[{"data":1,"prerenderedAt":957},["ShallowReactive",2],{"practiceExams":3,"practice-exam-questions-\u002Fpractice-exams\u002Faws-certified-data-engineer-associate-dea-c01\u002Fquestions":79},[4,15,23,32,42,51,61,70],{"id":5,"slug":6,"description":7,"questionCount":8,"isActive":9,"datePublicModified":10,"difficulty":11},10,"aws-certified-advanced-networking-specialty-ans-c01","The AWS Certified Advanced Networking - Specialty practice exam simulates the real test, offering scenario-based questions that assess your ability to design, implement, and troubleshoot complex AWS networking solutions. ",3531,true,"2024-11-13T00:00:00.000Z",{"title":12,"subtitle":13,"slug":6,"coverImageUrl":14},"AWS Certified Advanced Networking - Specialty","ANS-C01","",{"id":16,"slug":17,"description":18,"questionCount":19,"isActive":9,"datePublicModified":10,"difficulty":20},9,"aws-certified-data-engineer-associate-dea-c01","Prepare for your AWS Certified Data Engineer - Associate exam with our practice exam simulator. Featuring real exam scenarios, detailed explanations, and instant feedback to boost your confidence and success rate.",3312,{"title":21,"subtitle":22,"slug":17,"coverImageUrl":14},"AWS Certified Data Engineer - Associate","DEA-C01",{"id":24,"slug":25,"description":26,"questionCount":27,"isActive":9,"datePublicModified":28,"difficulty":29},8,"aws-certified-devops-engineer-professional-dop-c02","Boost your readiness for the AWS Certified DevOps Engineer - Professional (DOP-C02) exam with our practice exam simulator. Featuring realistic questions and detailed explanations, it helps you identify knowledge gaps and improve your skills.",2775,"2024-08-08T00:00:00.000Z",{"title":30,"subtitle":31,"slug":25,"coverImageUrl":14},"AWS Certified DevOps Engineer - Professional","DOP-C02",{"id":33,"slug":34,"description":35,"questionCount":36,"isActive":9,"datePublicModified":37,"difficulty":38},1,"aws-certified-solutions-architect-associate-saa-c03","Unlock your potential with the AWS Certified Solutions Architect - Associate Practice Exam Simulator. This comprehensive tool is designed to prepare you thoroughly and assess your readiness for the most sought-after AWS associate certification.",3813,"2024-06-13T00:00:00.000Z",{"title":39,"subtitle":40,"slug":34,"coverImageUrl":41},"AWS Certified Solutions Architect - Associate","SAA-C03","\u002Fimages\u002Fdifficulties\u002Faws-certified-solutions-architect-associatesaa-c03\u002Fcovers\u002Faws-SAA-C03.png",{"id":43,"slug":44,"description":45,"questionCount":46,"isActive":9,"datePublicModified":37,"difficulty":47},5,"aws-certified-cloud-practitioner-clf-c02","Master your AWS Certified Cloud Practitioner exam with our Practice Exam Simulator. Prepare effectively and assess your readiness with realistic practice exams designed to mirror the most popular official AWS exam.",4227,{"title":48,"subtitle":49,"slug":44,"coverImageUrl":50},"AWS Certified Cloud Practitioner","CLF-C02","\u002Fimages\u002Fdifficulties\u002Faws-certified-cloud-practitionerclf-c02\u002Fcovers\u002Faws-CLF-C02.png",{"id":52,"slug":53,"description":54,"questionCount":55,"isActive":9,"datePublicModified":56,"difficulty":57},4,"aws-certified-developer-associate-dva-c02","Unlock your potential as a software developer with the AWS Certified Developer - Associate Exam Simulator! Prepare thoroughly with realistic practice exams designed to mirror the official exam.",3787,"2024-06-06T00:00:00.000Z",{"title":58,"subtitle":59,"slug":53,"coverImageUrl":60},"AWS Certified Developer - Associate","DVA-C02","\u002Fimages\u002Fdifficulties\u002Faws-certified-developer-associatedva-c02\u002Fcovers\u002Faws-DVA-C02.png",{"id":62,"slug":63,"description":64,"questionCount":65,"isActive":9,"datePublicModified":56,"difficulty":66},6,"aws-certified-solutions-architect-professional-sap-c02","Elevate your career with the AWS Certified Solutions Architect - Professional Exam Simulator. Get ready to ace the most popular Professional AWS exam with our realistic practice exams. Assess your readiness, boost your confidence, and ensure your success.",8203,{"title":67,"subtitle":68,"slug":63,"coverImageUrl":69},"AWS Certified Solutions Architect - Professional","SAP-C02","\u002Fimages\u002Fdifficulties\u002Faws-certified-solutions-architect-professionalsap-c02\u002Fcovers\u002Faws-SAP-C02.png",{"id":71,"slug":72,"description":73,"questionCount":74,"isActive":9,"datePublicModified":56,"difficulty":75},7,"aws-certified-security-specialty-scs-c02","Advance