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Commit d38325c2 authored by Ryan McCormick's avatar Ryan McCormick Committed by GitHub
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feat: Add initial prometheus/grafana support for count (#303)

parent 6e0cfbd9
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applications/llm/count/Cargo.lock
View file @ d38325c2
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...@@ -2841,12 +3097,12 @@ dependencies = [ ...@@ -2841,12 +3097,12 @@ dependencies = [
"quinn", "quinn",
"rustls", "rustls",
"rustls-native-certs 0.8.1", "rustls-native-certs 0.8.1",
"rustls-pemfile", "rustls-pemfile 2.2.0",
"rustls-pki-types", "rustls-pki-types",
"serde", "serde",
"serde_json", "serde_json",
"serde_urlencoded", "serde_urlencoded",
"sync_wrapper", "sync_wrapper 1.0.2",
"tokio", "tokio",
"tokio-rustls", "tokio-rustls",
"tokio-util", "tokio-util",
...@@ -2872,7 +3128,7 @@ dependencies = [ ...@@ -2872,7 +3128,7 @@ dependencies = [
"mime", "mime",
"nom", "nom",
"pin-project-lite", "pin-project-lite",
"reqwest", "reqwest 0.12.12",
"thiserror 1.0.69", "thiserror 1.0.69",
] ]
...@@ -2946,7 +3202,7 @@ source = "registry+https://github.com/rust-lang/crates.io-index" ...@@ -2946,7 +3202,7 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "e5bfb394eeed242e909609f56089eecfe5fda225042e8b171791b9c95f5931e5" checksum = "e5bfb394eeed242e909609f56089eecfe5fda225042e8b171791b9c95f5931e5"
dependencies = [ dependencies = [
"openssl-probe", "openssl-probe",
"rustls-pemfile", "rustls-pemfile 2.2.0",
"rustls-pki-types", "rustls-pki-types",
"schannel", "schannel",
"security-framework 2.11.1", "security-framework 2.11.1",
...@@ -2964,6 +3220,15 @@ dependencies = [ ...@@ -2964,6 +3220,15 @@ dependencies = [
"security-framework 3.2.0", "security-framework 3.2.0",
] ]
[[package]]
name = "rustls-pemfile"
version = "1.0.4"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "1c74cae0a4cf6ccbbf5f359f08efdf8ee7e1dc532573bf0db71968cb56b1448c"
dependencies = [
"base64 0.21.7",
]
[[package]] [[package]]
name = "rustls-pemfile" name = "rustls-pemfile"
version = "2.2.0" version = "2.2.0"
...@@ -3352,6 +3617,12 @@ dependencies = [ ...@@ -3352,6 +3617,12 @@ dependencies = [
"unicode-ident", "unicode-ident",
] ]
[[package]]
name = "sync_wrapper"
version = "0.1.2"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "2047c6ded9c721764247e62cd3b03c09ffc529b2ba5b10ec482ae507a4a70160"
[[package]] [[package]]
name = "sync_wrapper" name = "sync_wrapper"
version = "1.0.2" version = "1.0.2"
...@@ -3372,6 +3643,27 @@ dependencies = [ ...@@ -3372,6 +3643,27 @@ dependencies = [
"syn 2.0.98", "syn 2.0.98",
] ]
[[package]]
name = "system-configuration"
version = "0.5.1"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "ba3a3adc5c275d719af8cb4272ea1c4a6d668a777f37e115f6d11ddbc1c8e0e7"
dependencies = [
"bitflags 1.3.2",
"core-foundation 0.9.4",
"system-configuration-sys",
]
[[package]]
name = "system-configuration-sys"
version = "0.5.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "a75fb188eb626b924683e3b95e3a48e63551fcfb51949de2f06a9d91dbee93c9"
dependencies = [
"core-foundation-sys",
"libc",
]
[[package]] [[package]]
name = "system-deps" name = "system-deps"
version = "6.2.2" version = "6.2.2"
...@@ -3575,6 +3867,16 @@ dependencies = [ ...@@ -3575,6 +3867,16 @@ dependencies = [
"syn 2.0.98", "syn 2.0.98",
] ]
[[package]]
name = "tokio-native-tls"
version = "0.3.1"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "bbae76ab933c85776efabc971569dd6119c580d8f5d448769dec1764bf796ef2"
dependencies = [
"native-tls",
"tokio",
]
[[package]] [[package]]
name = "tokio-rustls" name = "tokio-rustls"
version = "0.26.1" version = "0.26.1"
...@@ -3619,7 +3921,7 @@ dependencies = [ ...@@ -3619,7 +3921,7 @@ dependencies = [
"bytes", "bytes",
"futures-core", "futures-core",
"futures-sink", "futures-sink",
"http", "http 1.2.0",
"httparse", "httparse",
"rand", "rand",
"ring", "ring",
...@@ -3702,11 +4004,11 @@ dependencies = [ ...@@ -3702,11 +4004,11 @@ dependencies = [
"axum 0.7.9", "axum 0.7.9",
"base64 0.22.1", "base64 0.22.1",
"bytes", "bytes",
"h2", "h2 0.4.8",
"http", "http 1.2.0",
"http-body", "http-body 1.0.1",
"http-body-util", "http-body-util",
"hyper", "hyper 1.6.0",
"hyper-timeout", "hyper-timeout",
"hyper-util", "hyper-util",
"percent-encoding", "percent-encoding",
...@@ -3764,7 +4066,7 @@ dependencies = [ ...@@ -3764,7 +4066,7 @@ dependencies = [
"futures-core", "futures-core",
"futures-util", "futures-util",
"pin-project-lite", "pin-project-lite",
"sync_wrapper", "sync_wrapper 1.0.2",
"tokio", "tokio",
"tower-layer", "tower-layer",
"tower-service", "tower-service",
...@@ -4074,6 +4376,12 @@ dependencies = [ ...@@ -4074,6 +4376,12 @@ dependencies = [
"percent-encoding", "percent-encoding",
] ]
[[package]]
name = "urlencoding"
version = "2.1.3"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "daf8dba3b7eb870caf1ddeed7bc9d2a049f3cfdfae7cb521b087cc33ae4c49da"
[[package]] [[package]]
name = "utf16_iter" name = "utf16_iter"
version = "1.0.5" version = "1.0.5"
...@@ -4542,6 +4850,16 @@ dependencies = [ ...@@ -4542,6 +4850,16 @@ dependencies = [
"memchr", "memchr",
] ]
[[package]]
name = "winreg"
version = "0.50.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "524e57b2c537c0f9b1e69f1965311ec12182b4122e45035b1508cd24d2adadb1"
dependencies = [
"cfg-if 1.0.0",
"windows-sys 0.48.0",
]
[[package]] [[package]]
name = "wit-bindgen-rt" name = "wit-bindgen-rt"
version = "0.33.0" version = "0.33.0"
......
