Difference between revisions of "Zaqar/bp/placement-service"

Latest revision as of 18:42, 7 August 2014

Overview

Placement Service Draft v0.1

Rationale: Marconi has a storage bottleneck

Proposal goal: Remove that bottleneck

The placement service aims to address this by handling storage transparently and dynamically.

Transparency

User transparency: availability and use of the Marconi service must not be interrupted when a migration is taking place.
Implementation transparency: storage driver is handed a location/connection and only cares about the serialization/deserialization of data to that storage location.

Terminology

Marconi partition: one Marconi master, a set of Marconi workers, and a storage deployment. This is the minimum abstraction: one adds a Marconi partition, not a storage node or a Marconi worker
Marconi master: receives requests and forwards them round robin to Marconi workers
Marconi workers: process requests and communicate with storage
Storage deployment: a set of storage nodes - one or many, as long as they're addressable with a single client connection

Reference Deployment: Smart Proxy and Partition as a Unit

This approach is emerging as the leading reference implementation for handling scaling of the Marconi service. The primary components are:

A load balancer that can redirect tenant requests to a cluster URL
Operating Marconi at the partition level

Partitions

One master to round-robin tasks to workers
N Marconi web servers
A storage deployment

Operators can optimize N to match their storage configuration and persistence needs.

Smart Proxy

The smart proxy maintains a mapping from tenants/projects (ID-based) to partition URLs.

Migration Strategy

Freezing Export: have a migration service running on each Marconi partition. The service, when given a queue and a destination partition, launches an export worker. The export worker the communicates the desired data to the new partition's migration service, which in turn launches an import worker to bring in the data. In summary:

"Freeze" the source queue
Export the queue from the source
Import the queue to the destination
"Thaw" the queue

Freeze: set a particular queue as read-only at the proxy layer Thaw: restore a particular queue to normal status at the proxy layer

Advantages

Easier to implement
No changes to Marconi
Scalable
Transparent

Disadvantages

Requires the implementation of a smart proxy - this includes: routing requests, partition management, catalogue management, regeneration. and synchronization
Benefits from having access to raw_read and raw_write functions wrt storage layer

Current State

Concepts

Partitions

Partitions have: 1) a name, 2) a weight, and 3) a list of node URIs. For example:

{
  "default": {
    "weight": 100,
    "nodes": [
      "http://localhost:8889",
      "http://localhost:8888",
      "http://localhost:8887",
      "http://localhost:8886"
    ]
  }
}

Catalogue

Catalogue entries have: 1) a key, 2) a node URI, and 3) metadata. For example:

{
  "{project_id}.{queue_name}": {
    "href": "http://localhost:8889",
    "metadata": {
      "awesome": "sauce"
    }
  }
}

API

GET /v1/partitions  # list all registered partitions

GET /v1/partitions/{name}  # fetch details for a single partition
PUT /v1/partitions/{name}  # register a new partition
DELETE /v1/partitions/{name}  # 

# the catalogue is updated by operations routed through /v1/queues/{name}
GET /v1/catalogue  # list all entries in the catalogue for the given project ID
GET /v1/catalogue/{name}  # fetch info for the given catalogue entry

Implementation

Needs Review

Proxy (partition, catalogue, queues handling): https://review.openstack.org/#/c/43909/
Proxy (v1, health): https://review.openstack.org/#/c/44356/
Proxy (forward the rest of the routes): https://review.openstack.org/#/c/44364/

To Do

Hierarchical caching: store data in authoritative store (mongo replicaset) on write operations, and cache locally using Redis instance, hitting authoritative only on failed lookups
Benchmarking
Unit tests
Functional tests
Configuration
Catalogue and partition registry regeneration

Deployment

Bring up authoritative replicaset
Bring up redis-server on each box
launch marconi.proxy.app:app using a WSGI/HTTP server

