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Historically, Nova has depended on a single logical database and message queue
that all nodes depend on for communication and data persistence. This becomes
an issue for deployers as scaling and providing fault tolerance for these
systems is difficult.
We have an experimental feature in Nova called "cells", hereafter referred to
as "cells v1", which is used by some large deployments to partition compute
nodes into smaller groups, coupled with a database and queue. This seems to be
a well-liked and easy-to-understand arrangement of resources, but the
implementation of it has issues for maintenance and correctness.
See `Comparison with Cells V1`_ for more detail.
Cells v1 is considered experimental and receives much less testing than the
rest of Nova. For example, there is no job for testing cells v1 with Neutron.
The priority for the core team is implementation of and migration to cells v2.
Because of this, there are a few restrictions placed on cells v1:
#. Cells v1 is in feature freeze. This means no new feature proposals for cells
v1 will be accepted by the core team, which includes but is not limited to
API parity, e.g. supporting virtual interface attach/detach with Neutron.
#. Latent bugs caused by the cells v1 design will not be fixed, e.g.
`bug 1489581 <https://bugs.launchpad.net/nova/+bug/1489581>`_. So if new
tests are added to Tempest which trigger a latent bug in cells v1 it may not
be fixed. However, regressions in working function should be tracked with
bugs and fixed.
**Suffice it to say, new deployments of cells v1 are not encouraged.**
The restrictions above are basically meant to prioritize effort and focus on
getting cells v2 completed, and feature requests and hard to fix latent bugs
detract from that effort. Further discussion on this can be found in the
`2015/11/12 Nova meeting minutes
There are no plans to remove Cells V1 until V2 is usable by existing
deployments and there is a migration path.
Right now, when a request hits the Nova API for a particular instance, the
instance information is fetched from the database, which contains the hostname
of the compute node on which the instance currently lives. If the request needs
to take action on the instance (which is most of them), the hostname is used to
calculate the name of a queue, and a message is written there which finds its
way to the proper compute node.
The meat of this proposal is changing the above hostname lookup into two parts
that yield three pieces of information instead of one. Basically, instead of
merely looking up the *name* of the compute node on which an instance lives, we
will also obtain database and queue connection information. Thus, when asked to
take action on instance $foo, we will:
1. Lookup the three-tuple of (database, queue, hostname) for that instance
2. Connect to that database and fetch the instance record
3. Connect to the queue and send the message to the proper hostname queue
The above differs from the current organization in two ways. First, we need to
do two database lookups before we know where the instance lives. Second, we
need to demand-connect to the appropriate database and queue. Both of these
have performance implications, but we believe we can mitigate the impacts
through the use of things like a memcache of instance mapping information and
pooling of connections to database and queue systems. The number of cells will
always be much smaller than the number of instances.
There are availability implications with this change since something like a
'nova list' which might query multiple cells could end up with a partial result
if there is a database failure in a cell. A database failure within a cell
would cause larger issues than a partial list result so the expectation is that
it would be addressed quickly and cellsv2 will handle it by indicating in the
response that the data may not be complete.
Since this is very similar to what we have with current cells, in terms of
organization of resources, we have decided to call this "cellsv2" for
After this work is complete there will no longer be a "no cells" deployment.
The default installation of Nova will be a single cell setup.
The benefits of this new organization are:
* Native sharding of the database and queue as a first-class-feature in nova.
All of the code paths will go through the lookup procedure and thus we won't
have the same feature parity issues as we do with current cells.
* No high-level replication of all the cell databases at the top. The API will
need a database of its own for things like the instance index, but it will
not need to replicate all the data at the top level.
* It draws a clear line between global and local data elements. Things like
flavors and keypairs are clearly global concepts that need only live at the
top level. Providing this separation allows compute nodes to become even more
stateless and insulated from things like deleted/changed global data.
* Existing non-cells users will suddenly gain the ability to spawn a new "cell"
from their existing deployment without changing their architecture. Simply
adding information about the new database and queue systems to the new index
will allow them to consume those resources.
* Existing cells users will need to fill out the cells mapping index, shutdown
their existing cells synchronization service, and ultimately clean up their
top level database. However, since the high-level organization is not
substantially different, they will not have to re-architect their systems to
move to cellsv2.
* Adding new sets of hosts as a new "cell" allows them to be plugged into a
deployment and tested before allowing builds to be scheduled to them.
Comparison with Cells V1
In reality, the proposed organization is nearly the same as what we currently
have in cells today. A cell mostly consists of a database, queue, and set of
compute nodes. The primary difference is that current cells require a
nova-cells service that synchronizes information up and down from the top level
to the child cell. Additionally, there are alternate code paths in
compute/api.py which handle routing messages to cells instead of directly down
to a compute host. Both of these differences are relevant to why we have a hard
time achieving feature and test parity with regular nova (because many things
take an alternate path with cells) and why it's hard to understand what is
going on (all the extra synchronization of data). The new proposed cellsv2
organization avoids both of these problems by letting things live where they
should, teaching nova to natively find the right db, queue, and compute node to
handle a given request.
As mentioned above there is a split between global data and data that is local
to a cell.
The following is a breakdown of what data can uncontroversially considered
global versus local to a cell. Missing data will be filled in as consensus is
reached on the data that is more difficult to cleanly place. The missing data
is mostly concerned with scheduling and networking.
Global (API-level) Tables