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Advances in Care
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1 Advancing Cardiology and Heart Surgery Through a History of Collaboration 20:13
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On this episode of Advances in Care , host Erin Welsh and Dr. Craig Smith, Chair of the Department of Surgery and Surgeon-in-Chief at NewYork-Presbyterian and Columbia discuss the highlights of Dr. Smith’s 40+ year career as a cardiac surgeon and how the culture of Columbia has been a catalyst for innovation in cardiac care. Dr. Smith describes the excitement of helping to pioneer the institution’s heart transplant program in the 1980s, when it was just one of only three hospitals in the country practicing heart transplantation. Dr. Smith also explains how a unique collaboration with Columbia’s cardiology team led to the first of several groundbreaking trials, called PARTNER (Placement of AoRTic TraNscatheteR Valve), which paved the way for a monumental treatment for aortic stenosis — the most common heart valve disease that is lethal if left untreated. During the trial, Dr. Smith worked closely with Dr. Martin B. Leon, Professor of Medicine at Columbia University Irving Medical Center and Chief Innovation Officer and the Director of the Cardiovascular Data Science Center for the Division of Cardiology. Their findings elevated TAVR, or transcatheter aortic valve replacement, to eventually become the gold-standard for aortic stenosis patients at all levels of illness severity and surgical risk. Today, an experienced team of specialists at Columbia treat TAVR patients with a combination of advancements including advanced replacement valve materials, three-dimensional and ECG imaging, and a personalized approach to cardiac care. Finally, Dr. Smith shares his thoughts on new frontiers of cardiac surgery, like the challenge of repairing the mitral and tricuspid valves, and the promising application of robotic surgery for complex, high-risk operations. He reflects on life after he retires from operating, and shares his observations of how NewYork-Presbyterian and Columbia have evolved in the decades since he began his residency. For more information visit nyp.org/Advances…
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Content provided by Software Engineering. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Software Engineering or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ro.player.fm/legal.
Software Engineering Best Practices, System Design, High Scale, Algorithms, Math, Programming Languages, Statistics, Machine Learning, Databases, Front Ends, Frameworks, Low Level Machine Structure, Papers and Computing, Computer Science Book Reviews - Everything!
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352 episoade
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Manage series 3112408
Content provided by Software Engineering. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Software Engineering or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ro.player.fm/legal.
Software Engineering Best Practices, System Design, High Scale, Algorithms, Math, Programming Languages, Statistics, Machine Learning, Databases, Front Ends, Frameworks, Low Level Machine Structure, Papers and Computing, Computer Science Book Reviews - Everything!
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352 episoade
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1 ⏱️ java.util.Clock: Mocking Time 10:26
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mocking time
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1 📊 BigData Devops - ClickHouse & Grafana: High Cardinality Metrics 13:21
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📕 BOOK - Mastering ClickHouse - https://amzn.to/4b4NQPm
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1 ☁️ DevOps - Deploying Python Aws 18:25
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1 📦 DevOps - Multi-Stage Docker Builds 10:01
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1 🔗 Startups - Slack OAuth 2.0 App 15:48
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1 🤔 Distributed Systems - Modern Resiliency 23:52
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📕 BOOK - Distributed Systems - https://amzn.to/3CI5Mmi
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1 🤖 StartupTool - RunLLM - AI Support Engineer 19:50
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1 🤔 Cloud - AWS Account Management Strategies 14:35
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1 📚 AI - Reinforcement Learning from Human Feedback 22:11
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📕 BOOK - The StatQuest Illustrated Guide to Neural Networks and AI - https://amzn.to/4hhtOUo
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1 ⚡️ BigData - Apache Kafka Architecture 19:19
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📕 BEST BOOK on Kafka - Apache Kafka - The Definitive Guide - https://amzn.to/4gkpFxq
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1 🔬 Java - Mockito ArgumentCaptor 15:13
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1 🔑 Startup Tool - Hanko: Open-Source Authentication and User Management 17:45
