Orchestration - automation that supports processes and workflows, such as provisioning resources.
What is configuration Management?
Examples
The Periodic Table of DevOps Tools is the industry's go-to resource for identifying best-of-breed tools across the software delivery lifecycle
DevOps Periodic table - https://digital.ai/learn/devops-periodic-table/
Problem: To develop a microservice-based high-performance pricing execution engine (In the cloud with concurrent processing, scalability, and observability) to solve complex configure price quote (CPQ), use cases by processing the data of the Salesforce platform (Current eco-system falls short in terms of performance).
Use case: Large global enterprise companies often deal with significant amounts of complexity when creating configurations and pricing within their quoting process. They have to work with hundreds of thousands of pricing rules and configuration rules each time they create or update a quote.
Brainstorming: We had brainstormed with the team and break down the problem statement into smaller pieces/modules, and everyone has taken end-to-end ownership/responsibility of the one module. here I have taken ownership of observability.
On my Plate: I have to find out the most suitable solution for observability that support involves measuring, collecting, and analyzing various diagnostics signals from a distributed system. These signals may include metrics, traces, logs, events, profiles.
My Challenges: Develop an end-to-end diligent plan/roadmap for Observability under high uncertainty, and demonstrate how to implement observability throughout the organization from scratch. I visualized there was a steep learning curve.
Team Immediate thought: As we are developers who have experience in the Microsoft technology stack. In front of us, we have an easy/time-tested/proven approach to use Azure Application insight and buy the Phobos NuGet for Enterprise Application Monitoring using Akka.NET for Actor monitoring, Concurrent processing, Distributed Tracing.
Action/Overcome: I was made a decision to evaluate/explore the best option for observability.
I had made the to-do list as per attention-to-details and a sense of urgency, it helps me to navigate, stay prioritized, and be on track.
A category of artificial intelligence that uses algorithms to analyze data, learn from the data, and then make inferences about the data.
Use cases
| Data Analytics | Data Science |
|---|---|
| Definition Process and analyze data sets to model and communicate answer to specific questions with actionable data. |
A multi-disciplinary field that specializes in exposing insights from large data sets. |
Skills
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Goals
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Programming eBooks - https://books.google.co.in/books
When using the msearch (multi-search) API in Elasticsearch, you can search across multiple indices in a single request. Each search query in the msearch request can be targeted to a specific index..
PUT product-index
{
"settings": {
"analysis": {
"normalizer": {
"lowercaseNormalizer": {
"type": "custom",
"filter": [
"lowercase",
"asciifolding"
]
}
}
}
},
"mappings": {
"properties": {
"Product": {
"type": "object",
"properties": {
"ProductName": {
"type": "keyword",
"normalizer": "lowercaseNormalizer"
},
"ProductCode": {
"type": "keyword",
"normalizer": "lowercaseNormalizer"
},
"ProductDescription": {
"type": "text"
},
"ProductFamily": {
"type": "keyword",
"normalizer": "lowercaseNormalizer"
},
"Color": {
"type": "keyword"
}
}
}
}
}
}
#Add first Document in elasticsearch
PUT /product-index/_doc/1
{
"Product": {
"ProductName": "CBC Anti Virus",
"ProductCode": "Network",
"ProductDescription": "APAC",
"ProductFamily": "Sales Cloud",
"Color": "Silver"
}
}
PUT /product-index/_doc/2
{
"Product": {
"ProductName": "CBC Esoteric",
"ProductDescription": "CBC Panel - 1",
"ProductFamily": "Hardware",
"Color": "BLUE"
}
}
PUT /product-index/_doc/3
{
"Product": {
"ProductName": "CBC Oncology",
"ProductCode": "CBC Health",
"ProductFamily": "Software"
}
}
PUT /product-index/_doc/4
{
"Product": {
"ProductName": "CBC Panel",
"ProductCode": "Secure Wifi",
"ProductDescription": "Only One Charge Type"
}
}
PUT /product-index/_doc/5
{
"Product": {
"ProductName": "CBC Panel (Invitro)",
"ProductCode": "Secure Wifi",
"ProductDescription": "CBC Panel",
"ProductFamily": "Hardware",
"Color": "GREEN"
}
}
PUT /product-index/_doc/6
{
"Product": {
"ProductName": "CBC Panel - Beijing",
"ProductCode": "CBC Panel",
"ProductDescription": "Only One Charge Type",
"ProductFamily": "Software",
"Color": "BLUE"
}
}
PUT /product-index/_doc/7
{
"Product": {
"ProductName": "Esoteric",
"ProductCode": "CBC",
"ProductFamily": "Marketing Cloud",
"Color": "WHITE"
}
}
PUT /product-index/_doc/8
{
"Product": {
"ProductName": "Oncology",
"ProductCode": "Network",
"ProductDescription": "CBC",
"ProductFamily": "Sales Cloud",
"Color": "WHITE"
}
}
PUT order-index
{
"settings": {
"analysis": {
"normalizer": {
"lowercaseNormalizer": {
"type": "custom",
"filter": [
"lowercase",
"asciifolding"
]
}
}
}
},
"mappings": {
"properties": {
"Order": {
"type": "object",
"properties": {
"OrderCode": {
"type": "keyword",
"normalizer": "lowercaseNormalizer"
},
"Description": {
"type": "text"
},
"Family": {
"type": "keyword",
"normalizer": "lowercaseNormalizer"
},
"ProductName": {
"type": "keyword",
"normalizer": "lowercaseNormalizer"
},
"ProductId": {
"type": "keyword"
}
}
}
}
}
}
#Add first Document in elasticsearch
PUT /order-index/_doc/5c57754b-86a6-41f1-a4af-de65b531fe8f
{
"Order": {
"OrderCode": "Network",
"Description": "APAC",
"Family": "Sales Cloud",
"ProductName": "CBC Anti Virus",
"ProductId": 1
}
}
PUT /order-index/_doc/218c4907-89c2-482f-90cc-61dd7e27f999
{
"Order": {
"OrderCode": "Network",
"Description": "CBC Panel - 1",
"Family": "Hardware",
"ProductName": "CBC Esoteric",
"ProductId": 2
}
}
GET /product-index/_search
GET /order-index/_search
In the request body, provide the search queries in a newline-separated JSON format. Each search query should have two parts: the header and the search body. The header contains information about the index and search type, while the search body contains the actual search query DSL.
#Try 1
POST http://localhost:9200/_msearch
Content-type:application/json
Payload as below
{"index" : "product-index"}
{"query": {"match": {"Product.OrderCode": "Network"}}, "from" : 0, "size" : 10}
{"index" : "order-index"}
{"query": {"match": {"Order.OrderCode": "Network"}}}