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docs/rfcs/xxxx-river.md

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# River: A Flow-optimized config language
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* Date: 2022-06-27
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* Author: Robert Fratto (@rfratto), Matt Durham (@mattdurham)
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* PR: TODO
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* Status: Draft
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## Summary
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Grafana Agent developers have been working towards a feature called Grafana
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Agent Flow ([RFC-0004][]), a component-based re-imagining of Grafana Agent
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which compartmentalize the different configurable pieces of the agent, allowing
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users to more easily understand and debug configuration issues. Grafana Agent
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Flow was purposefully scoped broadly to allow for exploring many different
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component-based approaches for prototyping the experimental feature.
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The current implementation strategy focuses around expressions: settings for
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components can be derived from expressions which can reference and mutate the
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outputs of other components. Values can refer to arbitrary Go values like
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interfaces or channels, enabling component developers to easily allow users to
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construct data pipelines using Go APIs without requiring knowledge of the
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underlying implementation.
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The initial expressions prototype used [HCL][], which Flow's needs at the time.
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However, our growing dependency on passing around arbitrary Go values started
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to conflict with the limitations of HCL, making HCL increasingly insufficient
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for our specific use case.
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We examined alternatives to HCL such as YAML, CUE, Jsonnet, Lua, and Go itself.
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Eventually, we determined that the way we use arbitrary Go values in
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expressions for constructing pipelines is a new use case warranting a
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custom-built language.
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This document proposes River, an HCL-inspired declarative expressions-based
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language for continuous runtime evaluation. The decision to propose a new
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language is not taken lightly, and is seen as the last resort. As such, much of
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this proposal will focus on the rationale leading to this choice.
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## Goals
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* Minimize learning curve as much as possible to reduce friction
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* Make it easy for developers to consume for Flow components
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* Expose error messages in an easily understandable and actionable way
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* Natively support using Go values of any type
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* Natively support passing around and invoking real Go functions
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The language design will be scoped as small as possible, and new features will
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only be added over time as they are determined to be strictly necessary for
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Flow.
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## Non-Goals
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We are not aiming to create a general purpose configuration language. While it
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would be possible for River to eventually be used in different contexts by
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different projects, the primary goal today is specifically targeting Grafana
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Agent Flow.
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We will not provide a full specification for River here, only lightly
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describing it to allow implementation details to change over time.
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## Rationale
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### Why an expression language? Why not YAML?
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The entire rationale for creating a new language depends on the rationale that
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expressions provide a useful amount of capabilities to users. Expressions
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enable users to manipulate values to meet their own use cases in ways that
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otherwise would require dedicated feature work, such as:
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* Allowing users to merge metadata together from distinct sources when adding
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labels to metrics
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* Allowing users to chain Prometheus service discoveries (e.g., feed the output
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of Kubernetes Service Discovery into HTTP Service Discovery)
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* Allowing users to perform custom conditional logic, such as increasing rate
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limits during busier business months.
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Without expressions, we would need more components for common tasks. A
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`concat()` function call can be used to combine lists of discovered Prometheus
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targets, but without expressions, there would likely need to be a dedicated
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component for aggregating sets of targets together.
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The belief is that the work required to use and maintain an expression language
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is far less than the combined work to implement features that would be handled
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by expressions out of the box.
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YAML by itself does not support expressions. While expressions could be added
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to YAML through the use of templates (e.g., `field_a: {{ some_variable + 5
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}}`), it is beyond the scope of what YAML was intended for and would be more
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cumbersome to use compared to a language where expressions are a first-class
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concept.
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### Why an embedded language?
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Embedded languages are typically known for the ability for maintainers of the
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project to expose APIs to users of the embedded language, such as the Lua API
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used by Neovim. Embedded languages typically imply tight integration with the
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application embedding them, as opposed to something like YAML which is a
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language consumed once at load time.
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An embedded language is a good fit for Flow:
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* It makes it easy for developers to expose APIs which users can interact with
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or pass around. These APIs can be opaque arbitrary Go types which the user
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doesn't need to know the detail of, only that it refers to something like a
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stream of metric samples.
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* It is well-suited for continuous evaluation (i.e., the core feature of Flow)
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so configuration can adapt to a changing environment.
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### Why a declarative language? Why not Lua?