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BOOK - gRPC: Up and Running https://amzn.to/4h7ri2K
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1 🥸 Social Life - Dating Girls 23:53
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1 🤯 Paper - Chinese Minimax Model 18:09
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1 🧠 Paper: Post Trasnformer Paper 10:19
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📕 BOOK - LLM Prompt Engineering For Developers - https://amzn.to/4jiUoha
📕 BOOK - LLM Prompt Engineering For Developers - https://amzn.to/4jiUoha
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1 📱 Hyperview: Native Mobile Apps Simplified 20:45
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📕 Best Book React Native - https://amzn.to/3PvMLGx Book full title - React and React Native: A complete hands-on guide to modern web and mobile development with React.js
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1 📊 Startup Tool - Formbricks: Open Source Survey Platform 19:18
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📕 Book - The Lean Startup - https://amzn.to/4abWCec
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1 🛒 Startup Tool - E-Commerce Platform with Medusa 29:05
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📕 Book - The Lean Startup - https://amzn.to/4abWCec
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1 🐳 Docker Stack for VPS Deployment 25:13
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1 🤖 DeepSeek-V3: A 671B Parameter Mixture-of-Experts Language Model 30:29
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A 671B parameter Mixture-of-Experts language model. It highlights the model's architecture, including its innovative load balancing and multi-token prediction strategies, and its efficient training process using FP8 precision. Benchmark results demonstrate DeepSeek-V3's strong performance compared to other open-source and some closed-source models, particularly in math and code tasks. The document also provides instructions for running DeepSeek-V3 locally using various frameworks and hardware, including NVIDIA and AMD GPUs and Huawei Ascend NPUs. Finally, licensing and contact information are included.…
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1 🌐 Startup Tool - Tolgee Open-Source Localization Platform 13:44
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📕 Book - The Lean Startup - https://amzn.to/4abWCec
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1 🤖 Startup Tool - Postiz: AI-Powered Social Media Scheduling Tool 17:23
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📕 Book - The Lean Startup - https://amzn.to/4abWCec
To LLM agents or not that is the question.
awk
bert paler
gpt paper
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1 Downloading Models from Hugging Face 24:16
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1 Paper: Attention is all you need 17:52
17:52
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1 Interactive Natural Language Processing a Survey 19:11
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1 Lambda Kappa ACID BASE Indexing 10:38
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1 TCP, UDP, HTTP, gRPC, and QUIC 21:08
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1 Unifying the Dev, Test, and Prod Divide 12:58
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The single-environment paradigm in software development, contrasting it with the traditional multi-environment approach. Consolidating development, testing, and production simplifies processes and reduces deployment risks. This is achieved through strategies like progressive deployment, test-driven development, CI/CD, and carefully managed production testing using techniques such as dry runs, shadow traffic, and canary releases.…
Trino versus Apache Spark
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How java.util.Clock Saved My Sanity
DynamoDB’s RCUs: Predictable Performance
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The Abundant Java Ecosystem: Libraries, Spring, Databases, and Lombok
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1 👻 Plane Open Source Jira Alternative 19:03
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1 💰 Do high interest rates fix inflation 20:27
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1 🛟 System Design Dropbox Google Drive 16:09
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1 🦜Hive, Elasticsearch, PostgreSQL, Apache Doris 14:41
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Aws Redshift vs RDS vs DDB
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📕BOOK - Set Boundaries, Find Peace - https://amzn.to/48krxnn
📕BOOK - Hacking the System Design Interview - https://amzn.to/48tkn07
📕BOOK - AWS: Virtual Private CLoud tutorial (VPC) for Beginners - https://amzn.to/3Zv4rpL
📕BOOK - High Performance Spark - https://amzn.to/458wnRE
📕BOOK - Python for Data Analysis - https://amzn.to/48uvUMr
📕BOOK - gRPC: Up and Running - https://amzn.to/3taxlje
Userscripts and Tampermonkey
Python Template and Bridge Design Patterns
Trie
P-Value
Vs Code Useful Extensions.
