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2 changes: 1 addition & 1 deletion VERSIONS/GO_VERSION
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@@ -1 +1 @@
1.24.5
1.25.5
7 changes: 1 addition & 6 deletions content/docs/api/build_proto.md
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---
title: "Build_proto_api"
date: 2024-08-08T00:23:48+09:00
date: 2026-01-13T05:57:04Z
draft: false
weight: 1100
description: How to build gRPC proto files for calling API to your Vald cluster
Expand Down Expand Up @@ -41,12 +41,10 @@ Let's build proto files using your favorite programming language.
There are 3 steps to building API proto:

1. Install gRPC tools

- gRPC official document provides [the way to install for each language](https://grpc.io/docs/languages/).<br>
If your favorite programming language is not there, you can find 3rd party tools for building.

1. Download Vald api proto files and external dependence

- [vald api proto](https://github.com/vdaas/vald/tree/main/apis/proto/v1/vald)
- [vald payload proto](https://github.com/vdaas/vald/tree/main/apis/proto/v1/payload)
- [googleapis](https://github.com/googleapis/googleapis)
Expand Down Expand Up @@ -154,7 +152,6 @@ There are many tools for building proto in Rust, we use [tonic](https://github.c
```

1. Implement `build.rs` and Build proto

1. `build.rs`

