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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|
// Copyright 2016-2017, Pulumi Corporation. All rights reserved.
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|
syntax = "proto3";
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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";
|
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;
|
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
|
|
|
|
|
|
|
// 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) {}
|
Bring back component outputs
This change brings back component outputs to the overall system again.
In doing so, it generally overhauls the way we do resource RPCs a bit:
* Instead of RegisterResource and CompleteResource, we call these
BeginRegisterResource and EndRegisterResource, which begins to model
these as effectively "asynchronous" resource requests. This should also
help with parallelism (https://github.com/pulumi/pulumi/issues/106).
* Flip the CLI/engine a little on its head. Rather than it driving the
planning and deployment process, we move more to a model where it
simply observes it. This is done by implementing an event handler
interface with three events: OnResourceStepPre, OnResourceStepPost,
and OnResourceComplete. The first two are invoked immediately before
and after any step operation, and the latter is invoked whenever a
EndRegisterResource comes in. The reason for the asymmetry here is
that the checkpointing logic in the deployment engine is largely
untouched (intentionally, as this is a sensitive part of the system),
and so the "begin"/"end" nature doesn't flow through faithfully.
* Also make the engine more event-oriented in its terminology and the
way it handles the incoming BeginRegisterResource and
EndRegisterResource events from the language host. This is the first
step down a long road of incrementally refactoring the engine to work
this way, a necessary prerequisite for parallelism.
2017-11-29 16:42:14 +01:00
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rpc BeginRegisterResource(BeginRegisterResourceRequest) returns (BeginRegisterResourceResponse) {}
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rpc EndRegisterResource(EndRegisterResourceRequest) returns (EndRegisterResourceResponse) {}
|
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
|
|
|
}
|
|
|
|
|
Bring back component outputs
This change brings back component outputs to the overall system again.
In doing so, it generally overhauls the way we do resource RPCs a bit:
* Instead of RegisterResource and CompleteResource, we call these
BeginRegisterResource and EndRegisterResource, which begins to model
these as effectively "asynchronous" resource requests. This should also
help with parallelism (https://github.com/pulumi/pulumi/issues/106).
* Flip the CLI/engine a little on its head. Rather than it driving the
planning and deployment process, we move more to a model where it
simply observes it. This is done by implementing an event handler
interface with three events: OnResourceStepPre, OnResourceStepPost,
and OnResourceComplete. The first two are invoked immediately before
and after any step operation, and the latter is invoked whenever a
EndRegisterResource comes in. The reason for the asymmetry here is
that the checkpointing logic in the deployment engine is largely
untouched (intentionally, as this is a sensitive part of the system),
and so the "begin"/"end" nature doesn't flow through faithfully.
* Also make the engine more event-oriented in its terminology and the
way it handles the incoming BeginRegisterResource and
EndRegisterResource events from the language host. This is the first
step down a long road of incrementally refactoring the engine to work
this way, a necessary prerequisite for parallelism.
2017-11-29 16:42:14 +01:00
|
|
|
// BeginRegisterResourceRequest contains information about a resource object that was newly allocated.
|
|
|
|
message BeginRegisterResourceRequest {
|
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.
|
|
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string name = 2; // the name, for URN purposes, of the object.
|
2017-11-17 03:21:41 +01:00
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string parent = 3; // an optional parent URN that this child resource belongs to.
|
2017-10-15 12:52:04 +02:00
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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 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
|
|
|
}
|
|
|
|
|
Bring back component outputs
This change brings back component outputs to the overall system again.
In doing so, it generally overhauls the way we do resource RPCs a bit:
* Instead of RegisterResource and CompleteResource, we call these
BeginRegisterResource and EndRegisterResource, which begins to model
these as effectively "asynchronous" resource requests. This should also
help with parallelism (https://github.com/pulumi/pulumi/issues/106).
* Flip the CLI/engine a little on its head. Rather than it driving the
planning and deployment process, we move more to a model where it
simply observes it. This is done by implementing an event handler
interface with three events: OnResourceStepPre, OnResourceStepPost,
and OnResourceComplete. The first two are invoked immediately before
and after any step operation, and the latter is invoked whenever a
EndRegisterResource comes in. The reason for the asymmetry here is
that the checkpointing logic in the deployment engine is largely
untouched (intentionally, as this is a sensitive part of the system),
and so the "begin"/"end" nature doesn't flow through faithfully.
* Also make the engine more event-oriented in its terminology and the
way it handles the incoming BeginRegisterResource and
EndRegisterResource events from the language host. This is the first
step down a long road of incrementally refactoring the engine to work
this way, a necessary prerequisite for parallelism.
2017-11-29 16:42:14 +01:00
|
|
|
// BeginRegisterResourceResponse reflects back the properties initialized during creation, if applicable.
|
|
|
|
message BeginRegisterResourceResponse {
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2017-11-21 02:38:09 +01:00
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string urn = 1; // the URN assigned by the fabric.
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}
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Bring back component outputs
This change brings back component outputs to the overall system again.
In doing so, it generally overhauls the way we do resource RPCs a bit:
* Instead of RegisterResource and CompleteResource, we call these
BeginRegisterResource and EndRegisterResource, which begins to model
these as effectively "asynchronous" resource requests. This should also
help with parallelism (https://github.com/pulumi/pulumi/issues/106).
