Deployment
Willa Stiff
Although the deployment of broadband services slowed dramatically in the wake of the 2015 Title II Order, the Commission has taken many actions to accelerate deployment, including removing barriers to infrastructure investment, promoting competition in the telecommunications market, and by restoring the longstanding bipartisan light-touch regulatory framework for broadband Internet access services. Thanks to these efforts, the Report concludes that broadband services are now being deployed to all Americans on a reasonable and timely basis.
Nonetheless, closing the digital divide and furthering the deployment of advanced telecommunications capabilities remains the top priority for the FCC and the Report concludes there is much work still to be done.
This page documents deployments using dpl v1 which is thedefault version. The next major version dpl v2 will be released soon. Pleasesee the announcement blog post on details about the release process. Documentation for dpl v2 can be found here.
branch: name of the branch. If omitted, this defaults to the app-specific branch, or master. If the branch name is not known ahead of time, you can specify all_branches: true instead of branch: and use other conditions to control your deployment.
The OpenTelemetry Collector consists of a single binary which you can use indifferent ways, for different use cases. This section describes deploymentpatterns, their use cases along with pros and cons and best practices forcollector configurations for cross-environment and multi-backend deployments.
The AWS Amplify Console provides continuous deployment and hosting for modern web apps (single page apps and static site generators) with serverless backends. The Amplify Console offers globally available CDNs, custom domain setup, feature branch deployments, and password protection.
If the build succeeds, the app is deployed and hosted on a global CDN with an amplifyapp.com domain. You can now continuously deploy changes to your frontend or backend. Continuous deployment allows developers to deploy updates to their frontend and backend on every code commit to their Git repository.
IMPORTANT: you need to set proper HTTP caching headers for service-worker.js file in firebase.json file or you will not be able to see changes after first deployment (issue #2440). It should be added inside "hosting" key like next:
In YAML pipelines, we recommend that you put your deployment steps in a special type of job called a deployment job. A deployment job is a collection of steps that are run sequentially against the environment. A deployment job and a traditional job can exist in the same stage. Azure DevOps supports the runOnce, rolling, and the canary strategies.
For virtual machines, you don't need to define a pool. Any steps that you define in a deployment job with a virtual machine resource will run against that virtual machine and not against the agent in the pool. For other resource types such as Kubernetes, you do need to define a pool so that tasks can run on that machine.
We achieve this by using lifecycle hooks that can run steps during deployment. Each of the lifecycle hooks resolves into an agent job or a server job (or a container or validation job in the future), depending on the pool attribute. By default, the lifecycle hooks will inherit the pool specified by the deployment job.
deploy: Used to run steps that deploy your application. Download artifact task will be auto injected only in the deploy hook for deployment jobs. To stop downloading artifacts, use - download: none or choose specific artifacts to download by specifying Download Pipeline Artifact task.
runOnce is the simplest deployment strategy wherein all the lifecycle hooks, namely preDeploy deploy, routeTraffic, and postRouteTraffic, are executed once. Then, either on: success or on: failure is executed.
A rolling deployment replaces instances of the previous version of an application with instances of the new version of the application on a fixed set of virtual machines (rolling set) in each iteration.
For example, a rolling deployment typically waits for deployments on each set of virtual machines to complete before proceeding to the next set of deployments. You could do a health check after each iteration and if a significant issue occurs, the rolling deployment can be stopped.
Rolling deployments can be configured by specifying the keyword rolling: under the strategy: node.The strategy.name variable is available in this strategy block, which takes the name of the strategy. In this case, rolling.
With maxParallel: , you can control the number/percentage of virtual machine targets to deploy to in parallel. This ensures that the app is running on these machines and is capable of handling requests while the deployment is taking place on the rest of the machines, which reduces overall downtime.
Canary deployment strategy is an advanced deployment strategy that helps mitigate the risk involved in rolling out new versions of applications. By using this strategy, you can roll out the changes to a small subset of servers first. As you gain more confidence in the new version, you can release it to more servers in your infrastructure and route more traffic to it.
Canary deployment strategy supports the preDeploy lifecycle hook (executed once) and iterates with the deploy, routeTraffic, and postRouteTraffic lifecycle hooks. It then exits with either the success or failure hook.
The rolling strategy for VMs updates up to five targets in each iteration. maxParallel will determine the number of targets that can be deployed to, in parallel. The selection accounts for absolute number or percentage of targets that must remain available at any time excluding the targets that are being deployed to. It is also used to determine the success and failure conditions during deployment.
Pipeline decorators can be used in deployment jobs to auto-inject any custom step (for example, vulnerability scanner) to every lifecycle hook execution of every deployment job. Since pipeline decorators can be applied to all pipelines in an organization, this can be applied as part of enforcing safe deployment practices.
When you define an environment in a deployment job, the syntax of the output variable varies depending on how the environment gets defined. In this example, env1 uses shorthand notation and env2 includes the full syntax with a defined resource type.
This can happen when there's a name conflict between two jobs. Verify that any deployment jobs in the same stage have a unique name and that job and stage names don't contain keywords. If renaming doesn't fix the problem, review troubleshooting pipeline runs.
df19127ead