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The language Flow relies on should have a minimal learning curve. While a
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language like Lua could likely be a decent fit for Flow, imperative languages
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have steeper learning curves compared to declarative languages.
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Declarative languages natively map to configuration files, since configuration
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files are used to tell the application the desired state, reducing the learning
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curve for the language and making it easier for users to reason about what the
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final config state should be.
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### Why not HCL?
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> For some background, it's important to note that HCL can be considered two
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> separate projects: hashicorp/hcl (the language and expression evaluator) and
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> zclconf/go-cty (the value and type system used by HCL).
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HCL was the obvious first choice for the Flow prototype: it supports
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expressions, you can expose functions for users to call, and its syntax has a
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small learning curve.
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However, I found the [schema-driven processing][] API exposed by HCL to be
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difficult to work with for Flow, requiring a lot of boilerplate. While there is
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a library to interoperate with tagged Go structs, it was insufficient for
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passing around arbitrary Go values, requiring me to [fork][gohcl] both
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github.com/hashicorp/hcl/v2/gohcl and github.com/zclconf/go-cty/cty/gocty to
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reduce boilerplate. This fork contains a non-trivial amount of changes that
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would need to be maintained or contributed upstream to be tenable.
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Additionally, there is desired functionality that is not supported today in
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HCL/go-cty:
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1. A stronger focus on performance and memory usage, changing go-cty to operate
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around Go values instead of converting Go values to a custom representation.
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2. Ability to disable go-cty's requirement that strings are UTF-8 encoded
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3. Pass around functions as go-cty values (e.g., to allow a clustering
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component to expose a function to check for ownership of key against a hash
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ring)
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4. Ability to declare local variables in a scope without needing a `locals`
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block like as seen in Terraform.
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The combination of desired changes across gohcl and go-cty, the fork that was
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already necessary to make it easier to adopt HCL for Flow, and the desire to
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have a stronger interaction with arbitrary Go values led to the decision that a
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new Flow-specific language was warranted.
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### Why now?
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Grafana Agent Flow is already a dramatic change to the Agent. To avoid users
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being exhausted from the frequency of dramatic changes, it would be ideal for
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Grafana Agent Flow to ship with River instead of eventually migrating to River.
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## Minimizing impact
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New languages always have some amount of learning curve, and if the learning
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curve is too steep, the language will fail to be adopted.
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We will minimize this impact of a new language by:
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* Minimizing the learning curve as much as possible by not creating
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too many novel ideas at the language level.
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* Tend the syntax towards allowing users to copy-and-paste examples to learn as
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they go.
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* Heavily document the language so that all questions a user may have is
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answered.
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* Ensuring that error messages explain the problem and the resolution is
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obvious.
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## Proposal
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River is inspired by HCL. However, some of the syntax used by HCL will be
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changed to make River more easily identifiable as a different language.
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River focuses on expressions, attributes, and blocks.
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### Expressions
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Expressions resolve to values used by River. The type of expressions are:
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* Literal expressions:
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* Booleans: `true`, `false`
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* Numbers: `3`, `3.5`, `3e+10`, etc.
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* Strings: `"Hello, world!"`
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* Unary operations:
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* Logical NOT: `!true`
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* Negative: `-5`
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* Binary operations:
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* Math operators: `+`, `-`, `*`, `/`, `^` (pow)
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* Equality operators: `==`, `!=`, `<`, `<=`, `>`, `>=`
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* Logical operators: `||`, `&&`
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* Lists: `[1, 2, 3]`
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* Objects: `{ a = 5, b = 6 }`
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* Variable reference: `foobar`
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* Indexing: `some_list[0]`
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* Field access: `some_object.field_a`
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* Function calls: `concat([0, 1], [2, 3])`
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* Parenthesized expression: `(3 + 5)`
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### Attributes
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Attributes are key-value pairs which set individual settings, formatted as
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`<identifier> = <expression>`:
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```
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log_level = "debug"
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log_format = "logfmt"
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```
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### Blocks
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Blocks are named groupings of attributes, wrapping in curly braces. Blocks can
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also contain other blocks.
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```
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server {
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http_address = "127.0.0.1:12345"
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}
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prometheus.storage {
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remote_write {
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url = "http://localhost:9090/api/v1/write"
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}
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remote_write {
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url = "http://localhost:9091/api/v1/write"
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}
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}
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```
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Block names must consist of one or more identifiers separated by `.`. Blocks
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can also be given user-specified labels, denoted as a string wrapped in quotes:
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```
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prometheus.storage "primary" {
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// ...
