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How did INUC leverage AWS to minimize development time by over 35% and quickly deploy SaaS? INUC Inc. INUC is a B2B media platform software development company that specializes video content management system(CMS) services. INUC’s video CMS solution features live scheduling, VOD archiving, menu organization and management, as well as web interfaces for each type of content that media managers need. INUC provides various editions(templates) for video meeting minutes, in-house broadcasting, and live commerce, so the media managers simply can select the screen they want. The media managers also have the option to choose the appropriate license (Basic/Standard/Enterprise) and cloud service according to each customer's system policy and service scale. Name INUC Inc. Area Software development and supply Estab. Nov, 2010 Site https://sedn.software/ Migration of B2B On-premises Solution to the Cloud Challenges INUC was provided on-premises based solutions; however, with changes in the market and a growing customer demand, the need for cloud adoption became apparent. As their potential customer base expands from public and enterprise to healthcare and commerce, there is a growing demand for cloud services in the form of SaaS, and INUC expects to create opportunities for global expansion. In addition, all INUC’s media services were built on Docker, consisting of containers for API, Streaming Server, Chatting, Web, Storage, etc. The migration to the SaaS model was relatively easy, given the cloud environment was already prepared. Why SmileShark? SmileShark's wide experience and expertise were key attractions. Specifically, SmileShark's solutions and various suggestions during meeting helped INUC makes quick decisions. INUC expected that SmileShark's experience in various Kubernetes deployments and container operations would facilitate the achievemenet of their goal of transforming CMS services into SaaS within a tight time frame. In fact, SmileShark's prompt technical support helped INUC to smoothly migration to the cloud. " I would recommend SmileShark to startups or companies looking to migrate from on-premis solutions to SaaS " -Jason Shin, INUC CEO "Due to the nature of media services, we believe that it is reasonable to have a hybrid form that operates both existing on-premises servers and the cloud from a TCO (total cost of ownership) perspective.", "The cloud-based B2B SaaS model can be thought of as a content store that plans an independent brand," Explained Jason Shin, CEO of INUC, Inc. Safe and Swift Migration of Adopting ECS INUC reliably adopted the Amazon Web Services (AWS) cloud through SmileShark, experiencing flexibility and scalability beyond that of the traditional on-premises model. During the AWS architecture design process, Elastic Load Balancers (ELBs) and multiple availability zones were employed to enhance business continuity and customer satisfaction. Network traffic coming into the ELB is automatically distributed to multiple servers, preventing the load from being concentrated on one server and ensuring that even if a problem occurs in one server, the entire service is not affected. Additionally, by distributing the infrastructure using two or more Availability Zones, INUC can continue operations without service interruption even if a problem occurs in one Availability Zone . To migrate data leakage and security risks, INUC organized its infrastructure with public and private subnets, placing critical data and systems in the private subnet, shielding against external threats. This approach has bolstered customer satisfaction and protected the brand value of INUC in the long run. INUC adopted ECS (Elastic Container Service) to the AWS environment to simplify and enhance the efficiency of deploying, managing, and scaling Docker container-based applications. ECS significantly shortened time to market by streamlining the process of deploying & managing applications and allowing developers to concentrate on develeoping higher-quality service To ensure consistent service during traffic spikes, INUC implemented Auto Scaling Group, dynamically managing resources based on usage. Additionally, INUC set the ECS service type as Replica to maintain a specified number of tasks running continuously, thereby ensuring scalability and resilience of the tasks, and configured it to automatically adjust to workload demands. Managed services such as ElastiCache, Aurora, S3, etc have helped INUC reduce hardware and software maintenance costs, allowing them to focus more on core business activities. INUC established a fast and efficient development process through AWS services. Supported by AWS and SmileShark, developers quickly acquired new skill and developed cloud-optimized solutions, significantly accelerating INUC's technological innovation. Upcoming Development of Intelligent Services Based on STT INUC Next Step INUC is currently improving SEDN v2 with communication and incorporating AI applications based on deep learning algorithms into the cloud. Upcoming intelligent services include video scene analysis based on STT (Speech-to-Text), timestamp extraction highlight generation, and video keyword search. INUC is improving their media user experience(MX) and aims to create business opportunities with more content IP operators and strengthen their global market presence. ※ Click the image above to sign up for the SEDN beta service. Used AWS Services Amazon Elastic Container Service(ECS) Amazon Simple Storage Service(S3) Amazon ElastiCache Amazon Aurora Introduced SmileShark Services SmileShark BuildUp | Accurate infra suggestion / Rapid deployment support SmileShark Migration | SmileShark guides you through the entire migration to AWS SmileShark Tech Support | Get expert guidance and assistance achieving your objectives

AWS Config란? AWS Config는 AWS(Amazon Web Services)에서 제공하는 서비스로 기존 AWS 리소스를 검색하고, 서드 파티 리소스의 구성을 기록하고, 모든 세부 구성 정보가 포함된 리소스의 완전한 인벤토리를 내보내며, 특정 시점의 리소스 구성 방식을 확인할 수 있습니다. 이러한 기능에는 규정 준수 감사, 보안 분석, 리소스 변경 추적 및 문제 해결에 사용할 수 있습니다. 개요 AWS Config는 AWS 계정에 있는 AWS 리소스의 구성을 자세히 보여 줍니다. 자세하게 말씀드리자면 설정을 모니터링하고 해당 설정이 원하는 상태 또는 잠재적 규정 준수 요구 사항에 부합하는지 알려줍니다. 여기에는 리소스가 서로 어떻게 연관되어 있는지, 과거에 어떻게 구성되었는지 등이 포함되어 있어 시간이 지남에 따라 구성과 관계가 어떻게 변하는지 확인할 수 있습니다. AWS Config 작동 방식 AWS Config 기능 AWS Config 설정 시 다음을 완료할 수 있습니다: 리소스 관리 AWS Config에서 기록할 리소스 유형을 지정합니다. 요청 시 구성 스냅샷과 구성 기록을 받도록 Amazon S3 버킷을 설정하세요. 구성 스트림 알림을 보내도록 Amazon SNS를 설정합니다. AWS Config에 Amazon S3 버킷 및 Amazon SNS 주제에 액세스하는 데 필요한 권한을 부여합니다. 규칙 및 규정 준수 팩 AWS Config에서 기록된 리소스 유형에 대한 규정 준수 정보를 평가하는 데 사용할 규칙을 지정합니다. 규정 준수 팩 또는 AWS 계정에서 단일 엔티티로 배포하고 모니터링할 수 있는 AWS Config 규칙 및 수정 작업 모음을 사용합니다. 애그리게이터 애그리게이터를 사용하여 리소스 인벤토리 및 규정 준수에 대한 중앙 집중식 보기가 가능합니다. 애그리게이터는 여러 AWS 계정과 AWS 리전의 AWS Config 구성 및 규정 준수 데이터를 단일 계정과 리전으로 수집하는 AWS Config 리소스 유형입니다. 고급 쿼리 이 기능은 AWS 사용자가 여러 계정과 지역에 걸쳐 있는 리소스의 구성을 효과적으로 관리하고 모니터링할 수 있게 해주는 도구로, 복잡한 쿼리를 사용하여 필요한 정보를 빠르고 정확하게 얻을 수 있습니다. 샘플 쿼리 중 하나를 사용하거나 AWS 리소스의 구성 스키마를 참조하여 직접 쿼리를 작성하세요. AWS Config 사용 방법 AWS에서 애플리케이션을 실행할 때는 일반적으로 AWS 리소스를 사용하게 되는데, 이러한 리소스를 종합적으로 생성하고 관리해야 합니다. 애플리케이션에 대한 수요가 계속 증가함에 따라 AWS 리소스를 추적해야 할 필요성도 커지고 있습니다. AWS Config는 다음 시나리오에서 애플리케이션 리소스를 감독하는 데 도움이 되도록 설계되었습니다: 리소스 관리 리소스 구성에 대한 거버넌스를 강화하고 리소스 구성 오류를 감지하려면, 어떤 리소스가 존재하고 이러한 리소스가 어떻게 구성되는지에 대한 세분화된 가시성을 언제든지 확보해야 합니다. 각 리소스에 대한 호출을 폴링하여 이러한 변경 사항을 모니터링하지 않고도 리소스가 생성, 수정 또는 삭제될 때마다 알림을 받을 수 있도록 AWS Config를 사용할 수 있습니다. AWS 구성 규칙을 사용하여 AWS 리소스의 구성 설정을 평가할 수 있습니다. 리소스가 규칙 중 하나의 조건을 위반하는 것을 AWS 구성에서 감지하면, AWS 구성은 리소스를 비규격으로 플래그 지정하고 알림을 보냅니다. AWS 구성은 리소스가 생성, 변경 또는 삭제될 때 지속적으로 리소스를 평가합니다. 감사 및 규정 준수 AWS Config를 사용하면 리소스 구성 기록에 액세스할 수 있습니다. 구성 변경을 일으킨 AWS CloudTrail 이벤트와 구성 변경 사항을 연결할 수 있습니다. 이 정보를 통해 ‘변경한 사용자’, ‘변경한 IP 주소’ 등의 세부 정보에서 AWS 리소스와 관련 리소스에 대한 변경 결과에 이르기까지 전체적으로 파악할 수 있습니다. 이 정보를 사용하여 시간 경과에 따라 감사 및 규정 준수 평가에 도움이 되는 보고서를 생성할 수 있습니다. 구성 변경 사항 관리 및 문제 해결 서로 의존하는 여러 AWS 리소스를 사용하는 경우, 한 리소스의 구성을 변경하면 관련 리소스에 의도하지 않은 결과가 발생할 수 있습니다. AWS Config를 사용하면 수정하려는 리소스가 다른 리소스와 어떻게 연관되어 있는지 확인하고 변경의 영향을 평가할 수 있습니다. 또한 AWS Config에서 제공하는 리소스의 기록 구성을 사용하여 문제를 해결하고 문제가 있는 리소스의 문제가 없는 가장 최근 버전으로 액세스할 수 있습니다. 보안 분석 잠재적인 보안 취약점을 분석하려면 사용자에게 부여된 AWS IAM 권한 또는 리소스에 대한 액세스를 제어하는 Amazon EC2 보안 그룹 규칙과 같은 AWS 리소스 구성에 대한 자세한 기록 정보가 필요합니다. AWS Config가 기록되는 동안 언제든지 AWS Config를 사용하여 사용자, 그룹 또는 역할에 할당된 IAM 정책을 볼 수 있습니다. 이 정보를 통해 특정 시점에 사용자에게 부여된 권한을 확인할 수 있습니다. 또한 AWS Config를 사용하여 특정 시점에 열려 있던 포트 규칙을 포함한 EC2 보안 그룹의 구성을 볼 수 있습니다. 이 정보를 통해 보안 그룹이 특정 포트로 들어오는 TCP 트래픽을 차단했는지 여부를 확인할 수 있습니다. 관련 링크 AWS Config Features

AWS Lambda의 모든 것: 초보자를 위한 완벽한 가이드 2/2 - Console에서 람다 함수 생성, 트리거 설정 및 요금 계산 Written by Hyojung Yoon Hello! Today, we will continue to delve deeper into AWS Lambda. Especially in this part, we will practice creating Lambda functions and setting Lambda triggers using the AWS Console. We will also understand the pricing policy of AWS Lambda and learn how to calculate actual costs. Let’s begin! Start AWS Lambda Creating Lambda Functions in the Console Writing Lambda Function Code Configuring Lambda Functions Executing Lambda Runctions Setting Lambda Trigger Lambda Trigger + S3 AWS Lambda Pricing Lambda Pricing Policy Calculating Lambda Prices Interpreting Lambda Pricing Calculation Conclusion Start AWS Lambda 1. Creating Lambda Functions in the Console You can create your first function using the AWS Console. Select Lambda within the AWS Console. Press the [ Create function ] button to create a Lambda function. You will be presented with three options at the top. Create from scratch : Start building a function from the ground up Use a blueprint : Utilize AWS-provided templates that can be customized with sample code. Container image : Specifically for Docker containers. After making your selection, add a new function name and choose the desired runtime ¹ . ¹Runtime : Options for the programming language you want to write your Lambda in, such as Node.js, Python, Go, etc. Permissions specify the rights that will be granted to the Lambda function. Click [ Change default execution role ] to create a new role with the standard Lambda permissions. 2. Writing Lambda Function Code Review the function you created, here named hjLambda . Scroll down to the function code section. Here, you can select a template or design your own. Configuring Lambda Functions myHandler = The name of the Lambda function Lambda executes this handler method when the function is invoked, passing three arguments: event, context, and callback." event : Contains information from the caller, with all details about the event that triggered Lambda. context : Contains information about indirect calls to the Lambda function, the execution environment, and runtime. callback : Needed to send asynchronous responses, calling the callback function with results (or errors) after all operations inside the Lambda function are done, which AWS then processes as a response to the HTTP request. 3. Executing Lambda Functions Before running the Lambda function, we will first perform a test. Select [ Configure test events ] from the test dropdown menu, which opens a code editor for test event configuration. Select create new event, and enter an event name like MyEvent . Keep the event visibility settings private as default. From the template list, select hello-world and then click [ Save ] . Click the [ Test ] button and check the console for successful execution. In the execution result tab, confirm if the execution was successful. The function log section displays logs created by the Lambda function execution and key information reported in the log output. If the test went well, click the [ Deploy ] button to make it executable. 