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@dependabot dependabot bot commented on behalf of github Apr 21, 2023

Bumps github.com/docker/docker from 23.0.1+incompatible to 23.0.3+incompatible.

Release notes

Sourced from github.com/docker/docker's releases.

v23.0.3

23.0.3

Note

Due to an issue with CentOS 9 Stream's package repositories, packages for CentOS 9 are currently unavailable. Packages for CentOS 9 may be added later, or as part of the next (23.0.4) patch release.

Bug fixes and enhancements

  • Fixed a number of issues that can cause Swarm encrypted overlay networks to fail to uphold their guarantees, addressing CVE-2023-28841, CVE-2023-28840, and CVE-2023-28842.
    • A lack of kernel support for encrypted overlay networks now reports as an error.
    • Encrypted overlay networks are eagerly set up, rather than waiting for multiple nodes to attach.
    • Encrypted overlay networks are now usable on Red Hat Enterprise Linux 9 through the use of the xt_bpf kernel module.
    • Users of Swarm overlay networks should review GHSA-vwm3-crmr-xfxw to ensure that unintentional exposure has not occurred.

Packaging Updates

v23.0.2

23.0.2

For a full list of pull requests and changes in this release, refer to the relevant GitHub milestones:

Bug fixes and enhancements

... (truncated)

Commits
  • 59118bf Merge pull request from GHSA-232p-vwff-86mp
  • 219f21b Merge pull request #45196 from vvoland/integration-restart-race-23
  • b87f7f1 libnet/d/overlay: insert the input-drop rule
  • c6bf307 StartWithLogFile: Fix d.cmd race
  • 7f49ca2 TestDaemonRestartKillContainers: Fix loop capture
  • 98cbcb8 libnet/d/overlay: add BPF-powered VNI matcher
  • 5c5fac2 libnet/d/overlay: extract VNI match rule builder
  • c492a22 libn/d/overlay: enforce encryption on sandbox init
  • 018edb0 libnet/d/overlay: document some encryption code
  • a1fd2f2 Merge pull request #45157 from thaJeztah/23.0_backport_update_shfmt
  • Additional commits viewable in compare view

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Bumps [github.com/docker/docker](https://github.com/docker/docker) from 23.0.1+incompatible to 23.0.3+incompatible.
- [Release notes](https://github.com/docker/docker/releases)
- [Commits](moby/moby@v23.0.1...v23.0.3)

---
updated-dependencies:
- dependency-name: github.com/docker/docker
  dependency-type: indirect
...

Signed-off-by: dependabot[bot] <[email protected]>
@dependabot dependabot bot added the dependencies Pull requests that update a dependency file label Apr 21, 2023
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dependabot bot commented on behalf of github May 15, 2023

Looks like github.com/docker/docker is up-to-date now, so this is no longer needed.

@dependabot dependabot bot closed this May 15, 2023
@dependabot dependabot bot deleted the dependabot/go_modules/receiver/elasticsearchreceiver/github.com/docker/docker-23.0.3incompatible branch May 15, 2023 08:47
Garbett1 pushed a commit that referenced this pull request Oct 24, 2024
… Histo --> Histogram (open-telemetry#33824)

## Description

This PR adds a custom metric function to the transformprocessor to
convert exponential histograms to explicit histograms.

Link to tracking issue: Resolves open-telemetry#33827

**Function Name**
```
convert_exponential_histogram_to_explicit_histogram
```

**Arguments:**

- `distribution` (_upper, midpoint, uniform, random_)
- `ExplicitBoundaries: []float64`

**Usage example:**

```yaml
processors:
  transform:
    error_mode: propagate
    metric_statements:
    - context: metric
      statements:
        - convert_exponential_histogram_to_explicit_histogram("random", [10.0, 20.0, 30.0, 40.0, 50.0, 60.0, 70.0, 80.0, 90.0, 100.0]) 
```

**Converts:**

```
Resource SchemaURL: 
ScopeMetrics #0
ScopeMetrics SchemaURL: 
InstrumentationScope  
Metric #0
Descriptor:
     -> Name: response_time
     -> Description: 
     -> Unit: 
     -> DataType: ExponentialHistogram
     -> AggregationTemporality: Delta
ExponentialHistogramDataPoints #0
Data point attributes:
     -> metric_type: Str(timing)
StartTimestamp: 1970-01-01 00:00:00 +0000 UTC
Timestamp: 2024-07-31 09:35:25.212037 +0000 UTC
Count: 44
Sum: 999.000000
Min: 40.000000
Max: 245.000000
Bucket (32.000000, 64.000000], Count: 10
Bucket (64.000000, 128.000000], Count: 22
Bucket (128.000000, 256.000000], Count: 12
        {"kind": "exporter", "data_type": "metrics", "name": "debug"}
```

**To:**

```
Resource SchemaURL: 
ScopeMetrics #0
ScopeMetrics SchemaURL: 
InstrumentationScope  
Metric #0
Descriptor:
     -> Name: response_time
     -> Description: 
     -> Unit: 
     -> DataType: Histogram
     -> AggregationTemporality: Delta
HistogramDataPoints #0
Data point attributes:
     -> metric_type: Str(timing)
StartTimestamp: 1970-01-01 00:00:00 +0000 UTC
Timestamp: 2024-07-30 21:37:07.830902 +0000 UTC
Count: 44
Sum: 999.000000
Min: 40.000000
Max: 245.000000
ExplicitBounds #0: 10.000000
ExplicitBounds #1: 20.000000
ExplicitBounds #2: 30.000000
ExplicitBounds #3: 40.000000
ExplicitBounds #4: 50.000000
ExplicitBounds #5: 60.000000
ExplicitBounds #6: 70.000000
ExplicitBounds #7: 80.000000
ExplicitBounds #8: 90.000000
ExplicitBounds #9: 100.000000
Buckets #0, Count: 0
Buckets #1, Count: 0
Buckets #2, Count: 0
Buckets #3, Count: 2
Buckets #4, Count: 5
Buckets #5, Count: 0
Buckets #6, Count: 3
Buckets #7, Count: 7
Buckets #8, Count: 2
Buckets #9, Count: 4
Buckets #10, Count: 21
        {"kind": "exporter", "data_type": "metrics", "name": "debug"}
```

### Testing

- Several unit tests have been created. We have also tested by ingesting
and converting exponential histograms from the `statsdreceiver` as well
as directly via the `otlpreceiver` over grpc over several hours with a
large amount of data.

- We have clients that have been running this solution in production for
a number of weeks.

### Readme description:

### convert_exponential_hist_to_explicit_hist

`convert_exponential_hist_to_explicit_hist([ExplicitBounds])`

the `convert_exponential_hist_to_explicit_hist` function converts an
ExponentialHistogram to an Explicit (_normal_) Histogram.

`ExplicitBounds` is represents the list of bucket boundaries for the new
histogram. This argument is __required__ and __cannot be empty__.

__WARNING:__

The process of converting an ExponentialHistogram to an Explicit
Histogram is not perfect and may result in a loss of precision. It is
important to define an appropriate set of bucket boundaries to minimize
this loss. For example, selecting Boundaries that are too high or too
low may result histogram buckets that are too wide or too narrow,
respectively.

---------

Co-authored-by: Kent Quirk <[email protected]>
Co-authored-by: Tyler Helmuth <[email protected]>
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