As part of the bridge bringup, I've discoverd that the property state
returned from Creates does *not* always equal the state that is then
read from calls to Get. (I suspect this is a bug and that they should
be equivalent, but I doubt it's fruitfal to try and track down all
occurrences of this; I bet it's widespread). To cope with this, we will
return state from Create and Update, instead of issuing a call to Get.
This was a design we considered to start with and frankly didn't have
a super strong reason to do it the current way, other than that it seemed
elegant to place all of the Get logic in one place.
Note that providers may choose to return nil, in which case we will read
state from the provider in the usual Get style.
This adds a ReadLocations RPC function to the engine interface, alongside
the singular ReadLocation. The plural function takes a single token that
represents a module or class and we will then return all of the module
or class (static) properties that are currently known.
This change adds an engine gRPC interface, and associated implementation,
so that plugins may do interesting things that require "phoning home".
Previously, the engine would fire up plugins and talk to them directly,
but there was no way for a plugin to ask the engine to do anything.
The motivation here is so that plugins can read evaluator state, such
as config information, but this change also allows richer logging
functionality than previously possible. We will still auto-log any
stdout/stderr writes; however, explicit errors, warnings, informational,
and even debug messages may be written over the Log API.
This change restructures a lot more pertaining to deployments, snapshots,
environments, and the like.
The most notable change is that the notion of a deploy.Source is introduced,
which splits the responsibility between the deploy.Plan -- which simply
understands how to compute and carry out deployment plans -- and the idea
of something that can produce new objects on-demand during deployment.
The primary such implementation is evalSource, which encapsulates an
interpreter and takes a package, args, and config map, and proceeds to run
the interpreter in a distinct goroutine. It synchronizes as needed to
poke and prod the interpreter along its path to create new resource objects.
There are two other sources, however. First, a nullSource, which simply
refuses to create new objects. This can be handy when writing isolated
tests but is also used to simulate the "empty" environment as necessary to
do a complete teardown of the target environment. Second, a fixedSource,
which takes a pre-computed array of objects, and hands those, in order, to
the planning engine; this is mostly useful as a testing technique.
Boatloads of code is now changed and updated in the various CLI commands.
This further chugs along towards pulumi/lumi#90. The end is in sight.
This change includes approximately 1/3rd of the change necessary
to support output properties, as per pulumi/lumi#90.
In short, the runtime now has a new hidden type, Latent<T>, which
represents a "speculative" value, whose eventual type will be T,
that we can use during evaluation in various ways. Namely,
operations against Latent<T>s generally produce new Latent<U>s.
During planning, any Latent<T>s that end up in resource properties
are transformed into "unknown" property values. An unknown property
value is legal only during planning-time activities, such as Check,
Name, and InspectChange. As a result, those RPC interfaces have
been updated to include lookaside maps indicating which properties
have unknown values. My intent is to add some helper functions to
make dealing with this circumstance more correct-by-construction.
For now, using an unresolved Latent<T> in a conditional will lead
to an error. See pulumi/lumi#67. Speculating beyond these -- by
supporting iterative planning and application -- is something we
want to support eventually, but it makes sense to do that as an
additive change beyond this initial support. That is a missing 1/3.
Finally, the other missing 1/3rd which will happen much sooner
than the rest is restructuing plan application so that it will
correctly observe resolution of Latent<T> values. Right now, the
evaluation happens in one single pass, prior to the application, and
so Latent<T>s never actually get witnessed in a resolved state.
Unfortunately, this wasn't a great name. The old one stunk, but the
new one was misleading at best. The thing is, this isn't about performing
an update -- it's about NOT doing an update, depending on its return value.
Further, it's not just previewing the changes, it is actively making a
decision on what to do in response to them. InspectUpdate seems to convey
this and I've unified the InspectUpdate and Update routines to take a
ChangeRequest, instead of UpdateRequest, to help imply the desired behavior.
