Bucketis in the Product Management Tools Industry

Bucket

bucket

Amazon Simple Storage Service (Amazon S3) is a scalable object storage service that allows you to store and retrieve any amount of data from anywhere on the web. Creating an S3 bucket in AWS (Amazon Web Services) is a straightforward process that involves a few simple steps. This guide will walk you through the process of creating an S3 bucket using the AWS Management Console. Step-by-Step Guide: 1. Sign in to the AWS Management Console: Navigate to AWS Management Console, and sign in using your credentials. 2. Open the S3 Console: Once logged in, find and select "S3" from the list of AWS services. Alternatively, you can click here to go directly to the S3 console. 3. Create a New Bucket: In the S3 console, click on the "Create bucket" button. This will start the process of creating a new S3 bucket. 4. Configure Bucket Properties: Bucket Name: Choose a unique name for your bucket. Bucket names must be globally unique across all of AWS. Naming Conventions: Follow AWS naming conventions for S3 bucket names. They should be DNS-compliant and unique; avoid the use of capital letters. Region: Select the AWS region where you want your bucket to be located. This choice can affect latency and compliance regulations. Configure options: You can set options like versioning, logging, and tagging for your bucket. These configurations are optional but can enhance your management and security. 5. Set Permissions: Choose who can access your bucket and the objects within it. By default, only the bucket owner has access, but you can configure more granular permissions using Access Control Lists (ACLs) and Bucket Policies. 6. Review and Create: Review all the configurations you have chosen for your bucket. Ensure that the settings align with your requirements. Click "Create bucket" to finalize and create your new S3 bucket. 7. Access Your Bucket: Once the bucket is created, you can start uploading objects to it using the AWS Management Console, AWS SDKs, or AWS CLI (Command Line Interface). ‘Object’ tab: In Amazon S3 (Simple Storage Service), the "object tab" typically refers to the list of objects (files or data) stored within a specific S3 bucket. When you navigate to a bucket in the AWS Management Console or interact with it programmatically, you can view or manage the objects stored within that bucket. This tab or section displays details such as object names, sizes, timestamps, and other metadata associated with each object. It's a fundamental part of managing and accessing data stored in S3 buckets. ‘Properties’ tab: Accessing and managing these properties from the Properties tab in the AWS Management Console allows you to configure your S3 bucket according to your specific requirements, ensuring security, compliance, performance, and cost-effectiveness for your storage needs. ‘Permissions’ tab: Managing permissions effectively ensures that your S3 buckets and objects are secure and accessible only to authorized users and applications. It’s essential to configure permissions based on the principle of least privilege, granting only the minimum permissions necessary for users and applications to perform their required tasks. To manage media files in an S3 bucket using your program while ensuring that the "Block all public access" setting remains unchecked in development but enforced in production, you would typically handle this through AWS IAM policies and possibly S3 bucket policies. In your development environment, you may want to allow broader access to facilitate testing and development. You can achieve this by defining an IAM policy that grants necessary permissions to your IAM users or roles. Here’s an example policy that grants full access to an S3 bucket and its objects. Cross-Origin Resource Sharing (CORS) is a security feature implemented by web browsers that allows a web application running at one origin (domain) to access resources from a different origin. An origin is defined by the combination of scheme (protocol), host, and port of a URL. ‘Metrics’ tab: You can configure S3 to collect and report metrics on the bucket and object-level activity, such as the number of requests, data transfer size, and storage metrics. These metrics help you monitor the performance and usage of your S3 resources. ‘Management’ tab: The Management tab in Amazon S3 consolidates these features and settings in one place, making it easier for you to optimize storage costs, manage data lifecycle, ensure compliance, and monitor usage and performance metrics for your S3 buckets and objects. ‘Access Points’ tab: Access points provide a simplified and secure way to manage access to your S3 data, especially in scenarios where you need to segregate access based on different applications, teams, or security requirements. They help simplify access management by encapsulating permissions within the access point configuration, reducing the complexity of managing access controls at the bucket level. You can start managing your media files in AWS cloud storage by uploading directly or through your program. Every file contains an object URL that can be used on your site for end users. https://guideinhackernoon.s3.amazonaws.com/sample.png Security: Always apply the principle of least privilege when configuring bucket permissions. Monitoring and Management: Utilize AWS CloudWatch to monitor your S3 bucket metrics, and set up alerts for any unusual activity. By following these steps, you can create an S3 bucket in AWS quickly and securely, ready to store and manage your data in the cloud. Amazon Simple Storage Service (Amazon S3) is a scalable object storage service that allows you to store and retrieve any amount of data from anywhere on the web. Creating an S3 bucket in AWS (Amazon Web Services) is a straightforward process that involves a few simple steps. This guide will walk you through the process of creating an S3 bucket using the AWS Management Console. Step-by-Step Guide: Step-by-Step Guide: Step-by-Step Guide: 1. Sign in to the AWS Management Console: 1. Sign in to the AWS Management Console: Navigate to AWS Management Console, and sign in using your credentials. 2. Open the S3 Console: 2. Open the S3 Console: Once logged in, find and select "S3" from the list of AWS services. Alternatively, you can click here to go directly to the S3 console. 3. Create a New Bucket: 3. Create a New Bucket: In the S3 console, click on the "Create bucket" button. This will start the process of creating a new S3 bucket. 4. Configure Bucket Properties: 4. Configure Bucket Properties: Bucket Name : Choose a unique name for your bucket. Bucket names must be globally unique across all of AWS. Bucket Name Bucket Name Naming Conventions : Follow AWS naming conventions for S3 bucket names. They should be DNS-compliant and unique; avoid the use of capital letters. Naming Conventions Region : Select the AWS region where you want your bucket to be located. This choice can affect latency and compliance regulations. Region Region Configure options: You can set options like versioning, logging, and tagging for your bucket. These configurations are optional but can enhance your management and security. 5. Set Permissions: 5. Set Permissions: Choose who can access your bucket and the objects within it. By default, only the bucket owner has access, but you can configure more granular permissions using Access Control Lists (ACLs) and Bucket Policies. 6. Review and Create: 6. Review and Create: Review all the configurations you have chosen for your bucket. Ensure that the settings align with your requirements. Click "Create bucket" to finalize and create your new S3 bucket. 7. Access Your Bucket: 7. Access Your Bucket: Once the bucket is created, you can start uploading objects to it using the AWS Management Console, AWS SDKs, or AWS CLI (Command Line Interface). ‘Object’ tab : ‘Object’ tab ‘Object’ tab In Amazon S3 (Simple Storage Service), the "object tab" typically refers to the list of objects (files or data) stored within a specific S3 bucket. When you navigate to a bucket in the AWS Management Console or interact with it programmatically, you can view or manage the objects stored within that bucket. This tab or section displays details such as object names, sizes, timestamps, and other metadata associated with each object. It's a fundamental part of managing and accessing data stored in S3 buckets. ‘Properties’ tab : Accessing and managing these properties from the Properties tab in the AWS Management Console allows you to configure your S3 bucket according to your specific requirements, ensuring security, compliance, performance, and cost-effectiveness for your storage needs. ‘Properties’ tab ‘Properties’ tab ‘Permissions’ tab : Managing permissions effectively ensures that your S3 buckets and objects are secure and accessible only to authorized users and applications. It’s essential to configure permissions based on the principle of least privilege, granting only the minimum permissions necessary for users and applications to perform their required tasks. ‘Permissions’ tab ‘Permissions’ tab To manage media files in an S3 bucket using your program while ensuring that the "Block all public access" setting remains unchecked in development but enforced in production, you would typically handle this through AWS IAM policies and possibly S3 bucket policies. In your development environment, you may want to allow broader access to facilitate testing and development. You can achieve this by defining an IAM policy that grants necessary permissions to your IAM users or roles. Here’s an example policy that grants full access to an S3 bucket and its objects. Cross-Origin Resource Sharing (CORS) is a security feature implemented by web browsers that allows a web application running at one origin (domain) to access resources from a different origin. An origin is defined by the combination of scheme (protocol), host, and port of a URL. ‘Metrics’ tab : You can configure S3 to collect and report metrics on the bucket and object-level activity, such as the number of requests, data transfer size, and storage metrics. These metrics help you monitor the performance and usage of your S3 resources. ‘Metrics’ tab ‘Metrics’ tab ‘Management’ tab : The Management tab in Amazon S3 consolidates these features and settings in one place, making it easier for you to optimize storage costs, manage data lifecycle, ensure compliance, and monitor usage and performance metrics for your S3 buckets and objects. ‘Management’ tab ‘Management’ tab ‘Access Points’ tab : Access points provide a simplified and secure way to manage access to your S3 data, especially in scenarios where you need to segregate access based on different applications, teams, or security requirements. They help simplify access management by encapsulating permissions within the access point configuration, reducing the complexity of managing access controls at the bucket level. ‘Access Points’ tab ‘Access Points’ tab You can start managing your media files in AWS cloud storage by uploading directly or through your program. Every file contains an object URL that can be used on your site for end users. https://guideinhackernoon.s3.amazonaws.com/sample.png https://guideinhackernoon.s3.amazonaws.com/sample.png Security : Always apply the principle of least privilege when configuring bucket permissions. Security Security Monitoring and Management: Utilize AWS CloudWatch to monitor your S3 bucket metrics, and set up alerts for any unusual activity. By following these steps, you can create an S3 bucket in AWS quickly and securely, ready to store and manage your data in the cloud.

