Core Java C#

MawChin Lee

(Skype ID) - live:mawchin****, or using GMAIL : google hangout, eMail: ***********@*****.***

LinkedIn: https://www.linkedin.com/in/mawchin-lee-4ba87579/

San Jose CA 95132 U.S.A Phone 1-408-***-****

Summary:

Perform programming in Java7-8-9-11-14/ Core java, JCP ( JSR) java J2EE/J2Sw/J2ME -Java Micro edition;

JavaScript / Python 2.x – 3.x; Using VS Code / Extension and Visual Studio / Express to programming Go/

C-C++/C# and python; HTML5, NODEJS (V20.x)/with Cluster capability. Git and GitHub, Perform Software

automation testing framework operation - API test using postman, Apigee, Jmeter; UI testing framework

selenium, Test Complete, soapUI, cucumber, Robot framework, mocha chai

J2EE/Core Java, spring tool suite Micro service / Micronaut (lightweight )/ MVC framework dependency

injection (DI) and IoC, AOP, MVC, bean xml configuration. VM ELK stack [Elastic search - can be a cluster

with shard node / Log stash –Beats: for data ingest- KIBANA, SOLR (solrconfig.xml); Elastic search and SOLR

both are based on LUCENE search library - can install with Solr plugin also; basically it use Inverted index-

hash table index writer / reader/query, B- Tree structure system.

Java language feature: primary type, int (32 bit),short, long, float, double, byte, char, Boolean, String, class,

base / super class, abstract class, Method, abstract method, constructor, destructor, method overwrite /

virtual, interface, extends, implementation, thread /process, executor service (submit callable or runnable;

invoke any /all, future / get), array,, array list, set, list, tree / hash set, hash / tree map, queue / stack,

priority queue, java 8 : stream (- transform – aggregate – find,-reduce. map, flat map, filter, limit, skip, find

any / all, iterate, generate, concat, parallel/sequential, base64,date timer, optional, functional interface,

lambda, reflection; java 11/14 /17

Java script feature: array [], object var let, const, closure, carry, hoist, map function ( used to

iterate over array element), class vs prototypal (can add new method) inherence, use strict, function name,

function as first class object, memorization,. Call /apply./ binding, = vs … )

Python language: feature: object, interpreter, embedded,extensible; indentation formatted, ; list, set, tuple, dictionary, list slice ( 1]), Chain map, iter, next, generations, stop iteration, yield,

pass, map (function for list iteration), for loop, range, if elif else, do…while,switch ( control statement), def

function name, function parameter(default, *parameter, **parameter), delimiter join; docmain, init, del,

….package - numpy, scipy, panda, SCIKIT learn, JSON, HTTP request / response, urllib3,thread,…

Python web framework:

a: Django – manager, administrator, urls, wsgi – plus

b: Flask (with jinja2 template engine or angular / react integrated)

c: FastAPI (python 3.8)– through uvicorn and Type hinting (python 3.5) via rest architecture –open API

specification coupled with Jinja2 / satic file it supports web socket

d: Dask – python library for parallel and distribued computing, run code in parallel across multiple cores.

Can be run in sinle or cluster mode

C# .Net, ASP.Net, ASP.CORE, ASP.MVC, ASP.WEBSERVER, ASP.WINFORM, ADO.NET, T-SQL,, Entity

Framework (EF core) WebMatrix, and WebMatrix2 { SQL Data base included}, WPF(syncfusion

extension), WPF-MVVM ( .net MAUI) – Architecture of .net MPF to separate UI frmewordk with backend

and code esign. WCF, Entity Framework (EF core), visual studio installer ]

C# -feature: sort like but not complete C++, CLR /CLS, class /object / interface (inheritance – single only-,

polymorphism, encapsulation), method, no header file required LINQ / xml (like SQL query, collection,,

function is inline,namespaces scope, using system, GCC, event / delegate, lambda, boxing / unboxing,

Assembly (c# basic unit for deployment), exception, security, attribute, generics / reference, version,

threading,MSIL – JIT, c# library is like java package.

