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
|
|
|
{
|
2017-08-31 19:45:48 +02:00
|
|
|
"name": "@pulumi/pulumi-fabric",
|
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
|
|
|
"version": "0.0.1",
|
|
|
|
|
"description": "Pulumi's Fabric Node.js SDK",
|
|
|
|
|
"repository": "https://github.com/pulumi/pulumi-fabric/sdk/nodejs",
|
2017-09-02 01:00:16 +02:00
|
|
|
"main": "bin/index.js",
|
|
|
|
|
"typings": "bin/index.d.ts",
|
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
|
|
|
"scripts": {
|
Take an initial stab at closure serialization
This change contains an initial implementation of closure serialization
built atop V8, rather than our own custom runtime. This requires that
we use a Node.js dynamic C++ module, so that we can access the V8
APIs directly. No build magic is required beyond node-gyp.
For the most part, this was straight forward, except for one part: we
have to use internal V8 APIs. This is required for two reasons:
1) We need access to the function's lexical closure environment, so
that we may look up closure variables. Although there is a
tantalizingly-close v8::Object::CreationContext, its implementation
intentionally pokes through closure contexts in order to recover
the Function constructor context instead. That's not what we
want. We want the raw, unadulterated Function::context.
2) We need to control the lexical lookups of free variables so that
they can look past chained contexts, lexical contexts, withs, and
eval-style context extensions. Simply runing a v8::Script, or
simulating an eval, doesn't do the trick. Hence, we need to access
the unexported v8::internal::Context::Lookup function.
There is a third reason which is not yet implemented: free variable
calculation. I could use Esprima, or do my own scanner for free
variables, but I'd prefer to simply use the V8 parser so that we're
using the same JavaScript parser across all components. That too
is not part of the v8.h API, so we'll need to crack it open more.
To be clear, these are still exported public APIs, in proper headers
that are distributed with both Node and V8. They simply aren't part
of the "stable" v8.h surface area. As a result, I do expect that
maintaining this will be tricky, and I'd like to keep exploring how
to do this without needing the internal dependency. For instance,
although this works with node-gyp just fine, we will probably be
brittle across versions of Node/V8, when the internal APIs might be
changing. This will introduce unfortunate versioning headaches (all,
hopefully and thankfully, caught at compile-time).
2017-09-02 22:09:28 +02:00
|
|
|
"clean": "rm -rf bin/ && rm -rf runtime/native/build",
|
2017-09-04 20:26:35 +02:00
|
|
|
"build": "yarn run copyprotos && yarn run buildnative && tsc && yarn run binplace && yarn run lint",
|
2017-09-03 18:51:25 +02:00
|
|
|
"buildnative": "cd runtime/native/ && node-gyp build",
|
2017-09-04 20:26:35 +02:00
|
|
|
"lint": "tslint '{,!(node_modules|bin)/**/}*.ts'",
|
2017-09-02 01:00:16 +02:00
|
|
|
"copyprotos": "cp -r ../proto/nodejs proto/",
|
|
|
|
|
"binplaceprotos": "cp -r proto/ bin/proto/",
|
Take an initial stab at closure serialization
This change contains an initial implementation of closure serialization
built atop V8, rather than our own custom runtime. This requires that
we use a Node.js dynamic C++ module, so that we can access the V8
APIs directly. No build magic is required beyond node-gyp.
For the most part, this was straight forward, except for one part: we
have to use internal V8 APIs. This is required for two reasons:
1) We need access to the function's lexical closure environment, so
that we may look up closure variables. Although there is a
tantalizingly-close v8::Object::CreationContext, its implementation
intentionally pokes through closure contexts in order to recover
the Function constructor context instead. That's not what we
want. We want the raw, unadulterated Function::context.
2) We need to control the lexical lookups of free variables so that
they can look past chained contexts, lexical contexts, withs, and
eval-style context extensions. Simply runing a v8::Script, or
simulating an eval, doesn't do the trick. Hence, we need to access
the unexported v8::internal::Context::Lookup function.
There is a third reason which is not yet implemented: free variable
calculation. I could use Esprima, or do my own scanner for free
variables, but I'd prefer to simply use the V8 parser so that we're
using the same JavaScript parser across all components. That too
is not part of the v8.h API, so we'll need to crack it open more.