A Step-by-Step Guide to Creating an S3 Bucket in AWS Cloud

The Token Bucket Algorithm for API Rate Limiting in NodeJS: A Simple Guide

The TechBeat: Backing Up Weaviate with MinIO S3 Buckets to Achieve Strategic Enhancement to Data Management (4/13/2024)

The TechBeat: Backing Up Weaviate with MinIO S3 Buckets to Achieve Strategic Enhancement to Data Management (4/11/2024)

Backing Up Weaviate with MinIO S3 Buckets to Achieve Strategic Enhancement to Data Management

ডাটা ম্যানেজমেন্টে কৌশলগত বর্ধন অর্জনের জন্য MinIO S3 বাকেটের সাহায্যে ওয়েভিয়েট ব্যাক আপ করা হচ্ছে

Sichern von Weaviate mit MinIO S3-Buckets zur strategischen Verbesserung des Datenmanagements

Realizar una copia de seguridad de Weaviate con MinIO S3 Buckets para lograr una mejora estratégica en la gestión de datos

Sauvegarde de Weaviate avec les buckets MinIO S3 pour obtenir une amélioration stratégique de la gestion des données

डेटा प्रबंधन में रणनीतिक वृद्धि हासिल करने के लिए मिनियो एस3 बकेट के साथ वेविएट का बैकअप लेना

MinIO S3 バケットを使用して Weaviate をバックアップし、データ管理の戦略的な強化を実現

데이터 관리의 전략적 향상을 위해 MinIO S3 버킷으로 Weaviate 백업

Fazendo backup do Weaviate com buckets MinIO S3 para obter aprimoramento estratégico no gerenciamento de dados

Резервное копирование Weaviate с помощью сегментов MinIO S3 для достижения стратегического улучшения управления данными

Veri Yönetiminde Stratejik İyileştirme Sağlamak için Weaviate'i MinIO S3 Kovalarıyla Yedekleme

Sao lưu Weaviate bằng nhóm MinIO S3 để đạt được cải tiến chiến lược trong quản lý dữ liệu

使用 MinIO S3 Buckets 备份 Weaviate，实现数据管理的战略增强

Rate-limiting, or limiting the speed of request processing, is an important component in modern web applications and APIs. It allows you to manage traffic and protects the system from overloading due to an excessive number of requests. One of the most effective tools for implementing rating in Java applications is the Bucket4j library. Introduction to Bucket4j Bucket4j is a Java language library that provides an API for implementing rate limiting using token buckets. The token bucket method is based on an analogy with a bucket into which tokens drip at a certain rate. Each request to the service extracts a certain number of tokens from this bucket. If there are not enough tokens in the bucket to process the request, the request is postponed or rejected. The Main Features of Bucket4j Bucket4j offers a flexible configuration of rating policies: Multiple restriction strategies: Bucket4j supports various rate limiting strategies, including a limit based on the number of requests per time interval and a bandwidth limit. Flexible configuration: Developers can customize the bucket size, token replenishment rate, and maximum request queue size. Distributed limitation: Bucket4j integrates with distributed repositories such as Hazelcast, Ignite, and Redis, which allows the use of rate-limiting in scalable distributed systems. High performance: The library is optimized to provide high performance and low latency when processing requests. An Example of Using Bucket4j Let's look at a simple example of using Bucket4j to limit the number of requests to the REST API. Suppose we need to limit the number of requests to a certain API to no more than 100 requests per minute. Adding a dependency: First, let's add Bucket4j to the project as a Maven dependency: <dependency>
    <groupId>io.github.bucket4j</groupId>
    <artifactId>bucket4j-core</artifactId>
    <version>последняя версия</version>
</dependency> Creating and configuring a bucket: Bucket bucket = Bucket4j.builder()
    .addLimit(Bandwidth.classic(100, Refill.greedy(100, Duration.ofMinutes(1))))
    .build(); Here, we create a bucket with a limit ofa 100 tokens and a replenishment rate of 100 tokens per minute. Applying the Restriction Before processing each API request, we check whether there are enough tokens in the bucket: if (bucket.tryConsume(1)) {
  // Processing the request
} else {
  // We are sending a response with an error about exceeding the request limit
} Advantages and Limitations of Bucket4j Advantages: Bucket4j allows you to fine-tune the rating policy according to the requirements of the application. Flexibility: Integration with distributed storage makes it an ideal choice for scalable applications. Scalability: Bucket4j integrates seamlessly with various Java frameworks. Easy integration: Limitations: : Bucket4j is designed exclusively for Java applications. Java Dependency In distributed systems, it is necessary to manage the state of buckets to ensure consistency. The need for state management: Conclusion Bucket4j is a powerful tool for implementing rate-limiting in Java applications. Its flexibility, performance, and support for distributed systems make it an ideal choice for modern web applications and APIs that require efficient traffic management and overload protection.