your career in cloud cybersecurity with the AWS Certified Security - Specialty Exam Simulator! Tailored for professionals, this tool offers realistic practice exams to mirror the official exam.",5439,{"title":76,"subtitle":77,"slug":72,"coverImageUrl":78},"AWS Certified Security - Specialty","SCS-C02","\u002Fimages\u002Fdifficulties\u002Faws-certified-security-specialtyscs-c02\u002Fcovers\u002Faws_SCS_c02.png",{"id":16,"slug":17,"description":18,"content":80,"formalQuestionCount":81,"minQuestionCount":33,"maxQuestionCount":82,"formalTimeLimitCount":83,"minTimeLimitCount":5,"maxTimeLimitCount":84,"passingScore":85,"questionCount":19,"isActive":9,"dateCreated":86,"dateModified":87,"datePublicModified":10,"difficulty":88,"tags":956},"\u003Cp>The AWS Certified Data Engineer - Associate (DEA-C01) exam is recognized as a demanding certification that validates a candidate's expertise in managing and optimizing data-driven workflows within the AWS ecosystem. While this exam is geared towards professionals with a background in data engineering, it is by no means an easy feat and requires a thorough understanding of both foundational and advanced AWS data services.\u003C\u002Fp>\u003Cp> \u003C\u002Fp>\u003Cp>The DEA-C01 exam covers a broad range of topics, including but not limited to, data ingestion, transformation, storage, and visualization within AWS. Candidates must demonstrate a solid grasp of essential AWS data services such as Amazon Redshift, Glue, S3, and Kinesis, along with a deep understanding of how to architect and maintain scalable, secure, and high-performing data pipelines.\u003C\u002Fp>\u003Cp> \u003C\u002Fp>\u003Cp>A critical component of the exam focuses on data processing frameworks like Apache Spark and Hadoop, as well as an understanding of database services, both relational (RDS, Aurora) and non-relational (DynamoDB). Additionally, the exam tests the candidate's ability to apply machine learning workflows using services like Amazon SageMaker within a data engineering context.\u003C\u002Fp>\u003Cp>Security and compliance are integral to the exam, emphasizing the need for candidates to understand AWS's shared responsibility model and implement best practices for data governance, encryption, and access management. Services such as IAM, KMS, and AWS Lake Formation are frequently tested to ensure candidates can securely manage data at scale.\u003C\u002Fp>\u003Cp> \u003C\u002Fp>\u003Cp>In this exam, candidates are also expected to distinguish between various data storage and retrieval solutions, optimizing them based on specific use cases and cost considerations. This includes knowing when to utilize services like S3 for unstructured data versus using Redshift for structured data analytics.\u003C\u002Fp>\u003Cp> \u003C\u002Fp>\u003Cp>Overall, the questions in the DEA-C01 exam are designed to challenge both theoretical knowledge and practical application, with scenarios that require candidates to design, implement, and optimize complex data architectures. While the exam avoids overly complicated wording, the difficulty lies in the depth of knowledge requi\u003C\u002Fp>",65,75,130,200,72,"2024-08-21T15:42:10.743Z","2024-11-13T09:51:36.000Z",{"id":71,"title":21,"subtitle":22,"rating":52,"slug":17,"guideUrl":89,"categories":90,"services":562},"https:\u002F\u002Fd1.awsstatic.com\u002Ftraining-and-certification\u002Fdocs-data-engineer-associate\u002FAWS-Certified-Data-Engineer-Associate_Exam-Guide.pdf",[91,204,315,426],{"id":92,"title":93,"subtitle":94,"description":95,"content":96,"coverImageUrl":14,"weight":97,"subcategories":98},29,"Data Ingestion and Transformation","Domain 1","This domain covers the processes involved in ingesting and transforming data using AWS services. It includes tasks related to building and orchestrating data pipelines, and applying programming concepts to manage and optimize these processes.",null,34,[99,126,152,178],{"id":100,"title":101,"subtitle":102,"description":96,"questions":103},117,"Perform data ingestion","Task 1.1",[104],{"id":105,"subcategoryId":100,"content":106,"hint":107,"isPublic":9,"answers":108},31761,"You are working as a Data Engineer at a healthcare company that captures real-time patient data from numerous medical devices. The data from these devices are streamed continuously to an Amazon Kinesis Data Stream. To ensure low latency and