apisix VS Docker Compose

Through this intelligent caching mechanism, APISIX efficiently utilizes system resources when handling a large volume of requests, thereby improving overall system performance and stability. APISIX, with its advanced LRU cache, provides developers with a reliable and efficient API gateway solution, facilitating smooth communication with external services.

The main issue is that priority is documented in the config-default.yaml file, while the phase is buried in the code. Worse, some plugins run across different phases. For example, let's check the proxy proxy-rewrite plugin and, more precisely, the functions defined there:

// references: // https://github.com/tetratelabs/proxy-wasm-go-sdk/tree/main/examples // https://github.com/apache/apisix/blob/master/t/wasm/ package main import ( "github.com/tetratelabs/proxy-wasm-go-sdk/proxywasm" "github.com/tetratelabs/proxy-wasm-go-sdk/proxywasm/types" "github.com/valyala/fastjson" ) func main() { proxywasm.SetVMContext(&vmContext{}) } // each plugin has its own VMContext. // it is responsible for creating multiple PluginContexts for each route. type vmContext struct { types.DefaultVMContext } // each route has its own PluginContext. // it corresponds to one instance of the plugin. func (*vmContext) NewPluginContext(contextID uint32) types.PluginContext { return &pluginContext{} } type header struct { Name string Value string } type pluginContext struct { types.DefaultPluginContext Headers []header } func (ctx *pluginContext) OnPluginStart(pluginConfigurationSize int) types.OnPluginStartStatus { data, err := proxywasm.GetPluginConfiguration() if err != nil { proxywasm.LogErrorf("error reading plugin configuration: %v", err) return types.OnPluginStartStatusFailed } var p fastjson.Parser v, err := p.ParseBytes(data) if err != nil { proxywasm.LogErrorf("error decoding plugin configuration: %v", err) return types.OnPluginStartStatusFailed } headers := v.GetArray("headers") ctx.Headers = make([]header, len(headers)) for i, hdr := range headers { ctx.Headers[i] = header{ Name: string(hdr.GetStringBytes("name")), Value: string(hdr.GetStringBytes("value")), } } return types.OnPluginStartStatusOK } // each HTTP request to a route has its own HTTPContext func (ctx *pluginContext) NewHttpContext(contextID uint32) types.HttpContext { return &httpContext{parent: ctx} } type httpContext struct { types.DefaultHttpContext parent *pluginContext } func (ctx *httpContext) OnHttpResponseHeaders(numHeaders int, endOfStream bool) types.Action { plugin := ctx.parent for _, hdr := range plugin.Headers { proxywasm.ReplaceHttpResponseHeader(hdr.Name, hdr.Value) } return types.ActionContinue }

API7 takes Apache APISIX as its robust foundation, which is open-source and has an active community with over 600 contributors all over the world. The nature of open source allows users to examine the source code, which promotes transparency. This transparency helps users understand how APISIX works, verify its security, and identify and fix any potential vulnerabilities or bugs.

But the best part is that the libraries mentioned here and Apache APISIX are entirely open source, meaning you can look under the hood and modify things yourself.

Default configuration

4. Plugin definition: It is a really important part of plugin implementation that we define as a table with properties for the version, priority, name, and schema. The name and schema are the plugin's name and schema defined earlier. The version and priority are used by APISIX to manage the plugin. The version typically refers to the version that is currently in use like API versioning. If you publish and update your plugin logic, it is going to be 1.1 (You can set any version you wish). But you need to be very careful in choosing priority. The priority field defines in which order and phase your plugin should be executed. For example, the 'ip-restriction' plugin, with a priority of 3000, will be executed before the 'example-plugin', which has a priority of 0. This is due to the higher priority value of the 'ip-restriction' plugin. If you're developing your own plugin, make sure that you followed the order of plugins not to mess up the order of existing plugins. You can check the order of existing plugins in the config-default.yaml file and open the Apache APISIX Plugin Development Guide to determine.

Their use of etcd was a hard pass for me; I don't need more etcd in my life

Apache APISIX Apache APISIX is an open source, dynamic, real-time, high-performance cloud native API gateway. APISIX provides rich traffic management features such as load balancing, dynamic upstream, canary release, circuit breaking, authentication, observability, and more. Official website https://apisix.apache.org/ GitHub projects APISIX (the core): https://github.com/apache/apisix GitHub - apache/apisix: The Cloud-Native API Gateway GitHub - apache/apisix-dashboard: Dashboard for Apache APISIX GitHub - apache/apisix-website: Apache APISIX Website GitHub - apache/apisix-docker: the docker for Apache APISIX GitHub - apache/apisix-go-plugin-runner: Go Plugin Runner for APISIX GitHub - apache/apisix-java-plugin-runner: APISIX Plugin Runner in Java GitHub - apache/apisix-python-plugin-runner: Apache APISIX Python plugin runner GitHub - apache/apisix-helm-chart: Apache APISIX Helm Chart GitHub - apache/apisix-ingress-controller: ingress controller for K8s

Grafana configuration. Most of it comes from the configuration provided by APISIX.

Solutions are many, and could include Docker Compose, VS Code dev containers, Telepresence, Localstack or setting up temporary AWS accounts as a development environment for serverless applications.

Using Docker Compose to run Postgres and any third-party services locally provides a streamlined and consistent development environment. Developers can define services in a docker-compose.yml file, which enables them to configure and launch an entire stack with a single command. In this case, Postgres is encapsulated within a container with predefined configurations. Docker Compose also facilitates easy scaling, updates, and isolation of services, enhancing development efficiency and reducing the setup time for new team members or transitioning between projects. It encapsulates complex configurations, such as Postgres' performance monitoring and logging settings, in a manageable, version-controlled file, simplifying and replicating the service setup across different environments.

“Compose simplifies the control of your entire application stack, making it easy to manage services, networks, and volumes in a single, comprehensible YAML configuration file. Then, with a single command, you create and start all the services from your configuration file.” - Docker documentation

curl -fsSL https://get.docker.com -o get-docker.sh sudo sh get-docker.sh # Install docker compose sudo curl -L "https://github.com/docker/compose/releases/download/1.29.2/docker-compose-$(uname -s)-$(uname -m)" -o /usr/local/bin/docker-compose # Apply executable permissions to the binary sudo chmod +x /usr/local/bin/docker-compose # Run Project docker-compose up -d

Docker,

This foundation now opens the door to even more powerful concepts. You can explore more advanced concepts such as container networking, streamlining the management of complex applications with Docker Compose, and how to make your application data persistent using volumes.

In many projects that are containerized, especially in cases where development is also done locally with docker-compose, teams often have two Dockerfiles, 1 for Development, the other for Production. If you happen to have multiple environments like pre-prod, staging and so on, some teams could have different Dockerfiles for these environments.

sudo curl -L "https://github.com/docker/compose/releases/latest/download/docker-compose-$(uname -s)-$(uname -m)" -o /usr/local/bin/docker-compose

You can also use Docker Compose to deploy the cluster, without having to write all the previous commands.