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The '''scheduler''' examines schedules and creates jobs. | The '''scheduler''' examines schedules and creates jobs. |
Revision as of 19:41, 3 May 2013
- Launchpad Entry: QonoS scheduling service
- Created: 3 May 2013
- Contributors: Alex Meade, Eddie Sheffield, Andrew Melton, Iccha Sethi, Nikhil Komawar, Brian Rosmaita
Summary
This document describes the design and API of QonoS, a distributed high-availability scheduling service that has been implemented for the cloud[1]. QonoS is currently used as the scheduling component of a scheduled images service that is invoked by a Nova extension, so many of the examples in this document discuss that use case.
Service responsibilities include:
- Create scheduled tasks
- Perform scheduled tasks
- Handle rescheduling failed jobs
- Maintain persistent schedules
Conceptual Overview
The system consists of:
- an API
- a database
- one or more schedulers, and
- one or more workers.
The scheduler examines schedules and creates jobs.
A job describes a task that must be performed.
A worker performs a task. It obtains a task by polling the API and picking up the first task it is capable of handling.
Job Lifecycle
Jobs have the following statuses:
-
queued
: the job is ready to be processed by a worker -
processing
: the job has been picked up by a worker -
done
: the worker processing this job has decided that the job has been successfully completed -
timeout
: the worker processing this job has decided the job is taking too long and has stopped processing it. A job in this state can be picked up by another worker. -
error
: the worker notes that something went wrong, but the job could be retried -
canceled
: the worker decides that the job can't be done and should not be retried
Job Timeouts
There are two kinds of timeouts:
- hard timeout: once reached, the job is no longer available for retries
- soft timeout: is renewed by the worker, indicates that the worker is still doing the task (similar to a heartbeat)
Job Failures
Job failures are reported as job faults and stored in the database.
Overall System Diagram
Scalability
Creating a new, self-standing service allows for scaling the feature independently of the rest of the system.
Reliability
Users of the API may come to rely on this feature working every time or notifying them of failures.
It is important to have a scheduling service that understands information such as instances, tenants, etc if there is any desire to recover from errors or make performance decisions based on such information. This is opposed to having a more generic 'cron' service that knows nothing of the concept of an instance or image.
For example, listing schedules of a particular tenant would be much more efficient if the tenant was in a DB column instead of a blob in the DB.
Design
Entities
- Schedule
- the general description of what the service will do
- looks something like
{ "tenant_id" : <tenantId>, "schedule_id" : <scheduleId>, "job_type" : <keyword>, "metadata" : { // all the information for this job_type "key" : "value" } "schedule" : <the schedule info, exact format TBD> }
- Job
- a particular instance of a scheduled job_type
- e.g., 'snapshot'
- a particular instance of a scheduled job_type
- i.e., this is the thing that will be executed by a worker
- Worker
- a process that performs a Job
The QonoS scheduling service has the following functional components:
- API
- handles communication, both external requests and internal communication
- creates the schedule for a request and stores it in DB
- the only job_type we will implement is 'scheduled_image'
- Job Maker
- creates Jobs from schedules; the idea is that the Jobs table will consist of Jobs that are ready to be executed for the current time period
- Job Monitor
- keeps the Job table updated
- Worker monitor
- looks for dead workers
- Worker
- executes a job, keeps the job's 'status' updated
- does "best effort" ... if an error is encountered, it will log and terminate job
API
CRUD for schedules
POST /v1/schedules GET /v1/schedules GET /v1/schedules/{scheduleId} DELETE /v1/schedules/{scheduleId} PUT /v1/schedules/{scheduleId}
Request body for POST, PUT will be roughly the Schedule entity described above. POST would return the scheduleId.
CRUD for jobs
GET /v1/jobs GET /v1/jobs/{jobId} DELETE /v1/jobs/{jobId} GET /v1/jobs/{jobId}/status GET /v1/jobs/{jobId}/heartbeat PUT /v1/jobs/{jobId}/status * status in request body PUT /v1/jobs/{jobId}/heartbeat * heartbeat for this job (exact format TBD) in request body
NOTES:
- No POST, the job maker handles job creation.
- The worker will mark the job status as 'done' (or whatever) when it finishes.
- The /status and /heartbeat may be combined into a single call, not sure yet
GET /v1/workers GET /v1/workers/{workerId} GET /v1/workers/{workerId}/jobs/next * return job info, format TBD POST /v1/workers * returns a workerId, is done when a worker is instantiated, allows the system to keep track of the worker DELETE /v1/workers/{workerId} * should be called by the worker if/when it's safely taken down
Service
The service shall consist of a set of apis, worker nodes, and a DB.
API - Provides a RESTful interface for adding schedules to the DB
Worker - References schedules in the DB to schedule and perform jobs
DB - Tracks schedules and currently executing jobs
Database
- schedules
- jobs
- job faults
- must be useful!
Implementation
Typical flow of the system is as follows.
- User makes request to Nova extension
- Nova extension passes request to API
- API picks time of day to schedule
- Adds schedule entry to DB
- Worker polls DB for schedules needing action
- Worker creates job entry in DB
- Worker initiates image snapshot
- Worker waits for completion while updating 'last_touched' field in the job table (to indicate the Worker has not died)
- Worker updates DB to show the job has been completed
- Worker polls until a schedule needs action
Edge cases:
Worker dies in middle of job:
- A different worker will see the job has not been updated in awhile and take over, performing any cleanup it can.
- Jobs contain information of where they left off and what image they were working on (this allows a job whose worker died in the middle of an upload to be resumed)
Image upload fails
- Retry a certain number of times, afterwards leave image in error state
Instance no longer exists
- Remove schedule for instance
Code Repository
References
- ↑ QonoS was first described in https://wiki.openstack.org/wiki/Scheduled-images-service (29 October 2012).