More Ideas/Deprecated

Deprecated

@@ Line 2: / Line 2: @@
 <gallery>
-File:Placement-service.jpg|Placement Service Draft
+File:Placement-service.jpg|Placement Service Draft v0.1
 </gallery>
-Marconi depends on storage for maintaining state on messages. However, as it is designed now, this is a scaling bottleneck because at most one storage node can be specified per Marconi instance. This can be partially offset by taking advantage of built-in sharding and replication for storage providers like [http://docs.mongodb.org/manual/reference/program/mongos/ MongoDB], but many other storage engines do not provide such a system. Furthermore, the migration of queues from one storage node to another is not supported cleanly by most storage providers. More intelligent data migration can be performed by taking into account that Marconi operates at the level of queues.
+'''Rationale''': Marconi has a storage bottleneck
-The placement service aims to address this by providing a means to specify dynamically where storage for Marconi resources should be performed.
+'''Proposal goal''': Remove that bottleneck
-=== Responsibilities ===
+The placement service aims to address this by handling storage transparently and dynamically.
-* Maintaining a catalogue, a mapping of (Project + Queue) => storage node locations
-* Handling queue creation transparently
-* Handling migration transparently
-* Handling deletion of queues transparently
 === Transparency ===
@@ Line 21: / Line 16: @@
 * Implementation transparency: storage driver is handed a location/connection and only cares about the serialization/deserialization of data to that storage location.
-== Approach ==
+=== Terminology ===
-A placement service consists of the following components:
+* '''Marconi partition''': one Marconi master, a set of Marconi workers, and a storage deployment. This is the minimum abstraction: one adds a Marconi partition, not a storage node or a Marconi worker
+* '''Marconi master''': receives requests and forwards them round robin to Marconi workers
+* '''Marconi workers''': process requests and communicate with storage
+* '''Storage deployment''': a set of storage nodes - one or many, as long as they're addressable with a single client connection
-* A catalogue of mappings: {queue => [read locations], queue => [write locations], queue => status}
+== Reference Deployment: Smart Proxy and Partition as a Unit ==
-    * where status is one of ACTIVE or MIGRATING
-* A cache maintained in each Marconi instance of the mappings
-* A migration service
-=== Placement API ===
+This approach is emerging as the leading reference implementation for handling scaling of the Marconi service. The primary components are:
-The placement service must handle:
+* A load balancer that can redirect tenant requests to a cluster URL
+* Operating Marconi at the partition level
-* storage assignment
+=== Partitions ===
-* cataloging
-* migrations
-An API must be exposed to facilitate these operations.
+* One master to round-robin tasks to workers
+* N Marconi web servers
+* A storage deployment
-==== Storage Management ====
+Operators can optimize N to match their storage configuration and persistence needs.
-* Add node (POST /v1/storage: {'location': 'mongo1.storage.com' , 'weight': 100})
+=== Smart Proxy ===
-* Delete node (DELETE /v1/storage/mongo1.storage.com)
-* Change weight (PUT /v1/storage/mongo1.storage.com {'weight': 50}
-* Query storage (GET /v1/storage => [...], GET /v1/storage/mongo1.storage.com => {'weight': 100})
-==== Catalogue Management ====
+The smart proxy maintains a mapping from tenants/projects (ID-based) to partition URLs.
-* Add entry (POST)
+=== Migration Strategy ===
-* Update an entry (PUT)
-* Remove entry (DELETE)
-==== Migration ====
+Freezing Export: have a migration service running on each Marconi partition. The service, when given a queue and a destination partition, launches an export worker. The export worker the communicates the desired data to the new partition's migration service, which in turn launches an import worker to bring in the data. In summary:
-This means: "move object from location A to location B". In terms of the Placement service, it must:
+* "Freeze" the source queue
+* Export the queue from the source
+* Import the queue to the destination
+* "Thaw" the queue
-* Update the storage write location
+Freeze: set a particular queue as read-only at the proxy layer
-* Update the storage read location
+Thaw: restore a particular queue to normal status at the proxy layer
-* Update the entry status ("a" => "m")
-=== Catalogue ===
+=== Advantages ===
-The catalog, as described above, maintains these mappings from queues to locations.
+* Easier to implement
+* No changes to Marconi
+* Scalable
+* Transparent
