I have developed an app in Twilio which I would like to run from the cloud. I tried learning about AWS and Google App Engine but am quite confused at this stage:
I have 2 questions which I hope to get your help on:
1) How can I store my scripts and database in the cloud? Right now, everything is running out of my local machine but I would like to transfer the scripts and db to another server and run my app at a predetermined time of day. What would be the best way to do this?
2) How can I write a batch file to run my app at a predetermined time of day in the cloud?
I understand this does not have code, but I really hope someone can point me to the right direction. I have spent lots of time trying to understand this myself but still am unsure. Tks in adv.
Update: The application is a Twilio app that makes calls to people, the script simply applies an algorithm to make calls in a certain fashion and the database is a mysql db that provides the details of people to be called.
This is quite difficult to provide an exact answer without understanding what is the application, what is the DB or what is the script that you wish to run.
I can give you a couple of ideas that might be helpful in such cases.
OpsWorks (http://aws.amazon.com/opsworks/) is a managed service for managing applications. You can define your stack (multiple layers like web, workers, DB...) and what are the chef recipes that should run in various points in the life of the instances in each layer (startup, shutdown, app deployment or stack modification..). Then you can use the ability to add instances to each layer in specific days and hours, to implement the functionality of running at predetermined times as you requested.
In such a solution you can either have some of your instances (like DB) always on, or even to bootstrap them using the chef recipes every day, with restore from snapshot on start and create snapshot on shutdown.
Another AWS service that you use is Data Pipeline (http://aws.amazon.com/datapipeline/). It is designed to move data periodically between data sources, for example from a MySQL database to Amazon Redshift, the Data warehouse service. But you can use it to trigger scripts and run random shell scripts that you wish (http://docs.aws.amazon.com/datapipeline/latest/DeveloperGuide/dp-object-shellcommandactivity.html), and schedule it to run in various conditions like every hour/day or specific times (http://docs.aws.amazon.com/datapipeline/latest/DeveloperGuide/dp-concepts-schedules.html).
A simple path here would be just to create an EC2 instance in AWS, and put the components needed to run your app there. A thorough walk through is here:
http://docs.aws.amazon.com/AWSEC2/latest/UserGuide/get-set-up-for-amazon-ec2.html
Essentially you will create an EC2 virtual machine, which you can for most purposes treat just like any other Linux server. You can install MySQL on it, copy your script there, and run it. Of course whatever container or support libraries your code requires will need to be installed as well.
You don't say what OS you are using locally, but if it is Mac or Linux, you should be able to follow almost the same process to get your script running on an EC2 instance that you used on your local machine.
As you get to know AWS, there are sophisticated services you can use for deployment, infrastructure orchestration, database services, and so on. But just to get started running a script from a virtual machine should be pretty straightforward.
I recently developed a Twilio application using Ruby on Rails for the backend and found Heroku extremely simple to setup and launch. While Heroku does cost more than AWS, I found that the time I saved using Heroku more than made up this. As an early stage startup, we wanted to spend our time developing important features, and not "wasting" time optimizing our AWS cloud.
However, while I believe Heroku is ideal for early-stage websites/startups I do believe hosting should be reevaluated once a company reaches a certain size. At some point it becomes economically viable to devote resources into optimizing an AWS cloud solution because it will be cheaper than Heroku in the long run.
Related
I have a flask app that is deployed on Google's App Engine. I have noticed a minor bug and I would like to fix it but my database is already populated.
How can I make this minor code change and push / deploy back to my app without losing all my data? (which is probably a basic question but I'm not finding much. all tutorials online are focused on creating the app and deploy, not updating)
Thus far, I have been dropping and re-creating the tables whenever I redeploy, mostly out of ignorance. Here are the steps I have followed
1). make the change in my app
commit and push changes to bitbucket source code
in Google Cloud SDK: git pull
Google Cloud SDK: gcloud app deploy
These steps result in an empty database because the directory I am pushing from my local computer has an empty database. Is this where I should be using git merge?
Is this a database "migration" or is this a "git merge"? I'm not sure what the right terms are to use to research this further. Thanks.
There are a couple of angles to your question. I'm going to try to give you some information, but let me warn you, this isn't going to be a trivial change to your workflow, you'll have to change some things.
First of all, based on the way you worded your question I get the idea that you commit your database to git along with your code. If I got this right, then this is something that you need to stop doing. The database is not code, so it should not be committed to source control.
You should have a completely independent database on each installation of your application. For example, you will have a database on your own machine to do development. You will also need another database in your gcloud deployment. You may need more databases if you have other uses for your application. A very common third database for many people is one that is used for automated tests, which could also be located in your local development machine, but is not the same database that you use for day to day development.