Go - feature : a concurrency functional language ( no class but function can attach to a type), using go

routine, sync – waitgroup, Mutex / RWMutex., Map, Once, Cond – structure, map, make slice / channel,

selection or sender ( can close) / receiver, worker pool / queue job group, dispatcher defer, GCC, panic,

https /http handler, mux, buffer / unbuffered ( synchronized ) type named structure and interface. Generic

, reflect, func function name, Json, Variadic functions, init, flag:…

Scala –feature: object, statically typed functional programming, val, var, trait (interface), def function

name, MIXINS– extends / with - class, sealed class, implicit class, company object, singleton object, case

class (no need use new to create object) used in pattern match, apply / extraction, trail recursive ( only

one local stack for recursive), list, set, map, dictionary collection, AKKA -actor streaming model. Lift/

Play web framework.

C++ basic knowledge:: 1- Abstraction, Encapsulation { object: data vs method – static variable or function

{base (super or parent) vs extended(derived), use virtual keyword in class inheritance to avoid diamond

problem ; public, private, protect; virtual function – VTBL (class) and VPTR (object of class), class has a

pure virtual function F(virtual without code =0 ) is abstract class 2-Inheritance {base (super or parent)

vs extended(derived), use virtual keyword in class inheritance to avoid diamond problem ; public,

private, protect; virtual function – VTBL (class) and VPTR (object of class), class has a pure

virtual function F(virtual without code =0 ) is abstract class}, 3 - Polymorphism { Method: overloaded

defining type and/or number of parameters & overridden (same name and same parameter with virtual

keyword and access by pointer of base class; compiler time and runtime binding} 4- Smart pointer -to

avoid dangle pointer - and copy constructor, deep and shallow copy, Template.

VC ++, Linux/C/C++ /C++14 -17 STL container Library/collection ; C /C++ PTHREAD, Boost library: ASIO,

binding, collection, multi threading and resource synchronization – MUTEX (lock) vs SEMAPHORE ( count)

Embedded System Programming

- Embedded C/C++ system programming, RTOS– like Wind River VX work, Green Hill system integration,

Kernel Device Driver ( USB, Network, CAN, Wifi, UART, PCI, GPS, wearable device, FMCW, Board support

package(interface between OS and hardware of a specific computer board in embedded system, kernel`s

interface to device driver), cross compiler;

- Embedded programming has resources and memory constraints - memory pool, stack, queue, ring buffer,

interrupt vector / table (ISR); Boost/STL c++ library can also be used such as boost.pool, boost.circularbuffer,

boost.thread, boost.asio boost DFT, boost.smartpointer, but need consider memory resource limit and

performance issue.

- MATLAB ( numeric computation & visual programming ) - FFT (Fast Fourier transformation convolution) -

Digital Signal Processing (DSP ) –audio & image -with noise cancellation remover –to convert time domain

data to frequency data

Web UI

REACT —component (function, extended component, create component),

life cycle (mount, update, unmount), JSX, Http/HTTPS( Fetch, XmlhttpRequest, Axios, Ajax, or even web

socket) Https, Router, Redux / Flux, context, hooker; REACT native using yarn: yarn global add create-react-

native- app (using xcode & node JS, or using object C and swift) for mobile IOS Platform.

Angular –AOT - ahead time compiling--; component, containers – integrating the UI with the

non presentation layers of application, module, service, property / event / data binding,

template, metadata, material for UI, directive –component –class / style / modal, structural-ng if, ng for, ng

switch, ng template, pipe, DI, RxJS, NgRx, HTTP/HTTPS –SSL/TLS (certificate)or Oauth2; Some useful library

are Primeface / PrimeNG for data grid usage, KendoUI mostly used In JSP, Onsen UI and NGX bootstrap.

VUE JS ( React JS feature like). compiler provided and can be used by React and Angular

Mobile phone UI

- Iphone : the top player is to use Xcode & node JS & react – native / react native cli, watchman (monitor

files and file folder) or swift ( IOS programming language with feature like java / javc script and UI

design capability ); swift with object c and cocoa, uikit- are main IOS /MacOS development language or.