In order to support output properties (pulumi/coconut#90), we need to
modify the Create gRPC interface for resource providers slightly. In
addition to returning the ID, we need to also return any properties
computed by the AWS provider itself. For instance, this includes ARNs
and IDs of various kinds. This change simply propagates the resources
but we don't actually support reading the outputs just yet.
This change renames two provider methods:
* Read becomes Get.
* UpdateImpact becomes PreviewUpdate.
These just read a whole lot nicer than the old names.
This change adds a rudimentary cocogo SDK package. The only thing in
here is a cocogo.Resource type which will serve as the base marker for
all resource classes in IDL packages (see pulumi/coconut#133).
This change adds the ability to specify analyzers in two ways:
1) By listing them in the project file, for example:
analyzers:
- acmecorp/security
- acmecorp/gitflow
2) By explicitly listing them on the CLI, as a "one off":
$ coco deploy <env> \
--analyzer=acmecorp/security \
--analyzer=acmecorp/gitflow
This closes out pulumi/coconut#119.
This change introduces the basic requirements for analyzers, as per
pulumi/coconut#119. In particular, an analyzer can implement either,
or both, of the RPC methods, Analyze and AnalyzeResource. The former
is meant to check an overall deployment (e.g., to ensure it has been
signed off on) and the latter is to check individual resources (e.g.,
to ensure properties of them are correct, such as checking style,
security, etc. rules). These run simultaneous to overall checking.
Analyzers are loaded as plugins just like providers are. The difference
is mainly in their naming ("analyzer-" prefix, rather than "resource-"),
and the RPC methods that they support.
This isn't 100% functional since we need a way to specify at the CLI
that a particular analyzer should be run, in addition to a way of
recording which analyzers certain projects should use in their manifests.
This change adds a new Check RPC method on the provider interface,
permitting resource providers to perform arbitrary verification on
the values of properties. This is useful for validating things
that might be difficult to express in the type system, and it runs
before *any* modifications are run (so failures can be caight early
before it's too late). My favorite motivating example is verifying
that an AWS EC2 instance's AMI is available within the target region.
This resolvespulumi/coconut#107, although we aren't using this
in any resource providers just yet. I'll add a work item now for that...
This change tracks which updates triggered a replacement. This enables
better output and diagnostics. For example, we now colorize those
properties differently in the output. This makes it easier to diagnose
why an unexpected resource might be getting deleted and recreated.
This change, part of pulumi/coconut#105, rearranges support for
resource replacement. The old model didn't properly account for
the cascading updates and possible replacement of dependencies.
Namely, we need to model a replacement as a creation followed by
a deletion, inserted into the overall DAG correctly so that any
resources that must be updated are updated after the creation but
prior to the deletion. This is done by inserting *three* nodes
into the graph per replacement: a physical creation step, a
physical deletion step, and a logical replacement step. The logical
step simply makes it nicer in the output (the plan output shows
a single "replacement" rather than the fine-grained outputs, unless
they are requested with --show-replace-steps). It also makes it
easier to fold all of the edges into a single linchpin node.
As part of this, the update step no longer gets to choose whether
to recreate the resource. Instead, the engine takes care of
orchestrating the replacement through actual create and delete calls.
This change introduces a new RPC function to the provider interface;
in pseudo-code:
UpdateImpact(id ID, t Type, olds PropertyMap, news PropertyMap)
(bool, PropertyMap, error)
Essentially, during the planning phase, we will consult each provider
about the nature of a proposed update. This update includes a set of
old properties and the new ones and, if the resource provider will need
to replace the property as a result of the update, it will return true;
in general, the PropertyMap will eventually contain a list of all
properties that will be modified as a result of the operation (see below).
The planning phase reacts to this by propagating the change to dependent
resources, so that they know that the ID will change (and so that they
can recalculate their own state accordingly, possibly leading to a ripple
effect). This ensures the overall DAG / schedule is ordered correctly.
