Consider the following cluster running on Google Container Engine:
tier: g1-small
cpu cores: 2
memory: 1,7GB per cpu core (3,4GB total in this case)
autoscaling: enabled, min=2, max=5
On this cluster, I have the following Deployments running via Kubernetes:
Load Balancer using NGINX
Web App using Node.js (communicating with WordPress via REST calls)
example.com
CMS using WordPress on Apache (wp.example.com)
wp.example.com
For clarity, every request goes through the NGINX Load Balancer first, then, depending on the subdomain, to either the CMS or the Web App.
I'd like to have more control over how much resources each Deployment consumes in order to consume resources more efficiently by applying Kubernetes Limit Ranges to my Pods/Containers resources.
Limits can be set on CPU and Memory. These are well explained in the docs. So far, so good.
The problem I'm having is to figure out what limits to apply per Deployment.
Example
The WordPress Deployment contains two containers in the deployment.yaml file. One for the WordPress image itself, one for the Cloud SQL Proxy Container that is needed for WordPress to connect to my Cloud SQL Database. How would I know what each container needs with respect to CPU/Memory resources?
Furthermore, considering that all HTTP/HTTPS traffic hits my NGINX Load Balancer first, an educated guess would be apply relatively more resources to the NGINX Deployment than to my CMS and Web App Deployment, right?!.
So is there a way to better estimate how many resources each Deployment would need?
Any help is greatly appreciated!
k8s' default value to pods is 100m CPU request and no CPU limit, and no memory request/limit. If you don't set limitation pods/containers will consume as much as it need. Which is pretty convenient since usually you don't specify limitation one by one.
Nginx as a load balancer is pretty light-weighted. So it's hard to say which one needs more resources. I would follow the default at the beginning then use kubectl top pod to check CPU/memory pressure for tuning reference.
Related
i'm deploying and app to Amazon ECS and need some advice on application level monitoring (periodic HTTP 200 and/or body match). Usually i place it behind an ELB and i am sure that my ELB will take action if it sees too many HTTP errors.
However this time it's a very low budget project and the budget for the ELB should be avoided (also consider this is going to work with only one instance as the userbase is very limited).
What strategies could i adopt to grant that the application is alive (kill instance and restart in case of too many app errors)? Regarding the instance i know about AWS autohealing but that's infrastructure.
Obviously one of the problems is that not having an ELB i must bind the DNS to an EIP....so reassigning it it's crucial.
And obviously the solution should not involve any other EC2 instance, external services are acceptable but keeping it all inside AWS would be great.
Thanks a lot
Monitoring of ECS is important to improve the importance of your site. If you still think there could be issues related to deployment on AWS, I suggest to practice auto-scaling feature of AWS.
You can scale up ECS when needed and release it when not required.
Nagios is another open source monitoring tool that you can leverage. Easy to install and configure.
Idea
Gradually use a few small-scale dedicated servers in combination with an expensive cloud platform, where - on little traffic - the dedicated servers should first filled up before the cloud kicks in. Hedging against occasional traffic spikes.
nginx
Is there an easy way (without nginx plus) to achieve a "waterfall like" set-up, where small servers should first be served up to a maximum number of concurrent connections, or better, current bandwidth before the cloud platform sees any traffic?
Nginx Config, Libraries, Tools?
Thanks
You will use nginx upstream module.
If you want total control, set your cloud servers with backup parameter, so that they won't be used until your primary servers fail. Then use custom monitoring scripts to determine when those could servers should kick-in, change nginx config and remove the backup keyword from them. Also monitor conditions when you want to stop using the cloud servers and alter the nginx config.
More simple solution (but without fine tuning like avoiding spikes) is to use the max_conns=number parameter. Nginx should start to use the backup server if all other already have max number of connections (I didn't test it).