How to Use Bucket4j for Ratelimiters

Moby-Dick; or The Whale, by Herman Melville is part of HackerNoon’s Book Blog Post series. You can jump to any chapter in this book here: . Chapter 78: Cistern and Buckets [LINK TO TABLE OF LINK] CHAPTER 78. Cistern and Buckets. Nimble as a cat, Tashtego mounts aloft; and without altering his erect posture, runs straight out upon the overhanging mainyard-arm, to the part where it exactly projects over the hoisted Tun. He has carried with him a light tackle called a whip, consisting of only two parts, travelling through a single-sheaved block. Securing this block, so that it hangs down from the yard-arm, he swings one end of the rope, till it is caught and firmly held by a hand on deck. Then, hand-over-hand, down the other part, the Indian drops through the air, till dexterously he lands on the summit of the head. There—still high elevated above the rest of the company, to whom he vivaciously cries—he seems some Turkish Muezzin calling the good people to prayers from the top of a tower. A short-handled sharp spade being sent up to him, he diligently searches for the proper place to begin breaking into the Tun. In this business he proceeds very heedfully, like a treasure-hunter in some old house, sounding the walls to find where the gold is masoned in. By the time this cautious search is over, a stout iron-bound bucket, precisely like a well-bucket, has been attached to one end of the whip; while the other end, being stretched across the deck, is there held by two or three alert hands. These last now hoist the bucket within grasp of the Indian, to whom another person has reached up a very long pole. Inserting this pole into the bucket, Tashtego downward guides the bucket into the Tun, till it entirely disappears; then giving the word to the seamen at the whip, up comes the bucket again, all bubbling like a dairy-maid’s pail of new milk. Carefully lowered from its height, the full-freighted vessel is caught by an appointed hand, and quickly emptied into a large tub. Then remounting aloft, it again goes through the same round until the deep cistern will yield no more. Towards the end, Tashtego has to ram his long pole harder and harder, and deeper and deeper into the Tun, until some twenty feet of the pole have gone down. Now, the people of the Pequod had been baling some time in this way; several tubs had been filled with the fragrant sperm; when all at once a queer accident happened. Whether it was that Tashtego, that wild Indian, was so heedless and reckless as to let go for a moment his one-handed hold on the great cabled tackles suspending the head; or whether the place where he stood was so treacherous and oozy; or whether the Evil One himself would have it to fall out so, without stating his particular reasons; how it was exactly, there is no telling now; but, on a sudden, as the eightieth or ninetieth bucket came suckingly up—my God! poor Tashtego—like the twin reciprocating bucket in a veritable well, dropped head-foremost down into this great Tun of Heidelburgh, and with a horrible oily gurgling, went clean out of sight! “Man overboard!” cried Daggoo, who amid the general consternation first came to his senses. “Swing the bucket this way!” and putting one foot into it, so as the better to secure his slippery hand-hold on the whip itself, the hoisters ran him high up to the top of the head, almost before Tashtego could have reached its interior bottom. Meantime, there was a terrible tumult. Looking over the side, they saw the before lifeless head throbbing and heaving just below the surface of the sea, as if that moment seized with some momentous idea; whereas it was only the poor Indian unconsciously revealing by those struggles the perilous depth to which he had sunk. At this instant, while Daggoo, on the summit of the head, was clearing the whip—which had somehow got foul of the great cutting tackles—a sharp cracking noise was heard; and to the unspeakable horror of all, one of the two enormous hooks suspending the head tore out, and with a vast vibration the enormous mass sideways swung, till the drunk ship reeled and shook as if smitten by an iceberg. The one remaining hook, upon which the entire strain now depended, seemed every instant to be on the point of giving way; an event still more likely from the violent motions of the head. “Come down, come down!” yelled the seamen to Daggoo, but with one hand holding on to the heavy tackles, so that if the head should drop, he would still remain suspended; the negro having cleared the foul line, rammed down the bucket into the now collapsed well, meaning that the buried harpooneer should grasp it, and so be hoisted out. “In heaven’s name, man,” cried Stubb, “are you ramming home a cartridge there?—Avast! How will that help him; jamming that iron-bound bucket on top of his head? Avast, will ye!” “Stand clear of the tackle!” cried a voice like the bursting of a rocket. Almost in the same instant, with a thunder-boom, the enormous mass dropped into the sea, like Niagara’s Table-Rock into the whirlpool; the suddenly relieved hull rolled away from it, to far down her glittering copper; and all caught their breath, as half swinging—now over the sailors’ heads, and now over the water—Daggoo, through a thick mist of spray, was dimly beheld clinging to the pendulous tackles, while poor, buried-alive Tashtego was sinking utterly down to the bottom of the sea! But hardly had the blinding vapor cleared away, when a naked figure with a boarding-sword in his hand, was for one swift moment seen hovering over the bulwarks. The next, a loud splash announced that my brave Queequeg had dived to the rescue. One packed rush was made to the side, and every eye counted every ripple, as moment followed moment, and no sign of either the sinker or the diver could be seen. Some hands now jumped into a boat alongside, and pushed a little off from the ship. “Ha! ha!” cried Daggoo, all at once, from his now quiet, swinging perch overhead; and looking further off from the side, we saw an arm thrust upright from the blue waves; a sight strange to see, as an arm thrust forth from the grass over a grave. “Both! both!—it is both!”—cried Daggoo again with a joyful shout; and soon after, Queequeg was seen boldly striking out with one hand, and with the other clutching the long hair of the Indian. Drawn into the waiting boat, they were quickly brought to the deck; but Tashtego was long in coming to, and Queequeg did not look very brisk. Now, how had this noble rescue been accomplished? Why, diving after the slowly descending head, Queequeg with his keen sword had made side lunges near its bottom, so as to scuttle a large hole there; then dropping his sword, had thrust his long arm far inwards and upwards, and so hauled out poor Tash by the head. He averred, that upon first thrusting in for him, a leg was presented; but well knowing that that was not as it ought to be, and might occasion great trouble;—he had thrust back the leg, and by a dexterous heave and toss, had wrought a somerset upon the Indian; so that with the next trial, he came forth in the good old way—head foremost. As for the great head itself, that was doing as well as could be expected. And thus, through the courage and great skill in obstetrics of Queequeg, the deliverance, or rather, delivery of Tashtego, was successfully accomplished, in the teeth, too, of the most untoward and apparently hopeless impediments; which is a lesson by no means to be forgotten. Midwifery should be taught in the same course with fencing and boxing, riding and rowing. I know that this queer adventure of the Gay-Header’s will be sure to seem incredible to some landsmen, though they themselves may have either seen or heard of some one’s falling into a cistern ashore; an accident which not seldom happens, and with much less reason too than the Indian’s, considering the exceeding slipperiness of the curb of the Sperm Whale’s well. But, peradventure, it may be sagaciously urged, how is this? We thought the tissued, infiltrated head of the Sperm Whale, was the lightest and most corky part about him; and yet thou makest it sink in an element of a far greater specific gravity than itself. We have thee there. Not at all, but I have ye; for at the time poor Tash fell in, the case had been nearly emptied of its lighter contents, leaving little but the dense tendinous wall of the well—a double welded, hammered substance, as I have before said, much heavier than the sea water, and a lump of which sinks in it like lead almost. But the tendency to rapid sinking in this substance was in the present instance materially counteracted by the other parts of the head remaining undetached from it, so that it sank very slowly and deliberately indeed, affording Queequeg a fair chance for performing his agile obstetrics on the run, as you may say. Yes, it was a running delivery, so it was. Now, had Tashtego perished in that head, it had been a very precious perishing; smothered in the very whitest and daintiest of fragrant spermaceti; coffined, hearsed, and tombed in the secret inner chamber and sanctum sanctorum of the whale. Only one sweeter end can readily be recalled—the delicious death of an Ohio honey-hunter, who seeking honey in the crotch of a hollow tree, found such exceeding store of it, that leaning too far over, it sucked him in, so that he died embalmed. How many, think ye, have likewise fallen into Plato’s honey head, and sweetly perished there? About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Urbana, Illinois: Project Gutenberg. Retrieved April 2022 from Melville, Herman, 2001. Moby-Dick: or The Whale. https://www.gutenberg.org/files/2701/2701-h/2701-h.htm#link2HCH0078 This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at , located at . www.gutenberg.org https://www.gutenberg.org/policy/license.html

Moby-Dick; or The Whale: Chapter 78 - Cistern and Buckets

There has been a significant rise in the use of Decentralized storage over the past few years. One of the largest decentralized storage networks, Filecoin and Arweave, have brought about significant innovation of robust frameworks that use decentralized infrastructure to store and manage data. One of these frameworks is the 4EVERLAND bucket which allows uploads and pinning of Files to IPFS and Arweave. How does 4EVERLAND Bucket work? 4EVERLAND bucket is a decentralized object storage infrastructure that allows users to upload images, videos, and other supported files to decentralized storage networks like IPFS. By uploading a file to 4EVERLAND bucket, you get an IPFS hash which can be used to verify the data is stored in a decentralized manner. You also have an option to upload files through Arweave which offers permanent storage. 4EVERLAND Bucket can be leveraged in two ways: The dashboard is an interactive user interface accessible via a browser. The interface is simplified enough to allow a non-technical person to upload files to the bucket. A dashboard is also a great option if you find limitations in using the Buckets API. 1.  Dashboard 4EVERLAND Buckets API is compatible with Amazon S3 which is an Object storage service provided by Amazon. The set-up process for 4EVERLAND Buckets API is quite similar to that of Amazon S3 but the endpoints will be pointing to 4EVERLAND’s API. 2.  API Integration Once you upload a file, it can then be visible on 4EVERLAND’s dashboard. Some of the things you can do with 4EVERLANDs S3 API are: Fetching buckets File Upload Listing Files in the bucket Getting IPFS hash How to use 4EVERLAND’s Bucket API? 4EVERLAND's bucket API is simple to use and it can be used on Frameworks like React to deploy a single page Application or to upload images or files on the front-end. To get started. you will need to install the dependencies. For this, you need to have npm on your Dev environment. Below are the commands to install the AWS SDK: npm install @aws-sdk/client-s3 After installation, we will proceed to identify the Endpoint for our API.  4EVERLAND uses as the endpoint. We will also need to have our Auth tokens which can be obtained from your 4EVERLAND dashboard as seen in the image below. https://endpoint.4everland.co Once you have your Token, we will proceed to do an initial config of your s3 storage system. const AWS= require('aws-sdk');
const As3 = new AWS.s3({
    apiVersion: '2022-04-25',
    accessKeyID: 'SpecifyAPIKeyhere',
    secretAccessKey: 'specifySecretHere',
    endpoint: 'https://endpoint.4everland.co',
    region: 'us-north-1',
    s3ForcePathStyle: true
 }); After configuration, you can then proceed to call commands like to play with the S3 Client. ListObjects If you wish to upload a File to your bucket, you can use the putObject command and the configuration will look like this: Uploading a file to the 4EVERLAND bucket const FileUpload = {
    Bucket: 'testing',
    key: 'Home/hackathon',
    ContentType: 'image',
    Body: hackathonFile,
    ACL: 'Public',
    };
const request = s3.putObject(FileUpload);
request.on('header'), (statusCode, headers) => {
const ipfsHash = headers['4everland-hash'];
}).send(); In the code snippet above, we created a request to upload a file to my 4EVERLAND bucket which is . We also used the command putObject to upload the file to the Bucket from my local environment. testing The snipped also includes a request to get the IPFS hash of the Object. When you upload a file to 4EVERLAND bucket, 4EVERLAND inserts the IPFS hash in to the http header of the file. Once the files are uploaded, you have the option to sync the content to Arweave (AR) through 4EVERLNAD bucket. This option is not available via CLI but it can be done through the dashboard.  All you need to do is go to Buckets > Click on the bucket you wish to sync files to AR > Syc the content to AR. Once the content is synced, you will get access to the AR hash to verify the info is stored on Arweave. Fetching files from 4EVERLAND bucket Through the S3 SDK, you can also fetch buckets in which the files are stored. const listFiles = {
    Bucket: "testing",
};
s3.listObjectsV2(testing, function (err, list) {
    if (err) {
	    consolte.log("Error, check again!", err);
	 } else {
		console.log("Objects displayed correctly", list);
	}
	}); Aside from fetching files, you can also list out the Buckets in which your files are stored. Below is a simple example on how you can do it by using the command: listBuckets s3.listBuckets(function (err, list) {
    if (err) {
	    console.log("error when listing buckets", err);
	} else {
		console.log("data listed correctly", list);
	}
	}); Another alternative for listing Objects is through the . In your CLI, run to define your Access Keys and secret Key. From there you can list the objects by running: AWS CLI aws configure aws --endpoint-url https://endpoint.4everland.co s3 ls s3://testing Limitations There are a few limitations on the use of S3 which have been highlighted on the .  Some of the limitations like the length for bucket names can be mitigated by using the Buckets Dashboard which offers better flexibility. 4EVERLAND documentation There are many other use cases for 4EVERLAND buckets based on the s3 commands which are listed in the . Documentation Conclusion 4EVERLAND buckets API is a great alternative for users used to the Amazon AS3 bucket. By using the API, your Objects get stored on decentralized storage that is censorship-resistant and highly reliable.  4EVERLAND also allows you to sync your Files to Arweave which offers permanent storage of the files.

