So I am in the process of moving all the thumbnails of my major sites to S3 and now I am thinking about how I can consistently put all my CSS/JS/images that power the actual sites to it. It's easy enough to upload everything the first time but I am trying to think of a way to somehow automate the process everytime I push out to production.
Does anyone have any clever ways of doing this?
I used to use s3sync to compare and update the assets just before upload the site files using a bash file to iterate through my files
This works well but when the amount of likes to compare (lets say thousands) gets big this process start being really slow. If you have an small architecture (in term of assets) this would do the trick
to make this better I would recommend capistrano or some other assistant that helps you to deploy...this way you can run at all once..
upload assets
deploy your files
In the other hand you could take a look to cloudfront (amazon's CDN) and set it up using ORIGIN..this way you dont need to worry about upload the files to s3 since they will be automatically pulled on demand. The down side of this approach is the caching if you need to update a file and keep the same name (AKA expire the object)...you can do this in cloudfront but will need an script to do the task.
Depending in the traffic (and other factors, ofcourse) one or other path will fit the best.
Related
Background
We know it's possible to setup a devops pipeline that deploys updates to AEM via a blue/green approach by using crx2oak to migrate the content from old to new environment. Why is out of scope of this question.
The problem with this approach is the content copy operation can take a significant time, as the amount of content in the JCR grows. Other ideas to mittigate this are appreciated.
We also know that AEM can have a S3 datastore that off-loads the binary content into a S3 bucket which would not be re-built during blue/green deployment as per:
https://helpx.adobe.com/experience-manager/6-3/sites/deploying/using/storage-elements-in-aem-6.html#OverviewofStorageinAEM6
What is unclear from Adobe's documentation is whether the same S3 bucket can be shared across AEM instances (i.e. blue/green instances). Maybe it's just my google fu that has failed...
Question(s)
When a new AEM instance is configured to use a S3 datastore that already has content in it from the old instance, when crx2oak is used to migrate content, will the new instance be able to access the existing content?
Are there any articles/blogs that describe what the potential time savings of this approach would be?
Yes I could do an experiment, and may do so in the future to answer my own question. I'm looking for information from anyone who has already done this? I'm an engineer so will not re-invent the wheel if someone else has done so.
You can certainly share the same S3 bucket between instances - in fact, this is commonly used along with binary-less replication from author->publisher(s) and is a tried and true configuration.
It's even possible to share the same bucket between completely different environments (e.g. DEV/STAGE, or BLUE/GREEN in your case). The main "gotcha" to be aware of is with regard to DataStore Garbage Collection (DSGC) because it's very possible that there will be blobs which are referenced by only some of the instances sharing the bucket and so when purging unused blobs this needs to be taken into account.
This is all part of the design though, and there is a flag designed specifically for this purpose which tells DSGC to only execute the first phase (the "mark" phase) of GC, and skip the 2nd "sweep" phase, until all instances have marked which blobs they wish to keep/discard. Once all instances have done so the sweep phase can be run to purge blobs not needed by any instances using the bucket.
For a more detailed explanation see the Oak docs:
https://jackrabbit.apache.org/oak/docs/plugins/blobstore.html#Shared_DataStore_Blob_Garbage_Collection_Since_1.2.0
I find it helps to understand that pretty much all of the datastore implementations are done such that blobs are stored according to their checksum, so the same file added uploaded twice will only have one copy stored in the datastore, and there will be two segment store records referencing that same blob. In the same way, multiple AEM instances sharing the same bucket will be able to find a given blob regardless of which instance put it there in the first place.
You can observe see this in action easily with FileDataStore by finding a blob and sha256'ing it - e.g. (this example is on OS X, the checksum command on Linux/Windows will be slightly different):
$ shasum -a256 crx-quickstart/repository/datastore/0c/9e/40/0c9e405fc8d0f0405930cd0044611cfbf014938a1837ae0cfaa266d7732d1002
0c9e405fc8d0f0405930cd0044611cfbf014938a1837ae0cfaa266d7732d1002 crx-quickstart/repository/datastore/0c/9e/40/0c9e405fc8d0f0405930cd0044611cfbf014938a1837ae0cfaa266d7732d1002
There you can see that a) the filename is the checksum, and b) it's nested using the first 3 pairs of characters from that checksum, so you can locate the file by just knowing the hash and if you store the same binary, even if the name or JCR metadata is different, the blob referenced will be the same literal file on disk.
