note update

content/Discrete Math/Mathematical Proof.md

@@ -6,13 +6,40 @@ Author Profile:
 tags:
   - discrete_math
 Creation Date: 2023-11-04T19:10:00
-Last Date: 
-References:
+Last Date: 2023-12-13T10:10:22+08:00
+References: 
 ---
 ## Abstract
 - [[#Concise]], [[#Polished]] [[Mathematical Argument]] explaining the *validity* of [[Mathematical Statement]] to skeptic
-- There are many *proof methods* - [[#Proof by Construction/Example]], [[#Proof by Counter Example]], [[]]
+- There are many [[#Proof Methods]]
 
+## Proof Methods
+### Direct Proof
+- Is difficult when the thing we want to proof has an absence of a form like *Irrationality of a number*, which is number that does 
+### Proof by Deduction (演绎推理)
+- [[#Direct Proof]]
+- Used when the number of cases is *infinite*
+- Use [[Discrete Math#Theorem (定理)|Theorem]] & [[Discrete Math#Axioms (公理)|Axioms]] to proof something
+- Usually takes the form of - *To show that every element of a set satisfies a certain property, suppose x is a particular but arbitrarily chosen element of the set, and show that x satisfies the property*
+>[!example]
+>- Prove that the sum of any two even integers is even
+>- Prove the sum of any two rational numbers is rational
+### Proof by Exhaustion/Brute-force/Cases
+- List down all the possible cases and check on all cases
+- Useful there is a handful of possible cases
+
+### Proof by Construction/Example
+- A form of [[#Direct Proof]]
+- For [[Mathematical Statement#Existential]], we can proof by providing an example that fulfil the conditions
+### Indirect Proof
+
+### Proof by Counter Example
+- An example that shows that a [[Mathematical Statement]] isn't always true. Useful for [[Mathematical Statement#Universal]]
+
+### Proof by Contradiction (反证法)
+- [[#Indirect Proof]]
+- Proof the negation is true to proof the given [[Mathematical Proof]] false, vice versa
+- Useful when it is hard to use [[#Direct Proof]], where the negated [[Mathematical Statement]] has form to proof
 
 ## Terminologies
 
@@ -25,23 +52,3 @@ References:
 - And implies that proof for that case can be easily applied to all other cases
 - To remove very similar proof, for example, `a` & `b` are two consecutive odd number. We need to proof the product of the 2 consecutive odd numbers is always odd
 - we need to proof it correct for both `a<b` & `b<a` cases, we can remove proof for one of the cases using `WLOG`
-### Direct Proof
-- Is difficult when the thing we want to proof has an absence of a form like *Irrationality of a number*, which is number that does 
-### Indirect Proof
-
-### Proof by Counter Example
-- An example that shows that a [[Mathematical Statement]] isn't always true. Useful for [[Mathematical Statement#Universal]]
-### Proof by Construction/Example
-- A form of [[#Direct Proof]]
-- For [[Mathematical Statement#Existential]], we can proof by providing an example that fulfil the conditions
-### Proof by Exhaustion/Brute-force/Cases
-- List down all the possible cases and check on all cases
-- Useful there is a handful of possible cases
-### Proof by Deduction (演绎推理)
-- [[#Direct Proof]]
-- Used when the number of cases is *infinite*
-- Use [[Discrete Math#Theorem (定理)|Theorem]] & [[Discrete Math#Axioms (公理)|Axioms]] to proof something
-### Proof by Contradiction (反证法)
-- [[#Indirect Proof]]
-- Proof the negation is true to proof the given [[Mathematical Proof]] false, vice versa
-- Useful when it is hard to use [[#Direct Proof]], where the negated [[Mathematical Statement]] has form to proof

content/Tools/Datadog/Datadog APM.md

@@ -6,25 +6,26 @@ Author Profile:
 tags:
   - Datadog
 Creation Date: 2023-12-05T10:27:00
-Last Date: 2023-12-12T13:44:26+08:00
+Last Date: 2023-12-13T15:19:55+08:00
 References: 
 ---
 
 ## Abstract
 
 - [[Application Performance Monitoring (APM)]]
 
-## Serverless Setup
+## ECS Fargate Setup
 
 - The example below is based on [[ECS#Fargate|ECS Fargate]]
-- The entire setup is around [[ECS#Task Definition]], we need to add in 3 parts into it - [[#Pipe application log to AWS Firelens]], [[#AWS Firelens]] and [[#Datadog Agent Sidecar]]
+- Make sure [[Datadog Integration#AWS]] and [[Datadog App Tracer]] are done
+- The rest of the setup is around [[ECS#Task Definition]], we need to add in 3 parts into it - [[#Pipe log to AWS Firelens]], [[#AWS Firelens]] and [[#Datadog Agent Sidecar]]
 
