# Gerrit Multi-Site Plugin Design

This document collects and organizes thoughts about
the design of the Gerrit multi-site plugin,  supporting the definition of the
[implementation roadmap](#next-steps-in-the-road-map).

It first presents background for the problems the plugin will address and
the tools currently available in the Gerrit ecosystem that support the
solution. It then lays out an overall roadmap for implementing support for Gerrit
multi-site, and a snapshot of the current status of the design including associated
limitations and constraints.

## Approaches to highly scalable and available Gerrit

Companies that adopt Gerrit as the center of their development and review
pipeline often have the requirement to be available on a 24/7 basis. This requirement
may extend across large and geographically distributed teams in different continents.

Because of constraints defined by the [CAP theorem](https://en.wikipedia.org/wiki/CAP_theorem)
designing a performant and scalable solution is a real challenge.

### Vertical scaling and high availability

Vertical scaling is one of the options to support a high load and a large number
of users.  A powerful server with multiple cores and sufficient RAM to
potentially fit the most frequently used repositories simplifies the design and
implementation of the system. The relatively reasonable cost of hardware and availability
of multi-core CPUs make this solution highly attractive to some large
Gerrit setups. Further, the central Gerrit server can be duplicated with an
active/passive or active/active high availability configuration with the storage of the
Git repositories shared across nodes through dedicated fibre-channel lines or
SANs.

This approach can be suitable for mid to large-sized Gerrit installations where
teams are co-located or connected via high-speed dedicated networks. However,
when teams are located on opposite sides of the planet, even at the speed of light
the highest theoretical fire-channel direct connection can be limiting.  For example,
from San Francisco to Bangalore the theoretical absolute minimum latency is 50
msec. In practice, however, it is often around 150/200 msec in the best case
scenarios.

### Horizontal scaling and multi-site

In the alternate option, horizontal scaling, the workload is spread
across several nodes, which are distributed to different locations.
For our teams in San Francisco and Bangalore, each accesses a
set of Gerrit masters located closer to their geographical location, with higher
bandwidth and lower latency. (To control operational cost from the proliferation of
servers, the number of Gerrit masters can be scaled up and down on demand.)

This solution offers a higher level of scalability and lower latency across locations,
but it requires a more complex design.

### Multi-master and multi-site, the best of both worlds

The vertical and horizontal approaches can be combined to achieve
both high performance on the same location and low latency across
geographically distributed sites.

Geographical locations with larger teams and projects can have a bigger
Gerrit server in a high availability configuration, while locations with
less critical service levels can use a lower-spec setup.

## Focus of the multi-site plugin

The  multi-site plugin enables the OpenSource version of Gerrit
Code Review to support horizontal scalability across sites.

Gerrit has already been deployed in a multi-site configuration at
[Google](https://www.youtube.com/watch?v=wlHpqfnIBWE) and in a multi-master fashion
at [Qualcomm](https://www.youtube.com/watch?v=X_rmI8TbKmY). Both implementations
include fixes and extensions that are tailored to the specific
infrastructure requirements of each company's global networks. Those
solutions may or may not be shared with the rest of the OpenSource Community.
Specifically, Google's deployment is proprietary and not suitable for any
environment outside Google's data-centers.  Further, in
Qualcomm's case, their version of Gerrit is a fork of v2.7.

In contrast, the multi-site plugin is based on standard OpenSource components and
is deployed on a standard cloud environment. It is currently used in a multi-
master and multi-site deployment on GerritHub.io, serving two continents (Europe
and North America) in a high availability setup on each site.

# The road to multi-site

The development of the multi-site support for Gerrit is complex and thus has
been deliberately broken down into incremental steps. The starting point is a
single Gerrit master deployment, and the end goal is a fully distributed set of
cooperating Gerrit masters across the globe.

