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Comments below..<br>
<br>
<div class="moz-cite-prefix">On 5/21/2017 1:38 PM, Monty Taylor
wrote:<br>
</div>
<blockquote
cite="mid:522b78dc-c8af-eeeb-5593-da580c93cc8b@inaugust.com"
type="cite">Hi all!
<br>
<br>
As the discussion around PostgreSQL has progressed, it has come
clear to me that there is a decently deep philosophical question
on which we do not currently share either definition or agreement.
I believe that the lack of clarity on this point is one of the
things that makes the PostgreSQL conversation difficult.
<br>
<br>
I believe the question is between these two things:
<br>
<br>
* Should OpenStack assume the existence of an external database
service that it treat as an black-box on the other side of a
connection string?
<br>
<br>
* Should OpenStack take an active and/or opinionated role in
managing the database service?
<br>
<br>
A potentially obvious question about that (asked by Mike Bayer in
a different thread) is: "what do you mean by managing?"
<br>
<br>
What I mean by managing is doing all of the things you can do
related to database operational controls short of installing the
software, writing the basic db config files to disk and stopping
and starting the services. It means being much more prescriptive
about what types of config we support, validating config settings
that cannot be overridden at runtime and refusing to operate if
they are unworkable.
<br>
</blockquote>
<br>
I think it's helpful and important for us to have automation tooling
like tripleo, puppet, etc. that can stand up a MySQL database. But
we also have to realize that as shops mature, they will deploy more
complicated database topologies, clustered configurations, and
replication scenarios. So I think we shouldn't go overboard with
being prescriptive. We also have to realize that in the enterprise
space, databases are usually deployed and managed by a separate
database team, which means less control over that layer. So we
shouldn't force people into this model. We should provide best
practice documentation, examples (tripleo, puppet, ansible, etc.),
and leave it up to the operator. <br>
<br>
<blockquote
cite="mid:522b78dc-c8af-eeeb-5593-da580c93cc8b@inaugust.com"
type="cite">
<br>
Why would we want to be 'more active'? When managing and tuning
databases, there are some things that are driven by the
environment and some things that are driven by the application.
<br>
<br>
Things that are driven by the environment include things like the
amount of RAM actually available, whether or not the machines
running the database are dedicated or shared, firewall settings,
selinux settings and what versions of software are available.
<br>
</blockquote>
<br>
This is a good example of an area that we should focus on
documenting best practices and leave it to the operator to
implement. Guidelines around cpu, memory, security settings,
tunables, etc. are what's needed here. Today, there isn't really any
guidance or best practices on even sizing the database(s) for a
given deployment size. <br>
<br>
<blockquote
cite="mid:522b78dc-c8af-eeeb-5593-da580c93cc8b@inaugust.com"
type="cite">
<br>
Things that are driven by the application are things like
character set and collation, schema design, data types, schema
upgrade and HA strategies.<br>
</blockquote>
<br>
These are things that we can have a bit more control or direction
on.<br>
<br>
<blockquote
cite="mid:522b78dc-c8af-eeeb-5593-da580c93cc8b@inaugust.com"
type="cite">
<br>
One might argue that HA strategies are an operator concern, but in
reality the set of workable HA strategies is tightly constrained
by how the application works, and the pairing an application
expecting one HA strategy with a deployment implementing a
different one can have negative results ranging from unexpected
downtime to data corruption.
<br>
<br>
For example: An HA strategy using slave promotion and a VIP that
points at the current write master paired with an application
incorrectly configured to do such a thing can lead to writes to
the wrong host after a failover event and an application that
seems to be running fine until the data turns up weird after a
while.
<br>
</blockquote>
<br>
This is definitely a more complicated area that becomes more and
more specific to the clustering technology being used. Galera vs.
MySQL Cluster is a good example. Galera has an active/passive
architecture where the above issues become a concern for sure. While
MySQL Cluster (NDB) is an active/active architecture, so losing a
node only effects any uncommitted transactions, that could easily be
addressed with a retry. These topologies will become more
complicated as people start looking at cross regional replication
and DR.<br>
<br>
<blockquote
cite="mid:522b78dc-c8af-eeeb-5593-da580c93cc8b@inaugust.com"
type="cite">
<br>
For the areas in which the characteristics of the database are
tied closely to the application behavior, there is a constrained
set of valid choices at the database level. Sometimes that
constrained set only has one member.
<br>
<br>
The approach to those is what I'm talking about when I ask the
question about "external" or "active".
<br>
<br>
In the "external" approach, we document the expectations and then
write the code assuming that the database is set up appropriately.
We may provide some helper tools, such as 'nova-manage db sync'
and documentation on the sequence of steps the operator should
take.