-### Pipe application log to AWS Firelens
+### Pipe log to AWS Firelens
 
-- Add the following block inside the **application container block**
+- Add the following block inside the [[ECS#Task Definition]] of **container** that we want to access the log
 - Update the highlighted parts with your own values
 
-```json {4, 5, 7-9}
+```json {4-5, 7-9}
 "logConfiguration": {
   "logDriver": "awsfirelens",
   "options": {
@@ -38,15 +39,7 @@ References:
   }
 }
 ```
-- You can configure the Datadog app agent by setting the [[Environment Variable]] in the same **application container block**
-```json
-"environment": [
-	{
-		"name": "DD_SERVICE",
-		"value": "aegis-dev-backend"
-	}
-]
-```
+
 ### AWS Firelens
 
 - Update the highlighted parts with your own values
@@ -78,7 +71,11 @@ References:
 - Update the highlighted parts with your own values
 - There is [a list of environment variables](https://docs.datadoghq.com/serverless/guide/agent_configuration/) you can add to fine tune the agent
 
-```json {2, 4-5, 15, 19, 23, 27}
+>[!info] `DD_APM_ENV` overrides `DD_ENV` 
+
+>[!tip] We can use `DD_APM_IGNORE_RESOURCE` to ignore [[Trace]] from transmitted to Datadog
+
+```json {2, 4-5, 11, 15, 19, 23, 27}
 {
 	"name": "datadog-agent",
 	"image": "public.ecr.aws/datadog/agent:latest",
@@ -91,21 +88,21 @@ References:
 			"name": "ECS_FARGATE",
 			"value": "true"
 		},
-		{
-			"name": "DD_SERVICE",
-			"value": "aegis-dev-backend"
-		},
-		{
-			"name": "DD_ENV",
-			"value": "aegis-dev"
-		},
 		{
 			"name": "DD_API_KEY",
 			"value": "<YOUR_API_KEY>"
 		},
 		{
 			"name": "DD_SITE",
 			"value": "datadoghq.eu"
+		},
+		{
+          "name": "DD_APM_ENV",
+          "value": "aegis-stg"
+        },
+        {
+		  "name": "DD_APM_IGNORE_RESOURCES",
+		  "value": "['GET /health']"
 		}
 	],
 	"mountPoints": [],
@@ -116,7 +113,6 @@ References:
 ### Terraform Sample Codes
 
 - Refer to the above [[#Pipe application log to AWS Firelens]], [[#AWS Firelens]] and [[#Datadog Agent Sidecar]] for configuration details
-- Update the highlighted parts with your own values
 