To be clear, these are still exported public APIs, in proper headers
that are distributed with both Node and V8. They simply aren't part
of the "stable" v8.h surface area. As a result, I do expect that
maintaining this will be tricky, and I'd like to keep exploring how
to do this without needing the internal dependency. For instance,
although this works with node-gyp just fine, we will probably be
brittle across versions of Node/V8, when the internal APIs might be
changing. This will introduce unfortunate versioning headaches (all,
hopefully and thankfully, caught at compile-time).
2017-09-02 22:09:28 +02:00
|
|
|
"binplacenative": "mkdir -p bin/runtime/native/build/ && cp -r runtime/native/build/ bin/runtime/native/build/",
|
Implement free variable calculations
This change implements free variable calculations and wires it up
to closure serialization. This is recursive, in the sense that
the serializer may need to call back to fetch free variables for
nested functions encountered during serialization.
The free variable calculation works by parsing the serialized
function text and walking the AST, applying the usual scoping rules
to determine what is free. In particular, it respects nested
function boundaries, and rules around var, let, and const scoping.
We are using Acorn to perform the parsing. I'd originally gone
down the path of using V8, so that we have one consistent parser
in the game, however unfortunately neither V8's parser nor its AST
is a stable API meant for 3rd parties. Unlike the exising internal
V8 dependencies, this one got very deep very quickly, and I became
nervous about maintaining all those dependencies. Furthermore,
by doing it this way, we can write the free variable logic in
JavaScript, which means one fewer C++ component to maintain.
This also includes a fairly significant amount of testing, all
of which passes! :tada:
2017-09-03 18:38:16 +02:00
|
|
|
"binplacetestdata": "mkdir -p bin/tests/runtime/langhost/cases/ && find tests/runtime/langhost/cases/* -type d -exec cp -R {} bin/tests/runtime/langhost/cases/ \\;",
|
2017-09-04 20:26:35 +02:00
|
|
|
"binplace": "yarn run binplaceprotos && yarn run binplacenative && yarn run binplacetestdata",
|
|
|
|
|
"test": "yarn run cov && yarn run covreport",
|
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
|
|
|
"cov": "istanbul cover --print none node_modules/.bin/_mocha -- --timeout 15000 'bin/tests/**/*.spec.js'",
|
|
|
|
|
"covreport": "istanbul report text-summary && istanbul report text"
|
|
|
|
|
},
|
|
|
|
|
"devDependencies": {
|
|
|
|
|
"@types/minimist": "^1.2.0",
|
|
|
|
|
"@types/mocha": "^2.2.42",
|
|
|
|
|
"@types/node": "^8.0.25",
|
|
|
|
|
"istanbul": "^0.4.5",
|
|
|
|
|
"mocha": "^3.5.0",
|
2017-09-03 18:51:25 +02:00
|
|
|
"node-gyp": "^3.6.2",
|
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
|
|
|
"tslint": "^5.6.0",
|
|
|
|
|
"typescript": "^2.1.4"
|
|
|
|
|
},
|
|
|
|
|
"dependencies": {
|
Implement free variable calculations
This change implements free variable calculations and wires it up
to closure serialization. This is recursive, in the sense that
the serializer may need to call back to fetch free variables for
nested functions encountered during serialization.
The free variable calculation works by parsing the serialized
function text and walking the AST, applying the usual scoping rules
to determine what is free. In particular, it respects nested
function boundaries, and rules around var, let, and const scoping.
We are using Acorn to perform the parsing. I'd originally gone
down the path of using V8, so that we have one consistent parser
in the game, however unfortunately neither V8's parser nor its AST
is a stable API meant for 3rd parties. Unlike the exising internal
V8 dependencies, this one got very deep very quickly, and I became
nervous about maintaining all those dependencies. Furthermore,
by doing it this way, we can write the free variable logic in
JavaScript, which means one fewer C++ component to maintain.
This also includes a fairly significant amount of testing, all
of which passes! :tada:
2017-09-03 18:38:16 +02:00
|
|
|
"@types/acorn": "^4.0.2",
|
|
|
|
|
"acorn": "^5.1.1",
|
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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"google-protobuf": "^3.4.0",
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"grpc": "^1.4.1",
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"minimist": "^1.2.0",
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"source-map-support": "^0.4.16"
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}
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}
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