This change is most of pulumi/coconut#105. The only missing piece
is to generalize replacing the "ID" property with replacing arbitrary
properties; there are hooks in here for this, but until pulumi/coconut#90
is addressed, it doesn't make sense to make much progress on this.
This change overhauls the way we do object monikers. The old mechanism,
generating monikers using graph paths, was far too brittle and prone to
collisions. The new approach mixes some amount of "automatic scoping"
plus some "explicit naming." Although there is some explicitness, this
is arguably a good thing, as the monikers will be relatable back to the
source more readily by developers inspecting the graph and resource state.
Each moniker has four parts:
<Namespace>::<AllocModule>::<Type>::<Name>
wherein each element is the following:
<Namespace> The namespace being deployed into
<AllocModule> The module in which the object was allocated
<Type> The type of the resource
<Name> The assigned name of the resource
The <Namespace> is essentially the deployment target -- so "prod",
"stage", etc -- although it is more general purpose to allow for future
namespacing within a target (e.g., "prod/customer1", etc); for now
this is rudimentary, however, see marapongo/mu#94.
The <AllocModule> is the token for the code that contained the 'new'
that led to this object being created. In the future, we may wish to
extend this to also track the module under evaluation. (This is a nice
aspect of monikers; they can become arbitrarily complex, so long as
they are precise, and not prone to false positives/negatives.)
The <Name> warrants more discussion. The resource provider is consulted
via a new gRPC method, Name, that fetches the name. How the provider
does this is entirely up to it. For some resource types, the resource
may have properties that developers must set (e.g., `new Bucket("foo")`);
for other providers, perhaps the resource intrinsically has a property
that explicitly and uniquely qualifies the object (e.g., AWS SecurityGroups,
via `new SecurityGroup({groupName: "my-sg"}`); and finally, it's conceivable
that a provider might auto-generate the name (e.g., such as an AWS Lambda
whose name could simply be a hash of the source code contents).
This should overall produce better results with respect to moniker
collisions, ability to match resources, and the usability of the system.
This change adds basic support for discovering, loading, binding to,
and invoking RPC methods on, resource provider plugins.
In a nutshell, we add a new context object that will share cached
state such as loaded plugins and connections to them. It will be
a policy decision in server scenarios how much state to share and
between whom. This context also controls per-resource context
allocation, which in the future will allow us to perform structured
cancellation and teardown amongst entire groups of requests.
Plugins are loaded based on their name, and can be found in one of
two ways: either simply by having them on your path (with a name of
"mu-ressrv-<pkg>", where "<pkg>" is the resource package name with
any "/"s replaced with "_"s); or by placing them in the standard
library installation location, which need not be on the path for this
to work (since we know precisely where to look).
If we find a protocol, we will load it as a child process.
The protocol for plugins is that they will choose a port on their
own -- to eliminate races that'd be involved should Mu attempt to
pre-pick one for them -- and then write that out as the first line
to STDOUT (terminated by a "\n"). This is the only STDERR/STDOUT
that Mu cares about; from there, the plugin is free to write all it
pleases (e.g., for logging, debugging purposes, etc).
Afterwards, we then bind our gRPC connection to that port, and create
a typed resource provider client. The CRUD operations that get driven
by plan application are then simple wrappers atop the underlying gRPC
calls. For now, we interpret all errors as catastrophic; in the near
future, we will probably want to introduce a "structured error"
mechanism in the gRPC interface for "transactional errors"; that is,
errors for which the server was able to recover to a safe checkpoint,
which can be interpreted as ResourceOK rather than ResourceUnknown.
This changes two aspects of the ResourceProvider.Update RPC API:
1. Update needs to return an ID, in case the resource had to be
recreated in response to the request.
2. Include both the old and the new values for properties that are
being updated.
After a bit more thinking, we will create new SDK packages for each
of the languages we wish to support writing resource providers in.
This is where the RPC goo will live, so I have created a new sdk/
directory, moved the Protobuf/gRPC definitions underneath sdk/proto/,
and put the generated code into sdk/go/ and sdk/js/.