1. 1x master / single location.
2. 2x masters (active/standby) / single location - shared disks
3. 2x masters (active/passive) / single location - shared disks
4. 2x masters (active RW/active RO) / single location - shared disks
5. 2x masters (active RW/active RO) / single location - separate disks
6. 2x masters (active RW/active RO) / active + disaster recovery location
7. 2x masters (active RW/active RO) / two locations
8. 2x masters (active RW/active RW) sharded / two locations
9. 3x masters (active RW/active RW) sharded with auto-election / two locations
10. Multiple masters (active RW/active RW) with quorum / multiple locations

The transition between steps requires not only an evolution of the Gerrit
setup and the set of plugins but also the implementation of more mature methods to
provision, maintain and version servers across the network. Qualcomm has
pointed out that the evolution of the company culture and the ability to consistently
version and provision the different server environments are winning features of
their multi-master setup.

Google is currently running at Stage #10.  Qualcomm is at Stage #4 with the
difference that both masters are serving RW traffic, which is possible because the specifics
of their underlying storage, NFS and JGit implementation allows concurrent
locking at the filesystem level.

## TODO: Synchronous replication
Consider also synchronous replication for cases like 5, 6, 7... in which
cases a write operation is only accepted if it is synchronously replicated to the
other master node(s). This would provide 100% loss-less disaster recovery support. Without
synchronous replication, when the RW master crashes, losing data, there could
be no way to recover missed replications without soliciting users who pushed the commits
in the first place to push them again. Further, with synchronous replication
the RW site has to "degrade" to RO mode when the other node is not reachable and
synchronous replications are not possible.

We must re-evaluate the useability of the replication plugin for supporting
synchronous replication. For example, the replicationDelay doesn't make much
sense in the synchronous case. Further, the rescheduling of a replication due
to an in-flight push to the same remote URI also doesn't make much sense as we
want the replication to happen immediately. Further, if the ref-update of the
incoming push request has to be blocked until the synchronous replication
finishes, the replication plugin cannot even start a replication as there is no
ref-updated event yet. We may consider implementing the synchronous
replication on a lower level. For example have an "pack-received" event and
then simply forward that pack file to the other site. Similarly for the
ref-updated events, instead of a real git push, we could just forward the
ref-updates to the other site.

## History and maturity level of the multi-site plugin

This plugin expands upon the excellent work on the high-availability plugin,
introduced by Ericsson for implementing mutli-master at Stage #4. The git log history
of this projects still shows the 'branching point' where it started.

The current version of the multi-site plugin is at Stage #7, which is a pretty
advanced stage in the Gerrit multi-master/multi-site configuration.

Thanks to the multi-site plugin, it is now possible for Gerrit data to be
available in two separate geo-locations (e.g. San Francisco and Bangalore),
each serving local traffic through the local instances with minimum latency.

### Why another plugin from a high availability fork?

You may be questioning the reasoning behind
creating yet another plugin for  multi-master, instead of maintaining
a single code-base with the high-availability plugin. The choice stems from
the differing design considerations to address scalabiilty, as discussed above
for the vertical (single site) and horizonal (multi-site) approaches.

In theory, one could keep a single code-base to manage both approaches, however the
result would be very complicated and difficult to configure and install.
Having two more focussed plugins, one for high availability and another for
multi-site, allows us to have a simpler, more usable experience, both for developers
of the plugin and for the Gerrit administrators using it.

### Benefits

There are some advantages in implementing multi-site at Stage #7:

- Optimal latency of the read-only operations on both sites, which constitutes around 90%
  of the Gerrit traffic overall.

- High SLA (99.99% or higher, source: GerritHub.io) can be achieved by
  implementing both high availability inside each local site, and automatic
  catastrophic failover between the two sites.

- Access transparency through a single Gerrit URL entry-point.

- Automatic failover, disaster recovery, and leader re-election.

- The two sites have local consistency, with eventual consistency globally.

### Limitations

The current limitations of Stage #7 are:

- **Single RW site**: Only the RW site can accept modifications on the
  Git repositories or the review data.

- **Supports only two sites**:
  One could, potentially, support more sites, but the configuration
  and maintenance efforts are more than linear to the number of nodes.

- **Single point of failure:** The switch between the RO to RW sites is managed by a unique decision point.

- **Lack of transactionality**:
  Data written to one site is acknowledged before its replication to the other location.

- **Requires Gerrit v2.16 or later**: Data conisistency requires a server completely based on NoteDb.
  If you are not familiar with NoteDb, please read the relevant
  [section in the Gerrit documentation](https://gerrit-documentation.storage.googleapis.com/Documentation/2.16.5/note-db.html).