4EVERLAND's Bucket API for Decentralized Object Storage

Our team recently implemented an internal static website that allows employees to download technical reports. Since we're heavy AWS users, we naturally decided to host it on AWS S3, which provides a dedicated feature to build static websites ( ). S3 static website hosting Very quickly, however, we ran into an issue: AWS S3 does not provide any native, out-of-the-box authentication/authorization process. Because it was an internal-only website, we needed some kind of authorization mechanism to prevent non-authorized users from accessing our website and reports. We needed to find a solution to secure our static website on AWS S3. Discovering the Solution With CloudFront and Lambda@Edge We use for all Identity and User Management, so whatever solution we found had to plug-in with Okta. Okta Okta has several authentication/authorization flows, all of which require the application to perform a back-end check, such as verifying that the response/token returned by Okta is legit. So we needed to find a way to carry these checks/actions on a static website which uses a back end that we don't control. That's when we learned about , which lets you run at different stages of a request and response to and from CloudFront: AWS Lambda@Edge Lambda Functions We can trigger a Lambda Function at four different stages: When the request enters CloudFront ( ) viewer-request When the request goes out to the origin ( ) origin-request When the response is returned from the origin ( ) origin-response When the response is returned from CloudFront ( ) viewer-response We saw a solution to our original issue: that would check if the user is authorized, under two conditions: trigger a Lambda at the viewer-request stage If the user is authorized, let the request continue and return the restricted content If the user is not authorized, send an HTTP response to redirect them to a login page Implementing the Lambda@Edge function We'll cover here the key elements and main issues we faced. The complete code is available . Feel free to use it in your project! here Lambda@Edge restrictions and caveats During the development of the solution, we ran into several restrictions and caveats of Lambda@Edge. 1 – Environment variables Lambda@Edge Functions . That meant that we needed to find another way to pass data to our function. We opted for and in the Node.js code (we use Terraform to render the template when deploying the Lambda Function). cannot use environment variables SSM parameters templated parameter names 2 – Lambda package size limit For viewer events (reminder: we use the event), the Lambda package can be . One MB is pretty small considering that it includes (except of course the runtime/standard library) of your Lambda Function. viewer-request 1 MB at most all dependencies That's why instead of the original Python, because the Python package with its dependencies exceeded the 1 MB limit. we had to rewrite our Lambda in Node.js 3 – Lambda region Lambda@Edge functions can region. It's not a big issue but it means you'll need to: only be created in the us-east-1 Provision your AWS resources in that region to make things easier In Terraform, you'll need to have a separate AWS to access the bucket you want to protect if it's not in provider us-east-1 4 – Lambda role permission The IAM execution role associated with the Lambda@Edge functions in addition to the usual . See . must allow the principal service edgelambda.amazonaws.com lambda.amazonaws.com AWS - Setting IAM permissions and roles for Lambda@Edge Authorization mechanism with Okta Once we managed the above restrictions and caveats, we focused on the authorization/authorization. Okta offers several ways to authenticate and authorize users. We decided to go with , the industry-standard protocol for authorization. OAuth2 Okta implements the which adds a thin authentication layer on top of OAuth2 (that's the purpose of the ID token mentioned hereafter). Our solution would also work with pure OAuth2 with minimal modifications (removal of the ID token use in the code). Note: OpenID Connect (OIDC) standard OAuth2 itself offers several depending on the kind of application using it. In our case, we need the . authorization flows Authorization Code flow Here is the complete diagram of the Authorization Code flow taken from that shows how it works: developer.okta.com To summarize the flow: Our Lambda Function redirects the user to Okta where they will be prompted to login Okta redirects the user to our website/Lambda Function with a code Our Lambda Function checks if the code is legit and exchanges it for access and ID by sending a request to Okta tokens Depending on the result returned by Okta, we: Allow or deny access to the restricted content If access is allowed, save the access and ID tokens in a cookie to avoid having to re-authorize the user on every page Using JSON Web Tokens to store authorization result So far we have a working authorization process; however, we need to check the access/ID token on (a malicious user could forge an invalid cookie/tokens). Checking the tokens means sending a request to Okta and waiting for the response on the user visits, which and is clearly sub-optimal. every request every page slows down the loading times significantly While local verification of the Okta token is , as of this writing uses a (in-memory) cache when fetching the keys used to check the tokens. Because we're using AWS Lambda, and memory/state of the program isn't kept between invocations, the SDK is useless to us: it would still send one HTTP request to Okta for every user request, to retrieve the JWKs (JSON Web Keys). Worse, there is a limitation of 10 JWK requests per minute, which would make our solution stop working if there is more than 10 requests per minute. Note: theoretically possible the SDK provided by Okta LRU We decided to use to work around this. The initial authorization process is the same except that, instead of saving the access/ID tokens into a cookie, we create a JWT containing these tokens, and then save the JWT into a cookie. JSON Web Tokens Since the JWT is cryptographically signed: A malicious actor cannot forge one (they would need the private key used to sign them) The checking step required on every request is fast: we traded a long and I/O expensive HTTP request for a quick cryptographic check. Note on JWT expiration and renewal The JWT has a , to avoid having a valid JWT containing expired or revoked access/ID tokens. Another option would be to check the access/ID tokens regularly and revoke the associated JWT if needed, but then we would need a revocation mechanism, which would makes things more complex. pre-defined expiration time which should be reasonably short Finally, as suggested above, the tokens provided by Okta have an expiration time. It is possible (so the user doesn't have to re-login when the tokens expire) but we didn't implement that. to transparently renew them using a refresh token Conclusion While adding OAuth2 authentication to an S3 static bucket with Okta (or any other OAuth2 provider) is possible in an AWS-integrated and secure manner, it's certainly not straightforward. It requires writing a middleware between AWS and the OAuth2 provider (Okta in our case) using Lambda@Edge. We had to do the following ourselves: Validate the user authentication Remember the user authentication Refresh the user authentication (not implemented in our solution) Revoke the user authentication (TTL is implemented, but revocation before the end of the TTL is not) Finally, a bunch of AWS resources must be created to glue everything together and make it work. All this is worth the effort, because it works and our website is now more secure. You can find the code of the Lambda@Edge as well as the infrastructure (Terraform) here: https://github.com/GuiTeK/aws-s3-oauth2-okta Author: Guillaume Truchot, Site Reliability Engineer at Algolia, GitHub

