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Reading list

Machine Learning Basics for a Newbie
6 Steps of Machine learning Lifecycle Introduction to Predictive Modeling
Introduction to Exploratory Data Analysis & Data Insights Descriptive Statistics Inferential Statistics How to Understand Population Distributions?
Reading Data Files into Python Different Variable Datatypes
Probability for Data Science Basic Concepts of Probability Axioms of Probability Conditional Probability
Central Tendencies for Continuous Variables Spread of Data KDE plots for Continuous Variable Overview of Distribution for Continuous variables Normal Distribution Skewed Distribution Skeweness and Kurtosis Distribution for Continuous Variable
Central Tendencies for Categorical Variables Understanding Discrete Distributions Performing EDA on Categorical Variables
Dealing with Missing Values Understanding Outliers Identifying Outliers in Data Outlier Detection in Python Outliers Detection Using IQR, Z-score, LOF and DBSCAN
Sample and Population Central Limit Theorem Confidence Interval and Margin of Error
Bivariate Analysis Introduction
Covariance Pearson Correlation Spearman's Correlation & Kendall's Tau Correlation versus Causation Tabular and Graphical methods for Bivariate Analysis Performing Bivariate Analysis on Continuous-Continuous Variables
Tabular and Graphical methods for Continuous-Categorical Variables Introduction to Hypothesis Testing P-value Two sample Z-test T-test T-test vs Z-test Performing Bivariate Analysis on Continuous-Catagorical variables
Chi-Squares Test Bivariate Analysis on Categorical Categorical Variables
Multivariate Analysis A Comprehensive Guide to Data Exploration The Data Science behind IPL
Supervised Learning vs Unsupervised Learning Reinforcement Learning Generative and Descriminative Models Parametric and Non Parametric model
Machine Learning Pipeline Preparing Dataset Build a Benchmark Model: Regression Build a Benchmark Model: Classification
Evaluation Metrics for Machine Learning Everyone should know Confusion Matrix Accuracy Precision and Recall AUC-ROC Log Loss R2 and Adjusted R2
Dealing with Missing Values Replacing Missing Values Imputing Missing Values in Data Working with Categorical Variables Working with Outliers Preprocessing Data for Model Building
Understanding Cost Function Understanding Gradient Descent Math Behind Gradient Descent Assumptions of Linear Regression Implement Linear Regression from Scratch Train Linear Regression in Python Implementing Linear Regression in R Diagnosing Residual Plots in Linear Regression Models Generalized Linear Models Introduction to Logistic Regression Odds Ratio Implementing Logistic Regression from Scratch Introduction to Scikit-learn in Python Train Logistic Regression in python Multiclass using Logistic Regression How to use Multinomial and Ordinal Logistic Regression in R ? Challenges with Linear Regression Introduction to Regularisation Implementing Regularisation Ridge Regression Lasso Regression
Introduction to K Nearest Neighbours Determining the Right Value of K in KNN Implement KNN from Scratch Implement KNN in Python
Bias Variance Tradeoff Introduction to Overfitting and Underfitting Visualizing Overfitting and Underfitting Selecting the Right Model What is Validation? Hold-Out Validation Understanding K Fold Cross Validation
Introduction to Feature Selection Feature Selection Algorithms Missing Value Ratio Low Variance Filter High Correlation Filter Backward Feature Elimination Forward Feature Selection Implement Feature Selection in Python Implement Feature Selection in R
Introduction to Decision Tree Purity in Decision Tree Terminologies Related to Decision Tree How to Select Best Split Point in Decision Tree? Chi-Squares Information Gain Reduction in Variance Optimizing Performance of Decision Tree Train Decision Tree using Scikit Learn Pruning of Decision Trees
Introduction to Feature Engineering Feature Transformation Feature Scaling Feature Engineering Frequency Encoding Automated Feature Engineering: Feature Tools
Introduction to Naive Bayes Conditional Probability and Bayes Theorem Introduction to Bayesian Adjustment Rating: The Incredible Concept Behind Online Ratings! Working of Naive Bayes Math behind Naive Bayes Types of Naive Bayes Implementation of Naive Bayes
Understanding how to solve Multiclass and Multilabled Classification Problem Evaluation Metrics: Multi Class Classification
Introduction to Ensemble Techniques Basic Ensemble Techniques Implementing Basic Ensemble Techniques Finding Optimal Weights of Ensemble Learner using Neural Network Why Ensemble Models Work well?
Introduction to Stacking Implementing Stacking Variants of Stacking Implementing Variants of Stacking Introduction to Blending Bootstrap Sampling Introduction to Random Sampling Hyper-parameters of Random Forest Implementing Random Forest Out-of-Bag (OOB) Score in the Random Forest IPL Team Win Prediction Project Using Machine Learning Introduction to Boosting Gradient Boosting Algorithm Math behind GBM Implementing GBM in python Regularized Greedy Forests Extreme Gradient Boosting Implementing XGBM in python Tuning Hyperparameters of XGBoost in Python Implement XGBM in R/H2O Adaptive Boosting Implementing Adaptive Boosing LightGBM Implementing LightGBM in Python Catboost Implementing Catboost in Python
Different Hyperparameter Tuning methods Implementing Different Hyperparameter Tuning methods GridsearchCV RandomizedsearchCV Bayesian Optimization for Hyperparameter Tuning Hyperopt
Understanding SVM Algorithm SVM Kernels In-depth Intuition and Practical Implementation SVM Kernel Tricks Kernels and Hyperparameters in SVM Implementing SVM from Scratch in Python and R
Introduction to Principal Component Analysis Steps to Perform Principal Compound Analysis Computation of Covariance Matrix Finding Eigenvectors and Eigenvalues Implementing PCA in python Visualizing PCA A Brief Introduction to Linear Discriminant Analysis Introduction to Factor Analysis
Introduction to Clustering Applications of Clustering Evaluation Metrics for Clustering Understanding K-Means Implementation of K-Means in Python Implementation of K-Means in R Choosing Right Value for K Profiling Market Segments using K-Means Clustering Hierarchical Clustering Implementation of Hierarchial Clustering DBSCAN Defining Similarity between clusters Build Better and Accurate Clusters with Gaussian Mixture Models
Understand Basics of Recommendation Engine with Case Study
8 Ways to Improve Accuracy of Machine Learning Models
Introduction to Dask Working with CuML
Introduction to Machine Learning Interpretability Framework and Interpretable Models model Agnostic Methods for Interpretability Implementing Interpretable Model Understanding SHAP Out-of-Core ML Introduction to Interpretable Machine Learning Models Model Agnostic Methods for Interpretability Game Theory & Shapley Values
Introduction to Machine Learning Interpretability Framework and Interpretable Models model Agnostic Methods for Interpretability Implementing Interpretable Model Understanding SHAP Out-of-Core ML Introduction to Interpretable Machine Learning Models Model Agnostic Methods for Interpretability Game Theory & Shapley Values
Introduction to AutoML Implementation of MLBox Introduction to PyCaret TPOT Auto-Sklearn EvalML
Pickle and Joblib Introduction to Model Deployment
Deploying Machine Learning Model using Streamlit Deploying ML Models in Docker Deploy Using Streamlit Deploy on Heroku Deploy Using Netlify Introduction to Amazon Sagemaker Setting up Amazon SageMaker Using SageMaker Endpoint to Generate Inference Deploy on Microsoft Azure Cloud Introduction to Flask for Model Deploying ML model using Flask
Model Deployment in Android Model Deployment in Iphone