<br>
<br>
In the "active" approach, we still document expectations, but we
also validate them. If they are not what we expect but can be
changed at runtime, we change them overriding conflicting
environmental config, and if we can't, we hard-stop indicating an
unsuitable environment. Rather than providing helper tools, we
perform the steps needed ourselves, in the order they need to be
performed, ensuring that they are done in the manner in which they
need to be done.
<br>
</blockquote>
<br>
This might be a trickier situation, especially if the database(s)
are in a separate or dedicated environment that the OpenStack
service processes don't have access to. Of course for SQL commands,
this isn't a problem. But changing the configuration files and
restarting the database may be a harder thing to expect.<br>
<br>
<blockquote
cite="mid:522b78dc-c8af-eeeb-5593-da580c93cc8b@inaugust.com"
type="cite">
<br>
Some examples:
<br>
<br>
* Character Sets / Collations
<br>
<br>
We currently enforce at testing time that all database migrations
are explicit about InnoDB. We also validate in oslo.db that table
character sets have the string 'utf8' in them. (only on MySQL) We
do not have any check for case-sensitive or case-insensitive
collations (these affect sorting and comparison operations)
Because we don't, different server config settings or different
database backends for different clouds can actually behave
differently through the REST API.
<br>
<br>
To deal with that:
<br>
<br>
First we'd have to decide whether case sensitive or case
insensitive was what we wanted. If we decided we wanted case
sensitive, we could add an enforcement of that in oslo.db, and
write migrations to get from case insensitive indexes to case
sensitive indexes on tables where we detected that a case
insensitive collation had been used. If we decided we wanted to
stick with case insensitive we could similarly add code to enforce
it on MySQL. To enforce it actively on PostgresSQL, we'd need to
either switch our code that's using comparisons to use the
sqlalchemy case-insensitive versions explicitly, or maybe write
some sort of overloaded driver for PG that turns all comparisons
into case-insensitive, which would wrap both sides of comparisons
in lower() calls (which has some indexing concerns, but let's
ignore that for the moment) We could also take the 'external'
approach and just document it, then define API tests and try to
tie the insensitive behavior in the API to Interop Compliance. I'm
not 100% sure how a db operator would remediate this - but PG has
some fancy computed index features - so maybe it would be
possible.
<br>
</blockquote>
<br>
I think that abstraction with oslo.db would be the right path here.
But you are also right that we need to have a consistent compliance
policy at the API layer. We may fix things down at the DB level with
oslo.db, but everything on top of that needs to also fall in-line.
There is a very high chance that there are hard-coded workarounds or
assumptions in the services and apis today.<br>
<br>
<blockquote
cite="mid:522b78dc-c8af-eeeb-5593-da580c93cc8b@inaugust.com"
type="cite">
<br>
A similar issue lurks with the fact that MySQL unicode storage is
3-byte by default and 4-byte is opt-in. We could take the
'external' approach and document it and assume the operator has
configured their my.cnf with the appropriate default, or taken an
'active' approach where we override it in all the models and make
migrations to get us from 3 to 4 byte.
<br>
</blockquote>
<br>
I think an active approach on this would be ideal, just like the
utf8 and InnoDB settings are today. FYI, not all services are
enforcing these in a consistent manor today. Another example of
something that should be abstracted at the oslo.db layer and get the
human element out of the way.<br>
<br>
<blockquote
cite="mid:522b78dc-c8af-eeeb-5593-da580c93cc8b@inaugust.com"
type="cite">
<br>
* Schema Upgrades
<br>
<br>
The way you roll out online schema changes is highly dependent on
your database architecture.
<br>
<br>
Just limiting to the MySQL world:
<br>
<br>
If you do Galera, you can do roll them out in Total Order or
Rolling fashion. Total Order locks basically everything while it's
happening, so isn't a candidate for "online". In rolling you apply
the schema change to one node at a time. If you do that, the
application has to be able to deal with both forms of the table,
and you have to deal with ensuring that data can replicate
appropriately while the schema change is happening.
<br>
<br>
If you do DRBD active/passive or a single-node deployment you only
have one upgrade operation to perform, but you will only lock
certain things - depending on what schema change operations you
were performing.
<br>
<br>
If you do master/slave, you can roll out the schema change to your
slaves one at a time, wait for them all to catch up, then promote
a slave taking the current master out of commission - update the
old master then then put it into the slave pool. Like Galera
rolling, the app needs to be able to handle old and new versions
and the replication stream needs to be able to replicate between
the versions.
<br>
<br>
Making sure that the stream is able to replicate puts a set of
limitations on the types of schema changes you can perform, but it
is an understandable constrained set.