How to Add OAuth2 Authentication to an S3 Static Bucket With Okta

Managing Django Media & Static Files on Heroku with Bucketeer

With the new year starting, everyone is thinking about their goals for the year. Whether it is on a personal level or career-wise, we all wish to try new things. In this thread, the random channel shared what they have put on their bucket list for the year 2022. slogging This Slogging thread by Sara Pinto, Jack Boreham, Mónica Freitas, Teri Eyenike and Abeer occurred in slogging's official #random channel, and has been edited for readability. Sara Pinto Dec 22, 2021, 6:22 PM With the year ending, let's forget about the new year resolutions, and tell me: what's on your bucket list for 2022? Jack Boreham Dec 23, 2021, 1:15 PM -Get enough money to mortgage a house -Possibly get a full-time position instead of freelance -Get my black belt in kickboxing -create my own startup -get back into fitness and complete my PT course Mónica Freitas Dec 23, 2021, 3:37 PM Sara Pinto Okay, so quick and easy: Move out of my parents' house; Continue on my mental a physical improvement journey; Start traveling (as soon as covid lets me); Start investing; Relearn german and french properly; Do an interrail; Skydive; I will probably get more tattoos. Mónica Freitas Dec 23, 2021, 3:37 PM Sara Pinto What about you? Sara Pinto Dec 23, 2021, 4:57 PM Jack Boreham Oh wow, you have an ambitious year in front of you! I hope you can check all that out of your list. And after reading "black belt" I made a note to myself to not annoy you 😂 😂 1 Sara Pinto Dec 23, 2021, 5:07 PM Mónica Freitas Uhh good one! Any special reason for relearning the languages? Sara Pinto Dec 23, 2021, 5:17 PM Mónica Freitas For me, it has to be: Get more piercings Finish my degree Get a full-time job Learn how to do splits Start saving for real Maybe plan a big trip? So far this is it, I'll probably be adding to it through the year though haha Mónica Freitas Dec 27, 2021, 3:30 PM Sara Pinto, It's a dream of mine to know five languages. It's a hard dream but reachable. I've always seen languages as codes - once you know them, you're in on the secret. German and French were languages that I used to know but forgot over time, and I think with proper relearning, I can make them stick. Mónica Freitas Dec 27, 2021, 3:31 PM Sara Pinto TOUR TIME! LOVE IT! Why the split? My goal, flexibility wise, is just being able to reach my toes while standing ahah Sara Pinto Dec 27, 2021, 3:53 PM Mónica Freitas, I get it. I'm a language enthusiast, and I think it's such a skill to have. I think we lose a lot in translations. It becomes hard to get out point across in the way we wish. I hope you can relearn, and maybe you can teach me one thing or two haha Sara Pinto Dec 27, 2021, 3:57 PM Mónica Freitas Why not the split? Haha. I feel like it's doable and I think it would be fun. How cool would it be to say you can do the split? Mónica Freitas Dec 28, 2021, 12:13 PM Sara Pinto So true, and it gives you an advantage. Besides, you get more comfortable traveling, for instance, because you do know the language. Deal 😉 🔥 1 Mónica Freitas Dec 28, 2021, 12:14 PM Sara Pinto, I hope you can! ahaha Maybe you'll become TIKTOK famous for doing the split Sara Pinto Dec 28, 2021, 7:08 PM Mónica Freitas, now that would be some ambitious thought for 2022 haha Mónica Freitas Dec 29, 2021, 12:25 PM Sara Pinto fingers crossed :crossed_fingers: Sara Pinto Jan 7, 2022, 12:02 PM Limarc Ambalina Abeer Khamisi Hamisi Linh Smooke Daniel Guzman Teri Eyenike What about you? Teri Eyenike Jan 7, 2022, 1:19 PM Sara Pinto Here are some things I need to achieve in 2022 • Travel as I need to see the world • Get a full-time job • Indulge in adventure (skydiving, surfing, and hiking) • Financial independence (Invest and save) • Maybe relocate out of my country (japa as we call it here in Nigeria 🇳🇬 ) • Get an apartment for me 🔥 1 Abeer Jan 10, 2022, 1:42 PM Sara Pinto My bucket list/goals for 2022 is the following: Take control of my health (aka diet and exercise) Complete HackerShip Double down on my AWS knowledge Spend more time with friends and family Write more Be more in the moment 🔥 2 Sara Pinto Jan 10, 2022, 3:13 PM Teri Eyenike Wow, I need to take some tips from you! I loved the adventure topic. Have you ever tried any of these or do you want to try them for the first time? Sara Pinto Jan 10, 2022, 3:29 PM Abeer Great bucket list!! I like how you combine growing your knowledge with enjoying life. It can be difficult to reconcile the two. How's it going so far? Teri Eyenike Jan 10, 2022, 3:40 PM Sara Pinto, I have hiked and have done kayak. I haven't tried skydiving and surfing 🏄. Sara Pinto Jan 10, 2022, 3:57 PM Teri Eyenike That's pretty cool! I would like to try hiking, but I'm afraid I'll suck at it and just fall on my face 😂 I hope you can do it all!! 👍 1 😂 1 Teri Eyenike Jan 10, 2022, 4:08 PM Yes, I want to surf, but first I want to practice my swimming skills. 🔥 1 Abeer Jan 12, 2022, 4:10 PM Sara Pinto Like most endeavors, it’s going in waves. Some days I make a lot of headway, other days I feel like I ended up a step back. Overall I’m making good progress slowly changing my habits and lifestyle which I’m truly grateful for. That being said, I might have to add “Get more sleep” on my list 😵 Sara Pinto Jan 13, 2022, 10:15 AM Abeer We can't rush progress, and a good night's sleep is always needed! I hope this year goes as you wish!

What's on your 2022 Bucket List?

Occasionally you might want to rename an AWS S3 bucket you are managing with Terraform. However, the names of S3 buckets are immutable, which means you can’t change them directly. If you tried, Terraform would destroy the old one and then create a new one, resulting in data loss. To avoid this, you need to , move the data over to it, make the relevant Terraform state replacements, and finally delete the old bucket. create a new bucket with the desired name In this post, you will learn how to rename an AWS S3 bucket in Terraform. First things first – let’s say you have a bucket definition in your Terraform code: resource “aws_s3_bucket” “my_bucket” {
    bucket = “old-name”
} and you want to change the name of the bucket to . new-name Step 1 - Create the new bucket Firstly, we’ll need You can do this using the AWS CLI or the . Just make sure to properly replicate the old settings, especially the ACL (so that your data doesn’t accidentally become public). to create a new bucket. AWS console Now, we can copy all the files from the old to the new bucket: aws s3 sync s3://old-name s3://new-name Step 2 - Modify the State Now that we have our new bucket, we need to remove the old one from our Terraform state and the new one in its place: import terraform state rm aws_s3_bucket.my_bucket
terraform import aws_s3_bucket.my_bucket new-name If you tried to run Terraform now, it would show you that there’s drift—and yes, there would be! We’ve just imported a bucket into a resource which still has in the config. old-name Step 3 - Change the Code That’s why we now have to finally change the name of the bucket in our Terraform config: resource “aws_s3_bucket” “my_bucket” {
    bucket = “new-name”
} If you run Terraform now, you’ll see that there are no changes to be made. Step 4 - Do a Cleanup If you want to, you can now delete your old bucket using: aws s3 rm s3://old-name --recursive
aws s3 rb s3://old-name Make sure all the data has successfully been copied over to the new bucket. Step 5 - Run the Above Arbitrary AWS CLI Commands if You’re Using Spacelift If you’re using Spacelift then you can use to run the above arbitrary AWS CLI commands. The default runner image already contains the AWS CLI, so no changes are necessary there. tasks One additional thing you can do is while you’re running the migration, this way nobody will accidentally run Terraform or make any other changes while you’re moving the data. lock the Stack And that’s it! If you have any questions about how to rename an AWS S3 bucket, drop me a line in the comments and I’ll get back to you straight away. First Published here

