Self-Hosted Remote Build Cache: BuildBuddy vs bazel-remote vs NativeLink (2026)

If you use Bazel or any build system that supports remote caching, you know the difference between local builds and remote-cached builds can mean the difference between a 30-second feedback loop and a 15-minute wait. Remote build caches store compiled artifacts, test results, and intermediate outputs on a shared server so that every developer and CI runner benefits from each other’s work.

Public caching services exist, but for organizations with proprietary code, compliance requirements, or large artifact volumes, self-hosting your build cache gives you full control over data retention, network performance, and access policies. This guide compares three self-hosted remote build cache and execution servers: BuildBuddy for a full-featured build observability platform, bazel-remote for a lightweight HTTP cache, and NativeLink for a high-performance Rust-based cache with remote execution.

Why Use a Remote Build Cache?

Build systems like Bazel produce deterministic outputs — given the same inputs, they generate identical artifacts. A remote cache exploits this determinism by storing outputs from previous builds on a shared server. When another developer or CI job requests the same build action, the cache returns the pre-built result instead of re-compiling from source.

The benefits are substantial:

• Faster CI pipelines: Cached builds skip compilation, linking, and test execution entirely
• Developer productivity: Local builds complete in seconds when hitting the remote cache
• Cost savings: Reduced compute consumption across CI runners and developer machines
• Reproducible builds: Centralized cache ensures all environments use identical artifacts

For teams running Bazel at scale, a remote cache typically reduces average build times by 60-90 percent. The remaining compilation happens only for genuinely new or modified code paths.

BuildBuddy: Build Observability and Remote Cache

BuildBuddy is the most feature-rich open-source build platform for Bazel. Written in Go, it combines a remote cache, remote execution engine, build event viewer, and analytics dashboard into a single self-hosted deployment. With 740 GitHub stars and active development, it is widely adopted by teams that need both caching and build visibility.

Key Features

• Remote cache: HTTP/1.1 and gRPC-based artifact storage with configurable backends (disk, S3, GCS, Redis)
• Remote execution: Distributed build execution across worker nodes for parallel compilation
• Build event UI: Real-time visualization of build progress, test results, and action graphs
• Invocation history: Searchable history of all builds with timing breakdowns and failure analysis
• Build metrics: Dashboards showing cache hit rates, build durations, and resource utilization
• Role-based access control: Team-level permissions for build access and configuration
• GitHub and GitLab integration: Build status reporting and PR build result comments

Docker Compose Deployment

BuildBuddy provides an official Docker image with integrated caching and UI:

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services:
  buildbuddy:
    image: gcr.io/flank-public/buildbuddy-server:latest
    ports:
      - "8080:8080"
      - "1985:1985"
    volumes:
      - bb-config:/config
      - bb-cache:/cache
    command: >
      --config_file=/config/buildbuddy.config.yaml
    environment:
      - BB_CACHE_DIR=/cache

  buildbuddy-executor:
    image: gcr.io/flank-public/buildbuddy-executor:latest
    depends_on:
      - buildbuddy
    environment:
      - BB_BACKEND_ADDRESS=buildbuddy:1985
      - BB_CACHE_DIR=/executor-cache
      - BUILD_RUNNER_LOCAL_CACHE_DIRECTORY=/tmp/build-runner-cache
    volumes:
      - executor-cache:/executor-cache
      - /var/run/docker.sock:/var/run/docker.sock

volumes:
  bb-config:
  bb-cache:
  executor-cache:

Configure your .bazelrc to point to the self-hosted cache:

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build --remote_cache=grpc://localhost:1985
build --remote_instance_name=main
build --remote_upload_local_results=true

Storage Backend Options

BuildBuddy supports multiple storage backends for the remote cache:

For production deployments, pairing S3 or GCS for persistent storage with Redis for hot cache lookups delivers the best balance of performance and cost.

bazel-remote: Lightweight HTTP Cache

bazel-remote is a minimal, high-performance remote cache server written in Go. It implements the Bazel Remote Execution API (v2) and the HTTP/1.1 REST API, making it compatible with Bazel, Pants, and other build systems that support remote caching. At 735 GitHub stars, it is a battle-tested choice for teams that need caching without the overhead of a full build platform.