applications/llm/count/Cargo.toml
View file @ d38325c2
...@@ -33,3 +33,11 @@ serde_json = { version = "1" } ...@@ -33,3 +33,11 @@ serde_json = { version = "1" }
tokio = { version = "1", features = ["full"] } tokio = { version = "1", features = ["full"] }
tracing = { version = "0.1" } tracing = { version = "0.1" }
thiserror = "1.0" thiserror = "1.0"
opentelemetry = "0.20"
opentelemetry-prometheus = "0.13"
prometheus = "0.13"
rand = "0.8"
axum = "0.6"
[dev-dependencies]
reqwest = { version = "0.11", features = ["blocking"] }
\ No newline at end of file
applications/llm/count/README.md
View file @ d38325c2
...@@ -9,7 +9,7 @@ and then publish an event with the postprocessed data. ...@@ -9,7 +9,7 @@ and then publish an event with the postprocessed data.
```bash ```bash
# For more details, try TRD_LOG=debug # For more details, try TRD_LOG=debug
TRD_LOG=info cargo run -- --namespace triton-init --component backend --endpoint generate TRD_LOG=info cargo run --bin count -- --namespace triton-init --component backend --endpoint generate
# 2025-02-26T18:45:05.467026Z INFO count: Creating unique instance of Count at triton-init/components/count/instance # 2025-02-26T18:45:05.467026Z INFO count: Creating unique instance of Count at triton-init/components/count/instance
# 2025-02-26T18:45:05.472146Z INFO count: Scraping service triton_init_backend_720278f8 and filtering on subject triton_init_backend_720278f8.generate # 2025-02-26T18:45:05.472146Z INFO count: Scraping service triton_init_backend_720278f8 and filtering on subject triton_init_backend_720278f8.generate
...@@ -21,14 +21,33 @@ With no matching endpoints running, you should see warnings in the logs: ...@@ -21,14 +21,33 @@ With no matching endpoints running, you should see warnings in the logs:
2025-02-26T18:45:06.474161Z WARN count: No endpoints found matching subject triton_init_backend_720278f8.generate 2025-02-26T18:45:06.474161Z WARN count: No endpoints found matching subject triton_init_backend_720278f8.generate
``` ```
But after starting a matching endpoint, such as the To see metrics published to a matching endpoint, you can use the
[service_metrics example](examples/rust/service_metrics/src/bin/server.rs), [mock_worker example](src/bin/mock_worker.rs) in this directory to launch
you should see these warnings go away since the endpoint will automatically 1 or more workers that publish LLM Metrics:
get discovered. ```bash
# Can run multiple workers in separate shells
cargo run --bin mock_worker
```
After a matching endpoint gets started, you should see the warnings go away
since the endpoint will automatically get discovered.
Whether there are matching endpoints found or not, `count` will publish events, for example: When stats are found from the target endpoints being listened on, count will
aggregate and publish some metrics as both an event and to a prometheus web server:
``` ```
2025-02-26T18:45:46.501874Z INFO count: Publishing event l2c.backend.generate on Namespace { name: "triton-init" } with ProcessedEndpoints { capacity_with_ids: [], load_avg: NaN, load_std: NaN, address: "backend.generate" } 2025-02-28T04:05:58.077901Z INFO count: Aggregated metrics: ProcessedEndpoints { endpoints: [Endpoint { name: "worker-7587884888253033398", subject: "triton_init_backend_720278f8.generate-694d951a80e06bb6", data: ForwardPassMetrics { request_active_slots: 58, request_total_slots: 100, kv_active_blocks: 77, kv_total_blocks: 100 } }, Endpoint { name: "worker-7587884888253033401", subject: "triton_init_backend_720278f8.generate-694d951a80e06bb9", data: ForwardPassMetrics { request_active_slots: 71, request_total_slots: 100, kv_active_blocks: 29, kv_total_blocks: 100 } }], worker_ids: [7587884888253033398, 7587884888253033401], load_avg: 53.0, load_std: 24.0 }
``` ```
However, the events may not be very useful until there are corresponding stats found from endpoints for processing. To see the metrics being published in prometheus format, you can run:
```bash
curl localhost:9091/metrics
# # HELP llm_kv_blocks_active Active KV cache blocks
# # TYPE llm_kv_blocks_active gauge
# llm_kv_blocks_active{component="backend",endpoint="generate",worker_id="7587884888253033398"} 40
# llm_kv_blocks_active{component="backend",endpoint="generate",worker_id="7587884888253033401"} 2
# # HELP llm_kv_blocks_total Total KV cache blocks
# # TYPE llm_kv_blocks_total gauge
# llm_kv_blocks_total{component="backend",endpoint="generate",worker_id="7587884888253033398"} 100
# llm_kv_blocks_total{component="backend",endpoint="generate",worker_id="7587884888253033401"} 100
```
applications/llm/count/src/bin/mock_worker.rs 0 → 100644
View file @ d38325c2
// SPDX-FileCopyrightText: Copyright (c) 2024-2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
// SPDX-License-Identifier: Apache-2.0
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
use rand::Rng;
use std::sync::Arc;
use triton_distributed_llm::kv_router::protocols::ForwardPassMetrics;
use triton_distributed_runtime::{
logging,
pipeline::{
async_trait, network::Ingress, AsyncEngine, AsyncEngineContextProvider, Error, ManyOut,
ResponseStream, SingleIn,
},
protocols::annotated::Annotated,
stream, DistributedRuntime, Result, Runtime, Worker,
};
fn main() -> Result<()> {
logging::init();
let worker = Worker::from_settings()?;
worker.execute(app)
}
async fn app(runtime: Runtime) -> Result<()> {
let distributed = DistributedRuntime::from_settings(runtime.clone()).await?;
backend(distributed).await
}
struct RequestHandler {}
impl RequestHandler {
fn new() -> Arc<Self> {
Arc::new(Self {})
}
}
#[async_trait]
impl AsyncEngine<SingleIn<String>, ManyOut<Annotated<String>>, Error> for RequestHandler {
async fn generate(&self, input: SingleIn<String>) -> Result<ManyOut<Annotated<String>>> {
let (data, ctx) = input.into_parts();
let chars = data
.chars()
.map(|c| Annotated::from_data(c.to_string()))
.collect::<Vec<_>>();
let stream = stream::iter(chars);
Ok(ResponseStream::new(Box::pin(stream), ctx.context()))
}
}
async fn backend(runtime: DistributedRuntime) -> Result<()> {
// attach an ingress to an engine
let ingress = Ingress::for_engine(RequestHandler::new())?;
// make the ingress discoverable via a component service
// we must first create a service, then we can attach one more more endpoints
runtime
.namespace("triton-init")?