NOTE: max_conns parameter was only available in paid nginx between v1.5.9 and v1.11.5, so the only solution with these versions is own monitoring + reloading of nginx config when needed to change the upstream servers. Thanks Mickaël Le Baillif's comment to point out this parameter is now available to all.
I've found at that Instagram share their technology implementation with other developers trough their blog. They've some great solutions for the problems they run into. One of those solutions they've is an Elastic Load Balancer on Amazon with 3 nginx instances behind it. What is the task of those nginx servers? And what is the task of the Elastic Load balancers, and what is the relation between them?
Disclaimer: I am no expert on this in any way and am in the process of learning about AWS ecosystem myself.
The ELB (Elastic load balancer) has no functionality on its own except receiving the requests and routing it to the right server. The servers can run Nginx, IIS, Apache, lighthttpd, you name it.
I will give you a real use case.
I had one Nginx server running one WordPress blog. This server was, like I said, powered by Nginx serving static content and "upstreaming" .php requests to phpfpm running on the same server. Everything was going fine until one day. This blog was featured on a tv show. I had a ton of users and the server could not keep up with that much traffic.
My first reaction would be to just use the AMI (Amazon machine image) to spin up a copy of my server on a more powerful instance like m1.heavy. The problem was I knew I would have traffic increasing over time over the next couple of days. Soon I would have to spin an even more powerful machine, which would mean more downtime and trouble.
Instead, I launched an ELB (elastic load balancer) and updated my DNS to point website traffic to the ELB instead of directly to the server. The user doesn’t know server IP or anything, he only sees the ELB, everything else goes on inside amazon’s cloud.
The ELB decides to which server the traffic goes. You can have ELB and only one server on at the time (if your traffic is low at the moment), or hundreds. Servers can be created and added to the server array (server group) at any time, or you can configure auto scaling to spawn new servers and add them to the ELB Server group using amazon command line, all automatically.
Amazon cloud watch (another product and important part of the AWS ecosystem) is always watching your server’s health and decides to which server it will route that user. It also knows when all the servers are becoming too loaded and is the agent that gives the order to spawn another server (using your AMI). When the servers are not under heavy load anymore they are automatically destroyed (or stopped, I don’t recall).
This way I was able to serve all users at all times, and when the load was light, I would have ELB and only one Nginx server. When the load was high I would let it decide how many servers I need (according to server load). Minimal downtime. Of course, you can set limits to how many servers you can afford at the same time and stuff like that so you don’t get billed over what you can pay.
You see, Instagram guys said the following - "we used to run 2 Nginx machines and DNS Round-Robin between them". This is inefficient IMO compared to ELB. DNS Round Robin is DNS routing each request to a different server. So first goes to server one, second goes to server two and on and on.
ELB actually watches the servers' HEALTH (CPU usage, network usage) and decides which server traffic goes based on that. Do you see the difference?
And they say: "The downside of this approach is the time it takes for DNS to update in case one of the machines needs to get decommissioned."
DNS Round robin is a form of a load balancer. But if one server goes kaput and you need to update DNS to remove this server from the server group, you will have downtime (DNS takes time to update to the whole world). Some users will get routed to this bad server. With ELB this is automatic - if the server is in bad health it does not receive any more traffic - unless of course the whole group of servers is in bad health and you do not have any kind of auto-scaling setup.
And now the guys at Instagram: "Recently, we moved to using Amazon’s Elastic Load Balancer, with 3 NGINX instances behind it that can be swapped in and out (and are automatically taken out of rotation if they fail a health check).".
The scenario I illustrated is fictional. It is actually more complex than that but nothing that cannot be solved. For instance, if users upload pictures to your application, how can you keep consistency between all the machines on the server group? You would need to store the images on an external service like Amazon s3. On another post on Instagram engineering – “The photos themselves go straight to Amazon S3, which currently stores several terabytes of photo data for us.”. If they have 3 Nginx servers on the load balancer and all servers serve HTML pages on which the links for images point to S3, you will have no problem. If the image is stored locally on the instance – no way to do it.
