2018-05-22 21:43:36 +02:00
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// Copyright 2016-2018, Pulumi Corporation.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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Implement initial Lumi-as-a-library
This is the initial step towards redefining Lumi as a library that runs
atop vanilla Node.js/V8, rather than as its own runtime.
This change is woefully incomplete but this includes some of the more
stable pieces of my current work-in-progress.
The new structure is that within the sdk/ directory we will have a client
library per language. This client library contains the object model for
Lumi (resources, properties, assets, config, etc), in addition to the
"language runtime host" components required to interoperate with the
Lumi resource monitor. This resource monitor is effectively what we call
"Lumi" today, in that it's the thing orchestrating plans and deployments.
Inside the sdk/ directory, you will find nodejs/, the Node.js client
library, alongside proto/, the definitions for RPC interop between the
different pieces of the system. This includes existing RPC definitions
for resource providers, etc., in addition to the new ones for hosting
different language runtimes from within Lumi.
These new interfaces are surprisingly simple. There is effectively a
bidirectional RPC channel between the Lumi resource monitor, represented
by the lumirpc.ResourceMonitor interface, and each language runtime,
represented by the lumirpc.LanguageRuntime interface.
The overall orchestration goes as follows:
1) Lumi decides it needs to run a program written in language X, so
it dynamically loads the language runtime plugin for language X.
2) Lumi passes that runtime a loopback address to its ResourceMonitor
service, while language X will publish a connection back to its
LanguageRuntime service, which Lumi will talk to.
3) Lumi then invokes LanguageRuntime.Run, passing information like
the desired working directory, program name, arguments, and optional
configuration variables to make available to the program.
4) The language X runtime receives this, unpacks it and sets up the
necessary context, and then invokes the program. The program then
calls into Lumi object model abstractions that internally communicate
back to Lumi using the ResourceMonitor interface.
5) The key here is ResourceMonitor.NewResource, which Lumi uses to
serialize state about newly allocated resources. Lumi receives these
and registers them as part of the plan, doing the usual diffing, etc.,
to decide how to proceed. This interface is perhaps one of the
most subtle parts of the new design, as it necessitates the use of
promises internally to allow parallel evaluation of the resource plan,
letting dataflow determine the available concurrency.
6) The program exits, and Lumi continues on its merry way. If the program
fails, the RunResponse will include information about the failure.
Due to (5), all properties on resources are now instances of a new
Property<T> type. A Property<T> is just a thin wrapper over a T, but it
encodes the special properties of Lumi resource properties. Namely, it
is possible to create one out of a T, other Property<T>, Promise<T>, or
to freshly allocate one. In all cases, the Property<T> does not "settle"
until its final state is known. This cannot occur before the deployment
actually completes, and so in general it's not safe to depend on concrete
resolutions of values (unlike ordinary Promise<T>s which are usually
expected to resolve). As a result, all derived computations are meant to
use the `then` function (as in `someValue.then(v => v+x)`).
Although this change includes tests that may be run in isolation to test
the various RPC interactions, we are nowhere near finished. The remaining
work primarily boils down to three things:
1) Wiring all of this up to the Lumi code.
2) Fixing the handful of known loose ends required to make this work,
primarily around the serialization of properties (waiting on
unresolved ones, serializing assets properly, etc).
3) Implementing lambda closure serialization as a native extension.
This ongoing work is part of pulumi/pulumi-fabric#311.
2017-08-26 21:07:54 +02:00
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syntax = "proto3";
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2017-11-29 20:27:32 +01:00
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import "google/protobuf/empty.proto";
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Implement initial Lumi-as-a-library
This is the initial step towards redefining Lumi as a library that runs
atop vanilla Node.js/V8, rather than as its own runtime.
This change is woefully incomplete but this includes some of the more
stable pieces of my current work-in-progress.
The new structure is that within the sdk/ directory we will have a client
library per language. This client library contains the object model for
Lumi (resources, properties, assets, config, etc), in addition to the
"language runtime host" components required to interoperate with the
Lumi resource monitor. This resource monitor is effectively what we call
"Lumi" today, in that it's the thing orchestrating plans and deployments.
Inside the sdk/ directory, you will find nodejs/, the Node.js client
library, alongside proto/, the definitions for RPC interop between the
different pieces of the system. This includes existing RPC definitions
for resource providers, etc., in addition to the new ones for hosting
different language runtimes from within Lumi.
These new interfaces are surprisingly simple. There is effectively a
bidirectional RPC channel between the Lumi resource monitor, represented
by the lumirpc.ResourceMonitor interface, and each language runtime,
represented by the lumirpc.LanguageRuntime interface.
The overall orchestration goes as follows:
1) Lumi decides it needs to run a program written in language X, so
it dynamically loads the language runtime plugin for language X.
2) Lumi passes that runtime a loopback address to its ResourceMonitor
service, while language X will publish a connection back to its
LanguageRuntime service, which Lumi will talk to.
3) Lumi then invokes LanguageRuntime.Run, passing information like
the desired working directory, program name, arguments, and optional
configuration variables to make available to the program.
4) The language X runtime receives this, unpacks it and sets up the
necessary context, and then invokes the program. The program then
calls into Lumi object model abstractions that internally communicate
back to Lumi using the ResourceMonitor interface.
5) The key here is ResourceMonitor.NewResource, which Lumi uses to
serialize state about newly allocated resources. Lumi receives these
and registers them as part of the plan, doing the usual diffing, etc.,
to decide how to proceed. This interface is perhaps one of the
most subtle parts of the new design, as it necessitates the use of
promises internally to allow parallel evaluation of the resource plan,
letting dataflow determine the available concurrency.
6) The program exits, and Lumi continues on its merry way. If the program
fails, the RunResponse will include information about the failure.
