Ok now that you've done all tutorials in Substrate and run your dev blockchain. Where could you find sa sample chain spec and genesis settings so that you can run your substrate-node-template in production provided that you will not change anything in the configuration.
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We have build a few Microservices (MS) which have been deployed to our company's K8s clusters.
For current deployment, any one of our MSs will be built as a Docker image and they deployed manually using the following steps; and it works fine:
Create Configmap
Installing a Service.yaml
Installing a Deployment.yaml
Installing an Ingress.yaml
I'm now looking at Helm v3 to simplify and encapsulate these deployments. I've read a lot of the Helm v3 documentation, but I still haven't found the answer to some simple questions and I hope to get an answer here before absorbing the entire doc along with Go and SPRIG and then finding out it won't fit our needs.
Our Spring MS has 5 separate application.properties files that are specific to each of our 5 environments. These properties files are simple multi-line key=value format with some comments preceded by #.
# environment based values
key1=value1
key2=value2
Using helm create, I installed a chart called ./deploy in the root directory which auto-created ./templates and a values.yaml.
The problem is that I need to access the application.properties files outside of the Chart's ./deploy directory.
From helm, I'd like to reference these 2 files from within my configmap.yaml's Data: section.
./src/main/resource/dev/application.properties
./src/main/resources/logback.xml
And I want to keep these files in their current format, not rewrite them to JSON/YAML format.
Does Helm v3 allow this?
Putting this as answer as there's no enough space on the comments!
Check the 12 factor app link I shared above, in particular the section on configuration... The explanation there is not great but the idea is behind is to build one container and deploy that container in any environment without having to modify it plus to have the ability to change the configuration without the need to create a new release (the latter cannot be done if the config is baked in the container). This allows, for example, to change a DB connection pool size without a release (or any other config parameter). It's also good from a security point of view as you might not want the container running in your lower environments (dev/test/whatnot) having production configuration (passwords, api keys, etc). This approach is similar to the Continuous Delivery principle of build once, deploy anywhere.
I assume that when you run the app locally, you only need access to one set of configuration, so you can keep that in a separate file (e.g. application.dev.properties), and have the parameters that change between environments in helm environment variables. I know you mentioned you don't want to do this, but this is considered a good practice nowadays (might be considered otherwise in the future...).
I also think it's important to be pragmatic, if in your case you don't feel the need to have the configuration outside of the container, then don't do it, and probably using the suggestion I gave to change a command line parameter to pick the config file works well. At the same time, keep in mind the 12 factor-app approach in case you find out you do need it in the future.
I have a single repository that hosts my lambda functions on github. I would like to be able to deploy the new versions whenever new logic is pushed to master.
I did a lot of reasearch and found a few different approaches, but nothing really clear. Would like to know what others feel would be the best way to go about this, and maybe some detail (if possible) into how that pipeline is setup.
Thanks
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You can setup a CI/CD pipeline using CircleCI with its GitHub integration (which is an online Service, so you don't need to maintain anything, like a Jenkins server, for example)
Upon every commit to your repository, a CircleCI build will be triggered. Once the build process is over, you can declare sls deploy, sam deploy, use Terraform or even create a script to upload the .zip file from your GitHub repo to an S3 Bucket and then, within your script, invoke the create-function command. There's an example how to deploy Serverless applications using CircleCI along with the Serverless Framework here
Other options include TravisCI, AWS Code Deploy or even maintain your own CI/CD Server. The same logic applies to all of these tools though: commit -> build -> deploy (using one of the tools you've chosen).
EDIT: After #Matt's answer, it clicked that the OP never mentioned the Serverless Framework (I, somehow, thought he was already using it, so I pointed the OP to tutorials using the Serverless Framework already). I then decided to update my answer with a few other options for serverless deployment
I know that this isn't exactly what you asked for but I use Serverless Framework (https://serverless.com) for deployment and I love it. I don't do my deployments when I push to my repo. Instead I push to my repo after I've deployed. I like this flow because a deployment can fail due to so many things and pushing to GitHub is much less likely to fail. I this way, I prevent pushing code that failed to deploy to my master branch.