From memory S3 datastore uses prefixes rather than directory nesting because this performance better, but the principle is the same.
Finally, a couple of things to consider are:
1) S3 storage is relatively cheap (and practically unlimited) so there is an argument to be made that it's not as necessary to perform regular DSGC unless you're really trying to pinch pennies.
2) If you do run DSGC you need to think about how this will work with whatever backup strategy you're using for the AEM instances. For instance, if you roll back a segment store shortly after running DSGC you'll likely have to recover some of those purged blobs. You can use versioning and/or lifecycle rules to help with this, but it can add significant additional complexity and time to your restore process.
If you opt to simply skip DSGC and leave the blobs there indefinitely it's a good idea to make sure the access key or IAM roles AEM is using doesn't have the DeleteObject permission for the bucket, just to be sure a rogue GC process can't delete anything.
Hope this helps.
Edit
In all that I forgot to actually answer your question - yes it will save some time in cloning in most cases. You'll still need to sync the segment store (obviously) and there are various approaches for this. crx2oak is certainly one - you'll see in the documentation there are specific options for using it w/ S3 where you supply a configuration file (basically a serialised .config file like you'd use with Felix/OSGi).
You can also use something like rsync to simply copy the TAR files over (while at least the target AEM is stopped. Oak is generally atomic so a hot copy from the source can work in theory, but YMMV).
Finally you could obviously use Mongo and cluster the segment store that way, but all the usual cost/complexity/performance issues with doing so apply).
Another interesting development on the horizon for blue/green type is the CompositeNodeStore - there is a good talk from the 2017 adaptTo() conference that talks about this:
https://adapt.to/2017/en/schedule/zero-downtime-deployments-for-the-sling-based-apps-using-docker.html
An external datastore will help a lot, as usually the most space is used by binary assets. The pure content typed in by real people is much less.
On my current project (quite small, but relations should be normal):
Repository 4,8 GB total (4.1 GB Segment Store, 780 MB Index)
File DataStore 222 GB total
If you wanna do it, I have the following remarks:
There are different datastores available. For testing I would start with the File DataStore.
The S3 DataStore makes only sense in my point of view, if you are hosting at Amazons AWS anyway. Adobe Managed Services is doing this, and so S3 makes sense for them. But also there only if you have more than 500 GB assets.
If you use the green/blue approach, then be careful the DataStore garbage collection (just do it manually). The shared Datastore is meant for several publishers, that have the same content. As example you could have the following situation: Your editors delete some assets, you run the DataStore GC and finally your rollback your environment. That means the assets are still in the content repository, but the binaries are cleaned out of the DataStore.
In order to to use a shared file datastore, you need to do the following:
Unpack Quickstart java -jar AEM_6.3_Quickstart.jar -unpack
Create an directory for the file datastore (anywhere outside of the crx-quickstart folder)
Create a directory install inside the extracted crx-quickstart folder
Create a file called org.apache.jackrabbit.oak.plugins.blob.datastore.FileDataStore.cfg inside this install folder
This file contains just 1 line path=<path to file datastore> (see https://jackrabbit.apache.org/oak/docs/osgi_config.html)
Place a reference.key file inside the datastore directory. First time it will be created automatically. But if you use always the same key, the same hash-values are used all datastores across all your environments. This is also a prerequisite for a feature called "binary-less replication" (so binary would only be replicated the first time between author and publisher)
kind regards,
Alex
Dropbox claims that during syncing only the portion of files that changes are transmitted back to main server, which is obviously a great functionality, but how do they perform changes to files stored in Amazon S3 cloud? So for example, lets say a 30 page document on user's desktop contains changes to only page 4. Dropbox now syncs the blocks representing the changes and what happens on the backend if they files that they store are in the cloud? Does that mean they have to download the 30 page document stored in S3 to their server, then perform replacement of blocks representing page 4, and then uploading back to the cloud? I doubt this would be the case because that would be somewhat inefficient. The other option I could think of is if Amazon S3 provides update of file stored in the cloud based on byte ranges, so for example, make a PUT request to file X from bytes 100-200 which will replace all the bytes from 100 to 200 with value of PUT request. So I was curious how companies that use other cloud services such as Amazon, implement this type of syncing.