Due to (5), all properties on resources are now instances of a new
Property<T> type. A Property<T> is just a thin wrapper over a T, but it
encodes the special properties of Lumi resource properties. Namely, it
is possible to create one out of a T, other Property<T>, Promise<T>, or
to freshly allocate one. In all cases, the Property<T> does not "settle"
until its final state is known. This cannot occur before the deployment
actually completes, and so in general it's not safe to depend on concrete
resolutions of values (unlike ordinary Promise<T>s which are usually
expected to resolve). As a result, all derived computations are meant to
use the `then` function (as in `someValue.then(v => v+x)`).
Although this change includes tests that may be run in isolation to test
the various RPC interactions, we are nowhere near finished. The remaining
work primarily boils down to three things:
1) Wiring all of this up to the Lumi code.
2) Fixing the handful of known loose ends required to make this work,
primarily around the serialization of properties (waiting on
unresolved ones, serializing assets properly, etc).
3) Implementing lambda closure serialization as a native extension.
This ongoing work is part of pulumi/pulumi-fabric#311.
2017-08-26 21:07:54 +02:00
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import "google/protobuf/struct.proto";
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2017-09-20 02:23:10 +02:00
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import "provider.proto";
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Implement initial Lumi-as-a-library
This is the initial step towards redefining Lumi as a library that runs
atop vanilla Node.js/V8, rather than as its own runtime.
This change is woefully incomplete but this includes some of the more
stable pieces of my current work-in-progress.
The new structure is that within the sdk/ directory we will have a client
library per language. This client library contains the object model for
Lumi (resources, properties, assets, config, etc), in addition to the
"language runtime host" components required to interoperate with the
Lumi resource monitor. This resource monitor is effectively what we call
"Lumi" today, in that it's the thing orchestrating plans and deployments.
Inside the sdk/ directory, you will find nodejs/, the Node.js client
library, alongside proto/, the definitions for RPC interop between the
different pieces of the system. This includes existing RPC definitions
for resource providers, etc., in addition to the new ones for hosting
different language runtimes from within Lumi.
These new interfaces are surprisingly simple. There is effectively a
bidirectional RPC channel between the Lumi resource monitor, represented
by the lumirpc.ResourceMonitor interface, and each language runtime,
represented by the lumirpc.LanguageRuntime interface.
The overall orchestration goes as follows:
1) Lumi decides it needs to run a program written in language X, so
it dynamically loads the language runtime plugin for language X.
2) Lumi passes that runtime a loopback address to its ResourceMonitor
service, while language X will publish a connection back to its
LanguageRuntime service, which Lumi will talk to.
3) Lumi then invokes LanguageRuntime.Run, passing information like
the desired working directory, program name, arguments, and optional
configuration variables to make available to the program.
4) The language X runtime receives this, unpacks it and sets up the
necessary context, and then invokes the program. The program then
calls into Lumi object model abstractions that internally communicate
back to Lumi using the ResourceMonitor interface.
5) The key here is ResourceMonitor.NewResource, which Lumi uses to
serialize state about newly allocated resources. Lumi receives these
and registers them as part of the plan, doing the usual diffing, etc.,
to decide how to proceed. This interface is perhaps one of the
most subtle parts of the new design, as it necessitates the use of
promises internally to allow parallel evaluation of the resource plan,
letting dataflow determine the available concurrency.
6) The program exits, and Lumi continues on its merry way. If the program
fails, the RunResponse will include information about the failure.
Due to (5), all properties on resources are now instances of a new
Property<T> type. A Property<T> is just a thin wrapper over a T, but it
encodes the special properties of Lumi resource properties. Namely, it
is possible to create one out of a T, other Property<T>, Promise<T>, or
to freshly allocate one. In all cases, the Property<T> does not "settle"
until its final state is known. This cannot occur before the deployment
actually completes, and so in general it's not safe to depend on concrete
resolutions of values (unlike ordinary Promise<T>s which are usually
expected to resolve). As a result, all derived computations are meant to
use the `then` function (as in `someValue.then(v => v+x)`).
Although this change includes tests that may be run in isolation to test
the various RPC interactions, we are nowhere near finished. The remaining
work primarily boils down to three things:
1) Wiring all of this up to the Lumi code.
2) Fixing the handful of known loose ends required to make this work,
primarily around the serialization of properties (waiting on
unresolved ones, serializing assets properly, etc).
3) Implementing lambda closure serialization as a native extension.
This ongoing work is part of pulumi/pulumi-fabric#311.
2017-08-26 21:07:54 +02:00
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2017-09-22 04:18:21 +02:00
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package pulumirpc;
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Implement initial Lumi-as-a-library
This is the initial step towards redefining Lumi as a library that runs
atop vanilla Node.js/V8, rather than as its own runtime.
This change is woefully incomplete but this includes some of the more
stable pieces of my current work-in-progress.
The new structure is that within the sdk/ directory we will have a client
library per language. This client library contains the object model for
Lumi (resources, properties, assets, config, etc), in addition to the
"language runtime host" components required to interoperate with the
Lumi resource monitor. This resource monitor is effectively what we call
"Lumi" today, in that it's the thing orchestrating plans and deployments.
Inside the sdk/ directory, you will find nodejs/, the Node.js client
library, alongside proto/, the definitions for RPC interop between the
different pieces of the system. This includes existing RPC definitions
for resource providers, etc., in addition to the new ones for hosting
different language runtimes from within Lumi.
These new interfaces are surprisingly simple. There is effectively a
bidirectional RPC channel between the Lumi resource monitor, represented
by the lumirpc.ResourceMonitor interface, and each language runtime,
represented by the lumirpc.LanguageRuntime interface.
The overall orchestration goes as follows:
1) Lumi decides it needs to run a program written in language X, so
it dynamically loads the language runtime plugin for language X.