You can also use Flutter and Dart as develop tool; Expo / CRNA can be used without using mac OS Xcode

tool. React native provide more IOS module such as view, text, list view, scroll view, animated view style,

stylesheet, flexbox ( about screen size} navigator Bar, touchable highlight, IOS hardware usage

permission and some other UI elements. ). Flutter{Framework/widget, SDK, Dart c/C++ Engine, Dart: UI

library, embedder) and Dart (SDK, C/C++ feature like- function setter/getter, ASYNC- client

programming language) – By google ui kit. Flutter web frame coupled with Dart SDK dart::UI library can

also be used for IOS and Android development and deployment.

- Android: the top player is android studio, android SDK ( in java), android virtual device), xml –UI

design / material widget and dialog, KOTLIN (for android mobile, server side, and back end

web app development) 1.8.20 ( that is included in INTELLIJ IDEA or Android studio ) language- has feature

like java / Scala, used to design an android UI feature / game)). Note Android Studio use Gradle build tool.

Android DEX code and resource are bundled and called application package is APK.

KOTLIN can be used in any OS Environment for any application.

PHP ( mostly server side script- a kind of programming language with class / function / variabe like Java

Script- which can be embedded inside HTML and support connect to Database such as MSSQL, mail

Window and LINUX (redhat(application ) server, OpenShift ; LINUX bash shell script-CSH, KSH,

SSH,BASHJ/,TCSH ; is a unified platform to build, modernize, and deploy applications at scale, It is a cloud

based Kubernetes and CI/CD platform, that helps developers to build application, it aso contains Is service

mesh for micro service monitor and communication, web console for openshift cluster and application visual

monitor inside a web browser applications; Openshift also provide stand alone Code Ready container,

horizontal auto scaling, and health check for pods.

RedHat application server –Jboss –see Jboss developer studio [have lightweight server: undertow or wildfly,

WebSphere : a server(software framework that delivers content and assets for a client application

that hosts applications or software that delivers and business application through communication protocol- It

encompasses Web container as well as EJB container and Apache Tomcat is a source Java servlet container;https://www.redhat.com/en/technologies/cloud-computing/openshift

Micro service / Spring Boot /Spring framework

Micro Service ( u Service ) using spring boot / Quarkus ( native Kubernetes ready ) or spring framework with

JSP (usually with Kendo UI)or JSF (event / tag and embedded UI component): structures an application

as a collection of loosely coupled services (application is organized as a set of small automated /

independent cloud service software components – speed in design, safety in change, at scale and in

harmony- through message based or gateway enabled ).

BDD vs TDD – BDD is a team methodology –Behavior Driven, by user / tester created an automated

specifications (like Cucumber)-Based on Given-When-Then, based on scenario. TDD is a test developed

practice for application functionality- based on test case.

-Design pattern adopted could be -

Creation pattern, Structure patterns, Behavioural patterns, Domain driven or event driven pattern (coupled

with CQRS handling / async operation); Maven build tool, Restful API gateway, OOP, AOP (decouping),

DI(wiring), IoC (container for bean ), Spring Framework/ Spring boot and spring cloud (Spring Session ),

NETFLIX OSS Stack- Eureka client Discovery, ZUUL URL mapping/filter Security and Authentication /

Authorization with Oauth&Oauth2, SAML, single sign on, Ribbon client load balance, HYSTRIX – distributed

trace and circuit breaker Ecosystem. Third party API Gateway such as APIGEE and KONG.

-Micro service pattern is based on scalability, flexibility, independent and autonomous, decentralized

governance, Resiliency, failure isolation, continuous delivery through DevOps. design pattern may

classified as: Aggregator /API gateway, Saga pattern (Choreography, Orchestration), CQRS / Event

Sourcing / Branch Circuit Breaker. Decomposition, Asynchronous Messaging, Data Base or Shared

data;

Kubernetes / Service Mesh

-1) Kubernetes (k8s) server client micro service /app monitoring tool, Configure Map, CRD, CR, and

operators.

