How can i run mongo 2.6 and mongo 3.0 at the same time on my linux system ?
I need this because i have 2 projects one is working on mongo 2.6 and one is working on mongo 3.0
Any help is appreciated !!
If you really wan to do this, and I recommend you DO NOT, then the best way is to use a container tech, docker can work quite well or LXC or one of the others.
However, do note that there is a high chance that if your sever is in the "cloud" it is already vitualised as it is as such you will constantly be losing power and resources due to sub virtualising everything over and over.
DO NOT put them on the same host without some kind of separation there will be a high chance of resource contention and conflict that tools like ulimit just cannot solve (well, technically it could but it will be a hairball).
Related
I did an experiment by running a python app that is writing 2000 records into mongoDB.
The details of my setup of the experiment as follows:
Test 1: Local PC - Python App running on Local PC with mongoDB on Local PC (baseline)
Test 2: Docker - Python App on Linux Container with mongoDB on Linux Container with persist volume
Test 3: Docker - Python App on Linux Container with mongoDB on Linux Container without persist volume
I’ve generated the result in chart - on average writing data on local PC is about 30 secs. Where else on Docker, it takes about 80plus secs. Hence it seems like writing on Docker is almost 3 times slower than writing on local PC itself.
Should I want to improve the write speed or performance of the mongoDB in docker container, what is the recommended practice? Or should I put the mongoDB as a external volume without docker?
Thank you!
graph
Your system is not consistent in many ways - dynamic storage and CPU performance, other processes, dynamic system settings etc. There are a LOT of underlying things under storage only.
60 sec tests are not enough for anything
Simple operations are not good enough for baseline comparisons
There is ZERO performance impact with storage and CPU in case of containers, there is an impact in networking, but i assume, this is not applicable here
Databases and database management systems must be optimized in special ways, there is no "install and run" approach. We, sysadmins/db admins usually need days to have it running smoothly. Also, performance changes over time.
After couple of weeks of testing and troubleshooting. I finally got the answer and I shall share my findings with the rest of the DevOps or anyone who facing the same issue as me
Correct this statement if needed, Docker Container was started off with Linux, Microsoft join the container bandwagon late and in order to for the container works (with Linux), the DevOps team need to install Linux WSL2 in Windows. And that cost extra overheads which resultant in the process speed.
So to improve the performance speed with containers, the setup should be in Linux OS instead of Windows OS. (and yes the speed reduce drastically)
Which of these methods is correct?
One db container for each app
One db container for all apps
Install db without docker
I tried to find information, but nothing. Or I badly searched?
It is immature, but that doesn't seem to be stopping a lot of people using Docker for persistence.
The official Postgres image has 4.5 million pulls - Ok, this doesn't mean that all those images/containers are being used but it does suggest that it is a popular solution.
If you have already decided that you would like to use Docker, because of what containers can offer your architecture, then I don't think you will have trouble using it for persistence - assuming you are happy learning Docker.
I'm using Postgres and MySql in several projects quite successfully on Docker.
In choosing option 1 or 2, I would say that unless your apps are related to the same problem domain/company/project I would go with option 1. Of course, running costs will possibly factor in as well.
I generally go with option 1.
All 3 options could be valid but it depends on the use you have to perform.
In my server I've 1 container for every main postgresql releases currently I use.
I run all of them on different ports (use not random number for ports but some easy to remember because a problem with docker is remember all port numbers and other for every container).
pg84(port 8432), pg93(port 9332), pg94 (port 9432)
I link the pgXX to the container I need and that's perfect for me.
For my experience I prefer option 2 so.
In relational databases I would just pop in W3Schools tutorial, install mysql in my machine and start practicing! How can I learn non relational databases in a similar way? In most tutorials I read that these databases work with multiple nodes and data centers.
Does this mean that I will be unable to learn and practice, say Cassandra, using my own single pc?
You do it just like you do it with mySQL: You set up a database on your local machine and start experimenting.
Most database systems which focus on sharding and clustering also work as a stand-alone instance. But when you want to test these features specifically, you can often run multiple instances on the same machine. When you also want to try how they behave when they run on different machines, you can use a virtualization software like VMWare or VirtualBox to set up a bunch of virtual machines and build your virtual datacenter on your desktop.
