2/M=
github.com/envoyproxy/go-control-plane v0.13.4/go.mod h1:kDfuBlDVsSj2MjrLEtRWtHlsWIFcGyB2RMO44Dc5GZA=
github.com/envoyproxy/go-control-plane/envoy v1.32.4 h1:jb83lalDRZSpPWW2Z7Mck/8kXZ5CQAFYVjQcdVIr83A=
github.com/envoyproxy/go-control-plane/envoy v1.32.4/go.mod h1:Gzjc5k8JcJswLjAx1Zm+wSYE20UrLtt7JZMWiWQXQEw=

are skipped, and any checks implemented inside the shape inference code are not
executed.

The security impact of skipping those checks should be low, since the attack
scenario would require a malicious user to be able to control the model which as
stated above is already equivalent to code execution. In any case, the
recommendation is not to serve models using Eager mode since it also has
performance limitations.

## Multi-Tenant environments