.component("backend")?
.service_builder()
.create()
.await?
.endpoint("generate")
.endpoint_builder()
// Dummy stats handler to demonstrate how to attach a custom stats handler
.stats_handler(|_stats| {
println!("stats in: {:?}", _stats);
let request_total_slots = 100;
let request_active_slots = rand::thread_rng().gen_range(0..request_total_slots);
let kv_total_blocks = 100;
let kv_active_blocks = rand::thread_rng().gen_range(0..kv_total_blocks);
let stats = ForwardPassMetrics {
request_active_slots,
request_total_slots,
kv_active_blocks,
kv_total_blocks,
};
println!("stats out: {:?}", stats);
serde_json::to_value(stats).unwrap()
})
.handler(ingress)
.start()
.await
}
applications/llm/count/src/lib.rs 0 → 100644
View file @ d38325c2
// SPDX-FileCopyrightText: Copyright (c) 2024-2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
// SPDX-License-Identifier: Apache-2.0
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//! Library functions for the count application.
use axum::{routing::get, Router};
use prometheus::register_gauge_vec;
use serde::{Deserialize, Serialize};
use std::net::SocketAddr;
use triton_distributed_llm::kv_router::protocols::ForwardPassMetrics;
use triton_distributed_llm::kv_router::scheduler::Endpoint;
use triton_distributed_llm::kv_router::scoring::ProcessedEndpoints;
use triton_distributed_runtime::{
distributed::Component, service::EndpointInfo, utils::Duration, Result,
};
/// Configuration for LLM worker load capacity metrics
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct LLMWorkerLoadCapacityConfig {
pub component_name: String,
pub endpoint_name: String,
}
// TODO: This is _really_ close to the async_nats::service::Stats object,
// but it's missing a few fields like "name", so use a temporary struct
// for easy deserialization. Ideally, this type already exists or can
// be exposed in the library somewhere.
/// Stats structure returned from NATS service API
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct StatsWithData {
// Standard NATS Service API fields
pub average_processing_time: f64,
pub last_error: String,
pub num_errors: u64,
pub num_requests: u64,
pub processing_time: u64,
pub queue_group: String,
// Field containing custom stats handler data
pub data: serde_json::Value,
}
/// Prometheus metrics server for exposing metrics
pub struct PrometheusMetricsServer {
metrics: PrometheusMetrics,
}
impl PrometheusMetricsServer {
/// Initialize the metrics server
pub fn new() -> Result<Self> {
Ok(Self {
metrics: PrometheusMetrics::new()?,
})
}
/// Start the metrics server on the specified port
pub fn start(&mut self, port: u16) {
// Create an axum router with a metrics endpoint
let app = Router::new().route(
"/metrics",
get(|| async {
// Gather and encode metrics
use prometheus::Encoder;
let encoder = prometheus::TextEncoder::new();
let mut buffer = Vec::new();
encoder.encode(&prometheus::gather(), &mut buffer).unwrap();
String::from_utf8(buffer).unwrap()
}),
);
// Create a socket address to listen on
let addr = SocketAddr::from(([0, 0, 0, 0], port));
// Spawn the server in a background task
tokio::spawn(async move {
axum::Server::bind(&addr)
.serve(app.into_make_service())
.await
.unwrap();
});
tracing::info!("Prometheus metrics server started at {addr:?}/metrics");
}
/// Update metrics with current values
pub fn update(&mut self, config: &LLMWorkerLoadCapacityConfig, processed: &ProcessedEndpoints) {
self.metrics.update(config, processed);
}
}
/// Prometheus metrics collection
pub struct PrometheusMetrics {
kv_blocks_active: prometheus::GaugeVec,
kv_blocks_total: prometheus::GaugeVec,
requests_active: prometheus::GaugeVec,
requests_total: prometheus::GaugeVec,
load_avg: prometheus::GaugeVec,
load_std: prometheus::GaugeVec,
}
impl PrometheusMetrics {
/// Initialize all metrics
fn new() -> Result<Self> {
Ok(Self {
kv_blocks_active: register_gauge_vec!(
"llm_kv_blocks_active",
"Active KV cache blocks",
&["component", "endpoint", "worker_id"]
)?,
kv_blocks_total: register_gauge_vec!(
"llm_kv_blocks_total",
"Total KV cache blocks",
&["component", "endpoint", "worker_id"]
)?,
requests_active: register_gauge_vec!(
"llm_requests_active_slots",
"Active request slots",
&["component", "endpoint", "worker_id"]
)?,
requests_total: register_gauge_vec!(
"llm_requests_total_slots",
"Total request slots",
&["component", "endpoint", "worker_id"]
)?,
load_avg: register_gauge_vec!(
"llm_load_avg",
"Average load across workers",
&["component", "endpoint"]
)?,
load_std: register_gauge_vec!(
"llm_load_std",
"Load standard deviation across workers",
&["component", "endpoint"]
)?,
})
}
/// Helper method to set a gauge with worker-specific labels (3 labels)
fn set_worker_gauge(
&self,
gauge: &prometheus::GaugeVec,
config: &LLMWorkerLoadCapacityConfig,
worker_id: &str,
value: f64,
) {
gauge
.with_label_values(&[&config.component_name, &config.endpoint_name, worker_id])
.set(value);
}
/// Helper method to set a gauge with component/endpoint labels only (2 labels)
fn set_endpoint_gauge(
&self,
gauge: &prometheus::GaugeVec,
config: &LLMWorkerLoadCapacityConfig,
value: f64,
) {
gauge
.with_label_values(&[&config.component_name, &config.endpoint_name])
.set(value);
}
/// Update metrics with current values
fn update(&self, config: &LLMWorkerLoadCapacityConfig, processed: &ProcessedEndpoints) {
// Update per-worker metrics
for endpoint in processed.endpoints.iter() {
let worker_id = endpoint.worker_id().to_string();
let metrics = endpoint.data.clone();
self.set_worker_gauge(
&self.kv_blocks_active,
config,
&worker_id,
metrics.kv_active_blocks as f64,
);