Chat GPT Model
Bloom Filters
GraphQL vs Rest
Hadh Functions
Apache Kafka
AWS networking provides a broad set of services that enable you to , connect, and secure your applications and data. With AWS networking, you can easily connect your on-premises networks to AWS, create virtual private clouds (VPCs), and use a variety of networking services to route traffic, control access, and monitor your network. * Scalability: AWS networking is designed to scale with your needs. You can easily add or remove resources as your traffic demands change. * Reliability: AWS networking is built on a highly reliable global infrastructure. Your applications will be available even if there is a problem with one of your network components. * Security: AWS networking provides a variety of security features to protect your applications and data. You can control who has access to your network and what they can do.…
How should you add status fields to calculations
AWS networking involves creating, configuring, and managing networks on Amazon Web Services. It includes services like Virtual Private Cloud (VPC), Elastic Load Balancing (ELB), Route 53, and Direct Connect, allowing users to build secure, scalable, and highly available cloud infrastructures. Key concepts include subnets, security groups, network access control lists (ACLs), and gateways.…
Cores distribution and spark and partitioning
Debugging python projects with and without tools.
Programming interview patterns involve understanding data structures, algorithms, time/space complexity, problem-solving approaches, and coding practices. Familiarize yourself with arrays, strings, linked lists, trees, graphs, dynamic programming, recursion, backtracking, bit manipulation, and system design. Practice coding, optimize solutions, and enhance communication skills to efficiently express problem-solving processes during technical interviews.…
rollup. 200 word summary for sql cube and rollup SQL (Structured Query Language) is a programming language that is commonly used to manage and manipulate data in relational databases. Two common operations that can be performed on data in SQL are cube and rollup. A SQL cube operation calculates aggregate values across multiple dimensions, producing a multi-dimensional result set. The result set includes all possible combinations of values across the specified dimensions. For example, if we have data on sales by region, product, and date, a cube operation could be used to calculate total sales by region and product for each date. This would produce a result set with three dimensions: region, product, and date. A SQL rollup operation is similar to a cube operation, but it only calculates aggregate values for a subset of the dimensions. Specifically, a rollup operation calculates aggregate values for each combination of values in a specified subset of dimensions, and then for each level of aggregation, it calculates a total for the remaining dimensions. For example, if we have data on sales by region, product, and date, a rollup operation could be used to calculate total sales by region for each date, and then a grand total for all dates. This would produce a result set with two dimensions: region and date. Both cube and rollup operations are useful for summarizing large amounts of data and analyzing it across multiple dimensions. They can be used to generate reports and visualizations that help users better understand their data and make informed decisions based on it.…
Fast arrays for coding interview
Calculate the product of an array except self without using the division operator
How to work with multiple treatments in AB testing
Acid transactions are a set of properties that ensure reliable and consistent database transactions. The term "ACID" stands for Atomicity, Consistency, Isolation, and Durability.
Experiment in Japan to work one less day a week
The preconditions to t-tesy
The differences between lit and react
In this episode of programmers quickie podcast, we continue our exploration of SQL pivot and dive deeper into the syntax behind this powerful data analysis tool. If you're looking to take your pivot table skills to the next level, this episode is for you!
DynamoDB RCU WCU
Python Behave testing
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1 🪓 Design a Parking Lot - System Design Interview Question 11:07
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In a system design interview, you will be asked to design a complex system, such as a website, mobile app, or network infrastructure. The interviewer will evaluate your ability to decompose the problem into smaller subproblems, make trade-offs between different design decisions, and consider the scalability and performance of the final solution. The key to success in a system design interview is to clearly communicate your thought process and trade-offs, rather than getting bogged down in low-level implementation details.…
In Apache Spark, you can cache a DataFrame in memory using the cache() or persist() method. The cache() method is a shorthand for persist() with the default storage level of MEMORY_ONLY. You can use the persist() method to specify a different storage level if desired, such as MEMORY_AND_DISK or MEMORY_ONLY_SER.…
Why develop apps when you can create "social apps" without coding as side projects.