I don't know if you're familiar with the framework but it is super simple. The website describes the simple steps to creating and deploy a function like this.
1 # Step 1. Install serverless globally
2 $ npm install serverless -g
3
4 # Step 2. Create a serverless function
5 $ serverless create --template hello-world
6
7 # Step 3. deploy to cloud provider
8 $ serverless deploy
9
10 # Your function is deployed!
11 $ http://xyz.amazonaws.com/hello-world
There are also a number of plugins you can use to integrate easily with custom domains on APIGateway, prune older versions of lambda functions that might be filling up your limits, etc...
Overall, I've found it to be the easiest way to manage and deploy my lambdas. Hope it helps!
Given that you're using AWS Lambda, you may want to consider CodePipeline to automate your release process. [SAM(https://docs.aws.amazon.com/lambda/latest/dg/serverless_app.html) may also be interesting.
I too had the same problem. I wanted to manage 12 lambdas with 1 git repository. I solved it by introducing travis-ci. travis-ci saved the time and really useful in many ways. We can check the logs whenever we want and you can share the logs to anyone by sharing the URL. The sample documentation of all steps can be found here. You can go through it. 👍
Is it possible to specify to run a Google Cloud Build in a specific region and zone?
The documentation seems to outline how to run a kubectl in a specific region/zone for deploying containers, but it doesn't seem to document where to run the cloud build itself. I've also not found this setting in the automatic build trigger configuration.
The latest public doc on regionalization can be found here: https://cloud.google.com/build/docs/locations
(Earlier answer on this topic follows)
This is not yet an available feature, however, at Google Next we announced an EAP / soon to be Alpha feature called "Custom Workers" which will enable this functionality for you. You can watch the demo here: https://www.youtube.com/watch?v=IUKCbq1WNWc&feature=youtu.be
I have a bunch of marathon docker tasks that are run on our test deployment machines.
There is a Jenkins CI job, that triggers the deployment a whole bunch of docker containers that are run on marathon-mesos cluster. (3 mesos-slaves, 1 master and 1 marathon.)
There is another downstream jenkins job (a automated test suite) that is triggered after above job. Presently, we wait for sufficient time, so that deployment gets completed then only we proceed with this automation testsuite. I want to change this behavior. I know marathon exposes rest APIs using which I can determine if I am good to go - after all the containers are deployed and all health checks are passing - for running the automation test suite.
Question is: Is there any library already out there for marathon, that I can reuse to accomplish above task ? I do not want to reinvent the wheel.
When I posted this question, I had java library actually in mind, but forgot to mention that. I find #michael 's libraries are also very good. But this is what I settled upon. Marathon-client. I think I saw this, while browsing through mesosphere repositories but somehow missed it.
This is the library: marathon-client
I've successfully been using the two following libs:
Go: gambol99/go-marathon
Python: thefactory/marathon-python
I'm used to having a single entity checkout, build, test, and deploy code, on every commit change (whether it be for a staging server or a production server). Now that we have started looking into Ansible, I'm beginning to think that there are isolated roles with these tools.
Basically I'm asking is it Ansible's responsibility to handle compiling and testing the code before deployment, or should it grab artifacts from a CI server such as Bamboo and trust that artifact is ready for deployment?
I'm not sure about the idea of using ansible to do the compiling, I rather just do that inside of CI as they have facilities done just for that. As for testing it depends on type of tests - if those are unit tests then they should be ran right after build (preferably inside of CI again) and either fail or pass a build.
But if those tests are of integration/functional nature (where they verify whether service actually works in the environment as we expect) then they for sure should be a part of post_tasks of the playbook, and if they don't pass you should mark the deployment as failed and act accordingly. This of course gives an idea of having a safe way to do that, before the service is exposed to production traffic, so if the tests do not pass, you can safely unroll the thing.
Nope, Ansible's responsibility is not to handle compiling and testing the code before deployment.
Yes it should grab artifacts from a CI server such as Bamboo and trust that artifact is ready for deployment.
Ansible is a radically simple IT automation engine that automates cloud provisioning, configuration management, application deployment, intra-service orchestration, and many other IT needs.
https://www.ansible.com/how-ansible-works