Clearing out 'finished' service history in DC/OS - user-interface

I am currently setting up a POC network of dockerised services using DC/OS. As this is a POC, I have had to make many revisions to the containers in order to get things working.
Consequently, when drilling into some services using the DC/OS (v1.8.7) web UI, I can see hundreds of old tasks - the vast majority of which have a status of 'finished'.
I realise that I can filter out and just see the 'active' containers by clicking on the appropriate tab, but this is not what I am after because I would like to be able to see when a container is staging, and also - all the history for the finished tasks is worthless to me.
How do I purge DC/OS of these finished tasks, as they are clogging up the UI?
Is there a CLI command for this, or do I have to clear out stuff on the master nodes... or is there an handy plug-in that will manage this for me? I've been looking around both on the web and the master nodes, but can't work out what I need to do.

In DC/OS 1.8.x there is no UI or CLI method to influence garbage collection. You can however, with a custom install, influence some parameter, such as gc_delay (default value: 2 days in DC/OS) and others are using the Mesos defaults, like gc_disk_headroom (which is unchanged set to 0.1, which means, Mesos targets to have 10% of the assigned disk as free space).
For parameters you can change at install time see the Install Configuration Parameters docs for more details.

Related

Conditionally restart a service

I've just learned how to use notifications and subscriptions in Chef to carry out actions such as restarting services if a config file is changed.
I am still learning chef so may just have not got to this section yet but I'd like to know how to do the actions conditionally.
Eg1 if I change a config file for my stand alone apache server I only want to restart the service if we are outside core business hours ie the current local time is between 6pm and 6am. If we are in core business hours I want the restart to happen but at a later time, outside core hours.
Eg2 if I change a config file for my load balanced apache server cluster I only want restart the service if a) the load balancer service status is "running" and b) all other nodes in the cluster have their apache service status as running ie I'm not taking down more than one node in the cluster at once.
I imagine we might need to put the action in a ruby block that either loops until the conditions are met or sets a flag or creates a scheduled task to execute later but I have no idea what to look for to learn how best to do this.
I guess this topic is kind of philosophical. For me, Chef should not have a specific state or logic beyond the current node and run. If I want to restart at a specific time, I would create a cron job with a conditional and just set the conditional with chef (Something like debian's /var/run/reboot-required). Then crond would trigger the reboot.
For your second example, the LB should have no issues to deal with a restarting apache backend and failover to another backend. Given that Chef runs regulary with something called "splay" the probability is very low that no backend is reachable. Even with only 2 backends. That said, reloading may be the better way.

Some questions on Apache Aurora

I have been comparing Marathon with Aurora.
Marathon:
Easy to use
Light weight
More active to add new features
Aurora:
More feature sets, and more flexible object configurations
Heavy and difficult to use
More conservative adding new features
Right now, we can not decide which one to use. Here are several questions hope can be answered by someone:
How to handle group of tasks in Aurora? Grouping is supported in Marathon, a group of tasks can be managed together, but I cannot find grouping in Aurora.
How to config environment variables for processes/tasks in Aurora?
How to add event handler for status updates in Aurora? We would like to implement customized alerting. It is possible in Marathon.
Aurora is a great scheduler and is very solid, especially the templating and it's DSL makes aurora very powerful. I had a few gists ready and docs as an example but i can only post 2 url's here.
Aurora supports processes, tasks and jobs. Usually when we wish to have tasks executed on the same host we place these in processes, its also possible to combine or concat tasks. Aurora has excellent support for executing processes, they can be done sequential or parallel.
An example can be found here:
http://aurora.apache.org/documentation/latest/reference/configuration-tutorial/#sequentialtask-running-processes-in-parallel-or-sequentially
Another option is to run tasks combined.
{{replace with the aurora website}}/documentation/latest/reference/configuration-tutorial/#combining-tasks)
This is recently added to the documentation on how to add environment variables. For now you can check this link until its published on the website:
https://github.com/apache/aurora/blob/2a8c667ec1b48900530975169f132d9deb098399/docs/reference/configuration-tutorial.md#getting-environment-variables-into-the-sandbox
Currently to my knowledge there are no event handlers for status updates, perhaps someone else can answer this question better than me. An option that comes close:
What you can do is add a finalizing task that sends out an alert or triggers an event. This task will run after all processes are stopped, you can run multiple finalizing tasks. Do not have an direct link, but if you search for final on this page you find more:
{{replace with the aurora website}}/documentation/latest/reference/configuration/
And just saw this was a year ago, but perhaps someone else will be happy with this.

How to select CPU parameter for Marathon apps ran on Mesos?