Key Features

• Dual protocol support: gRPC Remote Execution API and HTTP/1.1 REST API
• Multiple storage backends: Disk, S3, GCS, and Azure Blob Storage
• Proxy cache mode: Chain with public caches (BuildBuddy Cloud, EngFlow) for hybrid setups
• AC authentication: Optional HTTP Basic Auth for cache access control
• Redis-based metadata index: Fast lookups even with millions of cached artifacts
• GZIP compression: Automatic compression of stored artifacts to reduce disk usage
• Prometheus metrics: Cache hit rates, storage utilization, and request latency
• Zero UI: Headless operation — designed for infrastructure teams that manage caches programmatically

Docker Compose Deployment

bazel-remote runs as a single container with configurable storage:

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services:
  bazel-remote:
    image: buchgr/bazel-remote-cache:latest
    ports:
      - "8080:8080"
      - "9092:9092"
    volumes:
      - cache-data:/data
    command: >
      --max_size=50
      --dir=/data
      --http_address=:8080
      --grpc_address=:9092
      --tls_enabled=false
      --htpasswd_file=/config/.htpasswd
    environment:
      - GOOGLE_APPLICATION_CREDENTIALS=/config/gcs-credentials.json

volumes:
  cache-data:

Configure Bazel to use bazel-remote:

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# .bazelrc
build --remote_cache=http://localhost:8080
build --remote_http_cache=http://localhost:8080
build --remote_upload_local_results=true

Resource Requirements

bazel-remote is remarkably lightweight. A small team can run it on a single VM with 50 GB of disk. The Redis metadata index consumes approximately 100 bytes per cached artifact, so even with millions of entries, memory usage stays manageable.

NativeLink: High-Performance Rust Cache and Remote Execution

NativeLink is a newer entrant in the remote cache space, written entirely in Rust for maximum performance. Backed by the Nix ecosystem, NativeLink provides both remote caching and remote execution with a focus on speed, correctness, and Nix-based reproducibility. With 1,525 GitHub stars, it has quickly gained traction among teams prioritizing build performance.

Key Features

• Rust-native performance: Memory-safe, high-throughput cache with minimal latency
• Remote execution: Distributed build execution with worker pool management
• Nix integration: First-class support for Nix-based build workflows and reproducibility
• Configurable storage tiers: Hot (memory/RAM), warm (NVMe SSD), and cold (object storage) tiers
• CAS (Content Addressable Storage): Efficient deduplication of build artifacts
• gRPC-based protocol: Full Remote Execution API v2 compliance
• Observable metrics: Prometheus-compatible metrics for cache hit rates and execution timing
• Multi-tenant support: Isolated cache namespaces for different teams or projects

Docker Compose Deployment

NativeLink ships as a single binary with a YAML configuration file:

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services:
  nativelink:
    image: nativelink/nativelink:latest
    ports:
      - "50051:50051"
      - "50052:50052"
    volumes:
      - ./nativelink-config.yaml:/etc/nativelink/config.yaml
      - cache-data:/data
    command: /etc/nativelink/config.yaml

volumes:
  cache-data:

Example configuration file (nativelink-config.yaml):

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stores:
  CAS_MAIN_STORE:
    filesystem:
      content_path: /data/cas
      temp_path: /data/cas-tmp
      read_buffer_size_bytes: 4194304
  AC_MAIN_STORE:
    fast_slow:
      fast:
        memory:
          eviction_policy:
            max_bytes: 1073741824  # 1 GB RAM cache
      slow:
        filesystem:
          content_path: /data/ac
          temp_path: /data/ac-tmp

servers:
  listen_address: "0.0.0.0:50051"
  services:
    bytestream:
      CasStore: CAS_MAIN_STORE
    grpc:
      CasStore: CAS_MAIN_STORE
      AcStore: AC_MAIN_STORE
    capabilities:
      CasStore: CAS_MAIN_STORE

Configure Bazel:

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# .bazelrc
build --remote_cache=grpc://localhost:50051
build --remote_instance_name=main
build --remote_upload_local_results=true

Feature Comparison Table

When to Use Each Tool

Choose BuildBuddy if you need more than just caching. Its build event UI, invocation history, and analytics dashboards make it the best choice for teams that want visibility into their build pipelines alongside the cache. The remote execution capability further accelerates builds by distributing compilation across worker nodes. If you are managing a CI/CD pipeline and want to speed up your builds, BuildBuddy integrates well with self-hosted CI systems.