- 2) CI/CD/Jenkins, Kubernetes (k8s), argo workflow for Kubernetes (monitoring)

Infrastructure as code

- 3) Terraform (for multi / hybrid cloud instance configure, version, and deployment) ; Pulumi package

ansible.cfg and ansible vault to store security data. It use servers /clients and connect nodes approach

to send module to node to execute and then remove module

- 4) Service Mesh (istiod) –, discovery, certificates - with Pilot/Citadel / Proxy Envoy / ingress gateway /

additions to handle micro services communications . MVC, bean xml configuration, Spring Data

JPA, hibernate, No-SQL Database Cassandra, MongoDB, POSTGRES SQL, Oracle, Tableau, BI-

business intelligence, dashboard, and visual analytics SQL related DB operation, Graph Database.

SALEFORCE - cloud based Custom relationship management(CRM) and sale data, Provide Apex (java like

language) for data access; Work experience of Snowflake cloud data storage, data lake / pipeline and

data security for business needed data and database.

GlusterFS is a scale storage area / network attached file system by Gluster and later by RedHat/RedHat gluster

storage server, available under AWS, EC2/EBS for cloud computing, gluster is a client /server component in

TCP/IP or sockets sirect protocol[ it also provide mirroring and replication (geo replication) for reliability and

availability. It installed as GlusterFS cluster can also be used with kubernetes pod

manifest GlustrerVolumeSource) GlusterFS is an in-tree storage plug in kubernetes. Glusterfs-client can be used

in worker nodes

Graph DB

1) Neo4j - feature: -1) Use SQL Like feature -2) Data model (Property Graph - flexible schema) -3) ACID

properties -4) Uses Native graph storage with Native GPE, 5) It supports two kinds of Java API:

Cypher /APOC – procedure and function library, API and Native Jva API to develop Java applications.,

Linux/C/C++ /C++14 -17 STL container Library/collection.

Graph DB graph algorithm – pathfinding- shortest distance, minimum spanning tree, page

Rank, Breadth first / depth first search, centrality (relationship of a node), community detection

(determine relationships of membrs of the same group over the external group).

RDF-> Resource Description Framework – RDF graph using sparql query: Triple-store:-subject,

predicate, object) or property graph. Based on RDF schema RDF of classes and properties can be

described as 1)Closed collection; and 2)Open means flexible, allow bring together difference sources

that have different versions of truth. Neo4j Bloom for graph data visualization and data science

analysis. Bloom use Server and client approach both can be installed with neo4j DBMS, or with web

browser, or customized installed. Bloom provide a)perspective view, b) near natural language

search, c) graph edit and filter and (d) graph data analysis. Graph types have knowledge graphs –

emphasis on contextual understanding and interlinked sets of tacts that describe real word entities,

events or things, fraud detection graphs, traffic / social communication graphs, … etc

Neo4J graphDB provide javascript, java, Go, Python driver; every language provide driver and can be

connect to it with driver URL, authorized by name,password or LDAP, configuration, etc, user wil need

open session and transaction Tx to wrap its cyphery query to create Node, relationship, label,

proper graph algorithm for your neo4j graph DB

2) AWS Neptune ( workbench / SageMaker / Jupyter notebook ) with DB cluster instance. Access using

Gremlin / opencypher / sparql query language, can integrated with elastic search.

3) Modelling Ontologies - is asking inherently ontological questions to “model domain knowledge”; an

ontology defines a set of representational primitives with which to "model a domain of knowledge or

discourse". The representational primitives are typically classes (or sets), attributes (or properties),and

relationships (or relations among class members). The four categories of ontology are The fourfold

structure is based on two distinctions. The first distinction is between substantial entities (objects and

kinds) and non-substantial entities (modes and attributes). The ontology can be seen as a 5- tuple

where its components are: Concepts, relationships, functions, individuals or instances and axioms

● GraphQL use a query language : “QL” or APIs and a runtime for fulfilling those queries with

your existing data. It is used to load data from a server to a client -- it's a way to get data from

an API into your application. The biggest difference between GraphQL and REST is the manner

in which data is sent to the client. In a REST architecture, the client makes an HTTP request and

data is sent as an HTTP response, while in GraphQL, the client requests data with

queries. in REST, the structure of the request object is defined on the server.