Thanks
As S3 and similar storages don't offer filesystem capabilities, anything that pretends to store files and directories needs to emulate a file system. And when doing this files are often split to pages of certain size, where each page is stored in a separate file in the storage. This way the changed block requires uploading only one page (for example) and not the whole file. I should note, that with files like office documents this approach can be faulty if file size is changed - for example, if you insert a page at the beginning or delete a page, then the whole file will be changed and the complete file would need to be re-uploaded. We didn't analyze how Dropbox in particular does his job, and I just described the common scenario. There exist also different "patch algorithms", where a patch can be created locally (if Dropbox has an older local copy in the cache) and then applied to one or more blocks on the server.
There are several synchronizing tools which transfer deltas over the wire like rsync, rdiff, rdiff-backup, etc. For bi-directional synchronising with S3 there are paid services like s3rsync for example. For pure client-side synchronising, tools like zsync can be considered (which is what many people employ to roll-out app updates).
An alternative approach would be to tar-ball a directory, generate a delta file (using rdiff or xdelta3), and upload the delta file by using a timestamp as part of the key. In order to sync, all you need to do is to perform these 2 checks client-side:
You have all the delta files from S3. If not pull them and apply them to generate the latest backup state.
Your last backup state corresponds to your current directory. If not generate a new delta file and push to S3.
The concerning factor here would be the at least 100% additional space utilization, client-side. But this approach will help you revert changes if needed.
I just started playing with the Azure Library for Lucene.NET (http://code.msdn.microsoft.com/AzureDirectory). Until now, I was using my own custom code for writing lucene indexes on the azure blob. So, I was copying the blob to localstorage of the azure web/worker role and reading/writing docs to the index. I was using my custom locking mechanism to make sure we dont have clashes between reads and writes to the blob. I am hoping Azure Library would take care of these issues for me.
However, while trying out the test app, I tweaked the code to use compound-file option, and that created a new file everytime I wrote to the index. Now, my question is, if I have to maintain the index - i.e keep a snapshot of the index file and use it if the main index gets corrupt, then how do I go about doing this. Should I keep a backup of all the .cfs files that are created or handling only the latest one is fine. Are there api calls to clean up the blob to keep the latest file after each write to the index?
Thanks
Kapil
After i answered this, we ended up changing our search infrastructure and used Windows Azure Drive. We had a Worker Role, which would mount a VHD using the Block Storage, and host the Lucene.NET Index on it. The code checked to make sure the VHD was mounted first and that the index directory existed. If the worker role fell over, the VHD would automatically dismount after 60 seconds, and a second worker role could pick it up.
We have since changed our infrastructure again and moved to Amazon with a Solr instance for search, but the VHD option worked well during development. it could have worked well in Test and Production, but Requirements meant we needed to move to EC2.
i am using AzureDirectory for Full Text indexing on Azure, and i am getting some odd results also... but hopefully this answer will be of some use to you...
firstly, the compound-file option: from what i am reading and figuring out, the compound file is a single large file with all the index data inside. the alliterative to this is having lots of smaller files (configured using the SetMaxMergeDocs(int) function of IndexWriter) written to storage. the problem with this is once you get to lots of files (i foolishly set this to about 5000) it takes an age to download the indexes (On the Azure server it takes about a minute,, of my dev box... well its been running for 20 min now and still not finished...).
as for backing up indexes, i have not come up against this yet, but given we have about 5 million records currently, and that will grow, i am wondering about this also. if you are using a single compounded file, maybe downloading the files to a worker role, zipping them and uploading them with todays date would work... if you have a smaller set of documents, you might get away with re-indexing the data if something goes wrong... but again, depends on the number....