```rust
Expand Down Expand Up @@ -207,7 +204,6 @@ There are many tools for building proto in Rust, we use [tonic](https://github.c
```

1. Implement code using client

1. `lib.rs`

Import build proto in `src/lib.rs`
Expand Down Expand Up @@ -241,7 +237,6 @@ There are many tools for building proto in Rust, we use [tonic](https://github.c
1. `src/client.rs`

There are 4 steps in `src/client.rs`:

1. Load dataset
1. Insert vector to Vald cluster
1. Search nearest neighbor vectors from Vald cluster after indexing finished
Expand Down
9 changes: 5 additions & 4 deletions content/docs/contributing/_index.md
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---
title: "Contributing_contributing"
date: 2024-01-10T18:16:47+09:00
draft: false
weight: 0
title: "Content Placeholder"
build:
render: never
list: never
publishResources: false
---

5 changes: 1 addition & 4 deletions content/docs/contributing/coding-style.md
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---
title: "Coding Style_contributing"
date: 2024-10-16T16:03:39+09:00
date: 2026-01-13T05:57:05Z
draft: false
weight: 300
description: Coding style for Vald project
Expand Down Expand Up @@ -815,7 +815,6 @@ tests := map[string]func(t *testing.T) test {

Test case names should be readable, meaningful, and understandable easily.
If you create a new test, the test name should be named based on the below-naming templates

- Success cases:
- Start with `success` or `{verb} success` or `success {verb}`
- End with the condition `when {condition}` or `with {condition}
Expand Down Expand Up @@ -988,7 +987,6 @@ Still, in some cases, you may need to change the generated code to meet your req
1. goleak usage

There are two methods for valid goroutine leak:

1. Use `goleak.VerifyNone()` to validate it on each test cases.
1. Use `goleak.VerifyTestMain()` to validate it on each package.

Expand Down Expand Up @@ -1135,7 +1133,6 @@ Still, in some cases, you may need to change the generated code to meet your req

By default, when testing the function of the struct, the target struct initialization is implemented by setting the data from the `fields` defined in the test case.
This initialization method has a few disadvantages:

1. When there are many fields in the struct, it is hard to set them all.
1. The default value is the zero value of the type, not the struct default value from the struct initialization function.

Expand Down
9 changes: 5 additions & 4 deletions content/docs/overview/_index.md
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@@ -1,7 +1,8 @@
---
title: "Overview_overview"
date: 2024-01-10T18:16:47+09:00
draft: false
weight: 0
title: "Content Placeholder"
build:
render: never
list: never
publishResources: false
---

10 changes: 1 addition & 9 deletions content/docs/overview/about-vald.md
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@@ -1,6 +1,6 @@
---
title: "About Vald_overview"
date: 2025-09-02T04:53:44Z
date: 2026-01-13T05:57:07Z
draft: false
weight: 100
description: What is Vald and what you can do with Vald
Expand Down Expand Up @@ -32,39 +32,31 @@ Vald is easy to use, feature-rich and highly customizable as you needed.
<!-- copied from README-->

- Asynchronous Auto Indexing

- Usually the graph requires locking during indexing, which causes stop-the-world. But Vald uses distributed index graphs so it continues to work during indexing.

- Customizable Ingress/Egress Filtering

- Vald implements it's own highly customizable Ingress/Egress filter.
- Which can be configured to fit the gRPC interface.
- Ingress Filter: Ability to Vectorize through filter on request.
- Egress Filter: rerank or filter the searching result with your own algorithm.

- Cloud-native based vector searching engine

- Horizontal scalable on memory and CPU for your demand.

- Auto Backup for Index data

- Vald supports to backup Vald Agent index data using Object Storage or Persistent Volume.

- Distributed Indexing

- Vald distributes vector index to multiple agents, and each agent stores different index.

- Index Replication

- Vald stores each index in multiple agents which enables index replicas.
- Automatically rebalancing the replica when some Vald agent goes down.

- Easy to use

- Vald can be easily installed in a few steps.

- Highly customizable

- You can configure the number of vector dimensions, the number of replica and etc.

- Multi language supported
Expand Down
3 changes: 1 addition & 2 deletions content/docs/overview/architecture.md
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@@ -1,6 +1,6 @@
---
title: "Architecture_overview"
date: 2024-08-08T00:23:48+09:00
date: 2026-01-13T05:57:06Z
draft: false
weight: 200
description: High-Level architecture design and overview of each component
Expand Down Expand Up @@ -63,7 +63,6 @@ Here are the concepts of Vald.
- Kubernetes based

Vald can integrate with Kubernetes which enables the following features.

- Orchestrated

Kubernetes supports container orchestration. All components in Vald can be managed by Kubernetes automatically.
Expand Down
6 changes: 1 addition & 5 deletions content/docs/overview/component/mirror-gateway.md
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@@ -1,6 +1,6 @@
---
title: "Mirror Gateway_overview/Component"
date: 2024-02-15T17:10:09+09:00
date: 2026-01-13T05:57:07Z
draft: false
weight: 600
description: Gateway for operating Vald cluster compatible with Multi-region and Multi AZ
Expand Down Expand Up @@ -66,27 +66,23 @@ Here's an overview of how the Mirror Gateway handles failures for each type of r
For more information about status code, please refer to [Mirror Gateway Troubleshooting](/docs/troubleshooting/mirror-gateway).

- Insert Request

- If the target host returns a status code of `ALREADY_EXISTS`, the Update request is sent to this host.
- If the target host returns a status code other than `OK`, `ALREADY_EXISTS`, the Mirror Gateway returns that status code without continuous processing.
- If all target hosts return a status code `ALREADY_EXISTS`, the Mirror Gateway returns `ALREADY_EXISTS`.
- If all target hosts return a status code `OK` or `ALREADY_EXISTS`, the Mirror Gateway returns `OK`.

- Update Request

- If the target host returns a status code `NOT_FOUND`, the Insert request is sent to this host.
- If the target host returns a status code other than `OK`, `ALREADY_EXISTS`, the Mirror Gateway returns that status code without continuous processing.