In GraphQL (Appollo style, or GraphQL with Hasura –open source, or IBM StepZn / Relay by facebook),

you define the object on the client.

1: GraphQL Server-side Components: have resolver, schema –SDL, schema stitch (type and field) and

may linked with DB. Used to parsing the queries coming from GraphQL client applications.

2: GraphQL Client-side Components: code, query /API or a JavaScript library that mlakes POST

requests to the GraphQL server. AWS AppSync service provide a gaphQL Api creation

3: Mutation is a GraphQL Operation that allows you to insert new data / modify the existing

data on server, graph QL -Rest API call for fetch/update from server side

Cloud Platform and Services:

● AMAZON cloud platform – cloud CLI, cloud Formation,, EC2, VM {{ S3 [Bucket, Upload File,

static hosting, etc…], AMI /IAM, LDAP- software protocal for locate data about org, ind and other resource,

a centralized directory storage for authentication and authorization - COGNITO User Pool and security .

La mbda Function, Lambda edge – Server less, Lambda Framework rest API, cloud API gateway Web

service, route53 (domain name and DNS setup), certification manager, Step function, cloud Front(CDN),,

SNS, SQS / SES (simple mail service), cloud watch/trail, Kinesis, Dynamo DB – all these AWS services should

be orchestrated by - role/permission/event/ customized app event /mail/s3 / other AWS services /AWS SDK-

to achieve the so called lambda functionality } } AWS MSK ( AWS managed Kafka ) AWS quick Sight - BI, AWS

x-ray (used for debug and monitor) and, Mongo DB - ATLAS, Aurora – MYSQL /POSTGRES DB cluster,

endpoint, auto scale, fault tolerate, high performance, security, policy ; AWS AppSync for graphQL API

creation, ECS/EKS, AWS SDK.

AWS Glue ( AWS managed ETL services), using crawler/classifier/trigger to predefine the

data catalog and extract (metadata table repository) as data store from the data source –

S3, RDS, Redshift, JDBC, Dynamo DB - To data target (one classifier one table) –

s3, RDS,Redshift,JDBC, Dynamo DB-; the crawler can use scheduler /Job-script ( PYSPARK

[python] or SCALA) to define and run crawler job. AWS Glue can be pipelined with AWS

Athena ( AWS query serves for data analysis) and AWS Redshift ( data warehouse and data

analytic services) to perform the data science job or merge with some message MQ

ingest streaming (KAFKA / flink ) for data pipeline job.

AWS NetTune graph DB cluster instance (POSTGRES DB Based).

IOT – AWS IOT / AZURE IOT

- local IOT basic unit concept - usually equipped with sensor (for [pressure, temperature, image/ flow /

light measurement info) and transmitter/receiver using signal –like Z-wave or radio signal - to

communicate with a IOT Hub (like AWS / Azure IOT Hub) { like a SBU - single board microprocessor

and communicator chip, embedded message queue,- certificate,secret, unit serial number, unit

name- }. the IOT hub using wifi / Cellular signal to communicate with cloud or any third party apps.

Traditional local IOT unit is controlled via an IOT Hub which communicate and collec attachted sensor

event / alert / configuration information /setup . That this component is named GeenGrass IOT edge

run time ( AWS) or IOT edge device (Azure)

AWS IOT - device gateway (MQTT message broker),Thing registry, Thing shadow (these data are stored

inside registry ), Rule Engine – To invoke AWS service /app via using MQTT topic hierarchy and filters,

Security (Certificates, Policy, etc.); Aws IOT device SDK provide MQTT Mosquito client for Pub/Sub and

define topic with AWS IOT MQTT message broker, The rule engine can be configured to invoke AWS

lambda function AWS glue and IOT may need orchestrate with other AWS services and application.

