I am working on a task to be able to backup VM image volumes in another server and location, the problem is, I don't want to copy the whole image file each time I want to start a backup job, I want to backup the whole image only once and then backup incrementally each time I want to do a backup from a vm.
Is there anyway to do that? I don't want to use snapshots because when the number of snapshots increases, it will have an impact on volume performance.
If there is another way or if there is a way to use snapshots more efficient, please tell me.
I have tried volume snapshot locally, I want to know how to do it externally or any other sufficient ways to do incremental external backups.
ive been working on a project allowing you to create full and incremental or differential backups of libvirt/kvm based virtual machines. It works by using the latest features provided by the libvirt and qemu projects (changed block tracking). So if the libvirt/qemu versions you are using are supporting the features, you might want to give it a try:
https://github.com/abbbi/virtnbdbackup
When I develop and update files on production server with PHP I just copy the files on the fly and everything seems to work without interrupting the server.
But if I am to update the code on the Go server and application and would need to kill the server, copy the src files to the server, run go install, and then start the server, this would interrupt the service, and if I do this quite often then it is going to look very bad for my users of the service.
How can I update files without the downtime when using Go with Go's http server?
PHP is an interpreted language, which means you provide your code in source format and the PHP interpreter will read it and execute it (it may create a more compact binary form so that it doesn't have to analyze the source again when needed).
Go is a compiled language, it compiles into a native executable binary; going further it is statically linked which means every code and library your app is referring to is compiled and linked when the executable is created. This implies you can't just "drop-in" new go modules into a running application.
You have to stop your running application and start the new version. You can however minimize the downtime: only stop the running application when the new version of the executable is already created and ready to be run. You may choose to compile it on a remote machine and upload the binary to the server, or upload the source and compile it on the server, it doesn't matter.
With this you could decrease the downtime to a maximum of few seconds, which your users won't notice. Also you shouldn't update in every hour, you can't really achieve significant updates in just an hour of coding. You could schedule updates daily (or even less frequently), and you could schedule them for hours when your traffic is low.
If even a few seconds downtime is not acceptable to you, then you should look for platforms which handle this for you automatically without any downtime. Check out Google App Engine - Go for example.
The grace library will allow you to do graceful restarts without annoyance for your users: https://github.com/facebookgo/grace
Yet in my experience restarting Go applications is so quick, unless you have an high traffic website it won't cause any trouble.
First of all, don't do it in that order. Copy and install first. Then you could stop the old process and run the new one.
If you run multiple instances of your app, then you can do a rolling update, so that when you bounce one server, the other ones are still serving. A similar approach is to do blue-green deployments, which has the advantage that the code your active cluster is running is always homogeneous (whereas during a rolling deploy, you'll have a mixture until they've all rolled), and you can also do a blue-green deployment where you normally have only one instance of your app (whereas rolling requires more than one). It does however require you to have double the instances during the blue-green switch.
One thing you'll want to take into consideration is any in-flight requests -- you may want to make sure that in-flight requests continue to go to old-code servers until their finished.
You can also look into Platform-as-a-Service solutions, that can automate a lot of this stuff for you, plus a whole lot more. That way you're not ssh'ing into production servers and copying files around manually. The 12 Factor App principles are always a good place to start when thinking about ops.
I don't need Hive or Pig, and Amazon Data Pipeline by default installs them on any EMR cluster it spins up. This makes testing take longer than it should. Any ideas on how to disable to install?
This is not possible as of today.
The only workaround would be to launch a small EMR cluster that you use for testing (like with single master - m1.small). Then use it with 'workergroup' rather than 'runsOn'.
Depending on type of activities you want to use, the workergroup field might or might not be supported. But you can always wrap everything in a script (python, shell or blah) and use it with ShellCommandActivity.
Update (correctly reminded by ChristopherB):
From 3.x AMI version, Hive and Pig is bundled in the AMI itself. So the steps do not pull any new packages from S3 but only activate the daemons on master node. So unless you are worried about them consuming your instance resources (CPU, memory etc), it should be okay. They would not take noticable time to run.
Does anyone know whether it is 100% safe to replace (copy + paste) an assembly with an updated version of itself, where all version history (AssemblyInfo.vb) is exactly the same but the only difference being that a minor code change took place in one of the aspx.vb files.
It is safe if you are sure you didn't break your existing code (method doesn't exist anymore, ...).
If you manually load assemblies make sure to update versions and tokens.
If you are not sure you can duplicate your website into another folder, create a test IIS instance and test the deployment of single files.
Keep in mind that a clean deployment is safe rather than single file deployments that may cause breaking changes if you are not extremely careful. This may not be a problem on test instances but should never be done on Live.
It is definitely possible and very easily doable but it can easily become a habit that can have a negative impact when the production system is becoming very large, possibly unstable and have a large number of users.