### Example of multi-site operations

Let's suppose the RW site is San Francisco and the RO site Bangalore. The
modifications of data will always come to San Francisco and flow to Bangalore
with a latency that can be between seconds and minutes, depending on
the network infrastructure between the two sites. A developer located in
Bangalore will always see a "snapshot in the past" of the data, both from the
Gerrit UI and on the Git repository served locally.  In contrast, a developer located in
San Francisco will always see the "latest and greatest" of everything.

Should the central site in San Francisco become unavailable for a
significant period of time, the Bangalore site will take over as the RW Gerrit
site. The roles will then be inverted.
People in San Francisco will be served remotely by the 
Bangalore server while the local system is down. When the San Francisco site
returns to service, and passes the "necessary checks", it will be re-elected as the
main RW site.

# Plugin design

This section goes into the high-level design of the current solution, lists
the components involved, and describes how the components interact with each other.

## What is replicated across Gerrit sites

There are several distinct classes of information that have to be kept
consistent across different sites in order to guarantee seamless operation of the
distributed system.

- **Git repositories**: They are stored on disk and are the most important
information to maintain.  The repositories store the following data:

  * Git BLOBs, objects, refs and trees.

  * NoteDb, including Groups, Accounts and review data

  * Project configurations and ACLs

  * Project submit rules

- **Indexes**: A series of secondary indexes to allow search and quick access
  to the Git repository data. Indexes are persistent across restarts.

- **Caches**: A set of in-memory and persisted data designed to reduce CPU and disk
  utilization and to improve performance.

- **Web Sessions**: Define an active user session with Gerrit, used to reduce
  load to the underlying authentication system.
  Sessions are stored by default on the local filesystem in an H2 table but can
  be externalized via plugins, like the WebSession Flatfile.

To achieve a Stage #7 multi-site configuration, all the above information must
be replicated transparently across sites.

## High-level architecture

The multi-site solution described here depends upon the combined use of different
components:

- **multi-site libModule**: exports interfaces as DynamicItems to plug in specific
implementation of `Brokers` and `Global Ref-DB` plugins.

- **broker plugin**: an implementation of the broker interface, which enables the
replication of Gerrit _indexes_, _caches_,  and _stream events_ across sites.
When no specific implementation is provided, then the [Broker Noop implementation](#broker-noop-implementation)
then libModule interfaces are mapped to internal no-ops implementations.

- **Global Ref-DB plugin**: an implementation of the Global Ref-DB interface,
which enables the detection of out-of-sync refs across gerrit sites.
When no specific implementation is provided, then the [Global Ref-DB Noop implementation](#global-ref-db-noop-implementation)
then libModule interfaces are mapped to internal no-ops implementations.

- **replication plugin**: enables the replication of the _Git repositories_ across
  sites.

- **web-session flat file plugin**: supports the storage of _active sessions_
  to an external file that can be shared and synchronized across sites.

- **health check plugin**: supports the automatic election of the RW site based
  on a number of underlying conditions of the data and the systems.

- **HA Proxy**: provides the single entry-point to all Gerrit functionality across sites.

The interactions between these components are illustrated in the following diagram:

![Initial Multi-Site Plugin Architecture](images/architecture-first-iteration.png)

## Implementation Details

### Multi-site libModule
As mentioned earlier there are different components behind the overarching architecture
of this solution of a distributed multi-site gerrit installation, each one fulfilling
a specific goal. However, whilst the goal of each component is well-defined, the
mechanics on how each single component achieves that goal is not: the choice of which
specific message broker or which Ref-DB to use can depend on different factors,
such as scalability, maintainability, business standards and costs, to name a few.

For this reason the multi-site component is designed to be explicitly agnostic to
specific choices of brokers and Global Ref-DB implementations, and it does
not care how they, specifically, fulfill their task.

Instead, this component takes on only two responsibilities:

* Wrapping the GitRepositoryManager so that every interaction with git can be
verified by the Global Ref-DB plugin.

* Exposing DynamicItem bindings onto which concrete _Broker_ and a _Global Ref-DB_
plugins can register their specific implementations.
When no such plugins are installed, then the initial binding points to no-ops.

