YARP, 强大的可编程的反向代理

YARP, 在Nginx、Apache、Ocelot等之外,一个.Net Core下Reverse Proxy的新起之秀,Microsoft官方维护开源,从此你拥有了强大的可编程的反向代理。

原文链接:YARP Documentation (microsoft.github.io)

YARP is a library to help create reverse proxy servers that are high-performance, production-ready, and highly customizable. Right now it’s still in preview, but please provide us your feedback by going to the GitHub repository.

We found a bunch of internal teams at Microsoft who were either building a reverse proxy for their service or had been asking about APIs and tech for building one, so we decided to get them all together to work on a common solution, this project.

YARP is built on .NET using the infrastructure from ASP.NET and .NET (.NET Core 3.1 and .NET 5.0). The key differentiator for YARP is that it’s been designed to be easily customized and tweaked via .NET code to match the specific needs of each deployment scenario.

We expect YARP to ship as a library, project template, and a single-file exe, to provide a variety of choices for building a robust, performant proxy server. Its pipeline and modules are designed so that you can then customize the functionality for your needs. For example, while YARP supports configuration files, we expect that many users will want to manage the configuration programmatically based on their own configuration management system, YARP will provide a configuration API to enable that customization in-proc. YARP is designed with customizability as a primary scenario rather than requiring you to break out to script or rebuild the library from source.


  • Header Routing

Proxy routes specified in config or via code must include at least a path or host to match against. In addition to these, a route can also specify one or more headers that must be present on the request.

  • Authentication and Authorization

The reverse proxy can be used to authenticate and authorize requests before they are proxied to the destination servers. This can reduce load on the destination servers, add a layer of protection, and ensure consistent policies are implemented across your applications.

  • Cross-Origin Requests (CORS)

The reverse proxy can handle cross-origin requests before they are proxied to the destination servers. This can reduce load on the destination servers and ensure consistent policies are implemented across your applications.

  • Session Affinity:

Session affinity is a mechanism to bind (affinitize) a causally related request sequence to the destination handled the first request when the load is balanced among several destinations. It is useful in scenarios where the most requests in a sequence work with the same data and the cost of data access differs for different nodes (destinations) handling requests. The most common example is a transient caching (e.g. in-memory) where the first request fetches data from a slower persistent storage into a fast local cache and the others work only with the cached data thus increasing throughput.

  • Load Balancing

Whenever there are multiple healthy destinations available, YARP has to decide which one to use for a given request. YARP ships with built-in load-balancing algorithms, but also offers extensibility for any custom load balancing approach.

  • Transforms

When proxying a request it’s common to modify parts of the request or response to adapt to the destination server’s requirements or to flow additional data such as the client’s original IP address. This process is implemented via Transforms. Types of transforms are defined globally for the application and then individual routes supply the parameters to enable and configure those transforms. The original request objects are not modified by these transforms, only the proxy requests.

  • Destinations Health Checks

In most of the real-world systems, it’s expected for their nodes to occasionally experience transient issues and go down completely due to a variety of reasons such as an overload, resource leakage, hardware failures, etc. Ideally, it’d be desirable to completely prevent those unfortunate events from occurring in a proactive way, but the cost of designing and building such an ideal system is generally prohibitively high. However, there is another reactive approach which is cheaper and aimed to minimizing a negative impact failures cause on client requests. The proxy can analyze each nodes health and stop sending client traffic to unhealthy ones until they recover. YARP implements this approach in the form of active and passive destination health checks.

Continue reading “YARP, 强大的可编程的反向代理”

Shard (database architecture)

A database shard, or simply a shard, is a horizontal partition of data in a database or search engine. Each shard is held on a separate database server instance, to spread load.

Some data within a database remains present in all shards, but some appears only in a single shard. Each shard (or server) acts as the single source for this subset of data.

Database architecture

Horizontal partitioning is a database design principle whereby rows of a database table are held separately, rather than being split into columns (which is what normalization and vertical partitioning do, to differing extents). Each partition forms part of a shard, which may in turn be located on a separate database server or physical location.

There are numerous advantages to the horizontal partitioning approach. Since the tables are divided and distributed into multiple servers, the total number of rows in each table in each database is reduced. This reduces index size, which generally improves search performance. A database shard can be placed on separate hardware, and multiple shards can be placed on multiple machines. This enables a distribution of the database over a large number of machines, greatly improving performance. In addition, if the database shard is based on some real-world segmentation of the data (e.g., European customers v. American customers) then it may be possible to infer the appropriate shard membership easily and automatically, and query only the relevant shard.

Disadvantages include:

Main section: Disadvantages

  • A heavier reliance on the interconnection between servers.
  • Increased latency when querying, especially where more than one shard must be searched.
  • Data or indexes are often only sharded one way, so that some searches are optimal, and others are slow or impossible.
  • Issues of consistency and durability due to the more complex failure modes of a set of servers, which often result in systems making no guarantees about cross-shard consistency or durability.

In practice, sharding is complex. Although it has been done for a long time by hand-coding (especially where rows have an obvious grouping, as per the example above), this is often inflexible. There is a desire to support sharding automatically, both in terms of adding code support for it, and for identifying candidates to be sharded separately. Consistent hashing is a technique used in sharding to spread large loads across multiple smaller services and servers.

Where distributed computing is used to separate load between multiple servers (either for performance or reliability reasons), a shard approach may also be useful. Continue reading “Shard (database architecture)”