self.set_worker_gauge(
&self.kv_blocks_total,
config,
&worker_id,
metrics.kv_total_blocks as f64,
);
self.set_worker_gauge(
&self.requests_active,
config,
&worker_id,
metrics.request_active_slots as f64,
);
self.set_worker_gauge(
&self.requests_total,
config,
&worker_id,
metrics.request_total_slots as f64,
);
}
// Update aggregate metrics
self.set_endpoint_gauge(&self.load_avg, config, processed.load_avg);
self.set_endpoint_gauge(&self.load_std, config, processed.load_std);
}
}
/// Collect endpoints from a component
pub async fn collect_endpoints(
component: &Component,
subject: &str,
timeout: Duration,
) -> Result<Vec<EndpointInfo>> {
// Collect stats from each backend
let stream = component.scrape_stats(timeout).await?;
// Filter the stats by the service subject
let endpoints = stream
.into_endpoints()
.filter(|e| e.subject.starts_with(subject))
.collect::<Vec<_>>();
tracing::debug!("Endpoints: {endpoints:?}");
if endpoints.is_empty() {
tracing::warn!("No endpoints found matching subject {subject}");
}
Ok(endpoints)
}
/// Extract metrics from endpoints
pub fn extract_metrics(endpoints: &[EndpointInfo]) -> Vec<ForwardPassMetrics> {
let endpoint_data = endpoints.iter().map(|e| e.data.clone()).collect::<Vec<_>>();
// Extract StatsWithData objects from endpoint services
let stats: Vec<StatsWithData> = endpoint_data
.iter()
.filter_map(|e| {
let metrics_data = e.as_ref()?;
metrics_data.clone().decode::<StatsWithData>().ok()
})
.collect();
tracing::debug!("Stats: {stats:?}");
// Extract ForwardPassMetrics nested within Stats object
let metrics: Vec<ForwardPassMetrics> = stats
.iter()
.filter_map(
|s| match serde_json::from_value::<ForwardPassMetrics>(s.data.clone()) {
Ok(metrics) => Some(metrics),
Err(err) => {
tracing::warn!("Error decoding metrics: {err}");
None
}
},
)
.collect();
tracing::debug!("Metrics: {metrics:?}");
metrics
}
/// Create ProcessedEndpoints from metrics and endpoints
pub fn postprocess_metrics(
metrics: &[ForwardPassMetrics],
endpoints: &[EndpointInfo],
) -> ProcessedEndpoints {
let processed_endpoints: Vec<Endpoint> = metrics
.iter()
.zip(endpoints.iter())
.filter_map(|(m, e)| {
e.id().ok().map(|id| Endpoint {
name: format!("worker-{id}"),
subject: e.subject.clone(),
data: m.clone(),
})
})
.collect();
ProcessedEndpoints::new(processed_endpoints)
}
applications/llm/count/src/main.rs
View file @ d38325c2
...@@ -24,8 +24,6 @@ ...@@ -24,8 +24,6 @@
//! - KV Cache Blocks: [Active, Total] //! - KV Cache Blocks: [Active, Total]
use clap::Parser; use clap::Parser;
use serde::{Deserialize, Serialize};
use triton_distributed_runtime::{ use triton_distributed_runtime::{
error, logging, error, logging,
traits::events::EventPublisher, traits::events::EventPublisher,
...@@ -33,6 +31,12 @@ use triton_distributed_runtime::{ ...@@ -33,6 +31,12 @@ use triton_distributed_runtime::{
DistributedRuntime, ErrorContext, Result, Runtime, Worker, DistributedRuntime, ErrorContext, Result, Runtime, Worker,
}; };
// Import from our library
use count::{
collect_endpoints, extract_metrics, postprocess_metrics, LLMWorkerLoadCapacityConfig,
PrometheusMetricsServer,
};
/// CLI arguments for the count application /// CLI arguments for the count application
#[derive(Parser, Debug)] #[derive(Parser, Debug)]
#[command(author, version, about, long_about = None)] #[command(author, version, about, long_about = None)]
...@@ -73,34 +77,8 @@ fn get_config(args: &Args) -> Result<LLMWorkerLoadCapacityConfig> { ...@@ -73,34 +77,8 @@ fn get_config(args: &Args) -> Result<LLMWorkerLoadCapacityConfig> {
}) })
} }
// we will scrape the service_name and extract the endpoint_name metrics
// we will bcast them as {namespace}.events.l2c.{service_name}.{endpoint_name}
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct LLMWorkerLoadCapacityConfig {
component_name: String,
endpoint_name: String,
}
/// LLM Worker Load Capacity Metrics
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct LLMWorkerLoadCapacity {
pub requests_active_slots: u32,
pub requests_total_slots: u32,
pub kv_blocks_active: u32,
pub kv_blocks_total: u32,
}
fn main() -> Result<()> {
logging::init();
let worker = Worker::from_settings()?;
worker.execute(app)
}
// TODO - refactor much of this back into the library
async fn app(runtime: Runtime) -> Result<()> { async fn app(runtime: Runtime) -> Result<()> {
let args = Args::parse(); let args = Args::parse();
// we will start by assuming that there is no oscar and no planner
// to that end, we will use CLI args to get a singular config for scraping a single backend
let config = get_config(&args)?; let config = get_config(&args)?;
tracing::info!("Config: {config:?}"); tracing::info!("Config: {config:?}");
...@@ -109,8 +87,7 @@ async fn app(runtime: Runtime) -> Result<()> { ...@@ -109,8 +87,7 @@ async fn app(runtime: Runtime) -> Result<()> {
let namespace = drt.namespace(args.namespace)?; let namespace = drt.namespace(args.namespace)?;
let component = namespace.component("count")?; let component = namespace.component("count")?;
// there should only be one count // Create unique instance of Count
// check {component.etcd_path()}/instance for existing instances
let key = format!("{}/instance", component.etcd_path()); let key = format!("{}/instance", component.etcd_path());
tracing::info!("Creating unique instance of Count at {key}"); tracing::info!("Creating unique instance of Count at {key}");
drt.etcd_client() drt.etcd_client()
...@@ -122,113 +99,53 @@ async fn app(runtime: Runtime) -> Result<()> { ...@@ -122,113 +99,53 @@ async fn app(runtime: Runtime) -> Result<()> {
.await .await