2) Lumi passes that runtime a loopback address to its ResourceMonitor
service, while language X will publish a connection back to its
LanguageRuntime service, which Lumi will talk to.
3) Lumi then invokes LanguageRuntime.Run, passing information like
the desired working directory, program name, arguments, and optional
configuration variables to make available to the program.
4) The language X runtime receives this, unpacks it and sets up the
necessary context, and then invokes the program. The program then
calls into Lumi object model abstractions that internally communicate
back to Lumi using the ResourceMonitor interface.
5) The key here is ResourceMonitor.NewResource, which Lumi uses to
serialize state about newly allocated resources. Lumi receives these
and registers them as part of the plan, doing the usual diffing, etc.,
to decide how to proceed. This interface is perhaps one of the
most subtle parts of the new design, as it necessitates the use of
promises internally to allow parallel evaluation of the resource plan,
letting dataflow determine the available concurrency.
6) The program exits, and Lumi continues on its merry way. If the program
fails, the RunResponse will include information about the failure.
Due to (5), all properties on resources are now instances of a new
Property<T> type. A Property<T> is just a thin wrapper over a T, but it
encodes the special properties of Lumi resource properties. Namely, it
is possible to create one out of a T, other Property<T>, Promise<T>, or
to freshly allocate one. In all cases, the Property<T> does not "settle"
until its final state is known. This cannot occur before the deployment
actually completes, and so in general it's not safe to depend on concrete
resolutions of values (unlike ordinary Promise<T>s which are usually
expected to resolve). As a result, all derived computations are meant to
use the `then` function (as in `someValue.then(v => v+x)`).
Although this change includes tests that may be run in isolation to test
the various RPC interactions, we are nowhere near finished. The remaining
work primarily boils down to three things:
1) Wiring all of this up to the Lumi code.
2) Fixing the handful of known loose ends required to make this work,
primarily around the serialization of properties (waiting on
unresolved ones, serializing assets properly, etc).
3) Implementing lambda closure serialization as a native extension.
This ongoing work is part of pulumi/pulumi-fabric#311.
2017-08-26 21:07:54 +02:00
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// ResourceMonitor is the interface a source uses to talk back to the planning monitor orchestrating the execution.
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service ResourceMonitor {
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2017-09-20 02:23:10 +02:00
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rpc Invoke(InvokeRequest) returns (InvokeResponse) {}
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2018-04-05 18:48:09 +02:00
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rpc ReadResource(ReadResourceRequest) returns (ReadResourceResponse) {}
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2017-11-29 20:27:32 +01:00
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rpc RegisterResource(RegisterResourceRequest) returns (RegisterResourceResponse) {}
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rpc RegisterResourceOutputs(RegisterResourceOutputsRequest) returns (google.protobuf.Empty) {}
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Implement initial Lumi-as-a-library
This is the initial step towards redefining Lumi as a library that runs
atop vanilla Node.js/V8, rather than as its own runtime.
This change is woefully incomplete but this includes some of the more
stable pieces of my current work-in-progress.
The new structure is that within the sdk/ directory we will have a client
library per language. This client library contains the object model for
Lumi (resources, properties, assets, config, etc), in addition to the
"language runtime host" components required to interoperate with the
Lumi resource monitor. This resource monitor is effectively what we call
"Lumi" today, in that it's the thing orchestrating plans and deployments.
Inside the sdk/ directory, you will find nodejs/, the Node.js client
library, alongside proto/, the definitions for RPC interop between the
different pieces of the system. This includes existing RPC definitions
for resource providers, etc., in addition to the new ones for hosting
different language runtimes from within Lumi.
These new interfaces are surprisingly simple. There is effectively a
bidirectional RPC channel between the Lumi resource monitor, represented
by the lumirpc.ResourceMonitor interface, and each language runtime,
represented by the lumirpc.LanguageRuntime interface.
The overall orchestration goes as follows:
1) Lumi decides it needs to run a program written in language X, so
it dynamically loads the language runtime plugin for language X.
2) Lumi passes that runtime a loopback address to its ResourceMonitor
service, while language X will publish a connection back to its
LanguageRuntime service, which Lumi will talk to.
3) Lumi then invokes LanguageRuntime.Run, passing information like
the desired working directory, program name, arguments, and optional
configuration variables to make available to the program.
4) The language X runtime receives this, unpacks it and sets up the
necessary context, and then invokes the program. The program then
calls into Lumi object model abstractions that internally communicate
back to Lumi using the ResourceMonitor interface.
5) The key here is ResourceMonitor.NewResource, which Lumi uses to
serialize state about newly allocated resources. Lumi receives these
and registers them as part of the plan, doing the usual diffing, etc.,
to decide how to proceed. This interface is perhaps one of the
most subtle parts of the new design, as it necessitates the use of
promises internally to allow parallel evaluation of the resource plan,
letting dataflow determine the available concurrency.
6) The program exits, and Lumi continues on its merry way. If the program
fails, the RunResponse will include information about the failure.
Due to (5), all properties on resources are now instances of a new
Property<T> type. A Property<T> is just a thin wrapper over a T, but it
encodes the special properties of Lumi resource properties. Namely, it
is possible to create one out of a T, other Property<T>, Promise<T>, or
to freshly allocate one. In all cases, the Property<T> does not "settle"
until its final state is known. This cannot occur before the deployment
actually completes, and so in general it's not safe to depend on concrete
resolutions of values (unlike ordinary Promise<T>s which are usually
expected to resolve). As a result, all derived computations are meant to
use the `then` function (as in `someValue.then(v => v+x)`).
Although this change includes tests that may be run in isolation to test
the various RPC interactions, we are nowhere near finished. The remaining
work primarily boils down to three things:
1) Wiring all of this up to the Lumi code.
