a7c41a8893
Github is just a mirror of the OpenStack git-repo. Changed from Github to OpenStack git url wherever possible. Change-Id: I7941ef86967de4efe7f23ff9fb11ec86c793901e
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This work is licensed under a Creative Commons Attribution 3.0 Unported
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License.
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http://creativecommons.org/licenses/by/3.0/legalcode
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======================
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High-Availability
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======================
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Kolla deployments will be maturing from evaluation-level environments to
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highly available and scalable environments supporting production
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applications and services. The goal for Kolla HA is to provide active/active,
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highly available and independently scalable OpenStack services. This spec
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focuses on providing high availability within a single Kolla-based
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OpenStack deployment.
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Problem description
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===================
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OpenStack consists of several core and infrastructure services. The services
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work in concert to provide a cloud computing environment. By default, the
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services are single points of failure and are unable to scale beyond a single
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instance.
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Use cases
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---------
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1. Fail any one or a combination of OpenStack core and/or infrastructure
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services and the overall system continues to operate.
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2. Scale any one or a combination of OpenStack core and/or infrastructure
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services without any interruption of service.
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Proposed change
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===============
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The spec consists of the following components for providing high
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availability and scalability to Kolla-based OpenStack services:
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MySQL Galera: A synchronous multi-master database clustering technology
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for MySQL/InnoDB databases that includes features such as:
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* Synchronous replication
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* Active/active multi-master topology
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* Read and write to any cluster node
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* True parallel replication, on row level
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* Direct client connections, native MySQL look & feel
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* No slave lag or integrity issues
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**Note:** Although Galera supports an active/active multi-master topology
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with multiple active writers, a few OpenStack services cause database
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deadlocks in this scenario. This is because these services use the
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SELECT... FOR UPDATE SQL construct, even though it's [documented][]
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not to. It appears that [Nova][] has recently fixed the issue and
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[Neutron][] is making progress
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[documented]: https://github.com/openstack/nova/blob/da59d3228125d7e7427c0ba70180db17c597e8fb/nova/openstack/common/db/sqlalchemy/session.py#L180-196
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[Nova]: http://specs.openstack.org/openstack/nova-specs/specs/kilo/approved/lock-free-quota-management.html
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[Neutron]: https://bugs.launchpad.net/neutron/+bug/1364358 https://bugs.launchpad.net/neutron/+bug/1331564
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Testing should be performed as part of the Galera implementation to verify
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whether the recent patches address the deadlock issues. If so, multiple
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active/active writers can exist within the Galera cluster. If not,then
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the initial implementation should continue using the well documented
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work around until the issue is completely resolved.
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Several OpenStack services utilize a message queuing system to send and
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receive messages between software components. The intention of this
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spec is to leverage RabbitMQ as the messaging system since it is most
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commonly used within the OpenStack community. Clustering and RabbitMQ
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Mirrored Queues provide active/active and highly scalable message
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queuing for OpenStack services.
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* RabbitMQ Clustering: If the RabbitMQ broker consists of a single node,
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then a failure of that node will cause downtime, temporary
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unavailability of service, and potentially loss of messages. A cluster
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of RabbitMQ nodes can be used to construct the RabbitMQ broker.
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Clustering RabbitMQ nodes are resilient to the loss of individual nodes
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in terms of overall availability of the service. All data/state
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required for the operation of a RabbitMQ broker is replicated across
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all nodes, for reliability and scaling. An exception to this are message
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queues, which by default reside on the node that created them, though
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they are visible and reachable from all nodes.
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* RabbitMQ Mirrored Queues: While exchanges and bindings survive the loss
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of individual nodes, message queues and their messages do not. This is
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because a queue and its contents reside on exactly one node, thus the
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loss of a node will render its queues unavailable. To solve these
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various problems, RabbitMQ has developed active/active high-availability
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for message queues. This works by allowing queues to be mirrored on
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other nodes within a RabbitMQ cluster. The result is that should one
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node of a cluster fail, the queue can automatically switch to one of the
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mirrors and continue to operate, with no unavailability of service. This
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solution still requires a RabbitMQ Cluster, which means that it will not
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cope seamlessly with network partitions within the cluster and, for that
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reason, is not recommended for use across a WAN (though of course,
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clients can still connect from as near and as far as needed).