* Flip the CLI/engine a little on its head. Rather than it driving the
planning and deployment process, we move more to a model where it
simply observes it. This is done by implementing an event handler
interface with three events: OnResourceStepPre, OnResourceStepPost,
and OnResourceComplete. The first two are invoked immediately before
and after any step operation, and the latter is invoked whenever a
EndRegisterResource comes in. The reason for the asymmetry here is
that the checkpointing logic in the deployment engine is largely
untouched (intentionally, as this is a sensitive part of the system),
and so the "begin"/"end" nature doesn't flow through faithfully.
* Also make the engine more event-oriented in its terminology and the
way it handles the incoming BeginRegisterResource and
EndRegisterResource events from the language host. This is the first
step down a long road of incrementally refactoring the engine to work
this way, a necessary prerequisite for parallelism.
2017-11-29 16:42:14 +01:00
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// EndRegisterResourceRequest completes the registration of a resource, and optionally adds extra derived output
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2017-11-21 02:38:09 +01:00
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// properties to an existing resource that is in flight. It must be called once per registration.
|
Bring back component outputs
This change brings back component outputs to the overall system again.
In doing so, it generally overhauls the way we do resource RPCs a bit:
* Instead of RegisterResource and CompleteResource, we call these
BeginRegisterResource and EndRegisterResource, which begins to model
these as effectively "asynchronous" resource requests. This should also
help with parallelism (https://github.com/pulumi/pulumi/issues/106).
* Flip the CLI/engine a little on its head. Rather than it driving the
planning and deployment process, we move more to a model where it
simply observes it. This is done by implementing an event handler
interface with three events: OnResourceStepPre, OnResourceStepPost,
and OnResourceComplete. The first two are invoked immediately before
and after any step operation, and the latter is invoked whenever a
EndRegisterResource comes in. The reason for the asymmetry here is
that the checkpointing logic in the deployment engine is largely
untouched (intentionally, as this is a sensitive part of the system),
and so the "begin"/"end" nature doesn't flow through faithfully.
* Also make the engine more event-oriented in its terminology and the
way it handles the incoming BeginRegisterResource and
EndRegisterResource events from the language host. This is the first
step down a long road of incrementally refactoring the engine to work
this way, a necessary prerequisite for parallelism.
2017-11-29 16:42:14 +01:00
|
|
|
message EndRegisterResourceRequest {
|
2017-11-21 02:38:09 +01:00
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string urn = 1; // the URN for the resource to attach output properties to.
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google.protobuf.Struct extras = 2; // optional additional output properties to add to the existing resource.
|
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}
|
|
|
|
|
Bring back component outputs
This change brings back component outputs to the overall system again.
In doing so, it generally overhauls the way we do resource RPCs a bit:
* Instead of RegisterResource and CompleteResource, we call these
BeginRegisterResource and EndRegisterResource, which begins to model
these as effectively "asynchronous" resource requests. This should also
help with parallelism (https://github.com/pulumi/pulumi/issues/106).
* Flip the CLI/engine a little on its head. Rather than it driving the
planning and deployment process, we move more to a model where it
simply observes it. This is done by implementing an event handler
interface with three events: OnResourceStepPre, OnResourceStepPost,
and OnResourceComplete. The first two are invoked immediately before
and after any step operation, and the latter is invoked whenever a
EndRegisterResource comes in. The reason for the asymmetry here is
that the checkpointing logic in the deployment engine is largely
untouched (intentionally, as this is a sensitive part of the system),
and so the "begin"/"end" nature doesn't flow through faithfully.
* Also make the engine more event-oriented in its terminology and the
way it handles the incoming BeginRegisterResource and
EndRegisterResource events from the language host. This is the first
step down a long road of incrementally refactoring the engine to work
this way, a necessary prerequisite for parallelism.
2017-11-29 16:42:14 +01:00
|
|
|
// EndRegisterResourceResponse is returned by the engine after a resource is completed. It includes any state
|
2017-11-21 02:38:09 +01:00
|
|
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// that was populated by the resource provider so that the language engine can blit it into the resource objects.
|
Bring back component outputs
This change brings back component outputs to the overall system again.
In doing so, it generally overhauls the way we do resource RPCs a bit:
* Instead of RegisterResource and CompleteResource, we call these
BeginRegisterResource and EndRegisterResource, which begins to model
these as effectively "asynchronous" resource requests. This should also
help with parallelism (https://github.com/pulumi/pulumi/issues/106).
* Flip the CLI/engine a little on its head. Rather than it driving the
planning and deployment process, we move more to a model where it
simply observes it. This is done by implementing an event handler
interface with three events: OnResourceStepPre, OnResourceStepPost,
and OnResourceComplete. The first two are invoked immediately before
and after any step operation, and the latter is invoked whenever a
EndRegisterResource comes in. The reason for the asymmetry here is
that the checkpointing logic in the deployment engine is largely
untouched (intentionally, as this is a sensitive part of the system),
and so the "begin"/"end" nature doesn't flow through faithfully.
* Also make the engine more event-oriented in its terminology and the
way it handles the incoming BeginRegisterResource and
EndRegisterResource events from the language host. This is the first
step down a long road of incrementally refactoring the engine to work
this way, a necessary prerequisite for parallelism.
2017-11-29 16:42:14 +01:00
|
|
|
message EndRegisterResourceResponse {
|
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 id = 1; // the unique ID assigned by the provider.
|
2017-11-21 02:38:09 +01:00
|
|
|
google.protobuf.Struct object = 2; // the resulting object properties, including provider defaults.
|
|
|
|
bool stable = 3; // if true, the object's state is stable and may be trusted not to change.
|
|
|
|
repeated string stables = 4; // an optional list of guaranteed-stable properties.
|
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
|
|
|
}
|