There are a couple of ways I would suggest trying or to be mindful of:
Create a installer or multiple installers depending on the projects
in you solution. These installer produce te excutable(s) to install
on the production server. This will be done manually. Backup the previous
installers for rollback.
You can create a ClickOnce application. This can be run manually and also can be scheduled using a stable scheduling app.
One can also make use of Visual Studio's publishing function. After
compiling code and setting it to release mode it gets publish via
file/network/ftp on the production space. This replaces all the markup files and assemblies.
The automate the process you can use a TFS Builder server and
schedule daily or weekly builds. These installations can be made
manually or one can use SMS(Microsoft System Management Services) to
schedule timely installations
One can use Windows Powershell as well
TFS Build Server and SMS carry cost implications of course but it
will be a small price to pay if problems on a production environment
can bring a company down.
There are a couple of ways to do this. See what might work and get into good habits when it comes to an production environment
The process of creating a new build and releasing it to production is a critical step in the SDLC but it is often left as an afterthought and varies greatly from one company to the next.
I'm hoping people will share improvements they have made to this process in their organisation so we can all takes steps to 'reduce the pain'.
So the question is, specify one painful/time consuming part of your release process and what did you do to improve it?
My example: at a previous employer all developers made database changes on one common development database. Then when it came to release time, we used Redgate's SQL Compare to generate a huge script from the differences between the Dev and QA databases.
This works reasonably well but the problems with this approach are:-
ALL changes in the Dev database are included, some of which may still be 'works in progress'.
Sometimes developers made conflicting changes (that were not noticed until the release was in production)
It was a time consuming and manual process to create and validate the script (by validate I mean, try to weed out issues like problem 1 and 2).
When there were problems with the script (eg the order in which things were run such as creating a record which relies on a foreign key record which is in the script but not yet run) it took time to 'tweak' it so it ran smoothly.
It's not an ideal scenario for Continuous Integration.
So the solution was:-
Enforce a policy of all changes to the database must be scripted.
A naming convention was important for ensuring the correct running order of the scripts.
Create/Use a tool to run the scripts at release time.
Developers had their own copy of the database do develop against (so there was no more 'stepping on each others toes')
The next release after we started this process was much faster with fewer problems, indeed the only problems found were due to people 'breaking the rules', eg not creating a script.
Once the issues with releasing to QA were fixed, when it came time to release to production it was very smooth.
We applied a few other changes (like introducing CI) but this was the most significant, overall we reduced release time from around 3 hours down to a max of 10-15 minutes.
We've done a few things over the past year or so to improve our build process.
Fully automated and complete build. We've always had a nightly "build" but we found that there are different definitions for what constitutes a build. Some would consider it compiling, usually people include unit tests, and sometimes other things. We clarified internally that our automated build literally does everything required to go from source control to what we deliver to the customer. The more we automated various parts, the better the process is and less we have to do manually when it's time to release (and less worries about forgetting something). For example, our build version stamps everything with svn revision number, compiles the various application parts done in a few different languages, runs unit tests, copies the compile outputs to appropriate directories for creating our installer, creates the actual installer, copies the installer to our test network, runs the installer on the test machines, and verifies the new version was properly installed.
Delay between code complete and release. Over time we've gradually increased the amount of delay between when we finish coding for a particular release and when that release gets to customers. This provides more dedicated time for testers to test a product that isn't changing much and produces more stable production releases. Source control branch/merge is very important here so the dev team can work on the next version while testers are still working on the last release.
Branch owner. Once we've branched our code to create a release branch and then continued working on trunk for the following release, we assign a single rotating release branch owner that is responsible for verifying all fixes applied to the branch. Every single check-in, regardless of size, must be reviewed by two devs.
We were already using TeamCity (an excellent continuous integration tool) to do our builds, which included unit tests. There were three big improvements were mentioning:
1) Install kit and one-click UAT deployments
We packaged our app as an install kit using NSIS (not an MSI, which was so much more complicated and unnecessary for our needs). This install kit did everything necessary, like stop IIS, copy the files, put configuration files in the right places, restart IIS, etc. We then created a TeamCity build configuration which ran that install kit remotely on the test server using psexec.
This allowed our testers to do UAT deployments themselves, as long as they didn't contain database changes - but those were much rarer than code changes.
Production deployments were, of course, more involved and we couldn't automate them this much, but we still used the same install kit, which helped to ensure consistency between UAT and production. If anything was missing or not copied to the right place it was usually picked up in UAT.
2) Automating database deployments
Deploying database changes was a big problem as well. We were already scripting all DB changes, but there were still problems in knowing which scripts were already run and which still needed to be run and in what order. We looked at several tools for this, but ended up rolling our own.