I've been playing with Mesos cluster for a little bit, and thinking of utilizing Mesos cluster in our production environment. One problem I can't seem to find an answer to: how to properly schedule long running apps that will have varying load?
Marathon has "CPUs" property, where you can set weight for CPU allocation to particular app. (I'm planning on running Docker containers) But from what I've read, it is only a weight, not a reservation, allocation, or limitation that I am setting for the app. It can still use 100% of CPU on the server, if it's the only thing that's running. The problem is that for long running apps, resource demands change over time. Web server, for example, is directly proportional to the traffic. Coupled to Mesos treating this setting as a "reservation," I am choosing between 2 evils: set it too low, and it may start too many processes on the same host and all of them will suffer, with host CPU going past 100%. Set it too high, and CPU will go idle, as reservation is made (or so Mesos think), but there is nothing that's using those resources.
How do you approach this problem? Am I missing something in how Mesos and Marathon handle resources?
I was thinking of an ideal way of doing this:
Specify weight for CPU for different apps (on the order of, say, 0.1 through 1), so that when going gets tough, higher priority gets more (as is right now)
Have Mesos slave report "Available LA" with its status (e.g. if 10 minute LA is 2, with 8 CPUs available, report 6 "Available LA")
Configure Marathon to require "Available LA" resource on the slave to schedule a task (e.g. don't start on particular host if Available LA is < 2)
When available LA goes to 0 (due to influx of traffic at the same time as some job was started on the same server before the influx) - have Marathon move jobs to another slave, one that has more "Available LA"
Is there a way to achieve any of this?
So far, I gather that I can possible write a custom isolator module that will run on slaves, and report this custom metric to the master. Then I can use it in resource negotiation. Is this true?
I wasn't able to find anything on Marathon rescheduling tasks on different nodes if one becomes overloaded. Any suggestions?
As of Mesos 0.23.0 oversubscription is supported. Unfortunately it is not yet implemented in Marathon: https://github.com/mesosphere/marathon/issues/2424
In order to dynamically do allocation, you can use the Mesos slave metrics along with the Marathon HTTP API to scale, for example, as I've done here, in a different context. My colleague Niklas did related work with nibbler, which might also be of help.

Does the kubernetes scheduler support anti-affinity?

I'm looking at deploying Kubernetes on top of a CoreOS cluster, but I think I've run into a deal breaker of sorts.
If I'm using just CoreOS and fleet, I can specify within the unit files that I want certain services to not run on the same physical machine as other services (anti-affinity). This is sort of essential for high availability. But it doesn't look like kubernetes has this functionality yet.
In my specific use-case, I'm going to need to run a few clusters of elasticsearch machines that need to always be available. If, for any reason, kubernetes decides to schedule all of my elasticsearch node containers for a given ES cluster on a single machine, (or even the majority on a single machine), and that machine dies, then my elasticsearch cluster will die with it. That can't be allowed to happen.
It seems like there could be work-arounds. I could set up the resource requirements and machine specs such that only one elasticsearch instance could fit on each machine. Or I could probably use labels in some way to specify that certain elasticsearch containers should go on certain machines. I could also just provision way more machines than necessary, and way more ES nodes than necessary, and assume kubernetes will spread them out enough to be reasonably certain of high availability.
But all of that seems awkward. It's much more elegant from a resource-management standpoint to just specify required hardware and anti-affinity, and let the scheduler optimize from there.
So does Kubernetes support anti-affinity in some way I couldn't find? Or does anyone know if it will any time soon?
Or should I be thinking about this another way? Do I have to write my own scheduler?
Looks like there are a few ways that kubernetes decides how to spread containers, and these are in active development.
Firstly, of course there have to be the necessary resources on any machine for the scheduler to consider bringing up a pod there.
After that, kubernetes spreads pods by replication controller, attempting to keep the different instances created by a given replication controller on different nodes.
It seems like there was recently implemented a method of scheduling that considers services and various other parameters. https://github.com/GoogleCloudPlatform/kubernetes/pull/2906 Though I'm not completely clear on exactly how to use it. Perhaps in coordination with this scheduler config? https://github.com/GoogleCloudPlatform/kubernetes/pull/4674
Probably the most interesting issue to me is that none of these scheduling priorities are considered during scale-down, only scale-up. https://github.com/GoogleCloudPlatform/kubernetes/issues/4301 That's a bit of big deal, it seems like over time you could weird distributions of pods because they stay whereever they are originally placed.
Overall, I think the answer to my question at the moment is that this is an area of kubernetes that is in flux (as to be expected with pre-v1). However, it looks like much of what I need will be done automatically with sufficient nodes, and proper use of replication controllers and services.
Anti-Affinity is when you don’t want certain pods to run on certain nodes. For the present scenario I think TAINTS AND TOLERATIONS can come handy. You can mark nodes with a taint, then ,only those pods which explicitly have tolerance for that taint are going to be allowed to run on that specific node.
Below I am describing how can anti-affinity concept be implemented:
Taint any node you want.
kubectl taint nodes gke-cluster1-default-pool-4db7fabf-726z env=dev:NoSchedule
here, env=dev is the key:value pair or rather the label for this node ,
NoSchedule is the effect which describes not to schedule any pod on this node unless with the specific toleration.
Create a deployment
kubectl run newdep1 --image=nginx
Add the same label as the label to the node to this deployment so that all pods of this deployment are hosted on this node and this node will not host any other pod without the matching label.
kubectl label deployments/newdep1 env=dev
kubectl scale deployments/newdep1 --replicas=5
kubectl get pods -o wide
running this you will see all pods of newdep1 will run on your tainted node.

How to Auto-start selenium nodes under Windows

I am trying to automate the startup of my Selenium Grid.
I have the Hub registered as a service, so that starts when the machine starts, but
the literature tells me I can't do the same with the node, because it won't be in a User context, and so I would not be able to get screenshots etc.
I've seen vague hints that you can add something to the registry to start a program, but I'm not really convinced thats what I want.
IT pulls down the servers for upgrades at intervals, and sessions are set to time out after X amount of inactivity, so its a tedious and silly process to open remote desktops to all 6 nodes, in order to log in, then start the process every time.
How do you best manage this?
- Configure the machines to auto-login, and place startSeleniumNode.bat in that users start-folder?
- Add some kind of commandline entry in the jenkins build script that launches the test, to call each of the 6 nodes in turn to start the selenium node (and how would you do that?)
Take a look at AlwaysUp - it allows you to run almost any application as a Windows service including Selenium Grid hubs and nodes.
I've previously created a fairly large Grid infrastructure using AlwaysUp for node management. It's very useful for starting up Grid on boot and lets you specify a user account to run as, schedule restarts at regular intervals and a lot more.

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