Choose bazel-remote if you need a simple, reliable cache with minimal operational overhead. Its headless design means no UI to maintain, and the single-container deployment is easy to manage. The proxy cache mode lets you chain it with public caches for hybrid workflows. If your team already monitors infrastructure with Prometheus, bazel-remote’s metrics integrate seamlessly. For teams managing containerized builds, consider pairing it with self-hosted container management tools for full pipeline visibility.

Choose NativeLink if raw cache performance is your top priority. Its Rust implementation delivers lower latency and higher throughput than Go-based alternatives, and the tiered storage architecture (RAM → SSD → object storage) automatically optimizes cost versus speed. The Nix integration makes it ideal for teams using Nix-based build workflows who need reproducible, cached builds across heterogeneous environments.

Why Self-Host Your Build Cache?

Self-hosting a remote build cache gives you control over artifact retention policies, network performance, and data sovereignty. Public cache services impose storage limits and may evict artifacts under load, causing unpredictable cache miss rates. A self-hosted cache lets you allocate exactly the storage you need and configure eviction policies based on your team’s workflow.

Network latency is another critical factor. A self-hosted cache on your LAN or within your cloud VPC eliminates the round-trip latency to a public service, which can add hundreds of milliseconds per cache lookup. At scale, those milliseconds compound across thousands of build actions.

Security-conscious organizations benefit from keeping build artifacts on-premises. Compiled binaries, test outputs, and dependency downloads never leave your infrastructure, reducing the attack surface and simplifying compliance audits.

FAQ

Can I use bazel-remote with build systems other than Bazel?

Yes. bazel-remote implements the standard Remote Execution API v2, which is supported by Pants, Buck2, and other build systems that have adopted the protocol. Any build tool that speaks the gRPC Remote Execution API or the HTTP/1.1 REST API can use bazel-remote as a cache.

How much disk space should I allocate for a remote build cache?

The required disk space depends on your project size, number of developers, and cache eviction policy. A starting point of 50 GB works for small teams (1-10 developers) with moderate build volumes. Medium teams should plan for 200-500 GB, and large organizations may need 1-2 TB or should offload cold artifacts to S3/GCS. Monitor the cache hit rate to determine if your allocation is sufficient — hit rates below 50 percent often indicate the cache is too small.

Does BuildBuddy require a separate database?

BuildBuddy stores build metadata and event data in an embedded SQLite database by default, which works fine for small teams. For production deployments with high build volumes, configure an external PostgreSQL database for better performance and durability. The remote cache itself uses your configured storage backend (disk, S3, GCS, or Redis), not the metadata database.

Can I chain multiple cache servers together?

Yes. bazel-remote supports proxy cache mode, allowing you to configure it to forward cache misses to an upstream cache. This is useful for hybrid setups where local CI runners hit a self-hosted cache first, and misses fall back to a public cache like BuildBuddy Cloud. BuildBuddy can also be configured with multiple storage tiers for similar behavior.

Is NativeLink production-ready?

NativeLink is actively developed and used in production by several organizations. Its Rust foundation provides memory safety and performance advantages, but the project is younger than BuildBuddy and bazel-remote. Evaluate it for your workload and test thoroughly before committing to production use. The active development cadence (regular commits as of May 2026) suggests rapid maturation.

How do I monitor cache effectiveness?

All three tools expose Prometheus metrics. Key metrics to track include:

• Cache hit rate: Percentage of build actions served from cache (target: 70%+)
• Cache size utilization: Current storage used vs. maximum configured
• Request latency: P50 and P99 response times for cache lookups
• Eviction rate: How often artifacts are removed to make room for new ones

Set up Grafana dashboards to visualize these metrics over time and alert on declining hit rates.