4. Setting Lambda Trigger 1) Lambda Trigger + S3 We will implement logic using an AWS Lambda function to copy files from one Amazon S3 bucket to another. ※ Cf: How can I use a Lambda function to copy files from one Amazon S3 bucket to another? Step 1: Create the source and destination Amazon S3 buckets. Open the Amazon S3 console and select create bucket. Create both the source and destination buckets. Here, the name of the source bucket is set to [ hjtestbucket ] and the destination bucket to [ hjtestbucket02 ] . Step 2: Create a Lambda Function Open the functions page in the Lambda console and create a function . Select the runtime dropdown and choose Python 3.9 , then create a Lambda function like the one shown in the picture. Select the code tab and paste the following JSON code. import boto3 import botocore import json import os import logging logger = logging.getLogger() logger.setLevel(logging.INFO) s3 = boto3.resource('s3') def lambda_handler(event, context): logger.info("New files uploaded to the source bucket.") key = event['Records'][0]['s3']['object']['key'] source_bucket = event['Records'][0]['s3']['bucket']['name'] destination_bucket = "destination_bucket" source = {'Bucket': source_bucket, 'Key': key} try: response = s3.meta.client.copy(source, destination_bucket, key) logger.info("File copied to the destination bucket successfully!") except botocore.exceptions.ClientError as error: logger.error("There was an error copying the file to the destination bucket") print('Error Message: {}'.format(error)) except botocore.exceptions.ParamValidationError as error: logger.error("Missing required parameters while calling the API.") print('Error Message: {}'.format(error)) After pasting the code, select [ Deploy ] . Step 3: Create an Amazon S3 Trigger for the Lambda Function Open the function page in the Lambda console and select [ Add trigger ] from the function overview. Select S3 from the trigger configuration dropdown. Enter the name of the source bucket and select All object create events for the event type. Acknowledge that using the same S3 bucket for both input and output is not recommended, then select Add. Step 4: Provide AWS IAM Permissions for the Lambda Function's Execution Role Like the following resource-based policy, add IAM permissions to the Lambda function's execution role to copy files to the destination S3 bucket. Open the functions page in the Lambda console and click the role name under configuration - execution role . In the IAM console, select [ Add permissions ] and then [ Create inline policy ]. Choose the [ JSON ] option and paste the JSON policy document below. ※ Note Replace destination-s3-bucket with your S3 destination bucket and source-s3-bucket with your S3 source bucket. Change the /* at the end of the resource ARN to the prefix value needed for your environment to restrict permissions. It is best to grant only the minimum permissions necessary to perform the action. For more details, refer to Granting least privilege. { "Version": "2012-10-17", "Statement": [ { "Sid": "putObject", "Effect": "Allow", "Action": [ "s3:PutObject" ], "Resource": [ "arn:aws:s3:::destination-s3-bucket/*" ] }, { "Sid": "getObject", "Effect": "Allow", "Action": [ "s3:GetObject" ], "Resource": [ "arn:aws:s3:::source-s3-bucket/*" ] } ] } Select [ Create policy ] to save the new policy. Step 5: Check if the Lambda Function is Executing Properly Now, to check if the Lambda trigger is working correctly, upload a file to the original S3 bucket. Click [ Upload ] and check the upload status. Go into the destination S3 bucket and verify that the file has been copied. If the same file is stored, you can tell the function is working properly. AWS Lambda Pricing 1. Lambda Pricing Policy Lambda costs are determined by three main factors: the number of requests, execution time, and memory size. Lambda offers 1 million free requests and 400,000 GB-seconds of free computing time per month, which allows small projects or those in the testing phase to use Lambda without additional costs. Free Tier Usage Limits Request Count 1 million requests free per month Computing Time 400,000GB-seconds free per month Storage First 512MB(0.5G) free of charge 2. Calculating Lambda Prices You can easily calculate Lambda prices using the AWS pricing calculator website. Let's calculate the AWS Lambda fees for 3,000,000 executions per month, each running for 1 second, with 512MB of memory (0.5 GB). Scroll down to [ Show Details ] to see how the pricing is determined. ※ Interpreting Lambda Pricing Calculation Here is the interpretation of the above calculation. Total Usage(GB-sec) = 3,000,000 x 1 x 0.5 = 1,500,000 GB-sec Subtracting the free tier allowance of 400,000 GB-seconds, Payable Usage(GB-sec) = 3,000,000 x 1 x 0.5 = 1,500,000 GB-sec The cost of GB-seconds for AWS Lambda is $0.0000166667 per GB-second. Execution Time Cost = 1,100,000 x 0,0000166667 = $18.33 After excluding the free tier of 1,000,000 requests, Payable Usage(Request Count) = 3,000,000 - 1,000,000 = 2,000,000 The cost per request is $0.20 per million, with 2,000,000 executions per month. Request Cost = 2,000,000/1,000,000 x 0.20 = $0.40 Temporary storage allows each Lambda function to use 512MB (=0.5GB) of storage at no additional cost. Additional Storage Cost = 0.5GB - 0.5GB = 0.00 Therefore, the total cost considering the free tier is about $18.73. Total = $0.40(Request Cost) + $18.33(Execution Time Cost) = $18.73 This calculation only considers the base costs, so additional costs may occur. Prices are subject to change, so it's best to check the latest information on the AWS official website. Conclusion Through this guide, you have learned how to create Lambda functions in the AWS console. Additionally, this series has introduced you to Lambda’s pricing policy and calculation methods, providing you with the basic steps needed to apply this knowledge to real business scenarios. I hope this experience will be beneficial as you design a variety of cloud services utilizing AWS Lambda. Links Copy S3 files to another S3 bucket with Lambda function | AWS re:Post Invoking Lambda functions - AWS Lambda Serverless Computing - AWS Lambda Pricing - Amazon Web Services

Are AWS Certifications worth it? : AWS Solutions Architect - Professional (SAP) Certification 1 Written by Minhyeok Cha Today, I've organized the AWS Solution Architect - Professional (SAP) certification exam questions in terms of real-world console or architectural structures. Question 1. A company needs to design a hybrid DNS solution. This solution uses Amazon Route 53 private hosting zones for the cloud.example.com domain for resources stored in VPC. The company has the following DNS resolution requirements: On-premises systems must be able to resolve and connect to cloud.example.com. All VPCs should be able to resolve cloud.example.com. There is already an AWS Direct Connect connection between the on-premises corporate network and the AWS Transit Gateway. What architecture should the company use to meet these requirements with the best performance? ⓐ Connect the private hosting zone to all VPCs. Create a Route 53 inbound resolver in a shared services VPC. Connect all VPCs to the transit gateway and create forwarding rules on the on-premises DNS server for cloud.example.com pointing to the inbound resolver. ⓑ Connect the private hosting zone to all VPCs. Deploy Amazon EC2 conditional forwarders in a shared services VPC. Connect all VPCs to the transit gateway and create forwarding rules on the on-premises DNS server for cloud.example.com pointing to the conditional forwarder. ⓒ Connect the private hosting zone to the shared services VPC. Create a Route 53 outbound resolver in the shared services VPC. Connect all VPCs to the transit gateway and create forwarding rules on the on-premises DNS server for cloud.example.com pointing to the outbound resolver. ⓓ Connect the private hosting zone to the shared services VPC. Create a Route 53 inbound resolver in the shared services VPC. Connect the shared services VPC to the transit gateway and create forwarding rules on the on-premises DNS server for cloud.example.com pointing to the inbound resolver. Solutions The key to this question is how to centrally manage DNS for a hybrid cloud using AWS services. Combining the company's requirements, the answer is A. Let's examine this one by one. Answer: A Breaking down the DNS requirements in the question: First, connecting the private hosting zone to all VPCs is configured as follows This setting allows traffic routing by directly connecting the private hosting to VPCs. As seen in the blue box, to use this function, you need to set enableDnsHostnames and enableDnsSupport to true in VPC settings. Second, establish a connection to the inbound resolver endpoint's IP address via Direct Connect or VPN . This allows on-premises to resolve and connect to cloud.example.com. Assuming DX and VPN are set up, implementing the Route 53 resolver's endpoint results in the following architecture. Using this architecture, you can create inbound and outbound endpoints (specified for VPCs) and create a VPC Route53 private hosting zone for the designated endpoints using the first method. By completing this task, you can verify that all VPCs (though they need to be specified separately ) and on-premises can resolve the domain through the AWS Transit Gateway and DX ( or VPN ). ※ cf. You can simply check the connected domain using the following command. Use the telnet command for port 53 connection confirmation between the inbound endpoint resolver IP address: telnet 53 . To check the validity of domain resolution, complete a domain name lookup from the on-premises DNS server or local host. For Windows: nslookup For Linux or macOS: dig If the previous command fails to return records, you can bypass the on-premises DNS server. Use the following command to send a DNS query directly to the inbound resolver endpoint IP address. For Windows: nslookup @ For Linux or macOS: dig @ Question 2 A company provides weather data to multiple customers through a REST-based API. The API is hosted in Amazon API Gateway and integrates with various AWS Lambda functions for each API operation. The company uses Amazon Route 53 for DNS and has created a resource record for Weather.example.com. The company stores data for the API in an Amazon DynamoDB table. The company needs a solution to provide failover capability for the API to another AWS region. Which solution meets these requirements? ⓐ Deploy a new set of Lambda functions in a new region. Update the API Gateway API to use an edge-optimized API endpoint targeting Lambda functions in both regions. Convert the DynamoDB table into a global table. ⓑ Deploy a new API Gateway API and Lambda functions in a different region. Change the Route 53 DNS record to multi-value answer. Add both API Gateway APIs to the response. Enable health check monitoring. Convert the DynamoDB table into a global table. ⓒ Deploy a new API Gateway API and Lambda functions in a different region. Change the Route 53 DNS record to a failover record. Enable health check monitoring. Convert the DynamoDB table into a global table. ⓓ Deploy a new API Gateway API in a new region. Change Lambda functions to global functions. Change the Route 53 DNS record to multi-value answer. Add both API Gateway APIs to the response. Enable health check monitoring. Convert the DynamoDB table into a global table. Solutions Question 2 involves frequently used AWS services in combination: API Gateway - Lambda - DynamoDB, with the DNS using Route 53 service records. This question seeks a combination that can handle failover to another region in case of an API outage. Many might think the answer is C, focusing solely on the “Change the Route 53 DNS record to a failover record” option. However, surprisingly, the answer is indeed C. Answer: C For DNS usage, if there's an outage, the following configuration is necessary for managing failover to another region : Create API resources in the main region (domain). Create API resources in the sub-region (domain). Map the created APIs to a custom domain. Create a Route 53 DNS failover record. Additionally, continue reading the problem, you’ll find health monitoring activation and DynamoDB global table. Completing these steps results in the following architecture. This problem mainly requires building a solution for disaster recovery, but this time we will also solve the API design. 1. Create APIs for both main and sub-regions. (Configure separate regions) It’s easy to create an API Gateway, but we need a domain name. AWS API G/W has a custom domain creation feature. It’s easy to make, but note that a TLS, i.e., ACM certificate, is required. Perform the same task in the sub-region as well. 2. Create a Route 53 health check. First, use the domain of the API in the main region created above. This step involves setting up an alarm to switch to the sub-region in case of an outage. 3. Routing Policy - Configure failover. You need to know that there are various record policy methods in Route 53. Among various policies, we need to check the failover method. Add records using primary (main region) and secondary (sub-region) in the main region - each created API domain - record type. 4. DynamoDB Global table There is a separate section for creating global table replicas, so it’s easy to find. Conclusion I hope the problems solved today help you with your certification preparation. Look forward to more in-depth problem explanations and key strategies in the next post!