2) Fixing the handful of known loose ends required to make this work,
primarily around the serialization of properties (waiting on
unresolved ones, serializing assets properly, etc).
3) Implementing lambda closure serialization as a native extension.
This ongoing work is part of pulumi/pulumi-fabric#311.
2017-08-26 21:07:54 +02:00
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}
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2018-11-12 18:26:31 +01:00
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// There is a clear distinction here between the "properties" bag sent across the wire as part of these RPCs and
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// properties that exist on Pulumi resources as projected into the target language. It is important to call out that the
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// properties here are in the format that a provider will expect. This is to say that they are usually in camel case.
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// If a language wants to project properties in a format *other* than camel-case, it is the job of the language to
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// ensure that the properties are translated into camel case before invoking an RPC.
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2018-04-05 18:48:09 +02:00
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// ReadResourceRequest contains enough information to uniquely qualify and read a resource's state.
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message ReadResourceRequest {
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string id = 1; // the ID of the resource to read.
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string type = 2; // the type of the resource object.
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string name = 3; // the name, for URN purposes, of the object.
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string parent = 4; // an optional parent URN that this child resource belongs to.
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google.protobuf.Struct properties = 5; // optional state sufficient to uniquely identify the resource.
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2018-08-03 23:06:00 +02:00
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repeated string dependencies = 6; // a list of URNs that this read depends on, as observed by the language host.
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Implement first-class providers. (#1695)
### First-Class Providers
These changes implement support for first-class providers. First-class
providers are provider plugins that are exposed as resources via the
Pulumi programming model so that they may be explicitly and multiply
instantiated. Each instance of a provider resource may be configured
differently, and configuration parameters may be source from the
outputs of other resources.
### Provider Plugin Changes
In order to accommodate the need to verify and diff provider
configuration and configure providers without complete configuration
information, these changes adjust the high-level provider plugin
interface. Two new methods for validating a provider's configuration
and diffing changes to the same have been added (`CheckConfig` and
`DiffConfig`, respectively), and the type of the configuration bag
accepted by `Configure` has been changed to a `PropertyMap`.
These changes have not yet been reflected in the provider plugin gRPC
interface. We will do this in a set of follow-up changes. Until then,
these methods are implemented by adapters:
- `CheckConfig` validates that all configuration parameters are string
or unknown properties. This is necessary because existing plugins
only accept string-typed configuration values.
- `DiffConfig` either returns "never replace" if all configuration
values are known or "must replace" if any configuration value is
unknown. The justification for this behavior is given
[here](https://github.com/pulumi/pulumi/pull/1695/files#diff-a6cd5c7f337665f5bb22e92ca5f07537R106)
- `Configure` converts the config bag to a legacy config map and
configures the provider plugin if all config values are known. If any
config value is unknown, the underlying plugin is not configured and
the provider may only perform `Check`, `Read`, and `Invoke`, all of
which return empty results. We justify this behavior becuase it is
only possible during a preview and provides the best experience we
can manage with the existing gRPC interface.
### Resource Model Changes
Providers are now exposed as resources that participate in a stack's
dependency graph. Like other resources, they are explicitly created,
may have multiple instances, and may have dependencies on other
resources. Providers are referred to using provider references, which
are a combination of the provider's URN and its ID. This design
addresses the need during a preview to refer to providers that have not
yet been physically created and therefore have no ID.
All custom resources that are not themselves providers must specify a
single provider via a provider reference. The named provider will be
used to manage that resource's CRUD operations. If a resource's
provider reference changes, the resource must be replaced. Though its
URN is not present in the resource's dependency list, the provider
should be treated as a dependency of the resource when topologically
sorting the dependency graph.
Finally, `Invoke` operations must now specify a provider to use for the
invocation via a provider reference.
### Engine Changes
First-class providers support requires a few changes to the engine:
- The engine must have some way to map from provider references to
provider plugins. It must be possible to add providers from a stack's
checkpoint to this map and to register new/updated providers during
the execution of a plan in response to CRUD operations on provider
resources.
- In order to support updating existing stacks using existing Pulumi
programs that may not explicitly instantiate providers, the engine
must be able to manage the "default" providers for each package
referenced by a checkpoint or Pulumi program. The configuration for
a "default" provider is taken from the stack's configuration data.
The former need is addressed by adding a provider registry type that is
responsible for managing all of the plugins required by a plan. In
addition to loading plugins froma checkpoint and providing the ability
to map from a provider reference to a provider plugin, this type serves
as the provider plugin for providers themselves (i.e. it is the
"provider provider").
The latter need is solved via two relatively self-contained changes to
plan setup and the eval source.
During plan setup, the old checkpoint is scanned for custom resources
that do not have a provider reference in order to compute the set of
packages that require a default provider. Once this set has been
computed, the required default provider definitions are conjured and
prepended to the checkpoint's resource list. Each resource that
requires a default provider is then updated to refer to the default
provider for its package.
While an eval source is running, each custom resource registration,
resource read, and invoke that does not name a provider is trapped
before being returned by the source iterator. If no default provider
for the appropriate package has been registered, the eval source
synthesizes an appropriate registration, waits for it to complete, and
records the registered provider's reference. This reference is injected
into the original request, which is then processed as usual. If a
default provider was already registered, the recorded reference is
used and no new registration occurs.
### SDK Changes
These changes only expose first-class providers from the Node.JS SDK.
- A new abstract class, `ProviderResource`, can be subclassed and used
to instantiate first-class providers.
- A new field in `ResourceOptions`, `provider`, can be used to supply
a particular provider instance to manage a `CustomResource`'s CRUD
operations.
- A new type, `InvokeOptions`, can be used to specify options that
control the behavior of a call to `pulumi.runtime.invoke`. This type
includes a `provider` field that is analogous to
`ResourceOptions.provider`.