Local device also need GeenGrass AWS IOT edge run time / service and select a suitable MQTT broker

to work with AWS IOT core using MQTT topic, pub/sub message flow for communication and

management. It also provide a multicast service – FUOTA (firmware updated over air to update each

sensor device is applicable.

● Microsoft Azure cloud – Azure console (portal), Window power shell, Azure CLI, ARM /API for

services deployment and management . VM – like EC2 approach— use SSH or RDP to connect,

Azure Storage – File / Queue/Blob (like AWS S3)/Table /Disk – Azure storage explorer, Azure

function – trigger,event,action- can use blob as its image storage, Logic application (work flow),

Web apps and Mobile Apps, Application gateway ( client side load balance), Azure data bricks

(like data lake/warehouse, spark for data analysis), Application Insight ( for monitoring/Log Analysis

), Application Front Door(CDN), { Azure Notification and Notification Hub (push message – by ways

of PNses, …), and Event Hub(concurrently real time data ingestion can be connected with KAFKA eco

system), Event grid for event processing, Azure service Health –check health of Azure service, Azure

service bus, Azure integration service / Azure Relay, Azure Blueprints : artefact of Azure resource

group, role assignment, policy assignment and ARM template

Azure ML / Azure AI, Azure Cognitive Service: -Vision, Speech, Language, Decision, Search; Bot Service,

Azure IAM access control (Role/policy based, or even RBAC), Cosmos DB ( multi model and turnkey

global distribution – SQL( core). Mongo DB, Cassandra. Azure Table, Gremlin (Graph based) - NOSQL

and relational database/DNS table, and SQL (SQL, MYSQL, Maria DB, POSTGRES ) Database,

Azure monitor – based on Dyna trace and log analytic, TLS/SSL certification biding for application

Security – Microsoft.

Active Directory, ACI /AKS (Rancher for multi cluster deployment and Helm for management)

HD Insight – using blob / data lake storage, ETL (Data Factory), Hadoop, Spark, KAFKA (or Azure

managed kafka services), Hive LLAP (us persistent daemons to provide an I/O layer and in-memory

caching for low latency queries), Hbase, IOT and some useful additions for data visualization /

monitoring / tracing / logging /–such as Garfana, Prometheus and kiali.

Azure Traffic Manager: work on DNS level ( Layer 7) Provide two benefits – 1) distribute of traffic

according to DNS of one of several traffic routing method, 2) Continuous monitoring of endpoint health

and automatic failover when endpoint fail. The work need some configure and use traffic manager

profiles; the health check applies to web App, VM and Azure cloud services,

Azure IOT - Like AWSIOT IOT core it provides bi-directional communication: HTTPS, AMPQ, MQTT

message router and Secure connectivity – per device security key or X.509 certificates . it use

Azure AD ( rule, policy and permission for user Authentication and authorization,and provides

scaling / monitoring capability; to add a the new IOT device the IOT hub create a connection String

and use a shared access key to authentication. Once connected the message is encrypted, Azure

IOT hub also provide Azure IOT SDK and Azure device, every device in IOT hub has a device twin (

Json format structure as metadata (like device registration info), IOT device communicate with IOT

hub through device twin and device provisioning . Azure IOT hub use Azure service Bus and

Azure Event Grid to Azure storage, Azure web Apps, Azure logic Apps. Azure IOT hub provide IOT

hub SDK (used to manage Azure IOT hub) can be used to create apps that run on IOT device and

can send data to Azure IOT hub. Azure IOT Edge let you run services such as Azure functions and

streaming analysis in your local environment - Device focused run time that enable user to

deploy, run, and monitor containerized Linux workloads & its runtime with IOT edge device --,

Azure Sphere provide for MCU and SDK.

Azure IOT centra-a SaaS offering for IOT device see https://apps.azureiotcentral.com to create IOT app.

Azure Synapse – Synapse SQL, Apache Spark integration, Data integration for Spark and Data lake,

Azure synapse studio.