Change the Name of your AWS S3 Bucket in Terraform Without Breaking Things

Most of the time, analyzing security through AWS policies resembles this diagram for me: Untangling who is holding which kite! AWS policies can be detailed and conflicting and it might take some puzzle-solving attitude to untangle them and find out what would be the final rule in effect. To untangle them, the first thing you need to know is what are the different types of policies and how do they apply and function. In this blog post, we will be talking about such policies, particularly in the context of S3 buckets. When it comes to permissions to an S3 bucket, there are three major policies that you can notice being applied: IAM policy S3 Bucket Policy S3 Access Control List Let's try to understand what these are. IAM Policy: IAM Policy specifies what are you allowed to do with any AWS resource. They are global and apply to all areas of AWS - S3, EC2, Lamda (basically any service in AWS). One can attach the IAM policy to IAM users, groups or roles to subject them to the permissions defined in the policy. IAM policies define what a principal can do in your AWS environment, There are different types of IAM policies - AWS Managed, Customer Defined & Inline. When you go to IAM AWS Managed Policies, you can see a number of policies pre-created and listed for S3, such as: Here is how AmazonS3ReadOnlyAccess is defined: { ], }
    ]
} { "Version" : "2012-10-17" , "Statement" : [ "Effect" : "Allow" , "Action" : [ "s3:Get*" , "s3:List*" , "s3-object-lambda:Get*" , "s3-object-lambda:List*" "Resource" : "*" S3 Bucket Policy: S3 Bucket policies are attached only to S3 Buckets  (can't be attached to a user, role/group, or any other resource like EC2, Lamda, etc.) The policy defines what actions are allowed or denied ON THE BUCKET. They can be broken down to the user level, defining READ, PUT, DELETE access per user, if needed. You might ask why would we need S3 buckets when we can already define most of them at an IAM level? It's mostly a matter of convenience. S3 Bucket policy allows you to define access controls at the bucket level itself. Suppose an S3 bucket holds confidential information, say employees' salaries. Suppose, you want to regulate access to this bucket. If you choose to go by the IAM route, you'd need to define appropriate users/groups/roles and edit the IAM policy to allow or deny access to this S3 bucket, per user, group or role. An easier way would be to define the bucket policy attached to this S3 bucket, which explicitly allows /denies access to certain users or groups to this bucket. It'd be easier to define, apply and manage. Not just the users within the same AWS account, an S3 bucket policy can also enable cross-account access to the S3 bucket without defining IAM roles. Another added advantage is the allowed size of the policy is up to 20 kb, which is significantly more than what's permitted for an IAM policy (2kb for Users, 5kb for groups & 10 kb for roles). Check out this video on my channel to learn how can you create and attach your own IAM and S3 Bucket policy: S3 ACL: This is a legacy access control mechanism that predates IAM. It's still useful if you want to apply policies at the object level i,e, to individual files in the bucket. When you create an S3 bucket, you can see this option present as one of the configurations: You can choose to enable ACLs and further specify the preferred object ownership. Note that object ownership interferes in scenarios such as when a bucket owner tries to delete the bucket along with all its objects or try out a cross-region replication. ACLs can be defined at the S3 bucket level or individual file level. When you define ACL at an object level, you can see a configuration panel like this: Note that if while creating the bucket you have blocked all public access, some options here would be already greyed out. Also, if you have selected Bucket owner preferred (as in diagram 2), you won't be able to edit the ACL. You can select Read here for all public users and now this particular file can be read by anyone on the internet. Note that the bucket itself is not public, but we have made this object public by configuring the ACL appropriately. Note: Object ACLs can be applied to individual IAM users or groups, but that can't be done by the console, one can do that through CLI or programmatically. So, what happens if there are these three policies separately defined regulating access to a bucket or its object? What does the final access look like? Here's the thumb rule: If, any of these policies specify an explicit Deny the action is denied. If no explicit deny is mentioned, but an explicit allow is also not mentioned, even then the action is denied. You need to specifically allow the action in any or all of these policies and also ensure that that particular action is not denied in any or all policies, only then would a request go through! A more elaborate diagram on the same is this: But, don't hold your breath, yet, we won't be walking through this in this blog post. :) I'll write a separate one to address the intricacies in the above diagram (officially published by AWS). So, hope this post was useful in demystifying the three types of policies and untangling those for you, If you have any queries/concerns pls drop them in the comments below. You can subscribe to or follow me on for more similar posts. this space Twitter If you are interested in more consultation, you can reach out to me . here Also Published Here

Untangling - IAM Policy, S3 Bucket Policy & S3 ACL

Hello! Today we will deploy a serverless infrastructure based on AWS Lambda for uploading images (and any other files) with private storage in an AWS S3 bucket. We will be using terraform scripts that are uploaded and available at my GitHub repository. kompotkot/hatchery This approach has the following advantages: lambda is called on request and therefore allows to save on server maintenance costs if this functionality is not key for your app lambda functions have an isolated runtime environment, which is ideal for processing uploaded files. Should malicious code be uploaded, the attacker will not be able to leave the sandbox, and the sandbox session will be forcibly terminated after some time storing files in an S3 bucket is very cheap Project structure As an example, we’ll be using an abstract app for journal entries with an API. We can upload an image in each entry, and the structure is similar to a file directory: - journal_1
  - entry_1
    - image_1
  - entry_2
    - image_1
    - image_n
  - entry_n
- journal_n Our hypothetical API has an endpoint for receiving an entry in a journal: curl \
  --request GET \
  --url 'https://api.example.com/journals/{journal_id}/entries/{entries_id}'
  --header 'Authorization: {token_id}' If in response to this endpoint is equal to 200, it means the user is authorized and has access to the journal. Accordingly, we will let them store images for this entry. status_code Registering the app on Bugout.dev To avoid adding an extra table to the database, which we would need for storing which image belongs to which entry, we will use from . This approach is used to simplify our infrastructure, but, if required, this step can be substituted for creating a new table in your database and writing an API for creating, modifying, and deleting data about the stored images. resources Bugout.dev Bugout.dev is open source and you can review the API documentation at the GitHub repository. We will need an account and a team called (you can use any name in relation to your project) at the page, you should save this team’s ID for the next step (in our case it’s ): myapp Bugout.dev Teams e6006d97-0551-4ec9-aabd-da51ee437909 Next, let’s create a Bugout.dev Application for our team myapp through a curl request (the token can be generated at the page) and save it in the variable: Bugout.dev Tokens BUGOUT_ACCESS_TOKEN curl \
  --request POST \
  --url 'https://auth.bugout.dev/applications' \
  --header "Authorization: Bearer $BUGOUT_ACCESS_TOKEN" \
  --form 'group_id=e6006d97-0551-4ec9-aabd-da51ee437909' \
  --form 'name=myapp-images' \
  --form 'description=Image uploader for myapp notes' \
  | jq . In response we will get confirmation of a successfully created app: {
    "id": "f0a1672d-4659-49f6-bc51-8a0aad17e979",
    "group_id": "e6006d97-0551-4ec9-aabd-da51ee437909",
    "name": "myapp-images",
    "description": "Image uploader for myapp notes"
} The ID will be used for storing , where every resource is the uploaded image’s metadata. The structure is set in any form depending on the required keys, in our case, it will look as follows: f0a1672d-4659-49f6-bc51-8a0aad17e979 resources {
    "id": "a6423cd1-317b-4f71-a756-dc92eead185c",
    "application_id": "f0a1672d-4659-49f6-bc51-8a0aad17e979",
    "resource_data": {
        "id": "d573fab2-beb1-4915-91ce-c356236768a4",
        "name": "random-image-name",
        "entry_id": "51113e7d-39eb-4f68-bf99-54de5892314b",
        "extension": "png",
        "created_at": "2021-09-19 15:15:00.437163",
        "journal_id": "2821951d-70a4-419b-a968-14e056b49b71"
    },
    "created_at": "2021-09-19T15:15:00.957809+00:00",
    "updated_at": "2021-09-19T15:15:00.957809+00:00"
} As a result, we have a remote database of sorts, where every time we upload an image to an S3 bucket, we’ll be writing which journal( ) and which entry( ) the image was added to under which ID, name, and extension. journal_id entry_id Preparing the AWS project environment AWS will store images in an S3 bucket and function as a server on Lambda for image manipulation. We will need an AWS account and a configured IAM user for terraform. It is an account with to all resources without having access to the web console: Programmatic access To get the access keys, add these variables to your environment: export AWS_ACCESS_KEY_ID=<your_aws_terraform_account_access_key>
export AWS_SECRET_ACCESS_KEY=<your_aws_terraform_account_secret_key> Let’s also deploy a VPC with the subnets: 2 private access 2 public access They will be useful for configuring the AWS Load Balancer. The code for this module can be found under . Let’s edit the variables in the file and launch the script: files_distributor/network variables.tf terraform apply From the output, add to your environment variables values for , и . AWS_HATCHERY_VPC_ID AWS_HATCHERY_SUBNET_PUBLIC_A_ID AWS_HATCHERY_SUBNET_PUBL IC_B_ID Server code In our project, we’ll be using . In my experience, I’ve noticed that as the packet with code surpasses 10MB, the upload speed to AWS drops dramatically. Even if we upload it to the S3 bucket in advance and then make a Lambda from it, AWS can lag for a long time. Therefore, if you are using third-party libraries it can make sense to use Lambda layers, whereas if you aren’t planning to use any libraries with lightweight code on CloudFront, consider looking into lambda@edge. a simple AWS Lambda function The full code can be found in the file in the repository. In my opinion, it’s more effective to work on nodejs, but to facilitate in-depth file processing we’ll use python. The code consists of main blocks: lambda_function.py MY_APP_JOURNALS_URL = "https://api.example.com"     # API эндпоинт для доступа к нашему приложению с заметками
BUGOUT_AUTH_URL = "https://auth.bugout.dev"         # Bugout.dev эндпоинт для записи ресурсов (метаданных картинок)
FILES_S3_BUCKET_NAME = "hatchery-files"      # Название S3 bucket, где мы будем хранить картинки
FILES_S3_BUCKET_PREFIX = "dev"               # Префикс S3 bucket, где мы будем хранить картинки
BUGOUT_APPLICATION_ID = os.environ.get("BUGOUT_FILES_APPLICATION_ID")   # Bugout.dev application ID созданный ранее Let’s expand the default exception to proxy the response from Bugout.dev Resources. E.g., if the image does not exist, when we request the resource, we’ll receive error 404, which we’ll in turn return to the client as a reply to the request for the missing image. class BugoutResponseException(Exception):
    def __init__(self, message, status_code, detail=None) -> None:
        super().__init__(message)
        self.status_code = status_code
        if detail is not None:
            self.detail = detail To save an image in an S3 bucket we’ll use the standard library that’ll let us parse the request’s body that was sent in format. We’ll save images under the path without specifying the file’s name and extension. cgi multipart/<image_type> {journal_id}/entries/{entry_id}/images/{image_id} def put_image_to_bucket(
    journal_id: str,
    entry_id: str,
    image_id: UUID,
    content_type: str,
    content_length: int,
    decoded_body: bytes,
) -> None:
    _, c_data = parse_header(content_type)
    c_data["boundary"] = bytes(c_data["boundary"], "utf-8")
    c_data["CONTENT-LENGTH"] = content_length