2018-08-07 02:50:29 +02:00
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string provider = 7; // an optional reference to the provider to use for this read.
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2018-04-05 18:48:09 +02:00
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}
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// ReadResourceResponse contains the result of reading a resource's state.
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message ReadResourceResponse {
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string urn = 1; // the URN for this resource.
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google.protobuf.Struct properties = 2; // the state of the resource read from the live environment.
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}
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2017-11-29 20:27:32 +01:00
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// RegisterResourceRequest contains information about a resource object that was newly allocated.
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message RegisterResourceRequest {
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Implement more precise delete-before-replace semantics. (#2369)
This implements the new algorithm for deciding which resources must be
deleted due to a delete-before-replace operation.
We need to compute the set of resources that may be replaced by a
change to the resource under consideration. We do this by taking the
complete set of transitive dependents on the resource under
consideration and removing any resources that would not be replaced by
changes to their dependencies. We determine whether or not a resource
may be replaced by substituting unknowns for input properties that may
change due to deletion of the resources their value depends on and
calling the resource provider's Diff method.
This is perhaps clearer when described by example. Consider the
following dependency graph:
A
__|__
B C
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D E F
In this graph, all of B, C, D, E, and F transitively depend on A. It may
be the case, however, that changes to the specific properties of any of
those resources R that would occur if a resource on the path to A were
deleted and recreated may not cause R to be replaced. For example, the
edge from B to A may be a simple dependsOn edge such that a change to
B does not actually influence any of B's input properties. In that case,
neither B nor D would need to be deleted before A could be deleted.
In order to make the above algorithm a reality, the resource monitor
interface has been updated to include a map that associates an input
property key with the list of resources that input property depends on.
Older clients of the resource monitor will leave this map empty, in
which case all input properties will be treated as depending on all
dependencies of the resource. This is probably overly conservative, but
it is less conservative than what we currently implement, and is
certainly correct.
2019-01-28 18:46:30 +01:00
|
|
|
// PropertyDependencies describes the resources that a particular property depends on.
|
|
|
|
message PropertyDependencies {
|
|
|
|
repeated string urns = 1; // A list of URNs this property depends on.
|
|
|
|
}
|
|
|
|
|
Implement initial Lumi-as-a-library
This is the initial step towards redefining Lumi as a library that runs
atop vanilla Node.js/V8, rather than as its own runtime.
This change is woefully incomplete but this includes some of the more
stable pieces of my current work-in-progress.
The new structure is that within the sdk/ directory we will have a client
library per language. This client library contains the object model for
Lumi (resources, properties, assets, config, etc), in addition to the
"language runtime host" components required to interoperate with the
Lumi resource monitor. This resource monitor is effectively what we call
"Lumi" today, in that it's the thing orchestrating plans and deployments.
Inside the sdk/ directory, you will find nodejs/, the Node.js client
library, alongside proto/, the definitions for RPC interop between the
different pieces of the system. This includes existing RPC definitions
for resource providers, etc., in addition to the new ones for hosting
different language runtimes from within Lumi.
These new interfaces are surprisingly simple. There is effectively a
bidirectional RPC channel between the Lumi resource monitor, represented
by the lumirpc.ResourceMonitor interface, and each language runtime,
represented by the lumirpc.LanguageRuntime interface.
The overall orchestration goes as follows:
1) Lumi decides it needs to run a program written in language X, so
it dynamically loads the language runtime plugin for language X.
2) Lumi passes that runtime a loopback address to its ResourceMonitor
service, while language X will publish a connection back to its
LanguageRuntime service, which Lumi will talk to.
3) Lumi then invokes LanguageRuntime.Run, passing information like
the desired working directory, program name, arguments, and optional
configuration variables to make available to the program.
4) The language X runtime receives this, unpacks it and sets up the
necessary context, and then invokes the program. The program then
calls into Lumi object model abstractions that internally communicate
back to Lumi using the ResourceMonitor interface.
5) The key here is ResourceMonitor.NewResource, which Lumi uses to
serialize state about newly allocated resources. Lumi receives these
and registers them as part of the plan, doing the usual diffing, etc.,
to decide how to proceed. This interface is perhaps one of the
most subtle parts of the new design, as it necessitates the use of
promises internally to allow parallel evaluation of the resource plan,
letting dataflow determine the available concurrency.
6) The program exits, and Lumi continues on its merry way. If the program
fails, the RunResponse will include information about the failure.
Due to (5), all properties on resources are now instances of a new
Property<T> type. A Property<T> is just a thin wrapper over a T, but it
encodes the special properties of Lumi resource properties. Namely, it
is possible to create one out of a T, other Property<T>, Promise<T>, or
to freshly allocate one. In all cases, the Property<T> does not "settle"
until its final state is known. This cannot occur before the deployment
actually completes, and so in general it's not safe to depend on concrete
resolutions of values (unlike ordinary Promise<T>s which are usually
expected to resolve). As a result, all derived computations are meant to
use the `then` function (as in `someValue.then(v => v+x)`).
Although this change includes tests that may be run in isolation to test
the various RPC interactions, we are nowhere near finished. The remaining
work primarily boils down to three things:
1) Wiring all of this up to the Lumi code.
2) Fixing the handful of known loose ends required to make this work,
primarily around the serialization of properties (waiting on
unresolved ones, serializing assets properly, etc).
3) Implementing lambda closure serialization as a native extension.
This ongoing work is part of pulumi/pulumi-fabric#311.
2017-08-26 21:07:54 +02:00
|
|
|
string type = 1; // the type of the object allocated.
|
|
|
|
string name = 2; // the name, for URN purposes, of the object.
|
2017-11-17 03:21:41 +01:00
|
|
|
string parent = 3; // an optional parent URN that this child resource belongs to.
|
2017-10-15 12:52:04 +02:00
|
|
|
bool custom = 4; // true if the resource is a custom, managed by a plugin's CRUD operations.
|
Implement components
This change implements core support for "components" in the Pulumi
Fabric. This work is described further in pulumi/pulumi#340, where
we are still discussing some of the finer points.