What is Amazon Lightsail : EC2 vs Lightsail comparison written by Hyojung Yoon Hello everyone. Today, let's take some time to explore Amazon's cloud service called Lightsail. Understanding both Amazon Lightsail and Amazon EC2, two key cloud computing services, is essential. These two services are part of AWS's major cloud solutions, each with its unique features and advantages. In this post, we'll delve into each service, especially focusing on the key features of Amazon Lightsail and when it's suitable. So, let's dive right in! What is Amazon Lightsail? Amazon Lightsail What is a VPS? Components ofLightsail Features of Lightsail Advantages of Lightsail Disadvantages of Lightsail EC2 vs Lightsail Differences between Amazon Lightsail and EC2 Which one should you use? Conclusion What is Amazon Lightsail? 1. Amazon Lightsail Amazon Lightsail is a Virtual Private Server(VPS)created by AWS. It includes everything you need to quickly launch your project, such as instances, container services, managed databases, CDN distribution , load balancers , SSD-based block storage, static IP addresses, DNS management for registered domains, and resource snapshots (backups), and more. It's specialized in making it easy and fast to build websites or web applications. 2. What is a VPS? A VPS stands for Virtual Private Server, which means taking a physical server and dividing it into multiple virtual servers. These segmented virtual servers are shared among various clients. While you share a physical server with others, each clients has its private server space. However, since everyone shares computing resources on one server, a user monopolizing too many resources can affect others in terms of RAM, CPU, etc. 3. Components of Lightsail Instances Containers Databases Networking Static IP Load Balancer(ELB) Deployment(CDN) DNS Zone : Domain & Sub-domain management Storage(S3, EBS) : Additional capacity available if instances run out of space Snapshots(AMI) : Scheduled for automatic backups Features of Lightsail 1. Advantages of Lightsail AWS Lightsail allows for intuitive instance creation, which is less complex than EC2 . With pre-configured bundles, users can swiftly deploy applications, websites, and development environments without a deep understanding of cloud architecture. Its user-friendly interface allows easy creation of containers, storage, and databases. This makes it ideal for beginners and smaller projects. 2. Disadvantages of Lightsail However, the advantages mentioned above can become limitations of Lightsail. It may not be suitable for applications expecting rapid increases in traffic or resource demands, and pre-configured bundles can limit detailed settings. Additionally, integrating with other AWS services may require migration. Other limitations include: Up to 20 instances per account 5 fixed IP addresses per account Up to 6 DNS zones per account Total 20TB block storage (disks) attachment 5 load balancers per account Up to 20 certificates EC2 vs Lightsail ​ Amazon Lightsail Amazon EC2 Pricing Fixed monthly price including all necessary features Pay-as-you-go pricing based on actual usage Instance Type Pre-configured instance types Customizable instances depending on the need Ease of Use Quick start with Lightsail's simple console (fewer settings required) Requires more setup and configurations, with a more complex dashboard Server Management Managed service with less effort Full control with more detailed management Networking Integrated with AWS Customizable with VPC and advanced networking settings Scalability Basic scalability Advanced auto scaling for greater flexibility Monitoring Lightsail monitoring included More detailed monitoring with CloudWatch Storage Type High-performance SSD-based storage Various storage options, including EBS Access Control Simpler user access management More detailed access control with IAM Backup Included AWS automatic backup, with some retention period Advanced AWS backup solutions with more options 1. Differences Between Amazon Lightsail and EC2 1) Cost Generally, Amazon Lightsail is cheaper. At 2GB memory, it charges $10, inclusive of 60GB SSD EBS volume and traffic costs. In contrast, EC2 charges $11.37 for a 3-year commitment (without upfront payment) for t3.small with 60GB EBS. Here, traffic costs are extra. Therefore, Lightsail is more economical for continuous usage. However, if you only use EC2 for the necessary time, it might be cost-effective. EC2 charges are based on actual usage, making it a more flexible option for cost management. 2) Features While EC2 offers more advanced features not available in Lightsail, it may lack some detailed options. Features not available in Lightsail include: Limited VPC -related functions Instance type changes Scheduled snapshot creation Detailed security group settings IAM role assignment Various load balancer options 2. Which one should you use? 1) Amazon EC2(Elastic Compute Cloud) Powerful and flexible cloud computing platform offered by AWS Customizable on-demand computing performance for all application needs Scalable resources for anything from websites to high-performance scientific simulations Seamlessly integrates with other AWS services Ideal for businesses with infrastructure managers capable of managing virtual servers, networks, security groups, etc. It's particularly beneficial for CPU-intensive operations and on-demand functionalities, allowing for efficient cost management. 2) Amazon Lightsail Simplifies the cloud experience Offers virtual servers, storage, and networking in easy-to-understand packages Ideal for simpler applications like personal websites, blogs, or small web apps Fixed pricing model simplifies budgeting Ideal for individuals looking for swift web service hosting without dedicated infrastructure management. It's more suitable for services emphasizing network traffic rather than CPU-intensive tasks. Conclusion Understanding the differences between Amazon EC2 and Lightsail is the first step toward harnessing cloud computing. EC2 offers high scalability and customization, while Lightsail provides a simple and intuitive cloud experience. By selecting the most appropriate service based on your requirements, technical expertise, and project complexity, you can ensure success in the digital landscape. Both have unique advantages, so choose according to your needs and expertise. So, enjoy your cloud surfing! ⛵⛵ Links Virtual Private Server and Web Hosting-Amazon Lightsail-Amazon Web Services Virtual Private Server and Web Hosting - Amazon Lightsail FAQs - Amazon Web Services

Written by Hyojung Yoon Hello, everyone! Today, we will delve into the fascinating world of Load Balancers and Load Balancing – pivotal technologies that make the world smarter by enabling web services to maintain stability, even in high traffic situations, especially in cloud environments like AWS. These technologies enhance the service's performance, stability, and scalability. Let’s begin our journey through the basic concepts of Load Balancers and Load Balancing to the types of AWS Load Balancers in this blog. What is a Load Balancer Load Balancer Scale Up and Scale Out What is a Load Balancing Load Balancing Benefits of Load Balancing Load Balancing Algorithms Static Load Balancing Round Robin Method Weighted Round Robin Method IP Hash Method Dynamic Load Balancing Least Connection Method Least Response Time Method Types of AWS Load Balancer ALB(Application Load Balancer) NLB(Network Load Balancer) ELB(Elastic Load Balancer) Conclusion What is a Load Balacer? 1. Load Balancer Load Balancers sit between the client and a group of servers, distributing traffic evenly across multiple servers and thereby mitigating the load on any particular server. When there is excessive traffic to a single server, it may not handle the load, leading to downtime. To address this issue, either a Scale Up or Scale Out approach is employed. 2. Scale Up and Scale Out Scale Up improves the existing server's performance, including tasks like upgrading CPU or memory, while Scale Out distributes traffic or workload across multiple computers or servers. Each method has its advantages and disadvantages, and choosing the more appropriate one is crucial. ​ Scale Up Scale Out Scalability Has limits in performance expansion Continuous expasion is possible Server Cost Cost increases significantly with performance upgrade. Generally, more cost-effective Operational Cost No significant change with scale up Increase as the number of servers increase Failover Single point of failure Lower possibility of total failure due to distributed load In the case of Scale Out , Load Balancing is essential to evenly distribute the load among multiple servers. The primary purpose of Load Balancing is to prevent any single server from being overwhelmed by distributing incoming web traffic across multiple servers, thus enhancing server performance and stability. What is a Load Balancing? 1. Load Balancing Load Balancing refers to the technology that distributes tasks evenly across multiple servers or computing resources, preventing service interruption due to excessive traffic and ensuring tasks are processed without delay. 2. Benefits of Load Balancing 1) Application Availability Server failures or maintenance can increase application downtime, rendering the application unusable for visitors. A load balancer automatically detects server issues and redirects client traffic to available servers, enhancing system fault tolerance. With load balancing, it is more manageable to: Undertake application server maintenance or upgrades without application downtime Facilitate automatic disaster recovery to your backup site Conduct health checks and circumvent issues leading to downtime 2) Application Scalability A load balancer can intelligently route network traffic between multiple servers. This allows your application to accommodate thousands of client requests, enabling you to: Circumvent traffic bottlenecks on individual servers Gauge application traffic to adaptively add or remove servers as required Integrate redundancy into your system for coordinated and worry-free operation 3) Application Security Load balancers, equipped with inbuilt security features, add an extra security layer to your Internet applications. They are invaluable for managing distributed denial-of-service attacks, where an attacker overwhelms an application server with concurrent requests, causing server failure. Additionally, a load balancer can: Monitor traffic and block malicious content Reduce impact by dispersing attack traffic across multiple backend servers Direct traffic through network firewall groups for reinforced security 4) Application Performance Load balancers enhance application performance by optimizing response times and minimizing network latency. They facilitate several crucial tasks to: Elevate application performance by equalizing load across servers Lower latency by routing client requests to proximate servers Guarantee reliability and performance of both physical and virtual computing resources Load Balancing Algorithms Various algorithms, such as Round Robin, Weighted Distribution, and Least Connections, are employed for load balancing, each serving different purposes and scenarios. 