All servers on the ELB would also need an external database. For that amazon has RDS – All machines can point to the same database and data consistency would be guaranteed.
On the image above, you can see an RDS "Read replica" - that is RDS way of load balancing. I don't know much about that at this time, sorry.
Try and read this: http://awsadvent.tumblr.com/post/38043683444/using-elb-and-auto-scaling
Can you please point the blog entry out?
Load balancers balance load. They monitor the Web servers health (response time etc) and distribute the load between the Web servers. On more complex implementations it is possible to have new servers spawn automatically if there is a traffic spike. Of course you need to make sure there is a consistency between the servers. THEY CAN share the same databases for instance.
So I believe the load balancer gets hit and decides to which server it will route the traffic according to server health.
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Nginx is a Web server that is extremely good at serving a lot of static content for simultaneous users.
Requests for dynamic pages can be offloaded to a different server using cgi. Or the same servers that run nginx can also run phpfpm.
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A lot of possibilities. I am on my cell phone right now. tomorrow I can write a little more.
Best regards.
I am aware that I am late to the party, but I think the use of NGINX instances behind ELB in Istagram blogpost is to provide high available load balancer as described here.
NGINX instances do not seem to be used as web servers in the blogpost.
For that role they mention:
Next up comes the application servers that handle our requests. We run Djangoon Amazon High-CPU Extra-Large machines
So ELB is used just as a replacement for their older solution with DNS Round-Robin between NGINX instances that was not providing high availability.
We are looking into setting up our application on AWS. This will run on 3 load balanced web servers. We have been looking into how to prevent DDOS attacks and how to serve a static page during maintenance and are looking at going with Nginx. So the setup would be Nginx in front of an elastic load balancer.
As with our setup when there is an upgrade to the application we update Nginx to serve a static maintenance page while a whole new stack comes online with its own elastic load balancer and to switch to the new application stack we will update the Nginx config to point to the new elastic load balancer.
Does this make any sense? the reason i am asking is that I cannot find anything on this type of setup online.
Thanks,
Colin.
The elastic load balancer works by using many ip-addresses. If you do dig amazon.com you can see how it's distributed with a low ttl. Once your nginx-server runs out of open ports it will go down.
It's however a very good idéa to use balancers in-front of your app-server. This scales very well with auto-scaling groups.
When you do the transition, just lower your CNAME ttl and point it to a new load balancer.
I see zero value going in this path-
Putting a single instance of nginx will just increase the complexity of the setup, cost more and most important will introduce a new single point of failure and performance/latency bottleneck (and will make your env much more vulnerable to DDOS).
AWS infrastructure is 100% programmable - learn how to control the ELB programatically : how to direct the traffic to a static site during maintenance (could be nginx hosted on one of your instances), and how to support your upgrade workflows.
I am a DevOps guy and presently I am running my Ruby on Rails application on ubuntu ec2 where the app and also the web server reside inside the same box but we are using mysql RDS cluster. I can see lot of spikes due to more traffic to the web site. So I am planning to change the system. I wanna put web server nginx in a separate instance and web app in a separate instance. But this needs a load balancer which should reside in nginx box, but once the traffic goes up, the nginx instance can be configured to auto scale. What about the app server instance? It can be configured to auto scale but it needs to attach itself to the web server and web server needs to discover the new app server which was created. How can achieve this? Kindly help me out to get this done.
When you are using one single web server at the moment, a transition to using nginx as static webserver and proxy for another backend webserver on another instance really makes sense and will give you performance boost.
However I am not sure if you really need autoscaling. Autoscaling mostly makes sense if you want to react on fast traffic spikes etc. If you have a more or less continuous workload that might increase over time, it should be easier to manually launch and add another backend server in the nginx config. If this does not work for you, you can still have a look at Amazon's Elastic Loadbalancers and Autoscaling afterwards.