    form_data = parse_multipart(BytesIO(decoded_body), c_data)

    for image_str in form_data["file"]:
        image_path = f"{FILES_S3_BUCKET_PREFIX}/{journal_id}/entries/{entry_id}/images/{str(image_id)}"
        s3.put_object(
            Body=image_str, Bucket=FILES_S3_BUCKET_NAME, Key=image_path
        ) When we extract an image from the S3 bucket we’ll need to encode it into base64 for correct transmission. def get_image_from_bucket(journal_id: str, entry_id: str, image_id: str) -> bytes:
    image_path = f"{FILES_S3_BUCKET_PREFIX}/{journal_id}/entries/{entry_id}/images/{image_id}"
    response = s3.get_object(Bucket=FILES_S3_BUCKET_NAME, Key=image_path)
    image = response["Body"].read()
    encoded_image = base64.b64encode(image)
    return encoded_image The function’s implementation is available at this GitHub , to sum up: lambda_handler(event,context) link Firstly, we assert that the request is formatted correctly and contains and journal_id entry_id Then we call our hypothetical app’s API https://api.example.com/journals/{journal_id}/entries/{entry_id} Depending on the request method: , or we read, upload or delete an image from the journal’s entry GET POST DELETE When we’re uploading to the S3 bucket, we check the extension and the file’s size. This can be expanded into hash verification to avoid uploading the same file, etc. Next, we’ll need to package into the Lambda library. Luckily, work with AWS functionality is ready out of the box. Let’s create an empty python environment, install the library and package the contents of : requests boto3 site-packages python3 -m venv .venv
source .venv/bin/activate
pip install requests
cd .venv/lib/python3.8/site-packages
zip -r9 "lambda_function.zip" . Place the created archive into the directory and add the Lambda function itself: lambda_function.zip files_distributor/bucket/modules/s3_bucket/files zip -g lambda_function.zip -r lambda_function.py Our server is ready, now we can upload code to AWS and deploy Lambda server, to do so use the script in : files_distributor/bucket terraform apply We’re left with: A private AWS S3 bucket that stores the Lambda function code hatchery-sources A private AWS S3 bucket that we’ll store our images into with the prefix hatchery-files dev AWS Lambda function with working server code An IAM role for the Lambda that allows writing into a specific S3 bucket and logs The IAM role rules are in . The other file is needed for the Lambda to function correctly. files_distributor/bucket/modules/iam/files/iam_role_lambda_inline_policy.j son iam_role_lambda_policy.json To debug Lambda you can just the required values or use the standard module for python. The output for every Lambda function call is available at AWS CloudWatch: print logging After creating the function, add a variable from our code to the Lambda environment, which you can do in the tab . BUGOUT_FILES_APPLICATION_ID Configuration/Environment  variables As the last step, save the AWS Lambda arn into the variable . AWS_HATCHERY_LAMBDA_ARN Configuring the AWS Load Balancer and open ports The only step left now is to create an AWS Security Group where we’ll set a port the AWS Load Balancer will listen to for subsequent data transmit into the Lambda function (in our case it’s 80 and 443). terraform apply \
    -var hatchery_vpc_id=$AWS_HATCHERY_VPC_ID \
    -var hatchery_sbn_public_a_id=$AWS_HATCHERY_SUBNET_PUBLIC_A_ID \
    -var hatchery_sbn_public_b_id=$AWS_HATCHERY_SUBNET_PUBLIC_B_ID \
    -var hatchery_lambda_arn=$AWS_HATCHERY_LAMBDA_ARN Congratulations, our AWS Lambda function is open to the world and ready to upload and return images for our journal entries app! This article was also published on Medium

AWS Lambda: How to Set Up Private Storage in an AWS S3 Bucket to Upload Images

What's AWS S3? Long story short... AWS S3, or Amazon Simple Storage Service, is storage for the Internet. Designed to make web-scale computing easier for developers. source: Amazon Why you need it? Well... to store files in the cloud. These files are stored in Buckets, a resource where you can upload any number of objects using the Amazon S3 API. How to create a Bucket? 1. Visit website. Amazon Web Services (AWS) 2. Sign in to your AWS Amazon Account (if you don't have one click on ). this link Select and use your email and password to enter your AWS Management console. "Root user" 3. In the AWS Management Console, search for , and select the first option. "S3" You'll be taken to the S3 Bucket dashboard. 4. Click on button Create Bucket 5. Enter the desired and select the geographical closest to you. Bucket name Region You can review the other options and change as needed but for a NOTE: basic configuration is not needed. Click on the button Create bucket 6. ... you should see a success message and the created bucket in your bucket list in the dashboard. Done! Related links from the source: Create and configure AWS S3 Bucket This article is part of the tutorials collection. Mini Ruby on Rails The collection is a series of short and straight forward tutorials. Directed to Ruby on Rails beginners, to help them set up a Rails application in a fast and easy way. Mini RoR

How To Create an AWS S3 Bucket

Problem statement: Part of our regular production upgrade we were trying backup data in s3 bucket with Item Count: 1,000,344 and Size: ~130 GB We were basically initiating a backup using the regular s3 commands like: --recursive ://< sync ://< ://< aws s3 cp s3 bucket>> aws s3 s3 bucket> s3 bucket>> During execution, we noticed it took hours and hours to perform the copy. There is no way to make it faster. The only workaround we found is to run these in parallel in multiple terminals so they all can operate on different s3 partitions at the same time and perform copy faster, which is neither an elegant solution nor scalable. aws commands Other options: We tried a couple of other options mentioned in stack overflow and AWS forums like S3 Batch operations S3 batch operations seem to solve this problem, but at this point, it doesn’t support it on objects encrypted based on the KMS key. When I created a job to copy the contents of the bucket with KMS key encryption enabled got the following error: Unsupported encryption type used: SSE_KMS When I read more about this AWS docs it stated under “Specifying a Manifest” section → Manifests that use server-side encryption with customer-provided keys (SSE-C) and server-side encryption with AWS KMS managed keys (SSE-KMS) are not supported https://docs.aws.amazon.com/AmazonS3/latest/dev/batch-ops-basics.html#specify-batchjob-manifest s3-dist-cp s3-dist-cp seems to be promising but when I ran it against a bucket with had closer to 6 TB of data the job failed while running “reduce” task after 40 minutes without any clear indication of why it failed Custom approach: Unfortunately, none of those mentioned above approaches solved our problem, so we came up with this approach. This approach can be further optimized, so think as a first step to solve this problem. It's a 2 step process, which is a combination of shell script and spark code. First, we need to generate the record file (with object keys), then running a spark code to copy the files in parallel across nodes in multiple tasks. Generating the record file: We need to generate a text file containing object keys of the items inside the source s3 bucket (to be copied), is done by running this command on any : EC2 instances aws s3 ls s3://test_bucket --recursive | awk > /tmp/output.txt '{print $4}' (just object keys one in each line) Output: data/solution=33/test1.mov data/solution=33/test2.mov, etc Spark code : sql.read()
 .textFile(file)
 .repartition( )
 .flatMap((FlatMapFunction<String, String>) s -> Arrays.asList(s.split( )).iterator(), Encoders.STRING())
 .map((MapFunction<String, String>) s -> String.format( , String.format( , source, s), target, s), Encoders.STRING())
 .foreachPartition((ForeachPartitionFunction<String>) iterator -> { (iterator.hasNext())
         Runtime.getRuntime().exec(iterator.next()).waitFor();
 }); 2000 "\n" "aws s3 cp %s s3://%s/%s" "s3://%s/%s" while Spark Submit: spark-submit — class com.s3.S3Copy s3://test_bucket/copier.jar test_bucket back_up_bucket s3://test_bucket/output.txt args[0] → Source bucket args[1] → Target bucket args[3] → s3 record file generated in previous step This code will read the “output.txt” file and splits into multiple partitions and runs them in parallel across multiple nodes. Performance Test With 15 EMR core nodes each of m4.xlarge instance type, we were able to copy of data in less than Since we pay EMR only for the time, we use it is cost-effective (further cost reduction is possible by going with SPOT or EC2 fleet configuration) and much scalable compared to the previous approach. 5.5 TB 40 minutes. Spark submit: spark-submit —conf spark.network.timeout=420000s —conf spark.executor.heartbeatInterval=410000s —conf spark.yarn.scheduler.mode=FAIR —conf spark.shuffle.service.enabled=true —conf spark.serializer=org.apache.spark.serializer.KryoSerializer —conf spark.executor.memoryOverhead=1024 —conf spark.driver.memoryOverhead=1024 —conf spark.executor.instances=74 —conf spark.executor.cores=6 —conf spark.driver.cores=6 —conf spark.driver.memory=10g —conf spark.executor.memory=10g —conf spark.default.parallelism=888 —deploy-mode cluster —master yarn —conf spark.sql.broadcastTimeout=360000 —class com.s3.S3Copy s3://dmp-dms-k8s-dev-fico-pto-tenant/copier.jar test_bucket back_up_bucket s3://test_bucket/output.txt Previously published at https://medium.com/javarevisited/copying-tbs-of-data-between-s3-buckets-8438dde7dadb