1. Static Load Balancing 1)Round Robin Method This method systematically allocates client requests across servers. It is apt when servers share identical specifications and the connections (sessions) with the server are transient. Example: For servers A, B, and C, the rotation order is A → B → C → A. 2) Weighted Round Robin Method This assigns weights to each server and prioritizes the server with the highest weight. When servers have varied specifications, this method increases traffic throughput by assigning higher weights to superior servers. Example: Server A's weight=8; Server B's weight=2; Server C's weight=3. Hence, 8 requests are assigned to Server A, 2 to Server B, and 3 to Server C. 3) IP Hash Method Here, the load balancer hashes the client IP address, converting IP addresses to numbers and mapping them to distinct servers. This method assures users are consistently directed to the same server. 2. Dynamic Load Balancing 1) Least Connection Method This method directs traffic to the server with the fewest active connections, presuming each connection demands identical processing power across all servers. 2) Least Response Time Method This considers both the current connection status and server response time, steering traffic to the server with the minimal response time. It is suitable when servers have disparate available resources, performance levels, and processing data volumes. If a server adequately meets the criteria, it is prioritized over a server that is unoccupied. This algorithm is employed by the load balancer to ensure prompt service for all users. Types of AWS Load Balancer 1. ALB(Application Load Balancer) Complex modern applications often operate on server farms, each composed of multiple servers assigned to specific application functions. An Application Load Balancer (ALB) redirects traffic after examining the request content, such as HTTP headers or SSL session IDs. For instance, an e-commerce application, possessing features like a product directory, shopping cart, and checkout functionality, when coupled with an ALB, dispenses content like images and videos without necessitating sustained user connection. When a user searches for a product, the ALB directs the search request to a server where maintaining user connection is not mandatory. Conversely, the shopping cart, which necessitates the maintenance of multiple client connections, transmits the request to a server capable of long-term data storage. It facilitates application-level load balancing, apt for HTTP/HTTPS traffic. It supports L7-based load balancers and can enforce SSL. 2. NLB(Network Load Balancer) A Network Load Balancer (NLB) operates by analyzing IP addresses and various network data to efficiently direct traffic. It allows you to trace the origin of your application traffic and allocate static IP addresses to multiple servers. The NLB uses both static and dynamic load balancing methods to distribute server load effectively. It’s an ideal solution for scenarios demanding high performance, capable of managing millions of requests per second while maintaining low latency. It’s especially adept at handling abrupt increases and fluctuations in traffic, making it particularly useful for real-time streaming services, video conferencing, and chat applications where establishing and maintaining a smart, optimized connection is crucial. In such cases, utilizing an NLB ensures effective management of connections and maintenance of session persistence. It conducts network-level load balancing, suitable for TCP/UDP traffic. It supports L4-based load balancers. 3. ELB(Elastic Load Balancer) Elastic Load Balancer (ELB) automatically allocates incoming traffic amongst various targets like EC2 instance containers and IP addresses across multiple Availability Zones. With ELB, the load on both L4 and L7 can be controlled. Should the primary address of your server alter, a new load balancer must be created and a target group must be assigned to a singular address, making the process more complex and cost-intensive with the increase in targets. It accommodates the four types of load balancers provided by AWS. It extends substantial scalability and adaptability to cater to diverse needs and environments. Conclusion We have delved into the intricate domains of load balancers and load balancing, recognizing the indispensable role a load balancer plays in moderating website and application traffic and allocating server load to bolster service performance and stability. Particularly within cloud environments like AWS, a plethora of load balancing options and functionalities are available, allowing the implementation of the most suited solution for your services and applications. Such technological advancements empower us to offer quicker and more reliable services, culminating in enhanced user experience and customer contentment, thus forging the path to business success. Links What is a Load Balancing? - Load Balancing Algorithm Explained - AWS Load Balancer - Amazon Elastic Load Balancer (ELB) - AWS What is an Application Load Balancer? - Elastic Load Balancing What is a Network Load Balancer? - Elastic Load Balancing What is an Elastic Load Balanceing? - Elastic Load Balancing

Written by Hyojung Yoon You may be wondering how much it will cost you to move to the AWS cloud, or you may be hesitant to move to the cloud because you're afraid you'll make a mistake and end up paying more. Well, listen up, because we've got the answer to all of your worries. Over the next 10 minutes, I'm going to show you how to estimate your AWS costs with the AWS Cost Calculator, which will help you estimate your AWS costs. First, let's take a quick look at AWS's pricing model, and then we'll show you how to calculate your costs, so let's get started! Benefits and Features AWS Pricing Model On-Demand Reserved Instances Spot Instances Savings Plans How to use AWS Pricing Calculator AWS Pricing Calculator Q&A Ways to save money on AWS Conclusion 1. Benefits and Features 1) Transparent pricing See the math behind the price for your service configurations. View prices per service or per group of services to analyze your architecture costs. 2) Share your estimate Save each estimate's unique link to share or revisit directly through your browser. Estimates are saved to AWS public servers. 3) Hierarchical estimates See and analyze service costs grouped by different parts of your architecture. 4) Estimate exports Export your estimate to a .csv, .pdf and .json file to quickly share and analyze your proposed architecture spend. 2. AWS Pricing Models 1) On-Demand The most basic pricing option, you pay for what you use. Users use it when they need it and are only charged for what they use, making your business more elastic. Choose this if you're primarily using resources on a temporary basis or for testing purposes. 📌Pros: Great for unpredictable workloads, flexible resource management 📌Cons: Most expensive pricing option, costs can add up quickly 2) Reserved Instances (RIs) Reserved Instances, also known as RIs, are an option to pay for capacity upfront and receive a discount by committing to use it for one or three years. When you reserve an instance, you pay the committed amount regardless of usage, and of the three payment options, the full upfront payment results in a larger discount. With discounts of up to 75% off the same on-demand capacity, reserved instances are available for EC2, RDS, and ElastiCache. 📌Pros: Cost savings, easier to set up and maintain than spot instances. 📌Cons: You pay for reserved capacity regardless of usage, and RI can be difficult to manage if you have a lot of instances, so many companies use AWS partners to manage their RIs. (If you reserve 100 instances through RI, but only use 70 due to service scaling or other reasons, you'll still have to pay for 100 instances for the duration of your contract) 3) Spot Instances AWS reserves more resources than customers need, so there is always spare compute capacity available. Users can purchase these extra instances at a discounted hourly rate with no prior commitment, which can be as much as 90% off. However, this method is less secure, and when the total number of EC2 instances runs out, the spot instances in use will be terminated. Therefore, it is recommended to use it for the purpose of performing specific operations instead of hosting a database or server. 📌Pros: Maximum cost savings, and the extra computer capacity will allow you to scale quickly. 📌Cons: Very unreliable as instances can be terminated at any time (but you will be warned 2 minutes before the instance is terminated) 4) Savings Plans (SP) A model that allows you to reduce your payment by up to 72% compared to the on-demand price. You'll commit for 1 or 3 years based on your hourly usage. You'll stay within your commitment, regardless of instance class or size, and if you go over your commitment, you'll be charged the on-demand rate. 📌Pros: You can get benefits of flexibility and convenience, regardless of instance class or size. 📌Cons: You have to pay a fixed amount regardless of usage, and you can't cancel, refund, or change after purchase. ※ LifeHack: It is pretty much impossible to refund or change RI or SP after purchase, so we strongly recommend you to purchase very carefully. 3. How to use AWS Pricing Calculator 1) Create estimate You can change the language setting in the top right corner, and the [Create estimate] Button shows you how to calculate your costs. 2) Add Services Search and add AWS services that you need. In this case, we'll calculate the cost of Amazon EC2, the most common AWS service. 3) Configure Services ① Choose a Region AWS has slightly different costs for each region, so choose the region where your service will be deployed. ※ It's a good idea to write a description (ex : dev_ if this is a development server) because it's convenient to see a summary of estimated costs later. ② Configure Specifications Choose the one that fits your operating system. Let's use Linux as an example, as it's the most popular. Let's arbitrarily put in that we're using 2 instances and calculate. ③ Choose an Instance Type Next, choose an instance type. We'll choose t3.medium, which is the most popular type. ④ Select a Pricing Option The pricing option is set to Savings Plan by default, so we'll change it to On-Demand. ⑤ Amazon EBS Select General Purpose SSD (gp3) from Amazon EBS. General-purpose SSD (gp3) is the most recent version and is less expensive than gp2. IOPS and throughput are set to the default values of 3000 and 125, and the storage size is arbitrary. For this article, we set it to 100 GB. When you select [Save and view summary] , you can see the estimated cost of the service, as shown below. In my estimate, you can see the upfront cost, monthly cost, and 12-month cost. If you are using multiple services together, you can add additional services such as EC2, ELB, etc. to be included in the service through the [Add Service] button. 4) Export My Estimate You can save it as a CSV or PDF file, or you can share it via the [Share] button with a URL, just like you would a saved estimate form. Another option is to save the estimate file before the service. 