- If all target hosts return a status code `ALREADY_EXISTS`, the Mirror Gateway returns `ALREADY_EXISTS`.
- If all target hosts return a status code `OK` or `ALREADY_EXISTS`, the Mirror Gateway returns `OK`.

- Upsert Request

- If all target hosts return a status code `ALREADY_EXISTS`, the Mirror Gateway returns `ALREADY_EXISTS`.
- If the target host returns a status code other than `OK` or `ALREADY_EXISTS`, the Mirror Gateway returns that status code without continuous processing.
- If all target hosts return a status code `OK` or `ALREADY_EXISTS`, the Mirror Gateway returns `OK`.

- Remove/RemoveByTimestamp Request

- If all target hosts return a status code `NOT_FOUND`, the Mirror Gateway returns `NOT_FOUND`.
- If the target host returns a status code other than `OK` or `NOT_FOUND`, the Mirror Gateway returns that status code without continuous processing.
- If all target hosts return a status code `OK` or `NOT_FOUND`, the Mirror Gateway returns `OK`.
9 changes: 5 additions & 4 deletions content/docs/performance/_index.md
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@@ -1,7 +1,8 @@
---
title: "Performance_performance"
date: 2024-01-10T18:16:47+09:00
draft: false
weight: 0
title: "Content Placeholder"
build:
render: never
list: never
publishResources: false
---

16 changes: 8 additions & 8 deletions content/docs/performance/loadtest.md
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---
title: "Loadtest_performance"
date: 2025-09-02T04:53:40Z
date: 2026-01-13T05:57:05Z
draft: false
weight: 200
description: Shows how to perform load test in the Vald cluster
Expand Down Expand Up @@ -43,14 +43,14 @@ Please refer to the [Sample configuration file](https://github.com/vdaas/vald/bl

Here are the important configurations and following the explanation.

| Name | Description | Example |
| :---------- | :---------------------------------------------------------------------------------------------------------------------------------------------------------------------- | :------------------------------------------ |
| service | By setting the value to the gateway, you can test the Vald cluster through the Vald gateway. <br />By setting the value to agent, you can test the Vald agent directly. | gateway or agent |
| Name | Description | Example |
| :---------- | :---------------------------------------------------------------------------------------------------------------------------------------------------------------------- | :------------------------------------------- |
| service | By setting the value to the gateway, you can test the Vald cluster through the Vald gateway. <br />By setting the value to agent, you can test the Vald agent directly. | gateway or agent |
| operation | To perform the specific load test action to the Vald cluster. | insert, streaminsert, search or streamsearch |
| dataset | The dataset is used in insert and stream insert operation. | |
| concurrency | The number of concurrent execution of the load test. | |
| batch_size | The batch size of the dataset. | |
| addr | The cluster you want to test | |
| dataset | The dataset is used in insert and stream insert operation. | |
| concurrency | The number of concurrent execution of the load test. | |
| batch_size | The batch size of the dataset. | |
| addr | The cluster you want to test | |

## Execute load test

Expand Down
9 changes: 5 additions & 4 deletions content/docs/release/_index.md
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---
title: "Release_release"
date: 2024-01-10T18:16:48+09:00
draft: false
weight: 0
title: "Content Placeholder"
build:
render: never
list: never
publishResources: false
---

9 changes: 5 additions & 4 deletions content/docs/support/_index.md
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@@ -1,7 +1,8 @@
---
title: "Support_support"
date: 2024-01-10T18:16:47+09:00
draft: false
weight: 0
title: "Content Placeholder"
build:
render: never
list: never
publishResources: false
---

9 changes: 5 additions & 4 deletions content/docs/tutorial/_index.md
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@@ -1,7 +1,8 @@
---
title: "Tutorial_tutorial"
date: 2024-01-10T18:16:47+09:00
draft: false
weight: 0
title: "Content Placeholder"
build:
render: never
list: never
publishResources: false
---

9 changes: 1 addition & 8 deletions content/docs/tutorial/get-started-with-faiss-agent.md
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@@ -1,6 +1,6 @@
---
title: "Get Started With Faiss Agent_tutorial"
date: 2024-10-16T16:03:40+09:00
date: 2026-01-13T05:57:06Z
draft: false
weight: 200
description: Running Vald cluster with faiss Agent on Kubernetes and execute client codes
Expand Down Expand Up @@ -200,9 +200,7 @@ If you are interested, please refer to [SDKs](/docs/user-guides/sdks).<br>

<details><summary>The detailed explanation of example code is here</summary><br>
This will execute 6 steps.

1. init

- Import packages
<details><summary>example code</summary><br>

Expand All @@ -228,7 +226,6 @@ If you are interested, please refer to [SDKs](/docs/user-guides/sdks).<br>
</details>

- Set variables

- The constant number of training datasets and test datasets.
<details><summary>example code</summary><br>

Expand Down Expand Up @@ -269,7 +266,6 @@ If you are interested, please refer to [SDKs](/docs/user-guides/sdks).<br>
</details>

1. load

- Loading from Fashion-MNIST dataset and set id for each vector that is loaded. This step will return the training dataset, test dataset, and ids list of ids when loading is completed with success.
<details><summary>example code</summary><br>

Expand Down Expand Up @@ -300,7 +296,6 @@ If you are interested, please refer to [SDKs](/docs/user-guides/sdks).<br>
</details>

1. Insert and Index

- Insert and Indexing 400 training datasets to the Vald agent.
<details><summary>example code</summary><br>

Expand Down Expand Up @@ -338,7 +333,6 @@ If you are interested, please refer to [SDKs](/docs/user-guides/sdks).<br>
</details>

1. Search

- Search 10 neighbor vectors for each 20 test datasets and return a list of the neighbor vectors.

- When getting approximate vectors, the Vald client sends search config and vector to the server via gRPC.
Expand Down Expand Up @@ -369,7 +363,6 @@ If you are interested, please refer to [SDKs](/docs/user-guides/sdks).<br>
</details>

1. Remove

- Remove 400 indexed training datasets from the Vald agent.
<details><summary>example code</summary><br>

Expand Down
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