Modified items

All recently modified items, latest first.

argocd-cli-bash-completion-3.0.12-1.1.lbn36.noarch: Bash command line completion support for argocd-cli.

argocd-cli-3.0.12-1.1.lbn36.x86_64: Argo CD is a declarative, GitOps continuous delivery tool for Kubernetes. This packages contains the CLI to interact with the ArgoCD installation in a Kubernetes cluster.

argocd-autopilot-zsh-completion-0.4.19-1.1.lbn36.noarch: zsh command line completion support for argocd-autopilot.

argocd-autopilot-fish-completion-0.4.19-1.1.lbn36.noarch: Fish command line completion support for argocd-autopilot.

argocd-autopilot-bash-completion-0.4.19-1.1.lbn36.noarch: Bash command line completion support for argocd-autopilot.

argocd-autopilot-0.4.19-1.1.lbn36.x86_64: New users to GitOps and Argo CD are not often sure how they should structure their repos, add applications, promote apps across environments, and manage the Argo CD installation itself using GitOps. Argo CD Autopilot saves operators time by: * Installing and managing the Argo CD application using GitOps. * Providing a clear structure for how applications are to be added and updated, all from git. * Creating a simple pattern for making updates to applications and promoting those changes across environments. * Enabling better disaster recovery by being able to bootstrap new clusters with all the applications previously installed. * Handling secrets for Argo CD to prevent them from spilling into plaintext git. (Soon to come) The Argo-CD Autopilot is a tool which offers an opinionated way of installing Argo-CD and managing GitOps repositories.

inspec-vault-0.4.10-1.lbn36.noarch: This InSpec resource pack uses the Vault SDK v0.8.0 and provides the required resources to write tests for resources in Vault. To use within you inspec installation; add the following to your profile's inspec.yml: depends: - name: inspec-vault path: /usr/share/inspec-vault supports: - platform: vault

inspec-gcp-1.11.109-1.lbn36.noarch: This InSpec resource pack uses the GCP SDK v0.8.0 and provides the required resources to write tests for resources in GCP. To use within you inspec installation; add the following to your profile's inspec.yml: depends: - name: inspec-gcp path: /usr/share/inspec-gcp supports: - platform: gcp

inspec-digitalocean-0.2.0-1.lbn36.noarch: This InSpec resource pack uses the Digital Ocean SDK and provides the required resources to write tests for resources in Digital Ocean. To use within you inspec installation; add the following to your profile's inspec.yml: depends: - name: inspec-digitalocean path: /usr/share/inspec-digitalocean supports: - platform: digitalocean

inspec-azure-1.118.43-1.lbn36.noarch: This InSpec resource pack uses the Azure SDK v0.8.0 and provides the required resources to write tests for resources in Azure. To install and use within you inspec installation; run the following $ inspec plugin install /usr/share/inspec-azure

inspec-aws-1.83.62-1.lbn36.noarch: This InSpec resource pack uses the AWS SDK and provides the required resources to write tests for resources in AWS. To install and use within you inspec installation; add the following to your profile's inspec.yml: depends: - name: inspec-aws path: /usr/share/inspec-aws supports: - platform: aws

python3-googleapis-common-protos-1.66.0-1.lbn36.noarch: Common protobufs used in Google APIs.

amazon-ssm-agent-3.2.815.0-1.lbn36.x86_64: This package provides the Amazon SSM Agent for managing EC2 Instances using Amazon EC2 Systems Manager (SSM). The SSM Agent runs on EC2 or on-premise instances and enables you to quickly and easily execute remote commands or scripts against one or more instances. When you execute a command, the agent on the instance processes the document and configures the instance as specified. This collection of capabilities helps you automate management tasks such as collecting system inventory, applying operating system (OS) patches, automating the creation of Amazon Machine Images (AMIs), and configuring operating systems (OSs) and applications at scale. Systems Manager works with managed instances: Amazon EC2 instances, or servers and virtual machines (VMs) in your on-premises environment that are configured for Systems Manager.

amanda-server-3.5.4-15.lbn36.x86_64: The amanda-server package should be installed on the AMANDA server, the machine attached to the device(s) (such as a tape drive) where backups will be written. You will also need to install the amanda package on the AMANDA server machine. And, if the server is also to be backed up, the server also needs to have the amanda-client package installed.

amanda-libs-3.5.4-15.lbn36.x86_64: This package contains basic Amanda libraries, which are used by all Amanda programs.

amanda-client-3.5.4-15.lbn36.x86_64: The Amanda-client package should be installed on any machine that will be backed up by AMANDA (including the server if it also needs to be backed up). You will also need to install the amanda package on each AMANDA client machine.

amanda-3.5.4-15.lbn36.x86_64: AMANDA, the Advanced Maryland Automatic Network Disk Archiver, is a backup system that allows the administrator of a LAN to set up a single master backup server to back up multiple hosts to one or more tape drives or disk files. AMANDA uses native dump and/or GNU tar facilities and can back up a large number of workstations running multiple versions of Unix. Newer versions of AMANDA (including this version) can use SAMBA to back up Microsoft(TM) Windows95/NT hosts. The amanda package contains the core AMANDA programs and will need to be installed on both AMANDA clients and AMANDA servers. Note that you will have to install the amanda-client and/or amanda-server packages as well.

gdal-libs-3.8.1-1.lbn36.x86_64: This package contains the GDAL file format library.

python3-ruamel-yaml-0.17.21-1.lbn36.x86_64: ruamel.yaml is a YAML 1.2 loader/dumper package for Python. It is a derivative of Kirill Simonov’s PyYAML 3.11

python3-django-celery-beat-2.8.1-1.lbn36.noarch: Version: 2.8.1 Web: http:/django-celery-beat.readthedocs.io/ Download: http:/pypi.python.org/pypi/django-celery-beat Source: http:/github.com/celery/django-celery-beat Keywords: django, celery, beat, periodic task, cron, scheduling About This extension enables you to store the periodic task schedule in the database. The periodic tasks can be managed from the Django Admin interface, where you can create, edit and delete periodic tasks and how often they should run. Using the Extension Usage and installation instructions for this extension are available from the Celery documentation. Important Warning about Time Zones Warning If you change the Django TIME_ZONE setting your periodic task schedule will still be based on the old timezone. To fix that you would have to reset the “last run time” for each periodic task: >>> from django_celery_beat.models import PeriodicTask, PeriodicTasks >>> PeriodicTask.objects.all().update(last_run_at=None) >>> PeriodicTasks.update_changed() N


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