What is AWS EFS? How to Optimize It?

Chetan
Chetan Last Updated : 02 Sep, 2022
6 min read

This article was published as a part of the Data Science Blogathon.

Introduction

Amazon EFS is an AWS file-sharing service that allows you to manage file shares like those used in traditional networks. This works by mounting them to an Infrastructure as a Service (IaaS) compute instance or local computers using the NFS protocol. In this post, we’ll look at the basics of AWS EFS, give you some tips to help you optimize performance, and see how it compares to other AWS storage options.

AWS EFS
Source: Amazon

 

What is AWS EFS?

It is one of the three primary storage services by AWS. It is a scalable cloud file system for Linux-based applications and workloads that can be combined with AWS cloud services and on-premises resources. Standard access storage is designed for frequently used files, while occasional access is designed to store long-term but less frequently used files at a lower cost.
EFS uses the NFSv4 protocol for its file system structure which mirrors the standard local structure and simplifies the transfer and access of your files. It can be used with Elastic Cloud Compute (EC2) instances or as a standalone file system. EFS requires no storage provisioning and is pay-per-use, allowing you to scale services as needed.
AWS EFS
Source: Amazon

 

AWS EFS Key Features

Shared storage
Files can be accessed from AWS services as well as on-premises. They can be accessed simultaneously by up to a thousand EC2 instances within the cloud or via VPN or AWS Direct Connect, making EFS suitable for a hybrid solution. Access to files is possible across multiple AWS Availability Zones (AZs) and regions for easier collaboration and global remote work.
Scalable performance
EFS is designed for low latency with IOPS and throughput that scales with usage and the number of attached instances, meaning performance increases as storage size increases. It offers a throughput of 10 GB/s and 500k IOPS at peak performance. EFS automatically scales as data is moved in or out, minimizing the worry of running out of space or paying for storage you’re not using. Learn more about how file sharing affects cloud scalability and agility.
Safe and compliant
EFS enables multiple layers of security and relies on your existing security infrastructure. It can be used with Access Management (IAM) roles, Amazon Identity, and VPC security groups and allows you to define file permissions using POSIX. EFS has built-in compliance with common regulatory standards, including PCI DSS, HIPAA, and SOC, with the ability to meet others as needed. Learn more about best practices for secure file sharing in the cloud.