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HAProxy provide load-balancing between clients and OpenStack API Endpoints.
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HAProxy is a free, very fast and reliable software solution offering high
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availability, load balancing, and proxying for TCP and HTTP-based
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applications. HAProxy implements an event-driven, single-process model
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which enables support for a high number of simultaneous connections.
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Memcached is required by nova-consoleauth, Horizon and Swift Proxy to store
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ephemeral data such as tokens. Memcached does not support typical forms of
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redundancy such as clustering. However, OpenStack services can support more
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than one Memcached instance by configuring multiple hostnames or IP addresses.
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The Memcached client implements hashing to balance objects among the
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instances. Failure of a Memcached instance only impacts a portion of the objects
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and the client automatically removes it from the list of instances.
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An Example configuration with two hosts:
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'memcached_servers = kolla1:11211,kolla2:11211'
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Memcached does not implement authentication and therefore is insecure.
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This risk is reduced in default deployments because Memcached is not exposed
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outside of localhost. Since deploying Memcahced in a highly-available manner
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requires exposing Memcached outside of localhost, precautions should be taken
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to reduce this risk.
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Keepalived is routing software that provides simple and robust facilities
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for load-balancing Linux systems. Keepalived will track the HAProxy process
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and failover/back between HAProxy instances with minimal service interruption.
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Keepalived implements the Virtual Router Redundancy Protocol (VRRP).
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VRRP creates virtual routers, which are an abstract representation of
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multiple routers, i.e. master and backup routers, acting as a group.
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The default gateway of a participating host is assigned to the
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virtual router instead of a physical router. If the physical router that
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is routing packets on behalf of the virtual router fails, another physical
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router is selected to automatically replace it. The physical router that
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is forwarding packets at any given time is called the master router.
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Neutron: HAProxy will provide high-availability and scalability to the
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neutron-server service by load-balancing traffic across multiple instances
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of the service. RabbitMQ clustering and mirrored queues will be used to
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provide high-availability and scalability for RPC messaging among Neutron
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components. Galera will provide high-availability and scalability to Neutron
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persistent data. Multiple Neutron Agents will be deployed across separate
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nodes. [Multiple L3/DHCP Agents][] will be assigned per tenant network to
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provide network high-availability for tenant networks.
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[Multiple L3/DHCP Agents]: https://wiki.openstack.org/wiki/Neutron/L3_High_Availability_VRRP
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Glance: Glance can use different back-ends to store OpenStack images. Examples
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include Swift, Ceph, Cinder and the default filesystem back-end. Although
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it is not required, it is highly recommended to use a backend that is highly
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scalable and fault-tolerant.
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Just as with the rest of the OpenStack API's, HAProxy and Keepalived can
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provide high-availability and scalability to the Glance API and Registry
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endpoints.
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Swift: Multiple Swift Proxy services can be used to provide high
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availability to the Swift object, account and container storage rings.
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Standard Swift replication provides high-availability to data stored within
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a Swift object storage system. The replication processes compare local data
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with each remote copy to ensure they all contain the latest version. Object
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replication uses a hash list to quickly compare subsections of each
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partition. Container and account replication use a combination of
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hashes and shared high water marks.
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Cinder: As with other stateless services, HAProxy can provide high
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availability and scalability to cinder-api. RabbitMQ clustering and mirrored
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queues can provide high-availability and scalability for RPC messaging among
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Cinder services. At the time of this writing, the only Cinder backend
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supported is LVM. LVM can be made [highly-available][] or a new Cinder
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backend, such as [Ceph][], can be added to Kolla which supports high
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availability and scalability for tenant-facing block storage services.
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Due to limitations described [here][], the Cinder volume manager can
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not be reliably deployed in an active/active or active/passive fashion.