The n-queens problem is a well-known problem in computer science and mathematics that involves placing n chess queens on a n x n chessboard such that no two queens are able to attack each other. This means that no two queens can be placed on the same row, column, or diagonal. The problem can be generalized to other chess pieces, such as the n-rooks problem (where the goal is to place n rooks on the board such that no two rooks can attack each other) or the n-knights problem (where the goal is to place n knights on the board such that no two knights can attack each other). The n-queens problem is often used as a test case for algorithms that solve combinatorial search problems, as it is a challenging problem that requires careful consideration of the constraints and the search space. There are several ways to solve the n-queens problem, including backtracking algorithms, constraint satisfaction algorithms, and heuristic search algorithms. In LeetCode, the n-queens problem is represented as problem 51 and can be found at the following link: https://leetcode.com/problems/n-queens/. The problem asks the user to implement a function that takes in an integer n and returns a list of all valid configurations of n queens on an n x n chessboard. The function should return an empty list if no valid configurations exist.…
The time that it takes computers to process information.
Consistent Hashing is a distributed hashing scheme that operates independently of the number of servers or objects in a distributed hash table by assigning them a position on an abstract circle, or hash ring. This allows servers and objects to scale without affecting the overall system.
A couple of mitigations for a couple of ab testing challenges
Here are scenarios where we would want to use AA testing before trying out and AB testing
HTTP/1 is a textual data protocol and is good in terms of readability, ease of reimplementing, and ease of debugging. However, Binary protocols(Used in HTTP/2 )
In probability theory and statistics, Bayes' theorem, named after Thomas Bayes, describes the probability of an event, based on prior knowledge of conditions that might be related to the event.
The token bucket is an algorithm used in packet-switched and telecommunications networks. It can be used to check that data transmissions, in the form of packets, conform to defined limits on bandwidth and burstiness.
In software design and engineering, the observer pattern is a software design pattern in which an object, named the subject, maintains a list of its dependents, called observers, and notifies them automatically of any state changes, usually by calling one of their methods.
There are six (6) criteria that should be applied when evaluating any Web site: authority, accuracy, objectivity, currency, coverage, and appearance.
The dataclass() decorator examines the class to find fields. A field is defined as a class variable that has a type annotation. With two exceptions described below, nothing in dataclass() examines the type specified in the variable annotation.
Python dependency management and packaging made easy. ... Poetry comes with all the tools you might need to manage your projects in a deterministic way
In computer networks, rate limiting is used to control the rate of requests sent or received by a network interface controller. It can be used to prevent DoS attacks and limit web scraping
dbt - Transform data in your warehouse What is dbt? dbt is a development framework that combines modular SQL with software engineering best practices to make data transformation reliable, fast,
HashAggregateExec is a unary physical operator (i.e. with one child physical operator) for hash-based aggregation that is created (indirectly through AggUtils.
The Spark SQL shuffle is a mechanism for redistributing or re-partitioning data so that the data is grouped differently across partitions
We have two types of automatic backups in dynamodb one is point in time and another one is snapshots.
System design
Giorgia Meloni is an Italian politician and journalist. A member of the Chamber of Deputies in Italy since 2006, she has led the Brothers of Italy political party since 2014, and has been the president of the European Conservatives and Reformists Party since 2020.
Apache spark unit tests
📚 Book - The Psychology of Money - https://www.amazon.com/Psychology-Money-Timeless-lessons-happiness/dp/0857197681#?&_encoding=UTF8&tag=planetizer0c-20&linkCode=ur2&linkId=c18c78f3d241db79ce045de652b93722&camp=1789&creative=9325
How can we pivot on spark?
Why a single file on your repository that describes the project could make life much easier for newcomer programmers
DataFrame.createOrReplaceTempView - Creates or replaces a local temporary view with this DataFrame. The lifetime of this temporary table is tied to the SparkSession that was used to create this DataFrame.