4. AWS Pricing Calculator Q&A Q1: Why is my estimate different than my actual bill? A1: The AWS Pricing Calculator estimates service costs based on a normalized monthly time frame. The Calculator assumes there are 730 hours in a month ((365 days * 24 hours) / 12 months in a year), which may be less or more than the actual hours in the current billing period. For e­xample, if you use an On-Demand EC2 instance that costs 0.10 USD an hour, you will see the following variances in pricing between your estimated cost and your actual monthly costs: Monthly cost estimated by the AWS Pricing Calculator: 730 hours x 0.10 USD = 73.00 USD Actual cost in February of a non-leap year: 28 days x 24 hours x 0.10 USD = 67.20 USD Actual cost in February of a leap year: 29 days x 24 hours x 0.10 USD = 69.60 USD Actual cost in November: 30 days x 24 hours x 0.10 USD = 72.00 USD Actual cost in October: 31 days x 24 hours x 0.10 USD = 74.40 USD If you use the same On-Demand EC2 instance for a year, your estimated and actual costs are the same: 12-month total cost estimated by the AWS Pricing Calculator: 730 hours x 12 months x 0.10 USD = 876.00 USD Actual total hours a non-leap year: 8760 hours x 0.10 USD = 876.00 USD Q2. If I purchased EC2 RI with the full upfront payment option, why do I still have monthly payments? A2. This is due to Amazon EBS. Amazon EBS is a service that provides block-level storage volumes that can be used with EC2 instances. EBS is not eligible for RI, so even if you pay for the full EC2 RI upfront, you will still have monthly payments for EBS. 5. AWS Cost Optimization with SmileShark You can easily optimize your AWS cost with SmileShark. ▶ Talk to SmileShark sales experts: https://www.smileshark.kr/contact?lang=en ▶ Learn about SmileShark's CloudOps service: https://www.smileshark.kr/cloudops?lang=en ▶ How to lower AWS cost through SmileShark: https://www.smileshark.kr/post/case-study-opensurvey-aws-migration-en?lang=en Conclusion In this blog, we've discussed AWS's pricing model and cost calculator, and we hope you'll use the AWS Pricing Calculator to help you estimate your costs, one of the most important factors in your AWS cloud journey. Links AWS Pricing Calculator Amazon EC2 Spot - Save up-to 90% on On-Demand Prices Reserved Instances Cloud Cost Savings - Savings Plans - Amazon Web Services Calculator FAQ

Written by Hyojung Yoon Hello! Today, we're going to learn about fundamental building blocks of AWS and other cloud platforms: the VPC. In this guide, you'll learn what a private cloud is, how it works, and why it's such an important part of your cloud environment. So let's get started with our comprehensive guide to VPCs! What is a VPC? What is a Private Cloud? What is Amazon VPC? Components of a VPC Subnets Routing tables Internet gateways and NAT gateways Network Access and Security Groups Benefits of Using a VPC VPCs and other cloud models Conclusion What is a VPC? What is a Private Cloud? A private cloud is a cloud computing environment dedicated to a single organization. Any cloud infrastructure has underlying compute resources like CPU and storage that you provision on demand through a self-service portal. In a private cloud, all resources are isolated and in the control of one organization. So, the private cloud is also called the internal or corporate cloud. What is Amazon VPC? A Virtual Private Cloud (VPC) is a private network space dedicated to a customer that is logically independent. If that sounds too difficult, let's imagine a large apartment complex as an AWS cloud environment . The apartment complex has a huge amount of land and in addition to apartments, it has tons of facilities such as common areas, gyms, and swimming pools. Now imagine that within this large complex, you have a penthouse for yourself. The penthouse has everything you need - a living room, bedroom, kitchen, and even a private terrace - and no one else can enter or use it without your permission. This penthouse in an apartment complex is a good representation of a VPC in the AWS cloud . A VPC is a secure, dedicated space where you can work digitally out of reach of others. A penthouse (VPC) in an apartment complex (AWS cloud) has its own unique characteristics. It's separate from the rest of the apartments, and it offers a high level of security and control, allowing you to control who is in and out of your home and when. When you live in an apartment, there are basic rules to follow, and residents are free to act within those rules. You can add and rearrange furniture in your own home as needed, but you can't bring exercise equipment from the gym, which is a common area within the apartment complex, into your own home. This is similar to how a VPC works. AWS gives you a designated space in the cloud, and you can configure it however you want within set rules. The difference is that with a VPC, you can request more resources as you need them, and if approved, they become part of your VPC. Components of a VPCs 1. Subnet A subnet is a small network that one network is divided into. Each subnet is assigned a range of IP addresses and can have its own policies for controlling network traffic. This allows you to divide your VPC into separate sections with specific purposes, such as hosting web servers or database servers. Within a VPC, you can create multiple subnets, each of which must exist within one Available Zone (AZ) and cannot extend across multiple zones. Launching AWS resources in separate Availability Zones protects your applications from failures in a single Availability Zone. A public subnet is a public network that is open to the outside world and can communicate directly with the rest of the Internet. A private subnet is not directly accessible from the outside and only allow one-way communication from inside to outside using a NAT gateway. 2. Routing tables and routers A routing table contains a set of rules called routes that determine where network traffic on a subnet or gateway is sent. Each subnet in a VPC must be associated with a routing table. Unless you set it up otherwise, it is associated with the VPC's default routing table. You can modify the routing table, create custom routing tables, and associate them with subnets to more precisely control traffic flow. 3. Internet gateways and NAT gateways An Internet gateway can be thought of as a gateway that allows communication between your VPC and the Internet. A Network Address Translation (NAT) gateway, on the other hand, is a NAT service that allows instances in your private subnet to access the Internet or other AWS services, while preventing the Internet from initiating a connection with those instances. This enables secure outbound connections to instances in your VPC's private subnet. 4. Network Access Control Lists and Security Groups Network Access Control Lists (ACLs) and security groups are the backbone of network security within a VPC. Network ACLs allow or deny specific inbound or outbound traffic at the subnet level. Network ACL rules are evaluated as traffic enters and leaves the subnet, not as it is routed within the subnet, meaning that the response to permitted inbound traffic follows the rules for outbound traffic and vice versa. In contrast, security groups operate at the individual resource level. They control inbound and outbound traffic to an instance and can specify allowable traffic based on ports and protocols. Each security group adds a separate set of rules for inbound and outbound traffic. Benefits of using VPC 1. Privacy and security By isolating your network infrastructure, a VPC ensures that your data is separate from other data in the public cloud. Features like security groups and network access control lists allow you to control inbound and outbound traffic, further securing your applications. 2. Customizable network configuration With a VPC, you have the freedom to customize your network configuration to meet your business needs. You can select IP address ranges, create subnets, configure route tables and network gateways. 3. Controlled traffic flow VPCs allow controlled access to resources. You can use routing tables, Internet gateways, and virtual private network (VPN) connections to direct and manage the flow of data within your network. 4. Extended IT infrastructure With a secure VPN connection, you can connect your on-premises resources to your cloud infrastructure, making it an extension of your own data center. This makes data transfer smoother and allows you to leverage the benefits of both environments. 5. Multiple connectivity options VPCs offer multiple connectivity options, including a private connection to your on-premises, a direct connection option to your office or local network, and a VPN connection over the internet. VPCs and other cloud models As you learn about cloud computing, it's a good idea to understand the differences between different models such as VPC, public cloud, hybrid cloud, and on-premises environments. Each model offers unique features to meet different needs. Public Clouds A public cloud can be described as a shared space that is open to the general public, like a plaza or park. Everyone can use the park's resources, such as benches and playgrounds, and it can accommodate many people at once. Public clouds have the advantage of being cost-effective because they are managed and operated by a cloud service provider, so you don't have to buy physical servers, and you don't have to worry about operating and maintaining them. This makes them ideal for businesses with fluctuating demand or public applications with many users. Private Clouds A private cloud is a building that is used exclusively by one family, like a single-family home. From the interior of the house to the yard, the family can decorate and manage it as they wish. However, this requires higher maintenance costs and management compared to an apartment complex. A private cloud is a cloud that can be used exclusively by a single customer with independent access. It's used where data needs to be protected, such as an organization's intranet or data center. The advantage of a private cloud is that it can be operated internally, allowing you to manage your data and resources efficiently. Hybrid Clouds A hybrid cloud is a combination of a public cloud and a private cloud, connected through technology that allows data and applications to be exchanged between the two. Think of it as a bridge between an island (private cloud) and a mainland (public cloud). Hybrid clouds combine the best of both cloud computing models, allowing sensitive data and applications that require security to operate in a private cloud, while relatively lightly loaded applications, etc. can operate in a public cloud. This allows organizations to reduce costs and maintain security and control to meet the needs of their business. ​ VPC Public Cloud Private Cloud Hybrid Cloud Privacy Private space within the public cloud Moderate Fully Controlled High Cost Depends on usage, cheaper than private clouds Inexpensive due to pay-as-you-go model Expensive due to the use of dedicated infrastructure Varies as a combination of public and private clouds Scalability High High Low ~ moderate High Control High Low ~ moderate High High Complexity Moderate Low High High Applications Web, Email, CRM, Collaboration, HR ERP, R&D, SCM, Analytics Call centers, Remote sites, Banking Conclusion We've covered a lot of ground, from VPC architectural frameworks to detailed comparisons with public, private, and hybrid clouds. To get the most out of VPC, you need to have a general understanding of the network, not just a grasp of VPC fundamentals. We hope this VPC guide has helped you get started. Links What is Amazon VPC? - Amazon Virtual Private Cloud What is a Private Cloud? - Private Cloud Explained - AWS What is Hybrid Cloud? - Hybrid Cloud Computing Explained - AWS Amazon VPC FAQ - AWS SmileShark Services SmileShark BuildUp | Accurate infra suggestion / Rapid deployment support SmileShark Migration | SmileShark guides you through the entire migration to AWS SmileShark Tech Support | Get expert guidance and assistance to achieve your goals