.context("Unable to create unique instance of Count; possibly one already exists")?; .context("Unable to create unique instance of Count; possibly one already exists")?;
let target = namespace.component(&config.component_name)?; let target_component = namespace.component(&config.component_name)?;
let target_endpoint = target.endpoint(&config.endpoint_name); let target_endpoint = target_component.endpoint(&config.endpoint_name);
let service_name = target.service_name(); let service_name = target_component.service_name();
let service_subject = target_endpoint.subject(); let service_subject = target_endpoint.subject();
tracing::info!("Scraping service {service_name} and filtering on subject {service_subject}"); tracing::info!("Scraping service {service_name} and filtering on subject {service_subject}");
let token = drt.primary_lease().child_token(); let token = drt.primary_lease().child_token();
let event_name = format!("l2c.{}.{}", config.component_name, config.endpoint_name);
let address = format!("{}.{}", config.component_name, config.endpoint_name,); // TODO: Make metrics host/port configurable
let event_name = format!("l2c.{}", address); // Initialize Prometheus metrics and start server
let mut metrics_server = PrometheusMetricsServer::new()?;
metrics_server.start(9091);
loop { loop {
let next = Instant::now() + Duration::from_secs(args.poll_interval); let next = Instant::now() + Duration::from_secs(args.poll_interval);
// collect stats from each backend // Collect and process metrics
let stream = target.scrape_stats(Duration::from_secs(1)).await?; let scrape_timeout = Duration::from_secs(1);
tracing::debug!("Scraped Stats Stream: {stream:?}"); let endpoints =
collect_endpoints(&target_component, &service_subject, scrape_timeout).await?;
// filter the stats by the service subject let metrics = extract_metrics(&endpoints);
let endpoints = stream let processed = postprocess_metrics(&metrics, &endpoints);
.into_endpoints() tracing::info!("Aggregated metrics: {processed:?}");
.filter(|e| e.subject.starts_with(&service_subject))
.collect::<Vec<_>>();
tracing::debug!("Endpoints: {endpoints:?}"); // Update Prometheus metrics
if endpoints.is_empty() { metrics_server.update(&config, &processed);
tracing::warn!("No endpoints found matching subject {}", service_subject);
}
// extract the custom data from the stats and try to decode it as LLMWorkerLoadCapacity // TODO: Who needs to consume these events?
let metrics = endpoints // Publish metrics event
.iter()
.filter_map(|e| match e.data.clone() {
Some(metrics) => metrics.decode::<LLMWorkerLoadCapacity>().ok(),
None => None,
})
.collect::<Vec<_>>();
tracing::debug!("Metrics: {metrics:?}");
// parse the endpoint ids
// the ids are the last part of the subject in hexadecimal
// form a list of tuples (kv_blocks_total - kv_blocks_active, requests_total_slots - requests_active_slots, id)
// this tuple represent the remaining capacity of each endpoint
let capacity_with_ids = metrics
.iter()
.zip(endpoints.iter())
.filter_map(|(m, e)| {
e.id().ok().map(|id| {
(
m.kv_blocks_total - m.kv_blocks_active,
m.requests_total_slots - m.requests_active_slots,
id,
)
})
})
.collect::<Vec<_>>();
// compute mean / std of LLMWorkerLoadCapacity
let load_values: Vec<f64> = metrics.iter().map(|x| x.kv_blocks_active as f64).collect();
let load_avg = load_values.iter().sum::<f64>() / load_values.len() as f64;
let variance = load_values
.iter()
.map(|&x| (x - load_avg).powi(2))
.sum::<f64>()
/ load_values.len() as f64;
let load_std = variance.sqrt();
let processed = ProcessedEndpoints {
capacity_with_ids,
load_avg,
load_std,
address: address.clone(),
};
// publish using the namespace event plane
tracing::info!(
"Publishing event {event_name} on namespace {namespace:?} with {processed:?}"
);
namespace.publish(&event_name, &processed).await?; namespace.publish(&event_name, &processed).await?;
// wait until cancelled or the next tick // Wait until cancelled or the next tick
match tokio::time::timeout_at(next, token.cancelled()).await { match tokio::time::timeout_at(next, token.cancelled()).await {
Ok(_) => break, Ok(_) => break,
Err(_) => { Err(_) => continue,
// timeout, we continue
continue;
}
} }
} }
Ok(()) Ok(())
} }
#[derive(Debug, Clone, Serialize, Deserialize)] fn main() -> Result<()> {
pub struct ProcessedEndpoints { logging::init();
/// (kv_blocks_total - kv_blocks_active, requests_total_slots - requests_active_slots, id) let worker = Worker::from_settings()?;
pub capacity_with_ids: Vec<(u32, u32, i64)>, worker.execute(app)
/// kv_blocks_active average
pub load_avg: f64,
/// kv_blocks_active standard deviation
pub load_std: f64,
/// {component}.{endpoint}
pub address: String,
} }
#[cfg(test)] #[cfg(test)]
...@@ -239,11 +156,7 @@ mod tests { ...@@ -239,11 +156,7 @@ mod tests {
#[test] #[test]
fn test_namespace_from_env() { fn test_namespace_from_env() {
env::set_var("TRD_NAMESPACE", "test-namespace"); env::set_var("TRD_NAMESPACE", "test-namespace");
// Parse args with no explicit namespace
let args = Args::parse_from(["count", "--component", "comp", "--endpoint", "end"]); let args = Args::parse_from(["count", "--component", "comp", "--endpoint", "end"]);
// Verify namespace was taken from environment variable
assert_eq!(args.namespace, "test-namespace"); assert_eq!(args.namespace, "test-namespace");
} }
} }
applications/llm/count/visualization/README.md 0 → 100644
View file @ d38325c2
# Metrics Visualization with Prometheus and Grafana
This directory contains configuration for visualizing metrics from the metrics aggregation service using Prometheus and Grafana.