* Detect out-of-sync refs across multiple gerrit sites:
Each change attempting to mutate a ref will be checked against the Ref-DB to
guarantee that each node has an up-to-date view of the repository state.

### Message brokers plugin
Each gerrit node in the cluster needs to be informed and inform all other nodes
about fundamental events, such as indexing of new changes, cache evictions and
stream events. This component will provide a specific pub/sub broker implementation
that is able to do so.

When provided, the message broker plugin will override the dynamicItem binding exposed
by the multi-site module with a specific implementation, such as Kafka, RabbitMQ, NATS, etc.

#### Broker Noop implementation
The default `Noop` implementation provided by the `Multi-site` libModule does nothing
upon publishing and producing events. This is useful for setting up a test environment
and allows multi-site library to be installed independently from any additional
plugins or the existence of a specific broker installation.
The Noop implementation can also be useful when there is no need for coordination
with remote nodes, since it avoids maintaining an external broker altogether:
for example, using the multi-site plugin purely for the purpose of replicating the Git
repository to a disaster-recovery site and nothing else.

### Global Ref-DB plugin
Whilst the replication plugin allows the propagation of the Git repositories across
sites and the broker plugin provides a mechanism to propagate events, the Global
Ref-DB ensures correct alignment of refs of the multi-site nodes.

It is the responsibility of this plugin to store atomically key/pairs of refs in
order to allow the libModule to detect out-of-sync refs across multi sites.
(aka split brain).  This is achieved by storing the most recent `sha` for each
specific mutable `refs`, by the usage of some sort of atomic _Compare and Set_ operation.

We mentioned earlier the [CAP theorem](https://en.wikipedia.org/wiki/CAP_theorem),
which in a nutshell states that a distributed system can only provide two of these
three properties: _Consistency_, _Availability_ and _Partition tolerance_: the Global
Ref-DB helps achieving _Consistency_ and _Partition tolerance_ (thus sacrificing
Availability).

See [Prevent split brain thanks to Global Ref-DB](#prevent-split-brain-thanks-to-global-ref-db)
For a thorough example on this.

When provided, the Global Ref-DB plugin will override the dynamicItem binding
exposed by the multi-site module with a specific implementation, such as Zoekeeper,
etcd, MySQL, Mongo, etc.

#### Global Ref-DB Noop implementation
The default `Noop` implementation provided by the `Multi-site` libModule accepts
any refs without checking for consistency. This is useful for setting up a test environment
and allows multi-site library to be installed independently from any additional
plugins or the existence of a specific Ref-DB installation.

### Eventual consistency on Git, indexes, caches, and stream events

The replication of the Git repositories, indexes, cache and stream events happen
on different channels and at different speeds. Git data is typically larger than
meta-data and has higher latency than reindexing, cache evictions or stream
events. This means that when someone pushes a new change to Gerrit on one site,
the Git data (commits, BLOBs, trees, and refs) may arrive later than the
associated reindexing or cache eviction events.

It is, therefore, necessary to handle the lack of synchronization of those
channels in the multi-site plugin and reconcile the events at the destinations.

The solution adopted by the multi-site plugin supports eventual consistency at
rest at the data level, thanks to the following two components which:

* **Identify not-yet-processable events**: 
A mechanism to recognize _not-yet-processable events_ related to data not yet
available (based on the timestamp information available on both the metadata
update and the data event)

* **Queue not-yet-processable events**: 
A queue of *not-yet-processable events* and an *asynchronous processor*
to check if they became processable. The system also is configured to discard
events that have been in the queue for too long.

### Avoid event replication loops

Stream events are wrapped into an event header containing a source identifier.
Events originated by the same node in the broker-based channel are silently
dropped so that they do not replicate multiple times.

Gerrit has the concept of **server-id** which, unfortunately, does not help
solve this problem because all the nodes in a Gerrit cluster must have the same
server-id to allow interoperability of the data stored in NoteDb.

The multi-site plugin introduces a new concept of **instance-id**, which is a UUID
generated during startup and saved into the data folder of the Gerrit site. If
the Gerrit site is cleared or removed, a new id is generated and the multi-site
plugin will start consuming all events that have been previously produced.