-Marconi can continue to function in a degraded state if the placement service goes down. The following capabilities will cease to function for Marconi if the placement service goes down:
+=== Disadvantages ===
-* Migration
+* Requires the implementation of a smart proxy - this includes: routing requests, partition management, catalogue management, regeneration. and synchronization
-* Queue creation
+* Benefits from having access to raw_read and raw_write functions wrt storage layer
-It may be possible to continue performing queue creation and deletion while the placement service is down by defaulting to the last storage location that Marconi held.
+== Current State ==
-The data contained in the catalogue can be regenerated by querying each Marconi endpoint and synchronizing against each cache.
+=== Concepts ===
-The Marconi catalogue contains a series of structures that look as follows:
+==== Partitions ====
+Partitions have: 1) a name, 2) a weight, and 3) a list of node URIs. For example:
 <pre><nowiki>
 {
-    "{project}.{queue}" : {
+  "default": {
-        "r": [("mongo://192.168.1.105:7777", "db1"), ("mongo://192.168.1.106:7777", "db2")],
+    "weight": 100,
-        "w": [("mongo://192.168.1.105:7777", "db1")],
+    "nodes": [
-        "s": "a"
+      "http://localhost:8889",
-     }
+      "http://localhost:8888",
+      "http://localhost:8887",
+      "http://localhost:8886"
+     ]
+  }
 }
 </nowiki></pre>
-An entry in the queue is found by concatenating a project with a queue name. "r" is the collection of locations where data for a particular queue can be gathered from. "w" is the locations where new data written to this queue are stored. "s" is the state of the queue: active "a" or migrating "m". A storage location is given by a URL and a database name.
+==== Catalogue ====
-The catalogue is filled with many such documents. The local cache for a given Marconi node is populated with the entries from this cache, to avoid lookups on each request.
-==== Adding Items to the Catalogue ====
-Whenever a Marconi queue is created, a hook is called that transfers control the the placement service. It then becomes the placement service's responsibility to:
-* Take the given project ID and namespace (queue name)
-* Assign a read storage location to it
-* Assign a write storage location to it
-* Store these locations in the catalogue
-* Return these locations to the Marconi worker
-==== Removing Items from the Catalogue ====
-When a Marconi queue has been deleted, a hook must be called to notify the Placement service. The placement service must then remove the entry from its catalogue and notify all subscribed Marconi listeners.
-=== Placement Policy Engine ===
-The placement service will use a weighted distribution to determine storage assignment for newly created queues. However, for certain tenants, we might want to assign them to special or dedicated storage.
+Catalogue entries have: 1) a key, 2) a node URI, and 3) metadata. For example:
-A weighted distribution might look like:
 <pre><nowiki>
 {
-    "mongo1.storage.com": 30,
+  "{project_id}.{queue_name}": {
-     "mongo2.storage.com": 20,
+     "href": "http://localhost:8889",
-     "mongo3.storage.com": 30,
+     "metadata": {
-    "mongo4.storage.com": 75,
+      "awesome": "sauce"
-     "mongo5.storage.com": 5,
+     }
+  }
 }
 </nowiki></pre>
-This means that the probability of a queue being stored on mongo1 is (30)/(30 + 20 + 30 + 75 + 5) => 18.75%.
+=== API ===
-The policy engine is responsible for maintaining this list of special tenants and their preferred mappings. Whenever a request to create a queue is received, Placement iterates through this list, and if the tenant is found, the associated dedicated storage is returned. If no such tenant is found, then the assignment of storage to the queue is determined by Placement.
+<pre><nowiki>
+GET /v1/partitions  # list all registered partitions
-=== Marconi Cache: Using PubSub ===
+GET /v1/partitions/{name}  # fetch details for a single partition
+PUT /v1/partitions/{name}  # register a new partition
+DELETE /v1/partitions/{name}  #
-If the Marconi catalog and the local caches are implemented using a pubsub-based transport, the invalidation procedure can be simplified. The catalog publishes on the cache channel and all listening Marconi workers update their local cache accordingly. Simple messages in the form of:
+# the catalogue is updated by operations routed through /v1/queues/{name}
+GET /v1/catalogue  # list all entries in the catalogue for the given project ID
-* <action> <queue> [<destination>]
+GET /v1/catalogue/{name}  # fetch info for the given catalogue entry
-* Where action is one of: delete, create, migrate
+</nowiki></pre>
