As a Solutions Engineer here at Kong, one question that frequently comes across my desk is “how can I transform a Kong logging plugin message into a format that my insert-observability-stack-here understands, (e.g., ELK, Loki, Splunk, etc.)?”
In this blog, I’m going to show you how to easily accomplish converting a Kong logging payload to the [Elastic Common Schema](https://www.elastic.co/guide/en/ecs/current/ecs-field-reference.html)Elastic Common Schema.
In order to accomplish this task, we’re going to be running Kong Gateway in Kubernetes and using two Kong plugins.
If you don’t already have an instance of Kong running in a Kubernetes cluster, connect to your cluster and run the following the commands to get one in seconds.
% kubectl create ns kong
% kubectl apply -f https://bit.ly/kong-ingress-dbless
% kubectl get po -n kong -w
NAME READY STATUS RESTARTS AGE
ingress-kong-7c4b795d5d-f2lpt 0/2 ContainerCreating 0 1s
ingress-kong-7c4b795d5d-f2lpt 0/2 Running 0 1s
ingress-kong-7c4b795d5d-f2lpt 1/2 Running 0 10s
ingress-kong-7c4b795d5d-f2lpt 2/2 Running 0 20s
^C
See [how to install Kong in Kubernetes](https://docs.konghq.com/gateway/latest/install/kubernetes/kubectl/)how to install Kong in Kubernetes for more information. Once you have an available instance of the Kong Gateway, continue.
First, create an empty Kubernetes manifest file called, elastic-common-schema.yaml.
Next, let’s define our KongPlugin resources. The first plugin we will create is the serverless pre-function. From the Kong plugin docs, a serverless pre-function plugin:
*Runs before other plugins run during each phase. The pre-function plugin can be applied to individual services, routes, or globally.*
Since we’re logging, we’re concerned with the log phase or “context”. For more information on all available plugin contexts, read this [doc](https://docs.konghq.com/gateway/latest/plugin-development/custom-logic/#available-contexts)doc.
Paste the below yaml in your manifest.
The above resource definition creates a KongPlugin that executes before the logging phase of each plugin defined in scope. The kong.ctx.shared.mystuff=kong.log.serialize() is a single line of Lua code that stores the logging payload into a shared context. From the Kong docs, a shared context is:
*A [Lua] table that has the same lifetime as the current request. This table is shared between all plugins. It can be used to share data between several plugins in a given request.*
For more info on shared contexts, see this [doc](https://docs.konghq.com/gateway/latest/plugin-development/pdk/kong.ctx/#kongctxshared)doc.
The key to doing the transformation is the custom_fields_by_lua configuration. From the Kong docs, the custom_fields_by_lua is:
*A list of key-value pairs, where the key is the name of a log field and the value is a chunk of Lua code, whose return value sets or replaces the log field value.*
% kubectl create ns myblog
% kubectl apply -f https://bit.ly/k8s-httpbin -n myblog
% kubectl get po -n myblog -w
NAME READY STATUS RESTARTS AGE
httpbin-64cdb8c89c-7rxm2 1/1 Running 0 5s
^C
% kubectl logs ingress-kong-7c4b795d5d-pg2c6 -n kong -c proxy -f | grep "@timestamp"
# You should see something similar to the below
{"@timestamp":"1667427319","url":{"original":"/testing/anything"},"http":{"response":{"status_code":200},"request":{"body":{"bytes":93}}},"client_ip":"10.48.0.1"}
{
"latencies": {
"request": 515,
"kong": 58,
"proxy": 457
},
"service": {
"host": "httpbin.org",
"created_at": 1614232642,
"connect_timeout": 60000,
"id": "167290ee-c682-4ebf-bdea-e49a3ac5e260",
"protocol": "http",
"read_timeout": 60000,
"port": 80,
"path": "/anything",
"updated_at": 1614232642,
"write_timeout": 60000,
"retries": 5,
"ws_id": "54baa5a9-23d6-41e0-9c9a-02434b010b25"
},
"request": {
"querystring": {},
"size": 138,
"uri": "/log",
"url": "http://localhost:8000/log",
"headers": {
"host": "localhost:8000",
"accept-encoding": "gzip, deflate",