In a nutshell, resources no longer imply external providers. It's
entirely possible to have a resource that logically represents
something but without having a physical manifestation that needs to
be tracked and managed by our typical CRUD operations.
For example, the aws/serverless/Function helper is one such type.
It aggregates Lambda-related resources and exposes a nice interface.
All of the Pulumi Cloud Framework resources are also examples.
To indicate that a resource does participate in the usual CRUD resource
provider, it simply derives from ExternalResource instead of Resource.
All resources now have the ability to adopt children. This is purely
a metadata/tagging thing, and will help us roll up displays, provide
attribution to the developer, and even hide aspects of the resource
graph as appropriate (e.g., when they are implementation details).
Our use of this capability is ultra limited right now; in fact, the
only place we display children is in the CLI output. For instance:
+ aws:serverless:Function: (create)
[urn=urn:pulumi:demo::serverless::aws:serverless:Function::mylambda]
=> urn:pulumi:demo::serverless::aws:iam/role:Role::mylambda-iamrole
=> urn:pulumi:demo::serverless::aws:iam/rolePolicyAttachment:RolePolicyAttachment::mylambda-iampolicy-0
=> urn:pulumi:demo::serverless::aws:lambda/function:Function::mylambda
The bit indicating whether a resource is external or not is tracked
in the resulting checkpoint file, along with any of its children.
2017-10-14 23:18:43 +02:00
|
|
|
google.protobuf.Struct object = 5; // an object produced by the interpreter/source.
|
Implement resource protection (#751)
This change implements resource protection, as per pulumi/pulumi#689.
The overall idea is that a resource can be marked as "protect: true",
which will prevent deletion of that resource for any reason whatsoever
(straight deletion, replacement, etc). This is expressed in the
program. To "unprotect" a resource, one must perform an update setting
"protect: false", and then afterwards, they can delete the resource.
For example:
let res = new MyResource("precious", { .. }, { protect: true });
Afterwards, the resource will display in the CLI with a lock icon, and
any attempts to remove it will fail in the usual ways (in planning or,
worst case, during an actual update).
This was done by adding a new ResourceOptions bag parameter to the
base Resource types. This is unfortunately a breaking change, but now
is the right time to take this one. We had been adding new settings
one by one -- like parent and dependsOn -- and this new approach will
set us up to add any number of additional settings down the road,
without needing to worry about breaking anything ever again.
This is related to protected stacks, as described in
pulumi/pulumi-service#399. Most likely this will serve as a foundational
building block that enables the coarser grained policy management.
2017-12-20 23:31:07 +01:00
|
|
|
bool protect = 6; // true if the resource should be marked protected.
|
2018-02-22 00:11:21 +01:00
|
|
|
repeated string dependencies = 7; // a list of URNs that this resource depends on, as observed by the language host.
|
Implement first-class providers. (#1695)
### First-Class Providers
These changes implement support for first-class providers. First-class
providers are provider plugins that are exposed as resources via the
Pulumi programming model so that they may be explicitly and multiply
instantiated. Each instance of a provider resource may be configured
differently, and configuration parameters may be source from the
outputs of other resources.
### Provider Plugin Changes
In order to accommodate the need to verify and diff provider
configuration and configure providers without complete configuration
information, these changes adjust the high-level provider plugin
interface. Two new methods for validating a provider's configuration
and diffing changes to the same have been added (`CheckConfig` and
`DiffConfig`, respectively), and the type of the configuration bag
accepted by `Configure` has been changed to a `PropertyMap`.
These changes have not yet been reflected in the provider plugin gRPC
interface. We will do this in a set of follow-up changes. Until then,
these methods are implemented by adapters:
- `CheckConfig` validates that all configuration parameters are string
or unknown properties. This is necessary because existing plugins
only accept string-typed configuration values.
- `DiffConfig` either returns "never replace" if all configuration
values are known or "must replace" if any configuration value is
unknown. The justification for this behavior is given
[here](https://github.com/pulumi/pulumi/pull/1695/files#diff-a6cd5c7f337665f5bb22e92ca5f07537R106)
- `Configure` converts the config bag to a legacy config map and
configures the provider plugin if all config values are known. If any
config value is unknown, the underlying plugin is not configured and
the provider may only perform `Check`, `Read`, and `Invoke`, all of
which return empty results. We justify this behavior becuase it is
only possible during a preview and provides the best experience we
can manage with the existing gRPC interface.
### Resource Model Changes
Providers are now exposed as resources that participate in a stack's
dependency graph. Like other resources, they are explicitly created,
may have multiple instances, and may have dependencies on other
resources. Providers are referred to using provider references, which
are a combination of the provider's URN and its ID. This design
addresses the need during a preview to refer to providers that have not
yet been physically created and therefore have no ID.
All custom resources that are not themselves providers must specify a
single provider via a provider reference. The named provider will be
used to manage that resource's CRUD operations. If a resource's
provider reference changes, the resource must be replaced. Though its
URN is not present in the resource's dependency list, the provider
should be treated as a dependency of the resource when topologically
sorting the dependency graph.
Finally, `Invoke` operations must now specify a provider to use for the
invocation via a provider reference.
### Engine Changes
First-class providers support requires a few changes to the engine:
- The engine must have some way to map from provider references to
provider plugins. It must be possible to add providers from a stack's
checkpoint to this map and to register new/updated providers during
the execution of a plan in response to CRUD operations on provider
resources.