I'm building an application that needs to download web content for offline viewing on an iPad. At present I'm loading some web content from the web for test purposes and displaying this with a UIWebView. Implementing that was simple enough. Now I need to make some modifications to support offline content. Eventually that offline content would be downloaded in user selectable bundles.
As I see it I have a number of options but I may have missed some:
Pack content in a ZIP (or other archive) file and unpack the content when it is downloaded to the iPad.
Put the content in a SQLite database. This seems to require some 3rd party libs like FMDB.
Use Core Data. From what I understand this supports a number of storage formats including SQLite.
Use the filesystem and download each required file individually. OK, not really a bundle but maybe this is the best option?
Considerations/Questions:
What are the storage limitations and performance limitations for each of these methods? And is there an overall storage limit per iPad app?
If I'm going to have the user navigate through the downloaded content, what option is easier to code up?
It would seem like spinning up a local web server would be one of the most efficient ways to handle the runtime aspects of displaying the content. Are there any open source examples of this which load from a bundle like options 1-3?
The other side of this is the content creation and it seems like zipping up the content (option 1) is the simplest from this angle. The other options would appear to require creation of tools to support the content creator.
If you have the control over the content, I'd recommend a mix of both the first and the third option. If the content is created by you (like levels, etc) then simply store it on the server, download a zip and store it locally. Use CoreData to store an Index about the things you've downloaded, like the path of the folder it's stored in and it's name/origin/etc, but not the raw data. Databases are not thought to hold massive amounts of raw content, rather to hold structured data. And even if they can -- I'd not do so.
For your considerations:
Disk space is the only limit I know on the iPad. However, databases tend to get slower if they grow too large. If you barely scan though the data, use the file system directly -- may prove faster and cheaper.
The index in CoreData could store all relevant data. You will have very easy and very quick access. Opening a content will load it from the file system, which is quick, cheap and doesn't strain the index.
Why would you do so? Redirect your WebView to a file:// URL will have the same effect, won't it?
Should be answered by now.
If you don't have control then use the same as above but download each file separately, as suggested in option four. after unzipping both cases are basically the same.
Please get back if you have questions.
You could create a xml file for each bundle, containing the path to each file in the bundle, place it in a folder common to each bundle. When downloading, download and parse the xml first and download each ressource one by one. This will spare you the overhead of zipping and unzipping the content. Create a folder for each bundle locally and recreate the folder structure of the bundle there. This way the content will work online and offline without changes.
With a little effort, you could even keep track of file versions by including version numbers in the xml file for each ressource, so if your content has been partially updated only the files with changed version numbers have to be downloaded again.
We have our production server running our website. Then we have a test server which has exact same data but with changes to code to do some new functionality. This web app has over 500 pages.
Is there any program that can
Login to the test site
Crawl through each page and then save the page as html
Compare with the same page saved with live site?
This way we can make sure that new features that we add to our test site will not break the live site when code updates are applied to production.
I am currently trying to use WinHTTrack website copier and then comparing the test and live folders with some code comparison tool like beyond compare. This works ok but there are lot of files changed because of the domain name changes.
Looking forward to ideas / solutions for this problem.
Regards
Have you looked at using Watir for this? It's not exactly the thing you are looking for but it might allow you some more granularity in your tests and ensure the site is functionally identical rather than getting caught up on changing guids, timestamps and all the other things that tend to change across any significant size website from day to day as part of it's standard functionality.
Apparently you can't make consistent, reproduceable builds in your project, can you? I would recommend moving towards that in the long run, it will save you a lot of headaches. That way you would know exactly what was deployed to which server when, so there would be no more need to bend around backwards to get the deployed sources back like this...
I know this is not a direct solution to your problem... but maybe it is worth comparing, whether you would save more in the long run by investing the efforts into your build process now, instead of implementing this workaround (and then improving your build process anyway - because one day you will almost surely need to do that).
wget has a --convert-links option, there are also some options to preserve cookies that might let you do it logged in http://drupal.org/node/118759#comment-664498
use an Offline Downloader, download all files to your computer from both sources, then compare the folder contents using a free tool like Total Commander.
EDIT
Load both of your sources into a CVS, and compare it there.