## Components
- **Prometheus**: Collects and stores metrics from the service
- **Grafana**: Provides visualization dashboards for the metrics
## Getting Started
1. Make sure Docker and Docker Compose are installed on your system
2. Start `count` and the corresponding `examples/rust/service_metrics/bin/server.rs` that populates dummy KV Cache metrics.
3. Start the visualization stack:
```bash
docker compose up -d
```
4. Web servers started:
- Grafana: http://localhost:3000 (default login: admin/admin)
- Prometheus: http://localhost:9090
## Configuration
### Prometheus
The Prometheus configuration is defined in `prometheus.yml`. It is configured to scrape metrics from the metrics aggregation service endpoint.
Note: You may need to adjust the target based on your host configuration and network setup.
### Grafana
Grafana is pre-configured with:
- Prometheus datasource
- Sample dashboard for visualizing service metrics
## Required Files
The following configuration files should be present in this directory:
- `docker-compose.yml`: Defines the Prometheus and Grafana services
- `prometheus.yml`: Contains Prometheus scraping configuration
- `grafana.json`: Contains Grafana dashboard configuration
- `grafana-datasources.yml`: Contains Grafana datasource configuration
- `grafana-dashboard-providers.yml`: Contains Grafana dashboard provider configuration
## Metrics
The prometheus service exposes the following metrics:
- `llm_load_avg`: Average load across workers
- `llm_load_std`: Load standard deviation across workers
- `llm_requests_active_slots`: Number of currently active request slots
- `llm_requests_total_slots`: Total available request slots
- `llm_kv_blocks_active`: Number of active KV blocks
- `llm_kv_blocks_total`: Total KV blocks available
## Troubleshooting
1. Verify services are running:
```bash
docker compose ps
```
2. Check logs:
```bash
docker compose logs prometheus
docker compose logs grafana
```
applications/llm/count/visualization/docker-compose.yml 0 → 100644
View file @ d38325c2
# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
services:
prometheus:
image: prom/prometheus:latest
container_name: prometheus
volumes:
- ./prometheus.yml:/etc/prometheus/prometheus.yml
- prometheus_data:/prometheus
command:
- '--config.file=/etc/prometheus/prometheus.yml'
- '--storage.tsdb.path=/prometheus'
# These provide the web console functionality
- '--web.console.libraries=/etc/prometheus/console_libraries'
- '--web.console.templates=/etc/prometheus/consoles'
- '--web.enable-lifecycle'
restart: unless-stopped
# TODO: Use more explicit networking setup when count is containerized
#ports:
# - "9090:9090"
#networks:
# - monitoring
network_mode: "host"
grafana:
image: grafana/grafana-enterprise:latest
container_name: grafana
volumes:
- ./grafana.json:/etc/grafana/provisioning/dashboards/llm-worker-dashboard.json
- ./grafana-datasources.yml:/etc/grafana/provisioning/datasources/datasources.yml
- ./grafana-dashboard-providers.yml:/etc/grafana/provisioning/dashboards/dashboard-providers.yml
- grafana_data:/var/lib/grafana
environment:
- GF_SECURITY_ADMIN_USER=admin
- GF_SECURITY_ADMIN_PASSWORD=admin
- GF_USERS_ALLOW_SIGN_UP=false
- GF_INSTALL_PLUGINS=grafana-piechart-panel
restart: unless-stopped
# TODO: Use more explicit networking setup when count is containerized
#ports:
# - "3000:3000"
#networks:
# - monitoring
network_mode: "host"
depends_on:
- prometheus
networks:
monitoring:
driver: bridge
volumes:
prometheus_data:
grafana_data:
applications/llm/count/visualization/grafana-dashboard-providers.yml 0 → 100644
View file @ d38325c2
# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
apiVersion: 1
providers:
- name: 'default'
orgId: 1
folder: ''
type: file
disableDeletion: false
updateIntervalSeconds: 10
allowUiUpdates: true
options:
path: /etc/grafana/provisioning/dashboards
foldersFromFilesStructure: true
applications/llm/count/visualization/grafana-datasources.yml 0 → 100644
View file @ d38325c2
# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
apiVersion: 1
datasources:
- name: prometheus
type: prometheus
access: proxy
# TODO: Use proper docker networking
# url: http://prometheus:9090
url: http://localhost:9090
isDefault: true
applications/llm/count/visualization/grafana.json 0 → 100644
View file @ d38325c2
{
"annotations": {
"list": [
{
"builtIn": 1,
"datasource": {
"type": "grafana",
"uid": "-- Grafana --"
},
"enable": true,
"hide": true,
"iconColor": "rgba(0, 211, 255, 1)",
"name": "Annotations & Alerts",
"type": "dashboard"
}
]
},
"copyright": [
"SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.",
"SPDX-License-Identifier: Apache-2.0",
"Licensed under the Apache License, Version 2.0 (the \"License\");",
"you may not use this file except in compliance with the License.",
"You may obtain a copy of the License at",
"http://www.apache.org/licenses/LICENSE-2.0",
"Unless required by applicable law or agreed to in writing, software",
"distributed under the License is distributed on an \"AS IS\" BASIS,",
"WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.",
"See the License for the specific language governing permissions and",
"limitations under the License."