DB scripts were organised in a directory structure by the release number. In addition to the scripts developers were required to add the filename of a script to a text file, one filename per line, which specified the correct order. We wrote a command-line tool which processed this file and executed the scripts against a given DB. It also recorded which scripts it had run (and when) in a special table in the DB and next time it did not run those again. This means that a developer could simply add a DB script, add its name to the text file and run the tool against the UAT DB without running around asking others what scripts they last ran. We used the same tool in production, but of course it was only run once per release.
The extra step that really made this work well is running the DB deployment as part of the build. Our unit tests ran against a real DB (a very small one, with minimal data). The build script would restore a backup of the DB from the previous release and then run all the scripts for the current release and take a new backup. (In practice it was a little more complicated, because we also had patch releases and the backup was only done for full releases, but the tool was smart enough to handle that.) This ensured that the DB scripts were tested together at every build and if developers made conflicting schema changes it would be picked up quickly.
The only manual steps were at release time: we incremented the release number on the build server and copied the "current DB" backup to make it the "last release" backup. Apart from that we no longer had to worry about the DB used by the build. The UAT database still occasionally had to be restored from backup (eg. since the system couldn't undo the changes for a deleted DB script), but that was fairly rare.
3) Branching for a release
It sounds basic and almost not worth mentioning, yet we weren't doing this to begin with. Merging back changes can certainly be a pain, but not as much of a pain as having a single codebase for today's release and next month's! We also got the person who made the most changes on the release branches to do the merge, which served to remind everyone to keep their release branch commits to an absolute minimum.
Automate your release process whereever possible.
As others have hinted, use different levels of build "depth". For instance a developer build could make all binaries for runnning your product on the dev machine, directly from the repository while an installer build could assemble everything for installation on a new machine.
This could include
binaries,
JAR/WAR archives,
default configuration files,
database scheme installation scripts,
database migration scripts,
OS configuration scripts,
man/hlp pages,
HTML documentation,
PDF documentation
and so on. The installer build can stuff all this into an installable package (InstallShield, ZIP, RPM or whatever) and even build the CD ISOs for physical distribution.
The output of the installer build is what is typically handed over to the test department. Whatever is not included in the installation package (patch on top of the installation...) is a bug. Challenge your devs to deliver a fault free installation procedure.
Automated single step build. The ant build script edits all the installer configuration files, program files that need changed ( versioning) and then builds. No intervention required.
There is still a script run to generate the installers when it's done, but we will eliminate that.
The CD artwork is versioned manually; that needs fixed too.
Agree with previous comments.
Here is what has evolved where I work. This current process has eliminated the 'gotchas' that you've described in your question.
We use ant to pull code from svn (by tag version) and pull in dependencies and build the project (and at times, also to deploy).
Same ant script (passing params) is used for each env (dev, integration, test, prod).
Project process
Capturing requirements as user 'stories' (helps avoid quibbling over an interpretation of a requirement, when phrased as a meaningful user interaction with the product)
following an Agile principles so that each iteration of the project (2 wks) results in demo of current functionality and a releasable, if limited, product
manage release stories throughout the project to understand what is in and out of scope (and prevent confusion abut last minute fixes)
(repeat of previous response) Code freeze, then only test (no added features)
Dev process
unit tests
code checkins
scheduled automated builds (cruise control, for example)
complete a build/deploy to an integration environment, and runs smoke test
tag the code and communicate to team (for testing and release planning)
Test process
functional testing (selenium, for example)
executing test plans and functional scenarios
One person manages the release process, and ensures everyone complies. Additionally all releases are reviewed a week before launch. Releases are only approved if there are:
Release Process
Approve release for a specific date/time
Review release/rollback plan
run ant with 'production deployment' parameter
execute DB tasks (if any) (also, these scripts can be version and tagged for production)
execute other system changes / configs
communicate changes
I don't know or practice SDLC, but for me, these tools have been indispensible in achieving smooth releases:
Maven for build, with Nexus local repository manager
Hudson for continuous integration, release builds, SCM tagging and build promotion
Sonar for quality metrics.
Tracking database changes to development db schema and managing updates to qa and release via DbMaintain and LiquiBase
On a project where I work we were using Doctrine's (PHP ORM) migrations to upgrade and downgrade the database. We had all manner of problems as the generated models no longer matched with the database schema causing the migrations to completely fail half way.
In the end we decided to write our own super basic version of the same thing - nothing fancy, just up's and down's that execute SQL. Anyway it worked out great (so far - touch wood). Although we were reinventing the wheel slightly by writing our own, the fact that the focus was on keeping it simple meant that we have far less problems. Now a release is a cinch.
I guess the moral of the story here is that it is sometimes OK to reinvent the wheel some times as long as you are doing so for a good reason.