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[highly-available]: https://access.redhat.com/documentation/en-US/Red_Hat_Enterprise_Linux/6/html/Cluster_Administration/ap-ha-halvm-CA.html
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[Ceph]: http://ceph.com/
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[here]: https://bugs.launchpad.net/cinder/+bug/1322190
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In general, the Kolla HA environment looks like:
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Security impact
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---------------
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Keystone UUID vs PKI tokens. Tokens are used as a mechanism to
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authenticate API requests of users. Keystone supports UUID and
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PKI token formats. PKI tokens provide better security, but are more
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difficult to deploy in an active/active manner. Therefore,
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it is recommended to start with UUID tokens and add PKI tokens
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in a future iteration.
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Performance Impact
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------------------
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The proposed high-availability spec should increase the performance of
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Kolla-based OpenStack clouds. A slight performance decrease can be expected due
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to the additional hop introduced by the load-balancing layer. However, the
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additional latency introduced by this layer is insignificant. Since this layer
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provides intelligent load-balancing of services, improved performance can be
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expected for services under moderate-to-heavy load. Without the intelligence
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provided by the load-balancing layer, overloaded services can become degraded
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and a decrease in performance can be expected.
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Performance tests should be conducted for the following scenarios to validate
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and/or improve the HA spec:
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1. The HA environment is functioning as expected.
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2. One or more API services are in a failed state.
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3. One or more Galera instances are in a failed state.
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4. One or more RabbitMQ Brokers are in a failed state.
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5. Adding services to/from the HA environment.
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Implementation
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==============
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Generally, the implementation should start off simple and add capabilities
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through development iterations. The implementation can be organized as follows:
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1. Multi-node: In order to implement HA, Kolla must first support being deployed
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to multiple hosts.
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2. Database: Implement a Galera container image that follows best practices
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used by existing Kolla images. Use existing tools to manage the image,
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the configuration file(s) and deployment of the Galera service in a highly
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available and scalable fashion.
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3. RabbitMQ: Implement a RabbitMQ container image that follows best practices
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used by existing Kolla images. Use existing tools to manage the image,
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the configuration file(s) and deployment of the Galera service in a highly
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available and scalable fashion.
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4. APIs: Implement HAProxy/Keepalived container images that follow best practices
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used by existing Kolla images. Use existing tools to manage the image,
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the configuration file(s) and deployment of the Galera service in a highly
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available and scalable fashion.
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5. Update Existing Images: Update existing container images with the necessary
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configuration to support HA. For example, OpenStack services should use the
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Virtual IP of the Galera cluster to communicate with the DB instead of an
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IP assigned to an individual DB instance.
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6. Update Existing Deployment Automation: Update automation scripts, playbooks,
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etc to support additional container images, configuration parameters, etc.
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introduced by the HA components.
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7. Testing: Follow the guidance provided in the performance impact section to
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test how the OpenStack environment responds and performances in various failure
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scenarios.
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Assignee(s)
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-----------
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Primary assignee:
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kolla maintainers
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Work Items
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----------
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1. Deploy existing Kolla across multiple physical hosts.
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2. Create containers for HAProxy, Keepalived.
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3. Add Galera Support to existing MariaDB container set.
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4. Add clustering/mirrored queue support to RabbitMQ container set.
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5. Add L3/DHCP agent HA to existing Neutron agent container set.
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6. Create Swift containers.
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7. Add/configure the Glance backend to support HA and scalability.
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8. Add/configure HAproxy for services, like keystone or horizon.
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Testing
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=======
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We don't know how to test multi-node deployment in CI/CD because
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we are unsure whether the gating system allows for deployments
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consisting of more than one VM. As a result, we will rely on manual
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testing of the solution as a starting point.
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Documentation Impact
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====================
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The integration-guide.md should be updated to include additional K/V
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pairs introduced by HA. Additionally, a document should be developed
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explaining how to deploy and configure Kolla in a highly-available
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fashion.
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References
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==========
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* [VRRP] http://en.wikipedia.org/wiki/Virtual_Router_Redundancy_Protocol
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