],
"editable": true,
"fiscalYearStartMonth": 0,
"graphTooltip": 0,
"id": 1,
"links": [],
"liveNow": false,
"panels": [
{
"datasource": {
"type": "prometheus",
"uid": "prometheus"
},
"fieldConfig": {
"defaults": {
"color": {
"mode": "palette-classic"
},
"custom": {
"axisCenteredZero": false,
"axisColorMode": "text",
"axisLabel": "",
"axisPlacement": "auto",
"barAlignment": 0,
"drawStyle": "line",
"fillOpacity": 20,
"gradientMode": "none",
"hideFrom": {
"legend": false,
"tooltip": false,
"viz": false
},
"lineInterpolation": "smooth",
"lineWidth": 2,
"pointSize": 5,
"scaleDistribution": {
"type": "linear"
},
"showPoints": "never",
"spanNulls": false,
"stacking": {
"group": "A",
"mode": "none"
},
"thresholdsStyle": {
"mode": "off"
}
},
"mappings": [],
"thresholds": {
"mode": "absolute",
"steps": [
{
"color": "green",
"value": null
},
{
"color": "red",
"value": 80
}
]
},
"unit": "percent"
},
"overrides": []
},
"gridPos": {
"h": 8,
"w": 12,
"x": 0,
"y": 0
},
"id": 1,
"options": {
"legend": {
"calcs": [
"mean",
"max"
],
"displayMode": "table",
"placement": "right",
"showLegend": true
},
"tooltip": {
"mode": "multi",
"sort": "none"
}
},
"title": "KV Cache Utilization by Worker",
"type": "timeseries",
"targets": [
{
"datasource": {
"type": "prometheus",
"uid": "prometheus"
},
"editorMode": "code",
"expr": "100 * llm_kv_blocks_active{component=\"$component\", endpoint=\"$endpoint\"} / llm_kv_blocks_total{component=\"$component\", endpoint=\"$endpoint\"}",
"legendFormat": "Worker {{worker_id}}",
"range": true,
"refId": "A"
}
]
},
{
"datasource": {
"type": "prometheus",
"uid": "prometheus"
},
"fieldConfig": {
"defaults": {
"color": {
"mode": "palette-classic"
},
"custom": {
"axisCenteredZero": false,
"axisColorMode": "text",
"axisLabel": "",
"axisPlacement": "auto",
"barAlignment": 0,
"drawStyle": "line",
"fillOpacity": 20,
"gradientMode": "none",
"hideFrom": {
"legend": false,
"tooltip": false,
"viz": false
},
"lineInterpolation": "smooth",
"lineWidth": 2,
"pointSize": 5,
"scaleDistribution": {
"type": "linear"
},
"showPoints": "never",
"spanNulls": false,
"stacking": {
"group": "A",
"mode": "none"
},
"thresholdsStyle": {
"mode": "off"
}
},
"mappings": [],
"thresholds": {
"mode": "absolute",
"steps": [
{
"color": "green",
"value": null
},
{
"color": "red",
"value": 80
}
]
},
"unit": "percent"
},
"overrides": []
},
"gridPos": {
"h": 8,
"w": 12,
"x": 12,
"y": 0
},
"id": 2,
"options": {
"legend": {
"calcs": [
"mean",
"max"
],
"displayMode": "table",
"placement": "right",
"showLegend": true
},
"tooltip": {
"mode": "multi",
"sort": "none"
}
},
"title": "Request Slot Utilization by Worker",
"type": "timeseries",
"targets": [
{
"datasource": {
"type": "prometheus",
"uid": "prometheus"
},
"editorMode": "code",
"expr": "100 * llm_requests_active_slots{component=\"$component\", endpoint=\"$endpoint\"} / llm_requests_total_slots{component=\"$component\", endpoint=\"$endpoint\"}",
"legendFormat": "Worker {{worker_id}}",
"range": true,
"refId": "A"
}
]
},
{
"datasource": {
"type": "prometheus",
"uid": "prometheus"
},
"fieldConfig": {
"defaults": {
"color": {
"mode": "thresholds"
},
"mappings": [],
"thresholds": {
"mode": "absolute",
"steps": [
{
"color": "green",
"value": null
},
{
"color": "yellow",
"value": 50
},
{
"color": "red",
"value": 80
}
]
},
"unit": "percent"
},
"overrides": []
},
"gridPos": {
"h": 8,
"w": 6,
"x": 0,
"y": 8
},
"id": 3,
"options": {
"orientation": "auto",
"reduceOptions": {
"calcs": [
"lastNotNull"
],
"fields": "",
"values": false
},
"showThresholdLabels": false,
"showThresholdMarkers": true
},
"pluginVersion": "10.0.0",
"title": "Average KV Cache Utilization",
"type": "gauge",
"targets": [
{
"datasource": {
"type": "prometheus",
"uid": "prometheus"
},
"editorMode": "code",
"expr": "100 * avg(llm_kv_blocks_active{component=\"$component\", endpoint=\"$endpoint\"}) / avg(llm_kv_blocks_total{component=\"$component\", endpoint=\"$endpoint\"})",
"legendFormat": "__auto",
"range": true,
"refId": "A"
}
]
},
{
"datasource": {
"type": "prometheus",
"uid": "prometheus"
},
"fieldConfig": {
"defaults": {
"color": {
"mode": "thresholds"
},
"mappings": [],
"thresholds": {
"mode": "absolute",
"steps": [
{
"color": "green",
"value": null
},
{
"color": "yellow",
"value": 50
},
{
"color": "red",
"value": 80
}
]
},
"unit": "percent"
},
"overrides": []
},
"gridPos": {
"h": 8,
"w": 6,
"x": 6,
"y": 8
},
"id": 4,
"options": {
"orientation": "auto",
"reduceOptions": {
"calcs": [
"lastNotNull"
],
"fields": "",
"values": false
},
"showThresholdLabels": false,
"showThresholdMarkers": true
},
"pluginVersion": "10.0.0",
"title": "Average Request Slot Utilization",
"type": "gauge",
"targets": [
{
"datasource": {
"type": "prometheus",
"uid": "prometheus"
},
"editorMode": "code",
"expr": "100 * avg(llm_requests_active_slots{component=\"$component\", endpoint=\"$endpoint\"}) / avg(llm_requests_total_slots{component=\"$component\", endpoint=\"$endpoint\"})",
"legendFormat": "__auto",
"range": true,
"refId": "A"
}
]
},
{
"datasource": {
"type": "prometheus",
"uid": "prometheus"
},
"fieldConfig": {
"defaults": {
"color": {
"mode": "palette-classic"
},
"custom": {
"axisCenteredZero": false,
"axisColorMode": "text",
"axisLabel": "",
"axisPlacement": "auto",
"barAlignment": 0,
"drawStyle": "line",
"fillOpacity": 20,
"gradientMode": "none",
"hideFrom": {
"legend": false,
"tooltip": false,
"viz": false
},
"lineInterpolation": "smooth",
"lineWidth": 2,
"pointSize": 5,
"scaleDistribution": {
"type": "linear"
},
"showPoints": "never",
"spanNulls": false,
"stacking": {
"group": "A",
"mode": "none"
},
"thresholdsStyle": {