(I would recommend VMWare for business use and VirtualBox for home use)
I'm a big fan of MongoDB. It's the NoSQL equivalent of MySQL.
Go to the Try It Out link on their home page and you can actually use it in a live session on their website - no download, no configuration, no hassle! Just use it and learn the basics.
Here's the quick start for Cassandra. http://wiki.apache.org/cassandra/GettingStarted
I don't see any reason you couldnt run that from local host. I think the point is that you Can scale these nosql solutions. Might want to check out mongodb or couchdb as well. Easy set up and both are great nosql solutions in my experience.
I would strongly suggest using something like Amazon EC2 for testing NoSQL solutions. You can definitely install a technology like MongoDB locally and create a replica set, but you should definitely put these on different physical machines if you can.
I have installed things like AppFabric, Couchbase and Mongo locally and created clusters and they always work really well locally. It's very easy because the networking part of it always goes smoothly.
Once you introduce two physical machines and a stronger network partition things get difficult.
You can create instances on EC2 for free last I checked if you use their Micro instances. You'll learn a lot.
Is MongoDB for Azure production ready ?
Can anyone share some experience with it ?
Looks like comfort is missing for using it for prod.
What do you think ?
Edit: Since there is a misunderstanding in my question i will try to redefine it.
The information i look into from the community is sharing an info of someone who is running mongo on windows azure to share experience from it.
What i mean by experience is not how to run it in the cloud(we already have the manual on 10gens faq) nor how many bugs it have(we can see that in mongo-azure jira).
What i am looking for is that how it is going with performance ?
Are there any problems(side effects) from running mongodb on azure ?
How does mongodb handle VM recycling ?
Does anyone tried sharding ?
In the end, is the mongo-azure worker role from 10gens stable for using it in production ?
Hope this clears out.
A bit of clarification here. MongoDB itself is production-ready. And MongoDB works just fine in Windows Azure, as long as you set up the scaffolding to get it to work in the environment. This typically entails setting up an Azure Drive, to give you durable storage. Alternatively, using a replicaset, you effectively have eventual consistency across the set members. Then, you could consider going with a standalone (or standalone with hot standby). Personally, I prefer a replicaset model, and that's typical guidance for production MongoDB systems.
As far as 10gen's support for Windows Azure: While the page #SyntaxC4 points to does clarify the wrapper is in a preview state, note that the wrapper is the scaffolding code that launches MongoDB. This scaffolding was initially released in December 2011, and has had a few tweaks since then. It uses the production MongoDB bits (and works just fine with version 2.0.5 which was published on May 9). One caveat is that the MongoDB replicaset roles are deployed alongside your application's roles, since the client app needs visibility to all replica set nodes (to properly build the set). To avoid this limitation, you'd need to run mongos and the entry point (and that's not part of 10gen's scaffolding solution).
Forgetting the preview scaffolding a moment: I have customers running MongoDB in production, with custom scaffolding. One of them is running a rather large deployment, with multiple shards, using a replicaset per shard.
So... does it work in Windows Azure? Yes. Should you take advantage of 10gen's supplied scaffolding? If you're just looking for a simple way to launch a replicaset, I think it's fine. If you want a standalone model, or a shard model, or if you need a separate deployment for MongoDB, you'd currently need to do this on your own (or modify the project 10gen published).
MongoLab is now offering Mongo as a service on Azure MongoLab Blog
Free Demo account is 0.5 GB storage are available in the Windows Azure Store
The warning message on their site says that it's a preview. This would mean that there would be no support for it at a product level in Windows Azure.
If you want to form your own opinion on a comfort level, you can take a look at their bug tracking system and get a feeling for what people are currently reporting as issues.
Anyone know how much disk space and ram a standard ubuntu install on mongo needs? trying to map out my VPS needs ...
There are no minimum requirements as such, but I wouldn't recomend running Mongo on the same box as your webserver.
MongoDB automatically uses all free memory on the machine as its cache
(http://docs.mongodb.org/manual/faq/fundamentals/#does-mongodb-require-a-lot-of-ram)
This, along with the reasons mentioned in this answer (albeit for RDBMS) makes running mongodb on a separate box (even a small one) a much better idea.