- In order to support updating existing stacks using existing Pulumi
programs that may not explicitly instantiate providers, the engine
must be able to manage the "default" providers for each package
referenced by a checkpoint or Pulumi program. The configuration for
a "default" provider is taken from the stack's configuration data.
The former need is addressed by adding a provider registry type that is
responsible for managing all of the plugins required by a plan. In
addition to loading plugins froma checkpoint and providing the ability
to map from a provider reference to a provider plugin, this type serves
as the provider plugin for providers themselves (i.e. it is the
"provider provider").
The latter need is solved via two relatively self-contained changes to
plan setup and the eval source.
During plan setup, the old checkpoint is scanned for custom resources
that do not have a provider reference in order to compute the set of
packages that require a default provider. Once this set has been
computed, the required default provider definitions are conjured and
prepended to the checkpoint's resource list. Each resource that
requires a default provider is then updated to refer to the default
provider for its package.
While an eval source is running, each custom resource registration,
resource read, and invoke that does not name a provider is trapped
before being returned by the source iterator. If no default provider
for the appropriate package has been registered, the eval source
synthesizes an appropriate registration, waits for it to complete, and
records the registered provider's reference. This reference is injected
into the original request, which is then processed as usual. If a
default provider was already registered, the recorded reference is
used and no new registration occurs.
### SDK Changes
These changes only expose first-class providers from the Node.JS SDK.
- A new abstract class, `ProviderResource`, can be subclassed and used
to instantiate first-class providers.
- A new field in `ResourceOptions`, `provider`, can be used to supply
a particular provider instance to manage a `CustomResource`'s CRUD
operations.
- A new type, `InvokeOptions`, can be used to specify options that
control the behavior of a call to `pulumi.runtime.invoke`. This type
includes a `provider` field that is analogous to
`ResourceOptions.provider`.
2018-08-07 02:50:29 +02:00
|
|
|
string provider = 8; // an optional reference to the provider to manage this resource's CRUD operations.
|
Implement more precise delete-before-replace semantics. (#2369)
This implements the new algorithm for deciding which resources must be
deleted due to a delete-before-replace operation.
We need to compute the set of resources that may be replaced by a
change to the resource under consideration. We do this by taking the
complete set of transitive dependents on the resource under
consideration and removing any resources that would not be replaced by
changes to their dependencies. We determine whether or not a resource
may be replaced by substituting unknowns for input properties that may
change due to deletion of the resources their value depends on and
calling the resource provider's Diff method.
This is perhaps clearer when described by example. Consider the
following dependency graph:
A
__|__
B C
| _|_
D E F
In this graph, all of B, C, D, E, and F transitively depend on A. It may
be the case, however, that changes to the specific properties of any of
those resources R that would occur if a resource on the path to A were
deleted and recreated may not cause R to be replaced. For example, the
edge from B to A may be a simple dependsOn edge such that a change to
B does not actually influence any of B's input properties. In that case,
neither B nor D would need to be deleted before A could be deleted.
In order to make the above algorithm a reality, the resource monitor
interface has been updated to include a map that associates an input
property key with the list of resources that input property depends on.
Older clients of the resource monitor will leave this map empty, in
which case all input properties will be treated as depending on all
dependencies of the resource. This is probably overly conservative, but
it is less conservative than what we currently implement, and is
certainly correct.
2019-01-28 18:46:30 +01:00
|
|
|
map<string, PropertyDependencies> propertyDependencies = 9; // a map from property keys to the dependencies of the property.
|
2019-01-31 23:27:53 +01:00
|
|
|
bool deleteBeforeReplace = 10; // true if this resource should be deleted before replacement.
|
Implement initial Lumi-as-a-library
This is the initial step towards redefining Lumi as a library that runs
atop vanilla Node.js/V8, rather than as its own runtime.
This change is woefully incomplete but this includes some of the more
stable pieces of my current work-in-progress.
The new structure is that within the sdk/ directory we will have a client
library per language. This client library contains the object model for
Lumi (resources, properties, assets, config, etc), in addition to the
"language runtime host" components required to interoperate with the
Lumi resource monitor. This resource monitor is effectively what we call
"Lumi" today, in that it's the thing orchestrating plans and deployments.
Inside the sdk/ directory, you will find nodejs/, the Node.js client
library, alongside proto/, the definitions for RPC interop between the
different pieces of the system. This includes existing RPC definitions
for resource providers, etc., in addition to the new ones for hosting
different language runtimes from within Lumi.
These new interfaces are surprisingly simple. There is effectively a
bidirectional RPC channel between the Lumi resource monitor, represented
by the lumirpc.ResourceMonitor interface, and each language runtime,
represented by the lumirpc.LanguageRuntime interface.
The overall orchestration goes as follows:
1) Lumi decides it needs to run a program written in language X, so
it dynamically loads the language runtime plugin for language X.
2) Lumi passes that runtime a loopback address to its ResourceMonitor
service, while language X will publish a connection back to its
LanguageRuntime service, which Lumi will talk to.
3) Lumi then invokes LanguageRuntime.Run, passing information like
the desired working directory, program name, arguments, and optional
configuration variables to make available to the program.
4) The language X runtime receives this, unpacks it and sets up the
necessary context, and then invokes the program. The program then
calls into Lumi object model abstractions that internally communicate
back to Lumi using the ResourceMonitor interface.
5) The key here is ResourceMonitor.NewResource, which Lumi uses to
serialize state about newly allocated resources. Lumi receives these
and registers them as part of the plan, doing the usual diffing, etc.,
to decide how to proceed. This interface is perhaps one of the
most subtle parts of the new design, as it necessitates the use of
promises internally to allow parallel evaluation of the resource plan,
letting dataflow determine the available concurrency.
6) The program exits, and Lumi continues on its merry way. If the program
fails, the RunResponse will include information about the failure.