The concept of the instance-id is very useful. Since other plugins could benefit
from it, it will be the first candidate to move into the Gerrit core,
generated and maintained with the rest of the configuration.  Then it can be
included in **all** stream events, at which time the multi-site plugin's 
"enveloping of events" will become redundant.

### Manage failures

The broker based solutions improve the resilience and scalability of the system.
But there is still a point of failure: the availability of the broker itself. However,
using the broker does allow having a high-level of redundancy and a multi-master
/ multi-site configuration at the transport and storage level.

At the moment, the acknowledge level for publication can be controlled via
configuration and allows to tune the QoS of the publication process. Failures
are explicitly not handled at the moment; they are just logged as errors.
There is no retry mechanism to handle temporary failures.

### Avoid Split Brain

The current solution of multi-site at Stage #7 with asynchronous replication
risks that the system will reach a Split Brain situation (see
[issue #10554](https://bugs.chromium.org/p/gerrit/issues/detail?id=10554)).

#### The diagram below illustrates the happy path with crash recovery returning the system to a healthy state.

![Healthy Use Case](images/git-replication-healthy.png)

In this case we are considering two different clients each doing a `push` on top of
the same reference. This could be a new commit in a branch or the change of an existing commit.

At `t0`: both clients see the status of `HEAD` being `W0`. `Instance1` is the
RW node and will receive any `push` request. `Instance1` and `Instance2` are in sync
at `W0`.

At `t1`: `Client1` pushes `W1`. The request is served by `Instance1` which acknowledges it
and starts the replication process (with some delay).

At `t2`: The replication operation is completed. Both instances are in a consistent state
`W0 -> W1`. `Client1` shares that state but `Client2` is still behind.

At `t3`: `Instance1` crashes.

At `t4`: `Client2` pushes `W2` which is still based on `W0` (`W0 -> W2`).
The request is served by `Instance2` which detects that the client push operation was based
on an out-of-date starting state for the ref. The operation is refused. `Client2`
synchronises its local state (e.g. rebases its commit) and pushes `W0 -> W1 -> W2`.
That operation is now considered valid, acknowledged and put in the replication queue until
`Instance1` becomes available.

At `t5`: `Instance1` restarts and is replicated at `W0 -> W1 -> W2`

#### The Split Brain situation is illustrated in the following diagram.

![Split Brain Use Case](images/git-replication-split-brain.png)

In this case the steps are very similar except that `Instance1` fails after acknowledging the
push of `W0 -> W1` but before having replicated the status to `Instance2`.

When in `t4` `Client2` pushes `W0 -> W2` to `Instance2`, this is considered a valid operation.
It gets acknowledged and inserted in the replication queue.

At `t5` `Instance1` restarts. At this point both instances have pending replication
operations. They are executed in parallel and they bring the system to divergence.

Root causes of the Split Brain problem:
- The RW node acknowledges a `push` operation before __all__ replicas are fully in sync.
- The other instances are not aware that they are out of sync.

Two possible approaches to solve the Split Brain problem:

- **Synchronous replication**: In this case the system would behave essentially as the
_happy path_ diagram shown above and would solve the problem by operating on the first of the causes,
at the expense of performance, availability and scalability. It is a viable and simple solution
for two nodes set up with an infrastructure allowing fast replication.

- **Centralise the information about the latest status of mutable refs**: This would operate
on the second cause. That is, it would allow instances to realise that _they are
not in sync on a particular ref_ and refuse any write operation on that ref.
The system could operate normally on any other ref and also would impose no
limitation in other functions such as, Serving the GUI, supporting reads, accepting new
changes or patch-sets on existing changes. This option is discussed in further
detail below.

**NOTE**: The two options are not exclusive.

#### Prevent split brain thanks to Global Ref-DB

The above scenario can be prevented by using an implementation of the Global Ref-DB
interface, which will operate as follows:

![Split Brain Prevented](images/git-replication-split-brain-detected.png)

The difference, in respect to the split brain use case, is that now, whenever a change of a
_mutable ref_ is requested, the Gerrit server verifies with the central RefDB that its
status __for this ref__ is consistent with the latest cluster status. If that is true
the operation succeeds. The ref status is atomically compared and set to the new status
to prevent race conditions.