-* Where destination is valid only for migrate, and if left unspecified, leaves the decision of destination up the placement service.
-Possibilities here include: Redis, ZeroMQ
-=== Placement Service API ===
-To be filled soon: a Python transport/storage API for managing the placement service catalogue and storage nodes.
-== Roadmap ==
-=== Phase 1: Replication and Sharding ===
-In the first iteration of this project, the goal is to provide an easy way to replicate and shard data across dynamically allocated storage nodes. The required features are:
-* Catalogue + management API
-* Storage allocation + management API: static weights
-* Policy engine: being able to assign dedicated storage to particular tenants
-* Local catalogue cache + push consistency
-=== Phase 2: Migration, Dynamism, and Deletion ===
-Phase 2 introduces the ability to migrate data (read: Marconi data, queues + messages) from one storage node to another. The ability to remove entries from the catalog and also schedule them to be removed from storage is considered. Finally, dynamically controlled storage allocation is introduced for more hands-off operation. In sum:
-* Migration + migration API: move data from storage node to node, set storage as read-only
-* Deletion: remove data from catalog and from storage nodes
-* Dynamism: monitor storage nodes and adjust weights based on node capacity and load
-=== Phase 3: Data Affinity and Generalization ===
-This phase optimizes and generalizes placement service. Conceptually, there's no reason placement service should serve only the needs of Marconi. Requirements:
-* Data affinity: attempt to cache particular storage connections on worker nodes where certain data appears more often
-    - Useful for reducing the number of cached connections
-* Generalization: make the placement service usable by other services
-=== Phase N: ??? ===
-Because the future is open, and predicting beyond this point is very difficult.
-== Ideas Under Consideration ==
-==== Periodic Refresh ====
-On a separate Marconi "thread", poll the catalogue service periodically (say, every 10 seconds). This actor is responsible for updating the cache. It queries the catalogue service and looks for changes.
-To enable this, migrations are only allowed a granularity of 5 minutes. This helps avoid race conditions on a catalogue resource, since the migration itself triggers a state change from active to migrating for a particular queue.
-==== Push Refresh ====
-This approach does away with time and puts the responsibility of invalidating caches on the placement service. All Marconi nodes must maintain a listen port connected to the placement service, and whenever a migration occurs, Marconi nodes receive updates on queues that are being affected.
+=== Implementation ===
-=== Deletions ===
+==== Needs Review ====
-Deletions take priority over migrations. If a migration is in progress for Q1, and a request to delete Q1 is made, then all messages for Q1 are deleted both from the initial storage location and the destination storage location. The migration is cancelled.
+* Proxy (partition, catalogue, queues handling): https://review.openstack.org/#/c/43909/
+* Proxy (v1, health): https://review.openstack.org/#/c/44356/
+* Proxy (forward the rest of the routes): https://review.openstack.org/#/c/44364/
-=== Dynamic Weight Management ===
+==== To Do ====
-The operator of the placement service can manually determine the weights of the storage locations to bootstrap the system. However, in the future, it would be preferred to dynamically update these weights based on host parameters such as:
+* Hierarchical caching: store data in authoritative store (mongo replicaset) on write operations, and cache locally using Redis instance, hitting authoritative only on failed lookups
+* Benchmarking
+* Unit tests
+* Functional tests
+* Configuration
+* Catalogue and partition registry regeneration
-* Storage location CPU load
+=== Deployment ===
-* Storage location remaining capacity
-This adds a level of intelligence to the placement storage layer that makes maintenance a more hands-free experience.
+* Bring up authoritative replicaset
+* Bring up redis-server on each box
+* launch marconi.proxy.app:app using a WSGI/HTTP server
-=== Connection Pooling ===
+== More Ideas/Deprecated ==
-To be filled soon: caching strategy for storage connections at the Marconi worker level
+[[Deprecated]]

Difference between revisions of "Zaqar/bp/placement-service"

Latest revision as of 18:42, 7 August 2014

Contents

Overview

Transparency

Terminology

Reference Deployment: Smart Proxy and Partition as a Unit

Partitions

Smart Proxy

Migration Strategy

Advantages

Disadvantages

Current State

Concepts

Partitions

Catalogue

API

Implementation

Needs Review

To Do

Deployment

More Ideas/Deprecated