pulumi/sdk/proto/languages.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
// Copyright 2016-2017, Pulumi Corporation. All rights reserved.
syntax = "proto3";
import "google/protobuf/struct.proto";
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
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.
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// LanguageRuntime is the interface that the planning monitor uses to drive execution of an interpreter responsible
// for confguring and creating resource objects.
service LanguageRuntime {
rpc Run(RunRequest) returns (RunResponse) {}
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.
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}
// RunRequest asks the interpreter to execute a program.
message RunRequest {
string project = 1; // the project name.
string stack = 2; // the name of the stack being deployed into.
string pwd = 3; // the program's working directory.
string program = 4; // the path to the program to execute.
repeated string args = 5; // any arguments to pass to the program.
map<string, string> config = 6; // the configuration variables to apply before running.
bool dryRun = 7; // true if we're only doing a dryrun (preview).
int32 parallel = 8; // the degree of parallelism for resource operations (<=1 for serial).
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
}
// RunResponse is the response back from the interpreter/source back to the monitor.
message RunResponse {
string error = 1; // an unhandled error if any occurred.
}
// ResourceMonitor is the interface a source uses to talk back to the planning monitor orchestrating the execution.
service ResourceMonitor {
rpc Invoke(InvokeRequest) returns (InvokeResponse) {}
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
rpc NewResource(NewResourceRequest) returns (NewResourceResponse) {}
}
// NewResourceRequest contains information about a resource object that was newly allocated.
message NewResourceRequest {
string type = 1; // the type of the object allocated.
string name = 2; // the name, for URN purposes, of the object.
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
repeated string children = 3; // an optional list of child URNs belonging to this parent resource.
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
}
// NewResourceResponse reflects back the properties initialized during creation, if applicable.
message NewResourceResponse {
string id = 1; // the unique ID assigned by the provider.
string urn = 2; // the URN assigned by the fabric.
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.
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
}