To make changes to your database schema you will not drop and recreate tables anymore, that is clearly something that you already realized that needs an improvement. A good approach to make these changes is to use a database migration framework. These tools allow you to generate short scripts that make these changes to the database in a more focused way, without destroying and recreating everything, and for that reason, the data is in general not lost. For Flask-SQLAlchemy, the best option for database migrations is Flask-Migrate, which is a lightweight wrapper around the Alembic migration framework. (I might be biased here as I'm the author of the Flask-Migrate extension!).
Documentation for Flask-Migrate: https://flask-migrate.readthedocs.io/en/latest/.
I have started to try to use the Google Cloud datalab. While I understand it is a Beta product, I find the Doc's very frustrating, to say the least.
The questions here and lack of responses as well as lack of new revisions or docs over the several months the project has been available make me wonder if there is any commitment to the product?
A beginning would be a notebook that shows data ingestion from external sources to both the datastore system and the Big query system. That is a common use case. I'd like to use my own data, it would be great to have a Notebook to ingest it. It seems that should be doable without huge effort? And it would get me (and others) out of this mess trying to link the various terse docs from various products and workspaces up and working together..
in addition to a better explanation of the Git hub connection process (prior question))
For BigQuery, see here: https://github.com/GoogleCloudPlatform/datalab/blob/master/content/datalab/tutorials/BigQuery/Importing%20and%20Exporting%20Data.ipynb
For GCS, see here: https://github.com/GoogleCloudPlatform/datalab/blob/master/content/datalab/tutorials/Storage/Storage%20Commands.ipynb
Those are the only two storage options currently supported in Datalab (which should not be used in any event for large scale data transfers; these are for small scale transfers that can fit in memory in the Datalab VM).
For Git support, see https://github.com/GoogleCloudPlatform/datalab/blob/master/content/datalab/intro/Using%20Datalab%20-%20Managing%20Notebooks%20with%20Git.ipynb. Note that this has nothing to do with Github, however.
As for the low level of activity recently, that is because we have been heads down getting ready for GCP Next (which happens this coming week). Once that is over we should be able to migrate a number of new features over to Datalab and get a new public release out soon.
Datalab isn't running on your local machine. Just the presentation part is in your browser. So if you mean the browser client machine, that wouldn't be a good solution - you'd be moving data from the local machine to a VM which is running the Datalab Python code (and this VM has limited storage space), and then moving it again to the real destination. Instead, you should use the cloud console or (preferably) gcloud command line on your local machine for this.
I have a restful angular app that is hosted on a AWS and I'm looking for a clean and quick deployment solution to put the new site live without taking down the previous. I don't have much DevOps experience so any advice would be great. The site is full RESTFUL so its just static pages.
I was looking at setting up a dokku with AWS plugin solution but was pretty sure its overkill and may not be able to detect my app because its just static pages (no node, rails, etc).
The best way to do this is to reconfigure the web server on the fly to point to the new application.
Install the new version of the app to a new location, update the web server config files to point to the new location, and reload the server.
For inflight requests, they will be satisfied by the old application, and all the new requests will hit the new application, with no down time between them save for the trivial delay when refreshing the web server (don't restart it, just tickle it to reload it's configuration files).
Similarly, you can do this solely at the file system, by installing the new app in a new directory parallel to the old one. Then:
mv appdir appdir.bak
mv appdir.new appdir
But this is not zero downtime, but it is a very, very short down time as the two inodes are renamed. Just ensure that both the new and old directories are on the same filesystem, and the mv will be instantaneous. The advantage is that you can trivially "undo" the operation in the same way.
There IS a window where you have no app at all. For a fraction of a second there will be no appdir, and you will serve up 404's for those few microseconds. So, do it when the system is quiet. But it's trivial to instrument and do.
We ended up going with TeamCity for our build/tests and deploying via Shipit.
https://github.com/shipitjs/grunt-shipit
https://www.jetbrains.com/teamcity/
Try to use git repo for live deployment https://danbarber.me/using-git-for-deployment/
A simple solution is to use a ELB. This will enable you to deploy a new instance, deploy the code, test it, update the ELB to switch traffic to the new instance and then you can then remove the old instance.
An easy solution to this is to always be running two instances, a production and a staging. These guys should be identical and interchangeable (because they are going to switch. Assign an elastic ip to your production. When it's time to update, copy the code onto the staging, make sure it's working, and then attach the elastic ip to staging. It is now production and production is now staging. This is not an ideal solution but it is very easy and the same principals apply to better solutions.
A better solution involves an elastic load balancer. Make sure you have 2 instances attached. When it is time to update, detach an instance, perform your update, make sure it is working and reattach it. Now you will have a brief point in time where the client could get either your new website or your old website. Detach the other old note, perform the update and reattach.