Spark SQL is a Spark module for structured data processing. It provides a programming abstraction called DataFrames and can also act as a distributed SQL query engine. It enables unmodified Hadoop Hive queries to run up to 100x faster on existing deployments and data.
We will describe how to use Apache Spark to get top 100 words from a file!
Apache Spark Paired RDDs are defined as RDDs containing the key-value pair(KVP), which consists of two linked data item in it. So, In most cases, the key is an identifier, and the value is data corresponding to the key value. Furthermore, Apache Spark operations work on RDDs that contain any objects.…
What is this name delta lake? Why delta? What is the core benefit of using it over a standard data lake? What are its disadvantages
Hive aws glue and additional data catalogs compare
In this episode we will discuss what are Go language to link and how is it different from other computer languages
SageMaker
What is AWS DynamoDB DAX and how does it relate to elastic cache
Java fork join pool uses the stealing algorithm in order to utilize better the threads that we have
In AWS the write capacity units is one write per second for an item of up to 1 KB in size
DynamoDb read capacity units and write capacity units
Why does reserve currency metals so much today in today's economy and what are the alternatives and investment opportunities in this area.
Common table expressions are very useful in constructing SQL and are your great next milestone to using SQL
What is the core of doing SEO did it change over the years and what would bring you to the topmost search results in the search engines
Here we discuss some of the most interesting product interview questions in the data area and in the data world
An intro to blockchain technology
What does term frequency means and what is its relationship with inverse document frequency that we use in order to identify categories of documents and in order to find testament and many more applications of this topic
📚 Book - https://amzn.to/39ty0Tq - "Terraform: Up & Running: Writing Infrastructure as Code" Terraform init will download all the dependencies needed by the terraform project like when you have a clean maven project, and running almost any mvn command will pull down the dependencies. tags in terraform helps you set the additional tag properties of the resources, if you want to set the name of the resource that would appear in aws then you need to set the tag with specific key and this key is Name actual names of resources, so if you would like to create a vpc resource in aws with name "myvpc" you need to actually set its tags which is different from aws tags you would set the tags { Name = "MyVpc" } and this would set the name of the resource in aws and not the tags in aws. Create EC2 The terraform name aws_instance The 2 mandatory arguments are ami and instance_type Example resource "aws_instance "MyEc2Instance" { ami = "ami_287428346" // some aws ami instance_type = "t2.micro" } Note to reference an id of a terraform instance need to specify ..id so aws_vpc.myvpc.id When we set an "aws_eip" which is elastic ip we have to tell it for which ec2 instance we assign it to, so the resource contains the "instance" property that we have to set. Aws account can give us up to 5 elastic ips. Security group - statefull firewall - stateful means if we allowed some traffic going in it would automatically allow traffic to go out, in stateless we have to set explicitly the input to the firewall and the output. resource "aws_security_group" "MySecurityGroup" { name = "Allow HTTPS" ingress { from_port = 443 to_port = 443 # This is a range of ports from to to is not output. protocol = "TCP" cird_blocks = ["0.0.0.0/0"] # All traffic. } egress { } } Then we can reference this MySecurityGroup from various resources such as ec2 instances. Dynamic Blocks - iterator, for_each var.mylistvar , content = port.value This allows us to use for_each.prefix the block you want to use the list for each in dynamic example variable "ingressrules" { # Here you set the list variable holding the data to be dynamically included. type = list(number) default = [80, 443] } dynamic "ingress" { # Now iterate and use the above list defined above. iterator = port for_each = var.ingressrules content { from_port = port.value } } Terraform dynamic blocks and security groups definition in Terraform and AWS elastic IP definition in Terraform and EC2 We continue also to investigate what does terraform init means.…
AWS elastic IP is not dynamic for itself it's actually a static public IPv4 IP so why is it called elastic because we dynamically assign it to host so if our host or easy to instance is down we can programmatically and dynamically assign such a static public IP into this new host so it's used for resiliency…
Unresilient World