 ```hcl
 resource "aws_ecs_task_definition" "backend_app" {
@@ -145,7 +141,11 @@ resource "aws_ecs_task_definition" "backend_app" {
 		{
 			"name": "DD_SERVICE",
 			"value": ""
-		}
+		},
+		{
+		    "name": "DD_ENV",
+		    "value": ""
+        },
 	  ]
       logConfiguration = {
         logDriver : "awsfirelens",
@@ -191,21 +191,21 @@ resource "aws_ecs_task_definition" "backend_app" {
           "value": "true"
         },
         {
-          "name": "DD_SERVICE",
-          "value": ""
+          "name": "DD_API_KEY",
+          "value": "<YOUR_API_KEY>"
         },
         {
-          "name": "DD_ENV",
+          "name": "DD_SITE",
           "value": ""
         },
         {
-          "name": "DD_API_KEY",
-          "value": "<YOUR_API_KEY>"
+          "name": "DD_APM_ENV",
+          "value": ""
         },
         {
-          "name": "DD_SITE",
-          "value": ""
-        }
+		  "name": "DD_APM_IGNORE_RESOURCES",
+		  "value": "['GET /health']"
+		}
       ],
       "mountPoints": [],
       "volumesFrom": [],
@@ -219,3 +219,8 @@ resource "aws_ecs_task_definition" "backend_app" {
 ```
 
 ## Terminologies
+
+
+## References
+- [Official ECS Fargate Integration](https://docs.datadoghq.com/integrations/ecs_fargate/?tab=webui)
+- [Official Datadog Agent Configuration](https://docs.datadoghq.com/serverless/guide/agent_configuration)

content/Tools/Datadog/Datadog App Tracer.md

@@ -0,0 +1,22 @@
+---
+Author:
+  - Xinyang YU
+Author Profile:
+  - https://linkedin.com/in/xinyang-yu
+tags:
+  - Datadog
+Creation Date: 2023-12-13, 13:55
+Last Date: 2023-12-13T14:32:51+08:00
+References: 
+---
+## Abstract
+- There are 2 ways to trace applications, one way is [Adding the tracer in Code](https://docs.datadoghq.com/tracing/trace_collection/dd_libraries/nodejs#adding-the-tracer-in-code), and another way is [Adding the tracer via command line arguments](https://docs.datadoghq.com/tracing/trace_collection/dd_libraries/nodejs#adding-the-tracer-via-command-line-arguments)
+>[!tip] I usually start with the second way, since it is not intrusive, so easy to add in. And it is already pretty powerful
+- We can fine tune the *tracer* by using this [list of environment variables](https://ddtrace.readthedocs.io/en/stable/configuration.html#) (More comprehensive)
+>[!tip] I always set the `DD_ENV` and `DD_SERVICE` to get [[Trace]] display nicely inside the Datadog dashboard
+
+
+
+## References
+- [Official Datadog Tracing Library](https://docs.datadoghq.com/tracing/trace_collection/dd_libraries/)
+- [ddtrace Configuration](https://ddtrace.readthedocs.io/en/stable/installation_quickstart.html)

content/Tools/Datadog/Datadog Integration.md

@@ -0,0 +1,23 @@
+---
+Author:
+  - Xinyang YU
+Author Profile:
+  - https://linkedin.com/in/xinyang-yu
+tags:
+  - Datadog
+Creation Date: 2023-12-13, 15:03
+Last Date: 2023-12-13T15:19:18+08:00
+References: 
+---
+## Abstract
+- In order for us to use *Datadog services* on other platforms, we need to integrate with those platforms first. *Datadog* provides a [list of supported integrations](https://docs.datadoghq.com/integrations/#all)
+
+## Integrations
+- Below is my notes of the integration I did
+### AWS
+- There are [many ways](https://docs.datadoghq.com/integrations/amazon_web_services/) to integrate *AWS* with *Datadog*. The easiest way to start is [automated integrated using CloudFormation](https://docs.datadoghq.com/getting_started/integrations/aws/)
+
+
+## References
+- [Official Datadog Supported Integrations](https://docs.datadoghq.com/integrations/#all)
+- [Offical Datadog and AWS Integration](https://docs.datadoghq.com/integrations/amazon_web_services/)

content/Tools/Datadog/Datadog.md

@@ -5,35 +5,30 @@ Author Profile:
   - https://linkedin.com/in/xinyang-yu
 tags:
   - Datadog
-Creation Date: 2023-10-15T21:25:00
-Last Date: 
-References:
+Creation Date: 2023-10-15T21:32:00
+Last Date: 2023-12-13T15:14:06+08:00
+References: 
 ---
 ## Abstract
+- A set of monitoring tools provided by a company called *Datadog*
 
-
-
-## Architecture
+## Components
+### Agent
+- A service that runs alongside the application to collect various [[Event-Driven Architecture#Event |Events]] and [[Metric]], and sends it to the *Datadog servers*
+>[!caution] Different from [[Datadog App Tracer]] which is on the application side
+### DogStatsD
+- An implementation of [[StatsD]] protocol
+- A *Metrics Aggregation Service* bundled with [[Datadog#Agent]] to send *custom metrics* from application to **Datadog servers**
+- Runs on port `8125` by default
 ![[datadog_architecture.png]]
-
-
 ## Setup
-### APM Setup
-- [Official Docs](https://docs.datadoghq.com/tracing/trace_collection/dd_libraries/python/?tab=containers)
-1. Configure [[#Agent]] for [[Application Performance Monitoring (APM)]]
-2. Add *Datadog Tracing Library* to code
-- By default, runs on port `8126`
+- [[Datadog Integration]]
+- [[Datadog App Tracer]]
+- [[Datadog APM#ECS Fargate Setup]]
+- [[Datadog RUM]]
 
-## Terminologies 
-### Backend
-### Agent
-- A service that runs alongside the application to collect various [[Event-Driven Architecture#Event |Events]] and [[Metric]], and sends it to the [[#Backend]]
 
-### Host Map
-- A visualisation of the host information & status, can be found under `Infrastructure -> Host Map` & `Infrastructure -> Infrastructure List`
-### Telemetry
+## Terminologies 
+### Telemetry 
 - A tool used for automatic collection, transmission, and measurement of data from remote sources
 - A sharp tool to optimise, debug & monitor system
-
-### Tagging
-- A way of adding dimensions to *Datadog* [[#Telemetry|Telemetries]] so they can be [[Aggregation|aggregated]] and compared in Datadog visualisations