Written by Hyojung Yoon With the cloud computing market growing rapidly, many organizations are turning to cloud storage services to store and manage their data. Today, we're going to compare and analyze the types of cloud storage and the three main storage services offered by AWS - S3, EFS, and EBS - and identify suitable use cases. Let's get started! What is Cloud Storage Features of Cloud Storage Types of Cloud Storage Block Storage File Storage Object Storage What is Amazon EBS Features of EBS When should I use EBS? What is Amazon EFS Features of EFS When should I use EFS? What is Amazon S3 Features of S3 When should I use S3? AWS Storage Services Comparison & Use Cases Conclusion What is Cloud Storage? Features of Cloud Storage Cloud storage has many benefits. It provides scalability, allowing you to quickly increase or decrease storage capacity as needed; it also provides redundancy, creating copies of your data to prevent data loss; and one of the biggest benefits is accessibility. You can access your data anytime, anywhere, from any device with an internet connection. Types of Cloud Storage Block Storage A block storage is a way of storing data by dividing it into "blocks" of a certain size. Each of these blocks has a unique address, which allows you to reconstruct the block to retrieve the data. It's similar to partitioning a computer drive to use space. Because block storage has unique addresses, it can have multiple access paths, allowing for quick retrieval. It can also be partitioned, allowing access from different OSs. AWS's block storage service is Elastic Block Store (EBS) . File Storage A file storage, or file-based storage, has a hierarchy of folders and files. Each file depends on a folder, which in turn depends on other folders. You can think of it as a Windows Explorer-like structure. You have folders within folders, and you store files in them. If you have a small number of files, you shouldn't have much trouble sorting and organizing them, but if you have a large number of files, sorting, organizing, and finding them can be a challenge. AWS's file storage service is Elastic File System (EFS) . Object Storage A object storage can be thought of as logical storage. While both block and file storage operate at the OS level, object storage operates at the application level. Because there are no physical constraints, you can grow your space as much as you want. Each piece of data is designated as an object and stored as a separate unit of data. Objects can be anything from machine learning (ML), sensor data, and more, as well as unstructured data like photos and videos. It stores data in a flat structure with no hierarchy. It's easily accessible, fast, and highly scalable. AWS's largest object storage service is Simple Storage Service (S3) . To make it a little easier for you to understand storage services, let's use a parking system analogy. You can think of block storage as a large parking lot , and a block as a space in the parking lot. Just as we park our cars in specific spaces, we store data in predetermined blocks. In block storage, each block has a unique address for where it's stored, so when a file is requested from the server, the data can be retrieved by reorganizing the blocks through this address. This is ideal for fast processing of structured data. File storage is a parking tower in a city center. The more cars parked in a parking tower, the more it becomes cluttered and the more difficult it becomes to park or leave. File storage can also degrade as the amount of data grows, increasing the resource demands to keep track of files and folders. Finally, object storage can be thought of as a valet parking service . You don't need to know where you park, just hand over your key, and it will park your car for you efficiently and securely. You also only need to hand over your key to retrieve your car. In object storage, all objects are stored in a single, flat space, unlike file storage, which has a hierarchical structure. This space has a unique identifier and the objects are stored as objects themselves, making them easy to access. Also, if you know the key(name) of an object, you can search for it quickly and easily. What is Amazon EBS(Elastic Block Storage)? Amazon EBS is a high-performance block storage service used by Amazon EC2 instances that provides persistent block storage volumes. It is recognized by EC2 instances like HDD and SSD types, and can deliver the performance you want. Features of EBS EC2 Instances stay separate when shut down, so no data is lost Each Volume is automatically repeated within the AZ Offers a variety of volume types that can be cost-optimized based on workload EBS volumes can be created and restored from backed up snapshots Ideal if you need access to DB, file system, or ras block-level storage When should I use EBS? Use when you need high-performance storage services for a single instance. What is Amazon EFS(Elastic File System)? Amazon EFS provides a simple, scalable, serverless file system that can be used with AWS cloud services and on-premises resources. Think of EFS as file storage for your Linux instances, similar to NFS and NAS folders in your company's on-premises environment. Features of EFS Quickly and easily create and configure file systems with a fully managed service Accessible from thousands of EC2s simultaneously Automatically and instantly expand or contract storage capacity as files are added or removed Files are stored redundantly in multiple Availability Zones so that if one Availability Zone is destroyed, the service can still be served from another Availability Zone When should I use EFS? EFS is ideal for workloads that require a shared file system for multiple EC2 instances, so it's a good choice for file storage for content management systems. What is Amazon S3(Simple Stoarge Services)? Amazon S3 is an internet-accessible object storage service. In other words, it's a service for storing data online, like Google Drive or iCloud. Features of S3 Highly scalable and stores any amount of data Highly durable and 99.99% available HTTP accessible and provides REST and SOAP interfaces Provides data protection through versioning and data backup and restore through hybrid configurations When should I use S3? For internal shared documents that you don't plan to open (read) often, you can store them on S3 at a lower cost than the other two storage services. However, if they are constantly shared and require frequent reads/writes, I recommend EFS It's also great for storing data that you can run complex queries on. It also supports static websites, so you can use it if you need to host multiple static HTML pages. AWS Storage Services Comparison & Usage Examples ​ EBS EFS S3 Latency Low Latency Low, Consistent Low, for mixed request types, and integration with CloudFront Throughput scale Single GB per second Multiple GBs per second Multiple GBs per second Availability/Durability Stored redundantly in a single AZ Stored redundantly across multiple AZs Stored redundantly across multiple AZs Access One EC2 instance in one AZ 1 to thousands of EC2 instances On-premise servers Simultaneous access from multi AZs Integrating the Web Millions of Connections File modification Editable Editable Uneditable Use case Boot volumes Transaction NoSQL Database Data Warehousing ETL Virtual Machine (VM) Web Services and Content Management Enterprise Application Home Directory Database Backup Developer Tools Container Storage Big Data Analytics Web Services and Content Management Media and Entertainment-Backup Big Data Analytics Data Lake *Amazon EBS Usage Examples Database: Retail companies can use EBS as the relational database for their e-commerce applications. The high performance of EBS ensures that applications can quickly read and write data from the database, keeping the site responsive even under heavy load. Enterprise applications: Multinational companies can use EBS for enterprise resource planning (ERP) systems that require fast input and output operations. Data warehousing: Financial institutions can use EBS as a data warehouse to store large amounts of transactional data for business intelligence applications. Boot volumes: Startups building cloud-based software can use EBS to host boot volumes for EC2 instances. This enables EC2 instances to boot quickly and maintain high performance. *Amazon EFS Usage Examples Shared workspace: Software development teams working together on a codebase can use EFS to share code files. All developers can access and edit files at the same time. Content management systems: News organizations can use EFS as a content management system where reporters, editors, and web designers can access and edit articles and related media files simultaneously. Machine learning: Machine learning models need access to large data sets during training. With EFS, multiple instances can read training data simultaneously, speeding up the training process. Web services and content delivery: Popular blogging platforms can use EFS to store blog content. EFS allows you to read files from multiple servers to serve content to users, making it more efficient to handle high traffic volumes. *Amazon S3 Usage Examples Media hosting: For video streaming services like Netflix, S3 can efficiently store and deliver large amounts of multimedia content to a global audience. Data lake: Healthcare analytics companies can use S3 as a data lake to securely store massive amounts of patient data and run machine learning models to gain insights. Static website hosting: Freelance web designers can use S3 to host client websites. It's simple to set up, reliable, and can handle large amounts of traffic. Backup and archiving: Businesses can use S3 to back up their on-premises data. S3's durability ensures that backup data is preserved accurately over long periods of time. Conclusion In this article, we've covered cloud storage services, specifically AWS's most popular storage services. The main AWS storage services we've covered in this article - Amazon EBS, Amazon EFS, and S3 - can be chosen based on your specific needs, budget, and desired level of management. When choosing a storage service, don't forget to consider not only cost and features, but also your needs and how the service fits into your long-term goals! Links What is Cloud Storage? - Cloud Storage Explained - AWS Amazon Elastic File System(EFS) Features | Cloud File Storage | AWS What is Object Storage? - Object Storage Explained - AWS What is Block Storage? - Block Storage Explained - AWS