"user-agent": "HTTPie/2.4.0",
"accept": "*/*",
"connection": "keep-alive"
},
"method": "GET"
},
"tries": [
{
"balancer_latency": 0,
"port": 80,
"balancer_start": 1614232668399,
"ip": "18.211.130.98"
}
],
"client_ip": "192.168.144.1",
"workspace": "54baa5a9-23d6-41e0-9c9a-02434b010b25",
"upstream_uri": "/anything",
"response": {
"headers": {
"content-type": "application/json",
"date": "Thu, 25 Feb 2021 05:57:48 GMT",
"connection": "close",
"access-control-allow-credentials": "true",
"content-length": "503",
"server": "gunicorn/19.9.0",
"via": "kong/2.2.1.0-enterprise-edition",
"x-kong-proxy-latency": "57",
"x-kong-upstream-latency": "457",
"access-control-allow-origin": "*"
},
"status": 200,
"size": 827
},
"route": {
"id": "78f79740-c410-4fd9-a998-d0a60a99dc9b",
"paths": [
"/log"
],
"protocols": [
"http"
],
"strip_path": true,
"created_at": 1614232648,
"ws_id": "54baa5a9-23d6-41e0-9c9a-02434b010b25",
"request_buffering": true,
"updated_at": 1614232648,
"preserve_host": false,
"regex_priority": 0,
"response_buffering": true,
"https_redirect_status_code": 426,
"path_handling": "v0",
"service": {
"id": "167290ee-c682-4ebf-bdea-e49a3ac5e260"
}
},
"started_at": 1614232668342
}
*which gets transformed into:*
{
"@timestamp": "1667427319",
"url": {
"original": "/testing/anything"
},
"http": {
"response": {
"status_code": 200
},
"request": {
"body": {
"bytes": 93
}
}
},
"client_ip": "10.48.0.1"
}Congratulations, you have transformed a Kong log payload into an Elastic Common Schema format ready for ingestion! This pattern can be used to easily transform Kong logging messages into any format for ingestion with any observability stack.
Traditional APIs are, in a word, predictable. You know what you're getting: Compute costs that don't surprise you Traffic patterns that behave themselves Clean, well-defined request and response cycles AI APIs, especially anything that runs on LLMs
[](https://konghq.com/blog/engineering/monetize-ai-apis)
Running Kong in front of your Solace Broker adds real benefits: Authentication & Access Control – protect your broker from unauthorized publishers. Validation & Transformation – enforce schemas, sanitize data, and map REST calls into event topics.
[](https://konghq.com/blog/engineering/smarter-event-driven-apis-kong-solace)
Architecture Overview A multicloud DCGW architecture typically contains three main layers. 1\. Konnect Control Plane The SaaS control plane manages configuration, plugins, and policies. All gateways connect securely to this layer. 2\. Dedicated C
[](https://konghq.com/blog/engineering/dedicated-cloud-gateways-managed-redis-multi-cloud)
The example below shows how an AI agent can be built using Volcano SDK with minimal code, while still interacting with backend services in a controlled way. The agent is created by first configuring an LLM, then defining an MCP (Model Context Prot
[](https://konghq.com/blog/engineering/secure-ai-agents-volcano-sdk-kong-mcp-proxy)
CLIs, MCP, and the Real Governance Tradeoffs Shaping Enterprise AI Agents The CLI case is real Let's start with the strongest version of the CLI argument. For well-known tools baked into model training data (e.g., git, grep, curl, jq, docker, kub
[](https://konghq.com/blog/enterprise/cli-vs-mcp-enterprise-ai-governance)
In January 2024, consumers in the United Kingdom made a record-breaking 14.5 million open banking payments. This milestone shows how dramatically the financial services industry has changed. It's the result of years of regulatory work that kicked of
[](https://konghq.com/blog/learning-center/guide-on-open-banking)
Kong Gateway is an API gateway and a core component of the Kong Konnect platform . Built on a plugin-based extensibility model, it centralizes essential functions such as proxying, routing, load balancing, and health checking, efficiently manag
[](https://konghq.com/blog/engineering/ai-voice-agents-kong-ai-gateway-cerebras)