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}
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prometheus.storage "secondary" {
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// ...
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}
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```
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### Type system
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Values are categorized as being one of the following:
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* `number`
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* `bool`
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* `string`
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* `list`
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* Elements within the list do not have to be the same type.
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* `object`
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* `function`
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* Function values differentiate River from HCL/go-cty, which does not support
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passing around or invoking function values.
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* `capsule`
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* Capsule is a catch-all type which refers to some arbitrary Go value which
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is not one of the other types. For example, `<-chan int` would be
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represented as a capsule in River.
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River types map to Go types as follows:
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* `number`: Go `int*`, `uint*`, `float*`
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* `bool`: Go `bool`
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* `string`: Go `string`, `[]byte`
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* `list`: Go `[]T`, `[...]T`.
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* `object`: Go `map[string]T`, and structs with at least one River tag
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* `function`: Any Go function.
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* If the final return value of the Go function is an error, it will be
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checked on calling; a non-nil error will cause the evaluation of the
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function to fail.
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* `capsule`: All other Go values.
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River acts like a combination of a configuration language like HCL and an
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embedded language like Lua due to its focus on supporting all Go values,
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including values which cannot be directly represented by the user (such as Go
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interfaces). This enables developers to use native Go types for easily passing
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around business logic which users wire together through their configuration.
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### River struct tags
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River struct tags are used to converting between River values and Go structs.
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Tags take one of the following forms:
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* `river:"example,attr"`: required attribute named `example`
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* `river:"example,attr,optional"`: optional attribute named `example`
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* `river:"example,block"`: required block named `example`
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* `river:"example,block,optional"`: optional block named `example`
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* `river:",label"`: Used for decoding block labels into a `string`.
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Attribute and block names must be unique across the whole type. When encoding a
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Go struct, inner blocks are converted into objects. Attributes are converted
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into River values of the appropriate type.
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### Errors
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There are multiple types of errors which may occur:
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* Lexing / parsing errors
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* Evaluation errors (when evaluating an expression into a River value)
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* Decoding errors (when converting a River value into a Go value)
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* Validation errors (when Go code validates a value)
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Errors should be displayed to the user in a way that gives as much information
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as possible. Errors which involve unexpected values should print the value to
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ease debugging.
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For this `example.river` config file which expects the `targets` field to be a
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list of objects:
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```
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prometheus.scrape "example1" {
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targets = 5
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}
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prometheus.scrape "example2" {
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targets = [5]
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}
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prometheus.scrape "example3" {
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targets = some_list_of_objects + 5
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}
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```
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Errors could be shown to the user like:
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```
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example.river:2:3: targets expects list value, got number
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| targets = 5
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Value:
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5
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example.river:6:3: list element 0 must be object, got number
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| targets = [5]
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Value:
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5
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example.river:10:13: cannot perform `+` on types list and number
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| some_list_of_objects + 5
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Expression:
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[{}] + 5
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```
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The errors print out the offending portion of the config file alongside the
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offending values. Printing out the offending values is useful when the values
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come from the result of referring to a variable or calling a function.
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### Concerns
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No existing tooling for River will exist from day one. While the initial
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implementation should include a formatter, tools like syntax highlighting or
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LSPs won't exist.
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## Alternatives considered
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### Handles
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Instead of passing around literal arbitrary Go values, handles could be used to
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_refer_ to arbitrary Go values. For example, a number could refer to some entry
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in an in-memory store which holds a Go channel or interface.
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Pros:
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* Works better with HCL in its current state without needing the gohcl fork
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* Would enable YAML, CUE, and Jsonnet to pass around arbitrary values
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Cons:
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* Still wouldn't allow HCL to pass around functions as values
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* More tedious for developers to work with (they now have to exchange handles
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for values).
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* Requires extra logic for making sure resources that handles refer to don't
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leak.
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[RFC-0004]: ./0004-agent-flow.md
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[HCL]: https://github.com/hashicorp/hcl
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[go-cty]: github.com/zclconf/go-cty
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[gohcl]: https://github.com/rfratto/gohcl
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[schema-driven processing]: https://github.com/hashicorp/hcl/blob/main/spec.md#schema-driven-processing

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