Written by Hyojung Yoon Hello! Today we're going to explore the world of cloud databases. In today's fast-paced, data-driven world, it's important to have a reliable and efficient database system. Amazon Web Services (AWS) offers two main services, Amazon EC2 and Amazon RDS , that cater to different database needs. But which service to use is your choice? This article will help you decide between EC2 and RDS. We'll compare the two in various ways, look at how they work, and discuss the cost differences. So let's get started! What is Amazon EC2? Features of Amazon EC2 Configuration of Amazon EC2 Instance Types of Amazon EC2 What is Amazon RDS? Features of Amazon RDS Types of Amazon RDS Databases Differences between EC2 and RDS Comparison in terms of cost Same usage scenario Cost variation depending on the situation Decision-making process between Amazon EC2 and Amazon RDS Conclusion What is Amazon EC2? 1. Features of Amazon EC2 Scalable compute capacity to meet your needs Choosing from a variety of instance types to fit your use case Choosing your operating system, applications, services, and even boot partition size Integration with other Amazon services, including Amazon S3, RDS and VPC 2. Configuration of Amazon EC2 AWS EC2 Instance Similar to a physical computer or server A virtual server on which you can run applications Instance power on = computer power on Amazon AMI (Amazon Machine Learning Image) Similar to the default operating system and software on a computer Pre-configured templates for creating new instances Amazon EBS (Elastic Block Store) Similar to a computer's hard drive Providing raw block-level storage that can be connected to EC2 3. Instance Types of Amazon EC2 ​ Type Description Example General Purpose t Low-cost general purpose Web services, DB m general purpose Application Server Memory Optimized r Processing large data sets Memory-intensive workloads Compute Optimized c Compute Optimization Compute-intensive applications Accelerated Computing p Graphics Optimization Machine learning, pixel streaming ​ g Graphics Optimization 3D modeling, encoding What is Amazon RDS? 1. Features of Amazon RDS Saas-based service that autoconfigures and maintains databases in the cloud. Instant compute scaling. Storage scaling is also easy Can handle high volume application read traffic by creating one or more replicas of a DB instance Supports 6 DB engines, giving you the ability to choose the right one for your needs 2. Types of Amazon RDS Database Amazon Aurora MySQL and PostgreSQL compatible relational databases PostgreSQL Open source relatiaonal databases MySQL The world's most popular open source relational databases MariaDB An offshoot of MySQL Provides similar functionality to the RDS MySQL service Oracle A relational database from Oracle SQL Server(MSSQL) A relational database management system developed by Microsoft Differences between EC2 and RDS Imagine you're planning a dinner party. You have two options: cook it yourself or hire a professional caterer. Cooking yourself gives you complete control over the menu selection and preparation to your liking, but it's time-consuming and requires cooking skills. On the other hand, hiring a professional caterer is more convenient and allows you to enjoy the party without worrying about cooking. The downside is that it can be expensive, and you have limited control over the menu. This is similar to choosing between Amazon EC2 and Amazon RDS for your database needs. You could say that EC2 is like cooking the dinner yourself and RDS is like hiring a chef . Like cooking dinner, using EC2 means that you do all the work yourself. You have to set up the kitchen (server), get the ingredients (software), and cook the meal (database management). Just as you can choose your database software and configuration in EC2, you have the freedom to choose your ingredients and cooking method, but it takes time and effort to prepare the meal. Similarly, managing a database in EC2 requires skills and resources, as you are responsible for maintaining and updating the server. RDS is like hiring a professional caterer for a dinner party: they handle everything from menu planning to food preparation to clean up. Just like you don't have to worry about cooking or cleaning when you hire a professional, you don't have to worry about managing your servers when you use RDS because AWS handles all the mundane tasks like backups and updates. However, hiring a professional is often more expensive than cooking for yourself. Similarly, RDS can be more expensive than EC2, but the time savings and convenience can make it worth the cost. Amazon EC2 Amazon RDS Control Full control of server and database permissions, operating system, database engine version, and choice of configuration settings Less Control than EC2 Managemanet Requires hands-on management. Updates, backups, and security are your responsibility. AWS handles administrative tasks such as backups, updates, and failover support Flexibility Highly flexible. Ability to customize the server and database to your needs Less flexible than EC2. You can't modify the underlying server or database engine. Cost Generally less expensive than RDS. Costs for EC2 instances, storage, and data trasfer. Generally higher than EC2. Include features like instances, storage, automatic backups, and software patching Availability User is responsible for ensuring high availability, such as setting up multiple instances or regions. RDS provides built-in redundancy and failover support for high availability Comparison in temrs of cost 1. Same usage scenario Suppose you need a single t3.medium instance with 100 GB of general-purpose (SSD) storage and are running a database operating in the Eastern (Northern Virginia) region of the United States. (All costs are calculated as of May 2023) EC2 - Instance cost(on-demand t3.medium) : $0.0416/hr - EBS storage cost(gp2) : $0.10/GB/month RDS - Instance cost(on-demand db.t3.medium) : $0.068/hr - RDS storage cost(gp2) : $0.115/GB/month Let's calculate the monthly costs assuming the instance runs 24/7 (approximately 720 hours per month). EC2 Monthly Cost - Instances : 720 hours * $0.0416/hr = about $30 - Storage : 100GB * $0.10/GB = $10 - Total : about $40 RDS Monthly Cost - Instances : 720 hours * $0.068/hr = about $49 - Storage : 100GB * $0.115/GB = $11.5 - Total : about $60.5 When comparing costs, EC2 looks cheaper, but RDS is a managed service, while EC2 requires you to manage the database yourself. The extra cost of RDS pays for convenience and features like automated backups and software patches. 2. Cost variation depending on the situation There are scenarios where the cost difference between Amazon EC2 and Amazon RDS can be different. High availability If your application requires high availability, you might need to run multiple instances. In this scenario, RDS might be more cost-effective because it provides features that you would have to implement and manage on your own in EC2, such as automated backups, failover support, and other high-availability features. Reserved instances(RI) Both EC2 and RDS offer reserved instances, which can save you a significant amount of money with a one or three-year commitment. The savings are potentially greater with RDS because the base cost is higher. Data transfer Depending on the amount of data you transfer, your costs can also vary. In most cases, RDS includes more data transfer costs than EC2. Therefore, choosing between EC2 and RDS based on cost alone can be misleading. RDS may cost more upfront, but when you factor in management costs and features like automatic backups, patch management, and high availability, it can save you money in the long run. It's always a good idea to consider the total cost of ownership, which includes both direct and indirect costs associated with each service. Decision-making process between Amazon EC2 and Amazon RDS The figure above is a diagram that visualizes Amazon's documentation to assist in the decision-making process to help you choose between Amazon EC2 and Amazon RDS. Conclusion Just like deciding whether to cook for yourself or hire a professional caterer for a dinner party, choosing between EC2 and RDS depends on your specific needs, budget, and desired level of management. The choice isn't just about cost or features, it's about understanding your needs and how the service fits into your long-term goals. As you navigate the ever-evolving cloud landscape, choose wisely to optimize your operations and increase user satisfaction. Links Fully Managed Relational Database - Amazon RDS - Amazon Web Services Secure and resizable cloud compute - Amazon EC2 - Amazon Web Services Amazon EC2 Instance Types - Amazon Web Services Choosing between Amazon EC2 and Amazon RDS - AWS Prescriptive Guidance Add services - AWS Pricing Calculator SmileShark Services SmileShark BuildUp | Accurate infra suggestion / Rapid deployment support SmileShark Migration | SmileShark guides you through the entire migration to AWS SmileShark Tech Support | Get expert guidance and assistance achieving your objectives

Written by Hyojung Yoon Hello! Today we're going to explore the world of cloud data warehouses, specifically Amazon Redshift and Google BigQuery. If you're curious about how companies store, analyze and manage massive amounts of data in today's data-driven world then the answer lies in Cloud data warehouses like Amazon Redshift and Google BigQuery . In this article, we'll first take a quick look at what a data warehouse is and what its characteristics are, and then do a comparative analysis of Redshift and BigQuery, two leading cloud data warehouse solutions. Let's get started! What is a Data Warehouse? The importance of data today Data Warehouse and Cloud Data Warehouse Features of Data Warehouse Benefits of Cloud Data Warehouse Scalability Flexibility Agility Cost Optimization Enhanced security Collaboration Comparison of Cloud Data Warehouses Amazon Redshift Google BigQuery Conclusion What is a Data Warehouse? The importance of data today People and machines produce vast amounts of data every day. It enables businesses, governments, and individuals to make informed choices and discover new insights. The importance of data is only growing as our reliance on technology increases, and data has become a key part of modern life. Understanding and utilizing data can help you make better decisions, increase efficiency, and make the most of the opportunities it presents. Data Warehouse and Cloud Data Warehouse Data warehouse is a portmanteau of the words Data and warehouse and refers to a structured and integrated environment of technology that aims to accumulate and integrate data in a time series to support efficient decision-making from a strategic perspective. In other words, it is a database that integrates, coordinates, and manages data from each of the distributed databases within an organization and converts them into a common format for efficient decision-making. Cloud data warehouse is a centralized, large-scale storage solution that enables organizations to store and analyze vast amounts of data in the cloud, making it easy to access and secure. Cloud data warehouses reduce an organization's infrastructure costs, increase flexibility, and are easily scalable. Here's an analogy to help you understand. If you think of books as data, you can think of your bookshelf, the place where you store and organize your books, as a "data warehouse" for your books. Let's say you want to share this collection of books with your friends and want them to be able to access your books anytime, anywhere. To do this, you decide to move your entire book collection to an online platform like an e-library. This is similar to a cloud data warehouse, where the data(in this case, books) is stored on the internet and can be easily accessed from anywhere. So, a cloud data warehouse is like an online bookshelf where all your data(books) are stored and organized for easy access, analysis, and sharing with others. Just like you can easily search for the book you want in an online library, a cloud data warehouse allows you to quickly search and analyze large amounts of data to find useful information and insights. Features or Data Warehouse Features 설명 Subject Oriented ​- Topic-driven rather than task-driven (data is classified and stored according to the organization's work topics) - Data structures that are not tied to a specific business function or application Integrated - Ensure data consistency with data modeling - Ensure data uniformity through enterprise-wide data standardization - Perform a series of transformations to integrate data as it is acquired Time Variant - Data is retained for long periods of time, storing snapshots of values at every moment in time to enable analysis and prediction of past and present trends. - Necessary for trend analysis of work changes or development over a period of time Non-volatile - After initial data load, no data refresh process exists - There is only data loading and data access - Even if data changes occur, they are reflected in the form of a snapshot without updating the change requirements Benefits of Cloud Data Warehouse 1. Scalability Cloud data warehouses are elastic, so they can seamlessly scale up or down as your business needs change. 