In this case `Instance2` enters a Read Only mode for the specific branch
until the replication from `Instance1` is completed successfully. At this point write
operations on the reference can be recovered.
If `Client2` can perform the `push` again vs `Instance2`, the server recognises that
the client status needs an update, the client will `rebase` and `push` the correct status.

__NOTE__:
This implementation will prevent the cluster to enter split brain but might result in a
set of refs in Read Only state across all the cluster if the RW node is failing after having
sent the request to the Ref-DB but before persisting this request into its `git` layer.

#### Geo located Gerrit master election

Once you go multi-site multi-master you can improve the latency of your calls by
serving traffic from the closest server to your user.

Whether you are running your infrastructure in the cloud or on premise you have different solutions you can look at.

##### AWS

Route53 AWS DNS service offers the opportunity of doing [Geo Proximity](https://docs.aws.amazon.com/Route53/latest/DeveloperGuide/routing-policy.html#routing-policy-geoproximity)
routing using [Traffic Flow](https://docs.aws.amazon.com/Route53/latest/DeveloperGuide/traffic-flow.html).

Traffic flow is a tool which allows the definition of traffic policies and rules via a UI. Traffic rules are of different types, among which *Geoproximity* rules.

When creating geoproximity rules for your resources you can specify one of the following values for each rule:

* If you're using AWS resources, the AWS Region that you created the resource in
* If you're using non-AWS resources, the latitude and longitude of the resource.

This allows you to have an hybrid cloud-on premise infrastructure.

You can define quite complex failover rules to ensure high availability of your system ([here](https://pasteboard.co/ILFSd5Y.png) an example).

Overall the service provided is pretty much a smart reverse-proxy, if you want more
complex routing strategies you will still need a proper Load Balancer.

##### GCE

GCE [doesn't offer](https://cloud.google.com/docs/compare/aws/networking#dns) a Geographical based routing, but it implicitly has geo-located DNS entries
when distributing your application among different zones.

The Load Balancer will balance the traffic to the [nearest available instance](https://cloud.google.com/load-balancing/docs/backend-service#backend_services_and_regions)
, but this is not configurable and the app server has to be in GC.

Hybrid architectures are supported but would make things more complicated,
hence this solution is probably worthy only when the Gerrit instances are running in GC.

##### On premise

If you are going for an on premise solution and using HAProxy as Load Balancer,
it is easy to define static ACL based on IP ranges and use them to route your traffic.

This [blogpost](https://icicimov.github.io/blog/devops/Haproxy-GeoIP/) explains how to achieve it.

On top of that, you want to define a DNS entry per zone and use the ACLs you just defined to
issue redirection of the calls to most appropiate zone.

You will have to add to your frontend definition your redirection strategy, i.e.:

```
http-request redirect code 307 prefix https://review-eu.gerrithub.io if acl_EU
http-request redirect code 307 prefix https://review-am.gerrithub.io if acl_NA
```

# Next steps in the roadmap

## Step-1: Fill the gaps in multi-site Stage #7 implementation:

- **Detection of a stale site**: The health check plugin has no awareness that one
  site that can be "too outdated" because it is still technically "healthy." A
  stale site needs to be put outside the balancing and all traffic needs to go
  to the more up-to-date site.

- **Web session replication**: This currently must be implemented at the filesystem level
  using rsync across sites.  This is problematic because of the delay it
  introduces. Should a site fail, some of the users may lose their sessions
  because the rsync was not executed yet.

- **Index rebuild in case of broker failure**: In the case of a catastrophic
  failure at the broker level, the indexes of the two sites will be out of
  sync. A mechanism is needed to recover the situation
  without requiring the reindex of both sites offline, since that could take
  as much as days for huge installations.

- **Git/SSH redirection**: Local users who rely on Git/SSH protocol are not able
  to use the local site for serving their requests, because HAProxy is not
  able to differentiate the type of traffic and, thus, is forced always to use the
  RW site, even though the operation is RO.

## Step-2: Move to multi-site Stage #8.

- Auto-reconfigure HAProxy rules based on the projects sharding policy

- Serve RW/RW traffic based on the project name/ref-name.

- Balance traffic with "locally-aware" policies based on historical data