Azure Arc - ( deploy Azure services anywhere to extended hybrid multi cloud infrastructure )

● GCP cloud platform has GCE, GAE, GKE (Kubernates and container) engines, and provide google developer

console to manage and deploy resources; a:) gcloud (command CLI -need installed )- google cloud SDK

for managing google cloud resources which provide tools for deploying and managing application; b:) App

Engine SDK - for build and deployment google platform cloud application – it provides a set of tools /

library for developing scable and reliable web applications using python, java, PHP, Go;

GSUTIL ( a python application for storage management); - Google Cloud object storage (object-based

storage for large amount of unstructured data) which can use ACL control; also support cloud SQL –

MySQL / PostgresSQL / Oracle; cloud Spanner – large scale relational DB, globally available for scale

Horizontal; NoSQL managed DB such as cloud datastore - use index ( or composite index through YAML )

structure storage by using SQL like query, or BIGQUERY, BIGTABLE - for financial analysis, IOT / Marketing

data - (it is originated from and require create /configure nodes, Memory store- like HBASE) -

DynamoDB;

GCP also provide cloud IAM – account / roles /ACL; DATAPREP – web base interface to clean and prepare

data among CSV,JSON and AVRO, Google DATAPROC – only for processing batch; and data cloud DataFlow

– for stream and batch data processing based on apache Bean (defining batch and streaming pipelines),

cloud composer (managed apache airflow –workflow management to create / schedule /monitor and

manage work flow to handle infrastructure google services; Computer/App engine, google cloud

Kubernetes Engineer(GKE), google function, google API gateway, cloud DNS, cloud

CDN( speed / cache/ performance) policy/action; google firewall - VPC rule for load balance, Allow/deny

for HT,TPS/HTTP routing); cloud VPN and VPN peering ;

gcloud google operations ( aka Stack Driver) for- monitoring – alert / alert policy / logging – for DB

operation, audit, security, VPC flow Logs /debugging/error reporting, google Pub/Sub (fully managed

message queue – Kafka connector, to decouple

publishers of events and subscribers to those events; it support implicit invocation) and cloud Task -

support explicit invocation and are appropriate for use case where a task producer needs to defer or control

the execution timing of a specific webhook or remote procedure call; cloud Key Management Services(KMS)

, google cloud XMPP (xml based protocol) –between app server, client apps and Firebase cloud message

(FCM), google cloud internet of thing (IOT) core (-has been refocus to use specialized partners),

Cloud Armor – web application firewall –WAF-, cloud Data lab,

cloud AI and ML and GKE Engineer work experience.

OpenAPI (Swagger.IO - Swagger Editor – JSON, YAML /Swagger UI ), HTTPCLIENT. Have work experience on

in memory cluster data storage such as Redis and Hazelcast mostly used for http/https session

management data caching

Bigdata / Hadoop / MessageQueue / Data pipeline ETL-DB

● Working experience of Big Data, Hadoop - hadoop Application, HDFS fs programming, HDFS distributed file

system and Linux server software network. Hadoop Eco System – ETL, Hadoop, Hive, HBASE,

Pig, SQOOP, - Hortonworks ( AMBARI HDP cluster Management) / Cloudera distribution –ML.

- 1 - message MQ: AMQP ( Rabbit MQ ), apach kafka, confluent

Kafka -publish-subscribe- brokers / zookeeper – distributed and partitioned “Topic” style Publisher /

subscriber Message Queue programming, Mirror Maker, Confluence (Avro Schema registry), kafka

connector, Apache Pulsar (Yahoo donated) /Storm / MQTT IOT Eclipse MOSQUITTO / PAHO, or MQTT /

HIVE MQ, IBM MQ. SPLJUNK (data ingest, log -, event / index and data query ),

- 2 - Streaming a: kafka streaming, b” Apache Flink streaming ( Table API -DB, Gelly – graph analysis,

FlinkML, dataset AP and datastream API, flink application ) and c: Spark Eco platform { Spark core RDD

API – transformation/Action, Spark SQL- dataset, Data Frame API, Spark Streaming – Direct Streaming /

Structure Streaming – unbound SQL table approach, MLIB - machine learning, apache camel (

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