2. Flexibility Cloud data warehouses support a variety of data types, including structured, semi-structured, and unstructured data, and make it easy for businesses to integrate data from different sources. 3. Agility Cloud data warehouses can quickly process and analyze large amounts of data in near real time. This enables faster, more agile decision-making by providing the insights you need to make informed decisions. 4. Cost Optimization Cloud data warehouses can be more cost-effective than traditional on-premises data warehouses because businesses don't have to invest in expensive hardware, software, and maintenance. 5. Enhanced security Cloud data warehouses come with advanced security measures to protect your data from unauthorized access and potential data breaches. These include encryption, firewalls, and regular security updates to keep your data safe. 6. Collaboration Cloud data warehouses enable collaboration between teams by allowing multiple users to access and analyze data anytime, anywhere. Comparison of Cloud Data Warehouses Amazon Redshift Google BigQuery Ease of Use & Setup Easy to set up and use Slightly easier due to severless architecture Data Storage Optimized for structured data Handles both structured and unstructured data Real-time Analytics Limited real-time analytics support Robust real-time analytics support Pricing​ Pay-as-you-go, based on nodes and hours of usage Pay-as-you-go, based on data storage and query volume Scalability ​Scalable with a managed cluster architecture Scalable with serverless architecture ​Security Robust security features Robust security features Integration Seamless integration with AWS services Seamless integration with Google Cloud Platform services Machine Learning Integration with Amazon SageMaker Integraion with BIgQuery ML 1. Amazon Redshift Provide a Cloud Data Platform focued on leveraging customer data Features and Advantages Fully managed cloud data warehouse at petabyte scale Seamless integration with other AWS services Easily store all processing results in an S3 data lake 10x faster performance than traditional DW with columnar storage, massively parallel query execution, and more Secure and manageable option for organizations with high security and compliance needs Use when you need to perform complex queries quickly or need regular batch processing Differences from traditional DW Store and analyze your data in a single S3 to get insights you can't get by analyzing individual data alone Pay-as-you-go pricing model where you only pay for the resources you use Analyze not only structured data but also semi-structured and unstructured data 2. Google BigQuery Analyze data optimized···Supports a variety of infrastructure environments Features and Advantages Fully managed cloud data warehouse at petabyte scale Built-in BI engine, powerful machine learning capabilities available through SQL extensions Easy to use and set up with a highly scalable serverless architecture Seamless integration with other Google services An attractive option for businesses looking for a powerful and easy-to-use data warehouse Use when you need real-time analytics for large datasets Differences from traditional DW Relatively easy to analyze data because you only need to know the SQL language No need to install and operate as a cloud service Can utilize powerful computing resources without investing in infrastructure Conclusion Amazon Redshift and Google BigQuery are both powerful cloud data warehouses, each with their own strengths and benefits. Redshift excels at scalability and data warehousing for AWS users, while BigQuery shines with its serverless architecture and seamless integration with other Google Cloud services. If you don't have any technical background, think of it as choosing between two flavors of ice cream - they're both delicious in their own right, but it depends on your preferences and the occasion. Similarly, the best choice for your business will depend on your needs, budget, and existing infrastructure. Understanding the differences between data warehouses and choosing the one that best suits your needs will enable you to make an informed decision that will help your business grow. Links What is a Data Warehouse? | Key Concepts | Amazon Web Services What is a data wareshouse? | Definition, components, architecture | SAP Insights What is a Data Warehouse? | Google Cloud Amazon Redshift Serverless - Amazon Web Services BigQuery Enterprise Data Warehouse | Google Cloud [Special Feature] Analyzing data quickly and easily with a 'cloud-based data platform' - ComputerWorld

Written by Hyojung Yoon Hello! Today we're going to talk about CDNs. In our ever-evolving digital world, we all want a fast and reliable connection to internet content. Have you ever wondered how websites load quickly when you access them from the other side of the world? The answer lies in a technology called a CDN, or Content Delivery Network . In this article, we'll take a quick look at what a CDN is, how it works, and do a comparative analysis of the leading CDN solutions. So let's get started! What is a CDN? How CDN works Benefits of CDN Improve web page load times Reduce bandwidth usage and costs Increase content availability Respond to traffic spikes Increased security Comparison of CDN Services CloudFront Akamai Cloudflare Fastly Conclusion What is a CDN? A Contents Delivery Network(CDN) is a network of servers distributed around the world to deliver content to users quickly and securely. By delivering content from servers closer to the user, it speeds up delivery and significantly reduces latency. To make it easier for you to understand, let's compare a CDN to a courier delivery system. Think of the Internet as a giant courier delivery system for websites and content. Just like a courier system that sends packages from one place to another, a CDN helps deliver content (images, videos, text, etc.) to your computer or smartphone. When you order something online, it's usually shipped from a warehouse to your home. Similarly, a CDN stores content in multiple locations around the world (called servers) and delivers it to you from the closest server. This makes content load faster and provides a seamless online experience. How CDNs work Imagine you're accessing your favorite website on your smartphone or computer. If the website's servers are located far away, the webpage might take a while to load. This is where a content delivery network, or CDN, can help speed up the delivery of the content you're trying to access. A CDN is a network of interconnected servers that work together to distribute content, such as images, videos, or web pages, to users around the world. When a user requests content, the CDN identifies the servers closest to the user (also known as edge servers ) and delivers the content from those servers instead of the origin server. This greatly reduces the time it takes for the content to travel, making it faster and more efficient to deliver. To further optimize this process, CDNs utilize caching , which stores copies of content on multiple servers across the network. By utilizing caching, when a user requests content, the requested content is readily available on the closest server. This allows CDNs to reduce latency-the time it takes for content to be delivered from the origin server to the user. As a result, CDNs play an important role in improving website and application performance, providing a faster, smoother internet experience for you and your fellow users. Benefits of CDN 1. Improve web page load times CDNs use CDN servers close to your users to serve content, which results in faster page load times. If your page load times are too slow, users might bounce, and your site traffic might decrease. A CDN reduces this bounce rate and increases the amount of time users spend on your site, so more users stay longer. 2. Reduce bandwidth usage and costs Web hosts charge based on the data transferred from their servers. By storing a copy of the content closer to the user, a CDN reduces the amount of data transferred from the original server. By doing so, the CDN reduces the amount of data that the original server has to serve, reducing bandwidth usage and costs. 3. Increase content availability Too many visitors at once or a hardware failure can cause your website to crash. Because CDNs are decentralized, they can handle more traffic and withstand hardware failures. Plus, if one or more CDN services go offline, other operational servers can replace them to ensure that your service is not interrupted. 4. Respond to traffic spikes A distributed denial of service (DDoS) attack attempts to bring down a server by sending large amounts of fake traffic to a website. CDNs can handle spikes in traffic by reducing the impact on the origin server through methods such as distributed processing, which spreads the load across multiple servers, and distinguishing between normal and abnormal requests. 5. Increased security CDNs can increase security by mitigating distributed denial of service (DDoS) attacks, improving secure authentication, and other optimizations. Comparison of CDN Services ​ CloudFront Akamai Cloudflare Fastly Company Amazon Web Services (AWS) Akamai Technologies Cloudflare Inc. Fastly Inc. Global Network 200+ edge locations 300,000+ servers 250+ cities 50+ POPs Security Features WAF, DDoS protection, SSL/TLS WAF, DDoS protection, SSL/TLS WAF, DDoS protection, SSL/TLS WAF, DDoS protection, SSL/TLS Pricing Pay-as-you-go, volume discount Custom pricing Free tier, pay-as-you-go, pro plans Pay-as-you-go, volume discount API & Integration AWS SDK & API Akamai API Cloudflare API Fastly API Additional Features Lambda@Edge, real time metrics Image and video optimization Argo smart routing, Workers Instant Pruge, Edge Compute 1. CloundFront A part of Amazon Web Services (AWS), one of the largest cloud providers Advantages Seamless AWS integration 200+ edge locations provide a wide-reaching network Pay-as-you-go with volume discounts available Lambda@Edge Disadvantages Less straightforward pricing limited free tier compared to Cloudflare Complex setup for beginners 2. Akamai A pioneer in the CDN market, offering experience and reliabillity Advantages 300,000+ servers provide a massive global network Fast, secure, high-performance content delivery Image/Video optimization Custom pricing for tailored solutions Disadvantages Custom pricing less transparent Lacks a free tier for small-scale users Complex setup for beginners 3. Cloudflare A user-friendly, feature-rich CDN provider Advantages A wide-reaching global network with 250+ cities Free tier for small-scale users Argo smart routing Cloudflare Workers enables serverless edge computing Disadvantages Lack some features needed for advanced use cases The global network is not as extensive as competitiors Additional features like Argo, Workers come with extra costs 4. Fastly A CDN provider focuses on speed, flexibility, and customization Advantages Instant Purge allows for rapid cache invalidation Edge-Compute platform for running custom code at the edge Pay-as-you-go pricing with volume discounts can be cost-effective Disadvantages A smaller global network compared to competitiors Lacks a free tier for small-scale users Complex setup for beginners Conclusion In today's digital landscape, CDNs are a critical component, ensuring fast and secure content delivery. In this article, we've provided a comparative analysis of the leading CDN solutions, as well as their strengths and limitations. With this in mind, careful consideration is essential when choosing the right CDN solution. Why not adopt the right CDN service for your business to boost website performance and improve user satisfaction? Links What is a CDN? - Content Delivery Network Explained - AWS What is a Content Delivery Network (CDN)? | How do CDNs work?| Cloudflare What is a content delivery network (CDN)? | IBM SmileShark Services SmileShark CloudFront | Fast and Secure Developer-friendly Content Delivery Network(CDN)