Due to (5), all properties on resources are now instances of a new
Property<T> type. A Property<T> is just a thin wrapper over a T, but it
encodes the special properties of Lumi resource properties. Namely, it
is possible to create one out of a T, other Property<T>, Promise<T>, or
to freshly allocate one. In all cases, the Property<T> does not "settle"
until its final state is known. This cannot occur before the deployment
actually completes, and so in general it's not safe to depend on concrete
resolutions of values (unlike ordinary Promise<T>s which are usually
expected to resolve). As a result, all derived computations are meant to
use the `then` function (as in `someValue.then(v => v+x)`).
Although this change includes tests that may be run in isolation to test
the various RPC interactions, we are nowhere near finished. The remaining
work primarily boils down to three things:
1) Wiring all of this up to the Lumi code.
2) Fixing the handful of known loose ends required to make this work,
primarily around the serialization of properties (waiting on
unresolved ones, serializing assets properly, etc).
3) Implementing lambda closure serialization as a native extension.
This ongoing work is part of pulumi/pulumi-fabric#311.
2017-08-26 21:07:54 +02:00
|
|
|
}
|
|
|
|
|
2017-11-29 20:27:32 +01:00
|
|
|
// RegisterResourceResponse is returned by the engine after a resource has finished being initialized. It includes the
|
|
|
|
// auto-assigned URN, the provider-assigned ID, and any other properties initialized by the engine.
|
|
|
|
message RegisterResourceResponse {
|
2018-04-05 18:48:09 +02:00
|
|
|
string urn = 1; // the URN assigned by the engine.
|
2017-11-29 20:27:32 +01:00
|
|
|
string id = 2; // the unique ID assigned by the provider.
|
|
|
|
google.protobuf.Struct object = 3; // the resulting object properties, including provider defaults.
|
|
|
|
bool stable = 4; // if true, the object's state is stable and may be trusted not to change.
|
|
|
|
repeated string stables = 5; // an optional list of guaranteed-stable properties.
|
2017-11-21 02:38:09 +01:00
|
|
|
}
|
|
|
|
|
2017-11-29 20:27:32 +01:00
|
|
|
// RegisterResourceOutputsRequest adds extra resource outputs created by the program after registration has occurred.
|
|
|
|
message RegisterResourceOutputsRequest {
|
|
|
|
string urn = 1; // the URN for the resource to attach output properties to.
|
|
|
|
google.protobuf.Struct outputs = 2; // additional output properties to add to the existing resource.
|
Implement initial Lumi-as-a-library
This is the initial step towards redefining Lumi as a library that runs
atop vanilla Node.js/V8, rather than as its own runtime.
This change is woefully incomplete but this includes some of the more
stable pieces of my current work-in-progress.
The new structure is that within the sdk/ directory we will have a client
library per language. This client library contains the object model for
Lumi (resources, properties, assets, config, etc), in addition to the
"language runtime host" components required to interoperate with the
Lumi resource monitor. This resource monitor is effectively what we call
"Lumi" today, in that it's the thing orchestrating plans and deployments.
Inside the sdk/ directory, you will find nodejs/, the Node.js client
library, alongside proto/, the definitions for RPC interop between the
different pieces of the system. This includes existing RPC definitions
for resource providers, etc., in addition to the new ones for hosting
different language runtimes from within Lumi.
These new interfaces are surprisingly simple. There is effectively a
bidirectional RPC channel between the Lumi resource monitor, represented
by the lumirpc.ResourceMonitor interface, and each language runtime,
represented by the lumirpc.LanguageRuntime interface.
The overall orchestration goes as follows:
1) Lumi decides it needs to run a program written in language X, so
it dynamically loads the language runtime plugin for language X.
2) Lumi passes that runtime a loopback address to its ResourceMonitor
service, while language X will publish a connection back to its
LanguageRuntime service, which Lumi will talk to.
3) Lumi then invokes LanguageRuntime.Run, passing information like
the desired working directory, program name, arguments, and optional
configuration variables to make available to the program.
4) The language X runtime receives this, unpacks it and sets up the
necessary context, and then invokes the program. The program then
calls into Lumi object model abstractions that internally communicate
back to Lumi using the ResourceMonitor interface.
5) The key here is ResourceMonitor.NewResource, which Lumi uses to
serialize state about newly allocated resources. Lumi receives these
and registers them as part of the plan, doing the usual diffing, etc.,
to decide how to proceed. This interface is perhaps one of the
most subtle parts of the new design, as it necessitates the use of
promises internally to allow parallel evaluation of the resource plan,
letting dataflow determine the available concurrency.
6) The program exits, and Lumi continues on its merry way. If the program
fails, the RunResponse will include information about the failure.
Due to (5), all properties on resources are now instances of a new
Property<T> type. A Property<T> is just a thin wrapper over a T, but it
encodes the special properties of Lumi resource properties. Namely, it
is possible to create one out of a T, other Property<T>, Promise<T>, or
to freshly allocate one. In all cases, the Property<T> does not "settle"
until its final state is known. This cannot occur before the deployment
actually completes, and so in general it's not safe to depend on concrete
resolutions of values (unlike ordinary Promise<T>s which are usually
expected to resolve). As a result, all derived computations are meant to
use the `then` function (as in `someValue.then(v => v+x)`).
Although this change includes tests that may be run in isolation to test
the various RPC interactions, we are nowhere near finished. The remaining
work primarily boils down to three things:
1) Wiring all of this up to the Lumi code.
2) Fixing the handful of known loose ends required to make this work,
primarily around the serialization of properties (waiting on
unresolved ones, serializing assets properly, etc).
3) Implementing lambda closure serialization as a native extension.
This ongoing work is part of pulumi/pulumi-fabric#311.
2017-08-26 21:07:54 +02:00
|
|
|
}
|