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Does cloud-init store the copy of the init it ran first?

emmalee last edited by

I'm sending my cloud-init file to Terraform via user_data. Is this stored anywhere on the machine that runs it? I know it may get merged with other stuff before it's run.
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guilherme last edited by
It seems to be stored under
```
/var/lib/cloud/instances
```
Under your https://devops.stackexchange.com/q/15483/18965 .
```
cd /var/lib/cloud/instances/$(cloud-init query instance_id)
```
For me I found the information I wanted in user-data.txt.
```
sudo cat "/var/lib/cloud/instances/$(cloud-init query instance_id)/user-data.txt"
```
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It is quite difficult to migrate the databases without downtime, however, using some approaches you can do it with very minimum impact, nearly a zero downtime. The main idea in this is to create new databases with new schema. Then make changes in your code. First migrate the data from the old database to the new database. Then make changes in your code such that it starts writing to both the databases, old and new. You need to decide a time (time when there will be least writes to the database). Then stop all the writes. Remove the old database and make sure all the writes should now happen to new database from now on. Then start the writes back. In this way, you can achieve DB migration with minimal downtime. You can check this for a detailed information on how this can be done.
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I see a number of answers here about the use of binding IP addresses to loopback interfaces. To be clear, this is not uncommon. It's actually something that is done quite often, for example to create a virtual IP address floating that can move (automatically or manually) from one machine to another with a high availability protocol. The loopback interface is always available on any device, which makes it a good interface to bind the address to. Also, binding IP addresses to loopback interfaces is often used when a device has multiple network connections, and you don't care about which interface is used to reach the device, you just want to communicate with the specific device regardless of the way it's reached. This is used for example when a machine is using a routing protocol like OSPF and BGP and does dynamic routing. Now back to your question: is this a good thing security wise? I don't think that in the situation you're describing this offers any real benefit to just adding the IP address to a physical interface and adding proper firewall rules there. In fact, you could argue that the added complexity increases the chances of someone forgetting to apply the rules correctly. Also, if multiple interfaces are available on the device, you need to apply the firewall filters on all interfaces. Personally, I wouldn't use a setup like this if your only goal would be to increase security. Everything you're doing there can be done with a nearly identical firewall filter on the physical interface.
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As I know for Git and Jenkins configuration we use SSH key authentication and secure token for security purpose. In your case you can't open all port to all then you can set revers proxy for your all URL using apache or nginx and forward traffic to port 80, So when request come first it's hit the port 80 and internally it will hit to your specific application port.
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At a minimum you need access to the shell. Without the shell, you will work as if you were 20 years ago or more. If you will host just one web application, at least you also need a public ip or domain preferable with https Also the usage of environment variables to avoid hardcoded values are required. The following strategies assume that you have shell access and a public ip or domain. let's not reinvent the wheel Dokku Dokku is an open-source platform-as-a-service (PaaS). If you're familiar with Heroku, you can consider Dokku a private Heroku that you manage. Basically, after the installation, you will have a private git url in which if you push some standard code, the app will be deployed. https://blog.back4app.com/what-is-dokku/ https://vimeo.com/68631325 https://www.freecodecamp.org/news/how-to-build-your-on-heroku-with-dokku/ I don't know any other similar open source platform. Buddy https://buddy.works/pricing In this platform you could automate some tasks. It is like a mini jenkins Minimal manual implementation Create a github repository Add a Dockerfile to your source code Use environment variables instead hardcoded values of database connection in the source code Install docker and git in the server Start a mongodb using docker and volumes After tests on your localhost, push to github Enter to the cloud and clone the git repository Execute the docker build to generate the image Execute docker run -p 80:xyz. xyz* is the port of your application
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Which flavor of Linux are you using? (eg Ubuntu/Debian, RHEL/CentOS etc) Also which version? (eg Ubuntu started using the "netplan" configuration by default in 20.04) At first glance, it looks like your DNS nameservers are hosed somehow. And can you post the results for doing a: netstat -nutpl? Look at which PID/Program Name is listening on port 53 (systemd-resolve? dnsmasq?) and check its nameserver configuration. Maybe check here: sudo cat /etc/resolv.conf and make sure the nameserver(s) listed there are what you think you should have them. or check the DNS-related services are even running with something like: Ubuntu: sudo service systemd-resolved status (NOTE BOTH of the 'd' endings) CentOS/RHEL: sudo service dnsmasq status (or whatever is using port 53, which is the default DNS port on most OSes)
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Openstack is something you might install to setup an self-service IaaS platform that manages VMs, storage and network. Whereas the top three cloud providers have written their own proprietary IaaS platforms a small cloud provider, or a large company, cannot feasibly code there own cloud-like management software, so they might setup their “private cloud” using openstack (or, say, a big vendors distribution of it) so that many internal projects can use it as self-service IaaS. To quote Wikipedia with some expansion by myself: OpenStack is a free and open-source software platform for cloud computing, mostly deployed as infrastructure-as-a-service (IaaS), whereby virtual servers and other resources are made available to [internal or external] customers. The software platform consists of interrelated components that control diverse, multi-vendor hardware pools of processing, storage, and networking resources throughout a data center. Users either manage it through a web-based dashboard, through command-line tools, or through RESTful web services. People might talk about it being “your operating system for private cloud” which is a bad analogy. In general the term “operating system” is often deliberate misused as it has positive connotations and might indicate to none technical people the broad benefits of investing in a given technology. For example people might also talk about container orchestrators such as Kubernetes or Docker Swarm being “the new operating systems of the cloud” which is a similar poor analogy. If a backup project said it provides connectors for AWS S3, Azure Blob, Google Cloud Storage, and Openstack Swift then it would be more clear exactly what it does: write large binary backup files into a cloud store. Such a product could then accurately say it supports AWS, Azure, GCP, and Openstack. Just to be clear I am not saying the the technology you are looking at actually uses those APIs I am making a general point about openstack having feature parity with many public cloud technologies.
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Your idea will work. The organization I work for maintains some open source examples how to do deploy to AWS using a pipeline. In comparison we use GitLab for the purpose. Instead of Travis we use GitLab Runner. You configure it using the file .gitlab-ci.yml which runs the tests and deploy the AWS Lambda to dev, test and production environment every time a commit is done. You store your secret account variables in the CI/CD settings of the repository. There are the usual drawbacks of AWS Lambda such as difficult or impossible to test and run locally and waiting for deployments takes time, but your deployment process will be good practice.
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X files, with X being the number of processors up to a limit (8, 16 or so). Preallocate size. Always on separate volume because I really like the ability to check the IO load on that one. Tempdb overload happens rarely, but if it happens.... it is good to be able to set an alarm. Regarding drives: if you CAN keep them on the same drive, you either have a very small database (in which case - get it on an M.2 / U.2 SSD with enough IOPS) or have a problem to start with - of the drive is "fake" (like a SAN delivering a LUN that in reality has a lot behind) I keep all my volumes these days on shared storage, and at the moment even on realtively slow HDD (7200 RPM), but it is backed by at the moment 6.4 TB of M.2 SSD which will even grow larger, so my read access time is pretty much guaranteed below one millisecond. Even with all ending up on the same discs, I really want separate volumes to check contention with one look. Same with mdf and ldf - all on their own volume.

Does cloud-init store the copy of the init it ran first?

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