<br>
<br>
In either approach the OpenStack service has to be able to talk to
both old and new versions of the schema. And in either approach we
need to make sure to limit the schema change operations to the set
that can be accomplished in an online fashion. We also have to be
careful to not start writing values to new columns until all of
the nodes have been updated, because the replication stream can't
replicate the new column value to nodes that don't have the new
column.
<br>
</blockquote>
<br>
This is another area where something like MySQL Cluster (NDB) would
operate differently because it's an active/active architecture. So
limiting the number of online changes while a table is locked across
the cluster would be very important. There is also the timeouts for
the applications to consider, something that could be abstracted
again with oslo.db.<br>
<br>
<blockquote
cite="mid:522b78dc-c8af-eeeb-5593-da580c93cc8b@inaugust.com"
type="cite">
<br>
In either approach we can decide to limit the number of
architectures we support for "online" upgrades.
<br>
<br>
In an 'external' approach, we make sure to do those things, we
write documentation and we assume the database will be updated
appropriately. We can document that if the deployer chooses to do
Total Order on Galera, they will not have online upgrades. There
will also have to be a deployer step to let the services know that
they can start writing values to the new schema format once the
upgrade is complete.
<br>
<br>
In an 'active' approach, we can notice that we have an update
available to run, and we can drive it from code. We can check for
Galera, and if it's there we can run the upgrade in Rolling
fashion one node at a time with no work needed on the part of the
deployer. Since we're driving the upgrade, we know when it's done,
so we can signal ourselves to start using the new version. We'd
obviously have to pick the set of acceptable architectures we can
handle consistently orchestrating.
<br>
</blockquote>
<br>
This would be an interesting idea to expand to a autonomic
orchestration framework within the control plane to handle the
database upgrades online and the restarting of the dependent
services in the correct order. If we only focus on the database
piece, it may not be as interesting for operators.<br>
<br>
<blockquote
cite="mid:522b78dc-c8af-eeeb-5593-da580c93cc8b@inaugust.com"
type="cite">
<br>
* Versions
<br>
<br>
It's worth noting that behavior for schema updates and other
things change over time with backend database version. We set
minimum versions of other things, like libvirt and OVS - so we
might also want to set minimum versions for what we can support in
the database. That way we can know for a given release of
OpenStack what DDL operations are safe to use for a rolling
upgrade and what are not. That means detecting such a version and
potentially refusing to perform an upgrade if the version isn't
acceptable. That reduces the operator's ability to choose what
version of the database software to run, but increases our ability
to be able to provide tooling and operations that we can be
confident will work.
<br>
</blockquote>
<br>
Validating the MySQL database version is a good idea. The features
do change over time. A good example is how in 5.7, you'll get
warnings about duplicate indexes being dropped in a future release
which will definitely affect multiple services today.<br>
<br>
<blockquote
cite="mid:522b78dc-c8af-eeeb-5593-da580c93cc8b@inaugust.com"
type="cite">
<br>
== Summary ==
<br>
<br>
These are just a couple of examples - but I hope they're at least
mildly useful to explain some of the sorts of issues at hand - and
why I think we need to clarify what our intent is separate from
the issue of what databases we "support".
<br>
<br>
Some operations have one and only one "right" way to be done. For
those operations if we take an 'active' approach, we can implement
them once and not make all of our deployers and distributors each
implement and run them. However, there is a cost to that.
Automatic and prescriptive behavior has a higher dev cost that is
proportional to the number of supported architectures. This then
implies a need to limit deployer architecture choices.
<br>
<br>
On the other hand, taking an 'external' approach allows us to
federate the work of supporting the different architectures to the
deployers. This means more work on the deployer's part, but also
potentially a greater amount of freedom on their part to deploy
supporting services the way they want. It means that some of the
things that have been requested of us - such as easier operation
and an increase in the number of things that can be upgraded with
no-downtime - might become prohibitively costly for us to
implement.
<br>
<br>
I honestly think that both are acceptable choices we can make and
that for any given topic there are middle grounds to be found at
any given moment in time.
<br>
<br>
BUT - without a decision as to what our long-term philosophical
intent in this space is that is clear and understandable to
everyone, we cannot have successful discussions about the impact
of implementation choices, since we will not have a shared
understanding of the problem space or the solutions we're talking
about.
<br>
<br>
For my part - I hear complaints that OpenStack is 'difficult' to
operate and requests for us to make it easier. This is why I have
been advocating some actions that are clearly rooted in an
'active' worldview.
<br>
<br>
Finally, this is focused on the database layer but similar
questions arise in other places. What is our philosophy on
prescriptive/active choices on our part coupled with automated
action and ease of operation vs. expanded choices for the deployer
at the expense of configuration and operational complexity. For
now let's see if we can answer it for databases, and see where
that gets us.
<br>
<br>
Thanks for reading.
<br>
<br>
Monty
<br>
<br>
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</blockquote>
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