With terraform we can use variables for example an integer which is defined as a number or a string or a list of strings and then we can reference these variables further down in the code in order to reuse them you can also output variables to the screen and we could also ask the customer to input interactively variable values into the console In this session - init plan apply destroy - state file - variables - terraform pattern consistent - resource keyword - resource identifier "aws_vpc" - our name "mypc" - in curly braces the parametesrs like cidr_block = "10.0.0.0/16" - `terraform init` - i's like mvn install - Download the plugins to use aws - We can run this command after created main.tf - pull down modules - `terraform plan` - will show what's its going to do - checks state - Get developer style diff before commit - What already created which diff - don't want to loose this state file - `terraform apply` - showing the diff - click `yes` to continue - resources created in aws! - `terraform destroy` - to delete all reources - confirm - `state file` `terraform.tfstate` - we can see locally all that we created with terraform! - this file will have ALL resources created by terraform - visibility! - we want this file to get missing - json format - .bak - track changes we made - used for diff # Variables - define variables - folder `variables` - `default` is like the value - we have `type` and then `default` for default value - `main.tf` create file in that folder ```json variable "vpcname" { type = string (or number boolean list(string) with values ["val1", "val2"] to access 1 [0]) default = "myvpc" } variable "mymap" { type = map default = { key1 = "value1" key2 = "value2" } } variable "mytuple" { type tuple([string, number, string]) default = ["mystr1", 45, "mystr2"] } variable "myobject" { type = object({name = string, port = number}) default { name = "myval1" default = "232" } } ``` - cidr_range would get used multiple times so just put it in var - use variables - `var.myvarname` can also be done with string interpolation - `var.mylist[0]` - `var.mymap["Key1"]` - interactive input variables ```json variable "inputname" { type = string description = "please enter value for input name" } ``` next use this - `var.inputname` as usuall - `terraform plan` will now ask to input the input vars values # Outputs ```json output "myoutput" { value = aws_vpc.myvpc.id } ``` so nw we can print the dynamic id we get when we run terraform. run `terraform plan` will not print the id as it's created only after the apply is run and resources actually run.…
Terraform main operations such as init plan apply and destroy and the state file telephone is a infrastructure as code tool a command line to help us create infrastructure with standard adjacent files and then run telephone apply in order to actually create this infrastructure either in AWS cloud or Google cloud or azure cloud or any other cloud provider even locally and it has many plugins. In this session init plan apply destroy state file variables terraform pattern consistentresource keyword resource identifier "aws_vpc" our name "mypc" in curly braces the parametesrs like cidr_block = "10.0.0.0/16" terraform init i's like mvn install Download the plugins to use aws We can run this command after created main.tf pull down modules terraform plan will show what's its going to do checks stateGet developer style diff before commit What already created which diff don't want to loose this state file terraform apply showing the diff click yes to continue resources created in aws! terraform destroy to delete all reources confirm state file terraform.tfstate we can see locally all that we created with terraform! this file will have ALL resources created by terraform visibility! we want this file to get missing json format .bak track changes we made used for diff Terraform main operations and components are: - [1] init [2] plan [3] apply [4] destroy - State files - variables - terraform pattern consistent - resource keyword - resource identifier "aws_vpc" - our name "mypc" - in curly braces the parametesrs like cidr_block = "10.0.0.0/16" - `terraform init` - i's like mvn install - Download the plugins to use aws - We can run this command after created main.tf - pull down modules - `terraform plan` - will show what's its going to do - checks state - Get developer style diff before commit - What already created which diff - don't want to loose this state file - `terraform apply` - showing the diff - click `yes` to continue - resources created in aws! - `terraform destroy` - to delete all reources - confirm - `state file` `terraform.tfstate` - we can see locally all that we created with terraform! - this file will have ALL resources created by terraform - visibility! - we want this file to get missing - json format - .bak - track changes we made - used for diff…
Telephone is a language declarative language for defining resources here we will describe their form in it and the command line how to install with regards to interjeed idea plugin and also the visual studio plugin
What are the differences in between the Bernoulli the binomial and the poison distributions and what are they
Coders Vs Managers
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