The fact of the matter is even if you just overwrite files on the live server there will only be a 10ms window or so where the client could get a new version of one file (e.g. the html) and the old version of another (e.g. the css). After that it will be perfect again.
Hi guys I've dumped (made a backup) of my Appengine datastore entities,following this tutorial, now I wonder if there is a way to restore the data locally ? so I can do some test and debug.
In windows, the datastore is in the directory
C:\Users\UserName\AppData\Local\Temp\AppName
In OSx this question can help you
In this directory are storade the datastore.db (the local storage), change the name (the app should not be running, and if is locked, kill all the python process)
Now go to the appengine dashboard
click in your app link
click in Blob Viewer (i'm assumming that you did the backup into a blobstore)
click in the file name
click in download
rename the file to datastore.db
copy to the previous path
start the app
Remote API (as koma mentions) is the main GAE-documented approach, and it's a good approach. Alternatively, you can download the entities using the cloud download tool, write your own store reader/deserializer, and execute it within your dev server local instance: http://gbayer.com/big-data/app-engine-datastore-how-to-efficiently-export-your-data. Read the part about the New Approach...
While these options are not automatic and require engineering, I really wanted to point out the side effect of doing this: We have been facing performance issues in the local development server for months now, specifically when the datastore has more than 1,000 entities with over 50 indexes. Just search for "require_indexes slow" and you'll see what I'm talking about.
I'm sure you have a solid reason to import lots of data locally for testing and debugging, just wanted to let you know your application will perform extremely slow, and debug mode will be impossibly slow; we can't even use debug mode with our setup anymore.
If you want to get some test data in your local db, you could copy some using the remote api
This is a subject of common discussion, but through all my research I have not actually found a sound answer to this.
I develop my websites offline, and then launch them live through my hosting account.
I utilize codeigniter, and on that basis there are some fundamental differences between my offline and online copies, namely base urls and database configurations. As such I cannot simply develop and test my websites offline and then upload them as it requires small configuration changes which are easy to overlook and good lead to a none working live website.
The other factor is that when I am developing offline, I might add a database table or a column whilst creating some functionality. When I upload my local developments to my host, they often do not work as I have forgotten to upload the new database structure. Obviously this cannot happen - there cannot be any opportunity for a damaged or broken live website.
Further to this, I'd like to be able to have logs of my development - version control of sorts such that if i develop a feature, and then something else stops working I can easily look backwards to at least see the code changes which could have caused the change.
My fourth requirement is as follows: if i go away on holiday for a week without my development laptop, and then get a bug report, I have no way of fixing it. If i fix it on the live copy, not only is it dangerous, but i'll inevitably not update it on my local copy - as such when i update my live copy next time, that change will be lost. Is there a way that on any computer i can access my development setup, edit and test, launch to the live site, whilst also committing it such that my laptop local copy is up to date.
So yes.. in general im looking for a solution to make my development processes more efficient/suitable. Any ideas?
Thanks
Don't deploy by simply copying. Deploy by using a script (I use Apache Ant) that will automate the copy of specific files for each environment, the replacement of some values, etc.
This just needs rigor. Make a todo list while developing, and check that every modification on the server is done. You might also test the deploy procedure on a pre-production server which has an similar configuration as the production server, make sure everything is OK, and then apply the same, tested procedure on the production server
Just use a version control system. SVN or Git are two free candidates.
Make your version control server available from anywhere. If it's an open-source project, free hosting solutions exist. Of course, if you don't have a development computer wvailable, you'll have to checkout the whole project, and probably install some tools to be able to develop, test and deploy. Just try to make it as easy as possible, or always have your laptop available. If you plan to work, have your toolbox with you. If you don't plan to work, then don't work. When you have finished some development, commit to the server. When you go back to your laptop, update your working copy from the server.
Small additions and clarifications to JB
Use any VCS, which can work (in a good way) with branches - your local and prod systems are good candidates for separate branches, where you share common code but have branch-specific config. It'll require some changes in your everyday workflow (code in "test", merge finished with "prod", deploy /by tools, not hand/ only after merge...), but it's fair price
Changing of workflow, again. As JB noted - don't deploy by hand, don't deploy wrong branch, don't deploy "prod" before finished merge. But now build-tools are rather smart, you can check such pre-condition inside builder
Just use VCS, maybe DVCS will be somehow better. I say strong "No-no" for Git as first VCS, but you have wide choice even without it - SVN (poor branch|merge comparing to DVCS), Bazaar (not a tool of my dream, but, who knows), Mercurial, Fossil SCM, Monotone
Don't work on live, never do anyting outside your SCM. One source of changes is a rule of happy developer. Or don't work at all at free-time, or have codebase always reacheable for you (free code-hosting /GoogleCode, SourceForge, BitBucket, Github, Assembla, LaunchPad/ or own server), get it as needed, change, save, deploy