How To Copy Terabytes of Data Between AWS S3 Buckets

FedEx Booz Allen Hamilton Republican National Committee Dow Jones & Co Verizon Wireless Time Warner Cable Wal Mart These eight organizations all have the same thing in common: Leaky S3 buckets that were misconfigured and exposed sensitive customer data. Amazon (or Simple Storage Service) bucket misconfigurations and breaches continue to show up in cybersecurity publications. A disappointing fact considering how newsworthy these breaches have been. S3 S3 is an object storage service on Amazon Web Services (AWS) that provides customers with infinitely scalable and durable storage for websites, mobile applications, backup and restore, and many other use cases. This service is one of the original services on and is often the first entry point into the cloud for organizations that are migrating to the cloud. Amazon AWS Why do misconfigurations of S3 buckets keep happening? I ask myself the same question. This is another case of “user error” being trotted out as the reason why organizations are breached due to misconfigured settings on an S3 bucket. I agree that a user plays a significant and lead role in these misconfigurations. I mean, AWS asks you to type in “confirm” before making a bucket public. So, yes, a user is to blame here. However, one of the most important roles of a security practitioner is to implement systems and tools to protect the organization systems and data from human mistakes. Mistakes happen and another round of security awareness training will not guarantee the next administrator won’t make a mistake. There are many ways to automate the security of sensitive S3 buckets, whether through the use of a Cloud Access Security Broker (CASB), cloud security SaaS solution, or native AWS services. The method of how organizations automate the security of S3 buckets is not important, the endstate of secure S3 buckets and a reduction of news articles about another S3 bucket breach is all that matters. Small businesses and startups often look to native services on their cloudservice providers to solve complex security issues. These services are often easier to configure and cheaper than third-party solutions. With this in mind, I spent 20 minutes in this to demonstrate how administrators can use native AWS Services to automate the security of S3 buckets. I SC2 Miami Chapter Cybersecurity Lightning Lab Specifically, we will walk through how to ensure that your S3 buckets remain private and with default encryption enabled. A public bucket means anyone can access that bucket. Anyone means anyone! Any AWS user can access the bucket from the internet, this misconfiguration is the reason many of those organizations linked above ended up in the news. This video will show you how easy it is to misconfigure but also remediate S3 buckets. S3 bucket security misconfigurations can be eliminated through the use of automated detection and remediation tools. As cybersecurity professionals, now more than ever, we are expected to defend systems and data with a smaller budget and fewer resources. Automating the detection, response, recovery, and communication of potential security misconfigurations allows your security team to use their limited time on the important security activities that matter.

How To Eliminate Leaky S3 Buckets Without Writing A Line Of Code

Your website will be accessible with . To access it with do this three extra steps: http https with the AWS Certificate Manager for your domain Create an certificate for your "root" S3 bucket. Associate the certificate to it Create an AWS CloudFront distribution Point the record of your apex domain to the new CloudFront distribution ALIAS How to Point a Naked Domain - Not Registered with Route 53 - to an AWS S3 Hosted Static Website So people can access your website through example.com instead of www.example.com . In this post, we're going to connect an with an AWS S3 hosted website. The naked domain is bought in a domain name registrar other than AWS Route 53. In this case . apex domain OVH For other registrars the steps are similar. Apex domains, generally, cannot make use of records. Allowed are A or records, pointing to static IPs. This makes it harder to use our naked domain for our website: . This is because of the dynamic nature of AWS S3 instances. They expose a subdomain endpoint, so they can route the internal traffic with freedom. CNAME AAAA example.com Let's start. Copy your current zone file , go to: , and reduce the (Time to Live). The authoritative name servers cache will expire faster now. This is good because we're going to change the (Name Server) records. Log in to your OVH account Domains > DNS zone TTL NS Now click on: , and copy your RRs (Resource Records). DNS zone > Change in text format It should look like: @ dns18.ovh.net. tech.ovh.net. ( ) dns18.ovh.net. ns18.ovh.net. mx3.mail.ovh.net. mx1.mail.ovh.net. mx2.mail.ovh.net. ??? ??? " |www.rubenbelow.com" "v=spf1 include:mx.ovh.com ~all"
_autodiscover._tcp mailconfig.ovh.net.
_imaps._tcp ssl0.ovh.net.
_submission._tcp ssl0.ovh.net.
autoconfig mailconfig.ovh.net.
autodiscover mailconfig.ovh.net.
ftp rubenbelow.com.
imap ssl0.ovh.net.
mail ssl0.ovh.net.
pop3 ssl0.ovh.net.
smtp ssl0.ovh.net.
www ??? $TTL 3600 IN SOA 2019112215 86400 3600 3600000 300 IN NS IN NS IN MX 100 IN MX 1 IN MX 5 IN A IN AAAA IN TXT 1 600 IN TXT IN SRV 0 0 443 IN SRV 0 0 993 IN SRV 0 0 465 IN CNAME IN CNAME IN CNAME IN CNAME IN CNAME IN CNAME IN CNAME IN CNAME * Some values are replaced with: ??? In the next step we're going to import our entries in AWS Route 53. Before, let us delete some entries. Records to delete: dns18.ovh.net. ns18.ovh.net.
... ??? ???
...
www ??? IN NS IN NS IN A IN AAAA IN CNAME Create an AWS Route 53 Hosted Zone , go to Route 53, and click on: . As: , use the name of your apex domain: . Log in to your AWS console Create Hosted Zone Domain Name example.com Modify your DNS file SOA record Before starting with the next step we need to change the (Start of Authority) record to match the new one. SOA Change: @	IN SOA dns18 . tech . ( ) .ovh .net .ovh .net 2019112215 86400 3600 3600000 300 To the SOA record in your new Hosted Zone. The entry should be now like: @	IN SOA ns awsdns com. awsdns-hostmaster.amazon.com. -289. -36. 1 7200 900 1209600 86400 Import your DNS file into Route 53 Now that we have a fresh hosted zone we'll import the RRs we exported from OVH. Do not import the previously deleted NS , A , and AAAA records! Click on your new Hosted Zone: (you'll see a list of RRs) example.com Click on: Import Zone File Paste your previously exported records DNS Import your records DNS If you get: . Delete the mismatching from the zone file. "Error parsing zone file: One resource cannot have multiple distinct TTL values" TTL From: IN TXT 600 "v=spf1 include:mx.ovh.com ~all" To: TXT IN "v=spf1 include:mx.ovh.com ~all" Add an ALIAS record So far, so good. Now we add an record for the naked domain; pointing to our AWS S3 bucket. A ALIAS example.com It should be like this but  with an S3 bucket URL instead of a CloudFront URL Do the same now with an AAAA record. Add a CNAME record Add a record for your subdomain pointing to your apex domain: . CNAME www example.com It should be like this Get your new NS entries Get the values of your entry. We're going to use them at OVH in the next step. NS They should be like: ns- .
ns- .
ns- .
ns- . 289 .awsdns-36 .com 1715 .awsdns-22 .co .uk 1241 .awsdns-27 .org 740 .awsdns-28 .net Add your new AWS NS values to your domains registrar In your OVH account go to: DNS servers Delete the old OVH records NS Add your new AWS records NS Good to go. Troubleshooting The changes will take some time to propagate (sometimes up to 24h). We can check the state of the DNS (Domain Name Server) update on: Zonemaster MXToolBox DNS Checker If the DNS update is done but you cannot access through your computer, it could be that your ISP (Internet Service Provider) still did not update their RR cache. In this case, you should be able to . example.com access your website through a VPN Thanks for learning with this tutorial. Follow me on GitHub . If for some casual the indications did not work for you; don't mind to drop me a line with the infringing points . I'll update the post correspondingly. References Migrating DNS Migrate DNS Domain in Use How to Resolve Error in AWS Route 53 Import Zone File More Posts Welcome

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