"mode": "off"
}
},
"mappings": [],
"thresholds": {
"mode": "absolute",
"steps": [
{
"color": "green",
"value": null
}
]
},
"unit": "none"
},
"overrides": []
},
"gridPos": {
"h": 8,
"w": 12,
"x": 12,
"y": 8
},
"id": 5,
"options": {
"legend": {
"calcs": [
"mean",
"max"
],
"displayMode": "table",
"placement": "right",
"showLegend": true
},
"tooltip": {
"mode": "multi",
"sort": "none"
}
},
"title": "Load Average & Standard Deviation",
"type": "timeseries",
"targets": [
{
"datasource": {
"type": "prometheus",
"uid": "prometheus"
},
"editorMode": "code",
"expr": "llm_load_avg{component=\"$component\", endpoint=\"$endpoint\"}",
"legendFormat": "Average",
"range": true,
"refId": "A"
},
{
"datasource": {
"type": "prometheus",
"uid": "prometheus"
},
"editorMode": "code",
"expr": "llm_load_std{component=\"$component\", endpoint=\"$endpoint\"}",
"hide": false,
"legendFormat": "StdDev",
"range": true,
"refId": "B"
}
]
},
{
"datasource": {
"type": "prometheus",
"uid": "prometheus"
},
"fieldConfig": {
"defaults": {
"color": {
"mode": "palette-classic"
},
"custom": {
"axisCenteredZero": false,
"axisColorMode": "text",
"axisLabel": "",
"axisPlacement": "auto",
"barAlignment": 0,
"drawStyle": "line",
"fillOpacity": 20,
"gradientMode": "none",
"hideFrom": {
"legend": false,
"tooltip": false,
"viz": false
},
"lineInterpolation": "smooth",
"lineWidth": 2,
"pointSize": 5,
"scaleDistribution": {
"type": "linear"
},
"showPoints": "never",
"spanNulls": false,
"stacking": {
"group": "A",
"mode": "none"
},
"thresholdsStyle": {
"mode": "off"
}
},
"mappings": [],
"thresholds": {
"mode": "absolute",
"steps": [
{
"color": "green",
"value": null
}
]
},
"unit": "none"
},
"overrides": []
},
"gridPos": {
"h": 8,
"w": 24,
"x": 0,
"y": 16
},
"id": 6,
"options": {
"legend": {
"calcs": [
"mean",
"max"
],
"displayMode": "table",
"placement": "right",
"showLegend": true
},
"tooltip": {
"mode": "multi",
"sort": "none"
}
},
"title": "Available Resources",
"type": "timeseries",
"targets": [
{
"datasource": {
"type": "prometheus",
"uid": "prometheus"
},
"editorMode": "code",
"expr": "sum(llm_kv_blocks_total{component=\"$component\", endpoint=\"$endpoint\"} - llm_kv_blocks_active{component=\"$component\", endpoint=\"$endpoint\"})",
"legendFormat": "Available KV Blocks",
"range": true,
"refId": "A"
},
{
"datasource": {
"type": "prometheus",
"uid": "prometheus"
},
"editorMode": "code",
"expr": "sum(llm_requests_total_slots{component=\"$component\", endpoint=\"$endpoint\"} - llm_requests_active_slots{component=\"$component\", endpoint=\"$endpoint\"})",
"hide": false,
"legendFormat": "Available Request Slots",
"range": true,
"refId": "B"
}
]
}
],
"refresh": "5s",
"schemaVersion": 38,
"style": "dark",
"tags": [
"llm",
"metrics"
],
"templating": {
"list": [
{
"current": {
"selected": false,
"text": "backend",
"value": "backend"
},
"datasource": {
"type": "prometheus",
"uid": "prometheus"
},
"definition": "label_values(llm_kv_blocks_active, component)",
"hide": 0,
"includeAll": false,
"label": "Component",
"multi": false,
"name": "component",
"options": [],
"query": {
"query": "label_values(llm_kv_blocks_active, component)",
"refId": "StandardVariableQuery"
},
"refresh": 1,
"regex": "",
"skipUrlSync": false,
"sort": 0,
"type": "query"
},
{
"current": {
"selected": false,
"text": "generate",
"value": "generate"
},
"datasource": {
"type": "prometheus",
"uid": "prometheus"
},
"definition": "label_values(llm_kv_blocks_active{component=\"$component\"}, endpoint)",
"hide": 0,
"includeAll": false,
"label": "Endpoint",
"multi": false,
"name": "endpoint",
"options": [],
"query": {
"query": "label_values(llm_kv_blocks_active{component=\"$component\"}, endpoint)",
"refId": "StandardVariableQuery"
},
"refresh": 1,
"regex": "",
"skipUrlSync": false,
"sort": 0,
"type": "query"
}
]
},
"time": {
"from": "now-15m",
"to": "now"
},
"timepicker": {},
"timezone": "",
"title": "LLM Worker Metrics",
"uid": "llm-worker-metrics",
"version": 1,
"weekStart": ""
}
applications/llm/count/visualization/prometheus.yml 0 → 100644
View file @ d38325c2
# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
global:
scrape_interval: 1s
evaluation_interval: 1s
scrape_configs:
- job_name: 'count'
static_configs:
# TODO: Use proper docker networking
# - targets: ['host.docker.internal:9091']
- targets: ['localhost:9091']
lib/llm/src/kv_router.rs
View file @ d38325c2
...@@ -23,8 +23,8 @@ use triton_distributed_runtime::{component::Component, DistributedRuntime}; ...@@ -23,8 +23,8 @@ use triton_distributed_runtime::{component::Component, DistributedRuntime};
pub mod indexer; pub mod indexer;
pub mod protocols; pub mod protocols;
pub mod publisher; pub mod publisher;
mod scheduler; pub mod scheduler;
mod scoring; pub mod scoring;
use crate::kv_router::{ use crate::kv_router::{
indexer::{KvIndexer, KvIndexerInterface, RouterEvent}, indexer::{KvIndexer, KvIndexerInterface, RouterEvent},
......
lib/llm/src/kv_router/scoring.rs
View file @ d38325c2
...@@ -15,11 +15,12 @@ ...@@ -15,11 +15,12 @@
//! Scoring functions for the KV router. //! Scoring functions for the KV router.
use serde::{Deserialize, Serialize};
use std::collections::HashSet; use std::collections::HashSet;
use crate::kv_router::scheduler::Endpoint; use crate::kv_router::scheduler::Endpoint;
#[derive(Debug, Default)] #[derive(Debug, Default, Serialize, Deserialize)]
pub struct ProcessedEndpoints { pub struct ProcessedEndpoints {
pub endpoints: Vec<Endpoint>, pub endpoints: Vec<Endpoint>,
pub worker_ids: Vec<i64>, pub worker_ids: Vec<i64>,
......
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