Aurora is a multi-tenant system; a single software instance runs on a server, serving multiple clients/tenants. To share resources among tenants, it implements isolation of:
CPU is a soft limit, and handled differently from memory and disk space. Too low a CPU value results in throttling your application and slowing it down. Memory and disk space are both hard limits; when your application goes over these values, it’s killed.
Let’s look at each resource type in more detail:
Mesos uses a quota based CPU scheduler (the Completely Fair Scheduler) to provide consistent and predictable performance. This is effectively a guarantee of resources – you receive at least what you requested, but also no more than you’ve requested.
The scheduler gives applications a CPU quota for every 100 ms interval. When an application uses its quota for an interval, it is throttled for the rest of the 100 ms. Usage resets for each interval and unused quota does not carry over.
For example, an application specifying 4.0 CPU has access to 400 ms of CPU time every 100 ms. This CPU quota can be used in different ways, depending on the application and available resources. Consider the scenarios shown in this diagram.
Scenario A: the application can use up to 4 cores continuously for every 100 ms interval. It is never throttled and starts processing new requests immediately.
Scenario B : the application uses up to 8 cores (depending on availability) but is throttled after 50 ms. The CPU quota resets at the start of each new 100 ms interval.
Scenario C : is like Scenario A, but there is a garbage collection event in the second interval that consumes all CPU quota. The application throttles for the remaining 75 ms of that interval and cannot service requests until the next interval. In this example, the garbage collection finished in one interval but, depending on how much garbage needs collecting, it may take more than one interval and further delay service of requests.
Technical Note: Mesos considers logical cores, also known as hyperthreading or SMT cores, as the unit of CPU.
To correctly size Aurora-run Mesos tasks, specify a per-shard CPU value that lets the task run at its desired performance when at peak load distributed across all shards. Include reserve capacity of at least 50%, possibly more, depending on how critical your service is (or how confident you are about your original estimate : -)), ideally by increasing the number of shards to also improve resiliency. When running your application, observe its CPU stats over time. If consistently at or near your quota during peak load, you should consider increasing either per-shard CPU or the number of shards.
Mesos uses dedicated memory allocation. Your application always has access to the amount of memory specified in your configuration. The application’s memory use is defined as the sum of the resident set size (RSS) of all processes in a shard. Each shard is considered independently.
In other words, say you specified a memory size of 10GB. Each shard would receive 10GB of memory. If an individual shard’s memory demands exceed 10GB, that shard is killed, but the other shards continue working.
Technical note: Total memory size is not enforced at allocation time, so your application can request more than its allocation without getting an ENOMEM. However, it will be killed shortly after.
Size for your application’s peak requirement. Observe the per-instance memory statistics over time, as memory requirements can vary over different periods. Remember that if your application exceeds its memory value, it will be killed, so you should also add a safety margin of around 10-20%. If you have the ability to do so, you may also want to put alerts on the per-instance memory.
Disk space used by your application is defined as the sum of the files’
disk space in your application’s directory, including the stdout and
stderr logged from your application. Each shard is considered
independently. You should use off-node storage for your application’s
data whenever possible.
In other words, say you specified disk space size of 100MB. Each shard would receive 100MB of disk space. If an individual shard’s disk space demands exceed 100MB, that shard is killed, but the other shards continue working.
After your application finishes running, its allocated disk space is reclaimed. Thus, your job’s final action should move any disk content that you want to keep, such as logs, to your home file system or other less transitory storage. Disk reclamation takes place an undefined period after the application finish time; until then, the disk contents are still available but you shouldn’t count on them being so.
Technical note : Disk space is not enforced at write so your application can write above its quota without getting an ENOSPC, but it will be killed shortly after. This is subject to change.
Size for your application’s peak requirement. Rotate and discard log files as needed to stay within your quota. When running a Java process, add the maximum size of the Java heap to your disk space requirement, in order to account for an out of memory error dumping the heap into the application’s sandbox space.
Other resources, such as network bandwidth, do not have any performance guarantees. For some resources, such as memory bandwidth, there are no practical sharing methods so some application combinations collocated on the same host may cause contention.
Aurora requires resource quotas for production non-dedicated jobs. Quota is enforced at the job role level and when set, defines a non-preemptible pool of compute resources within that role.
To grant quota to a particular role in production use aurora_admin set_quota command.
NOTE: all job types (service, adhoc or cron) require role resource quota unless a job has dedicated constraint set.
Under a particular resource shortage pressure, tasks from production jobs may preempt tasks from any non-production job. A production task may only be preempted by tasks from production jobs in the same role with higher priority.