AWS EFS Backup Solution

Since a storage solution is only beneficial if it can be backed up, you should be aware of the EFS backup options. Note that there are other ways if you want to use third-party products integrated with AWS. Also, read more about the general aspects of cloud backup and archiving.
Amazon Backup Service
It is a completely managed service that allows you to manage, create, and automate incremental backups according to a schedule. This system is PCI and ISO Compliant and HIPAA Eligible to ensure your compliance requirements are covered. AWS backup can be used regardless of whether your system has a cloud-native, hybrid, or on-premise configuration.This solution is easy to implement, and incremental backups help keep your costs down but require manually suspending backed-up applications and processes and only allow backups to be stored on EFS.
Backup EFS to EFS
There is no built-in EFS backup, and EFS has no native snapshot mechanism. Using this process, you can still manage backup schedules and lifecycles like you would with AWS Backup. The main disadvantage of this option is that it requires some programming knowledge and is not easy to follow. In addition, if you are not careful to change the time limits according to the amount of data backed up, your process may fail.
Backup to Amazon S3
Backing up your data to S3 is another option that can help reduce your storage costs. This process starts the same as an EFS to EFS backup, but instead of moving incremental backups from S3 to EFS at the end of the process, they are left in S3.
Like EFS to EFS, you can schedule backups and manage lifecycles, but you also need to have some programming skills and be familiar with using scripts to automate processes.

How to Optimize AWS EFS Performance

To get the greatest return on investment with EFS, you will need to take steps to optimize the performance of your configuration. Although the specific changes will depend on your needs, the following tips apply to most EFS users.
Track your EFS Burst credits
One of the biggest shocks for EFS users comes when they first run out of cracked credits, and their performance plummets. To avoid this, manually monitor your burst credits or add an alert to CloudWatch to notify you when they run low. By scheduling backups for periods of low usage or off-hours, you’ll help save your credits for when you need them. You should remember that EFS volumes start with a transfer rate of 0.5 MB/s and only 7.2 minutes of burst credits for up to 100 MB/s throughput, which is probably not enough to meet your needs. You can increase these numbers by increasing the amount of data you store, but there’s no way to buy more credits.
Don’t run apps from EFS
Elastic Block Storage (EBS) is a better choice if you plan to run and host applications from EFS. EFS is not designed for large file read volumes or the high speed required by tasks such as codebase management or application deployment, so you should not attempt to use it for these tasks. Instead, stick to tools that deploy code to local file systems or containers. Using EFS as designed to store media assets, exported data files, asynchronous logs, etc., will ensure that you see the performance you expect and that your productivity does not suffer.
Select the correct performance mode
The EFS system is designed with two different performance mode options: General Purpose and Max I/O.
General Purpose is the default setting that will work best for most users. It targets lower throughput levels in exchange for lower latency and is suitable for web hosting and content management tasks. Max I/O focuses on higher throughput at the cost of higher latency, making it better for tasks like extensive data analysis or media processing.
Note that both will experience throughput performance gains when you attach multiple concurrent instances if the workload can be spread across the cases.

AWS: EBS vs. S3 vs. EFS

To know if EFS is the best choice, you’ll want to compare it to your other two main options, EBS and S3.
EBS vs S3 vs EFS

Source: msp360.com

 

AWS EFS
EFS is relatively easy to learn to use because it mirrors the traditional file hierarchy structure. Because it allows multiple instances to connect across regions and AZs, it doesn’t require as much redundant storage as other options. It allows for easy cloud file sharing and collaboration. As previously mentioned, EFS is ideal for use in global content management systems, big data analytics, and media processing workflows.
AWS EBS
It provides low-latency block storage for EC2 instances; AWS EBS uses volumes. Setup can be a bit complicated as it requires you to choose a volume type from the start based on your performance requirements, and it doesn’t automatically scale like other options. EBS is intended for hosting and storing applications and large-scale databases. Learn more about AWS EBS in our extensive blog post series.
AWS S3
The Simple Storage Service (S3) provides object storage without the use of EC2 instances that is accessible directly over the Internet. It is the cheapest option and offers much storage flexibility, but it may require some programming knowledge as it is usually managed through the AWS Software Development Kit (SDK). Learn how to mount Amazon S3 as a disk to simplify management.S3 works well for static website hosting, version control, log file storage, media distribution or streaming, and extensive data analysis.

Conclusion

The cloud doesn’t do everything for you; while some services have internal backup mechanisms, others don’t. It becomes a responsibility that rests solely with the customer. This is the case with NFS file share data stored on Amazon EFS. You must ensure an effective Amazon EFS backup plan if you use Amazon EFS.

  • It is one of the three primary storage services by AWS. It is a scalable cloud file system for Linux-based applications and workloads that can be combined with AWS cloud services and on-premises resources.
  • EFS is not designed for large file read volumes or the high speed required by tasks such as codebase management or application deployment, so you should not attempt to use it for these tasks
  • EFS is relatively easy to learn to use because it mirrors the traditional file hierarchy structure. Because it allows multiple instances to connect across regions and AZs, it doesn’t require as much redundant storage as other options. It allows for easy cloud file sharing and collaboration.

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Chetan
Chetan

Data Analyst who love to drive insights by visualizing the data and extracting the knowledge from it. Automating various tasks using python & builds Real time Dashboard's using tech like React and node.js. Capable of Creaking complex SQL queries to fetch the accurate data.

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