durability, you decide to distribute the data to multiple downstream services for immediate processing. Several machine learning models and storage solutions need to consume this data simultaneously with different processing workloads. Due to the varying requirements, you aim to achieve a fan-out pattern. Furthermore, alerts and notifications need to be sent to healthcare professionals based on specific thresholds. You decide to use Amazon SNS for this purpose. What is the most appropriate way to set up the system to achieve this? \n\n","Consider how Amazon SNS integrates with other AWS services for both fan-in and fan-out patterns, ensuring that various downstream consumers can independently process the data.",[109,113,118,122],{"id":110,"questionId":105,"content":111,"hint":112,"isCorrect":9},144090,"Create an Amazon SNS topic and subscribe different Amazon SQS queues, AWS Lambda functions, and HTTP endpoints to the SNS topic. Stream data from Amazon Kinesis to the SNS topic for distribution.","This solution allows multiple downstream consumers to subscribe to the SNS topic, enabling a fan-out pattern. Each consumer can handle the data independently, meeting different processing workloads.",{"id":114,"questionId":105,"content":115,"hint":116,"isCorrect":117},144091,"Directly stream data from Amazon Kinesis to multiple AWS Lambda functions.","While AWS Lambda can process data from Kinesis, it doesn't inherently provide a fan-out mechanism to distribute data to various other services.",false,{"id":119,"questionId":105,"content":120,"hint":121,"isCorrect":117},144092,"Stream data from Amazon Kinesis to an Amazon S3 bucket, and then use AWS Glue to read from S3 and invoke different consumers.","While this approach handles data storage and transformation, it introduces unnecessary latency and doesn't directly use SNS for immediate data distribution and notifications.",{"id":123,"questionId":105,"content":124,"hint":125,"isCorrect":117},144093,"Use Amazon Kinesis Data Firehose to deliver data to multiple S3 buckets and then process the data.","Amazon Kinesis Data Firehose is used for loading data streams into data lakes and other stores but doesn't support complex fan-out mechanisms directly.",{"id":127,"title":128,"subtitle":129,"description":96,"questions":130},118,"Transform and process data","Task 1.2",[131],{"id":132,"subcategoryId":127,"content":133,"hint":134,"isPublic":9,"answers":135},31889,"As an AWS Certified Data Engineer, you have been tasked with creating a data API to make customer data available to other systems in real-time. Your company uses Amazon RDS for PostgreSQL to store customer data. You need to ensure that the data transformation and processing are efficient and that other systems can consume the data with minimal latency. How can you best achieve this within the AWS ecosystem?","Consider services that can help you expose data through APIs and think about how data can be transformed and made available efficiently.",[136,140,144,148],{"id":137,"questionId":132,"content":138,"hint":139,"isCorrect":117},144602,"Set up Amazon Kinesis Data Firehose to stream data from Amazon RDS directly to other systems.","Amazon Kinesis Data Firehose is typically used for streaming data to other AWS services such as S3 or Redshift, and not for exposing APIs for real-time data access from RDS.",{"id":141,"questionId":132,"content":142,"hint":143,"isCorrect":9},144603,"Use AWS Lambda functions to access and transform data from RDS, and expose the transformed data via Amazon API Gateway.","AWS Lambda can be triggered to access, process, and transform data from Amazon RDS. Amazon API Gateway can then be used to expose this transformed data as APIs, ensuring efficient data access with minimal latency.",{"id":145,"questionId":132,"content":146,"hint":147,"isCorrect":117},144604,"Use AWS Glue to transform data and write the results back to Amazon RDS for consumption.","While AWS Glue is excellent for ETL jobs, it is primarily designed for batch processing, not for real-time data access. Writing the results back to RDS for real-time API access would not be efficient.",{"id":149,"questionId":132,"content":150,"hint":151,"isCorrect":117},144605,"Directly access Amazon RDS through other systems without any intermediate processing.","Directly accessing RDS from multiple other systems would increase load and latency on the database, potentially resulting in performance issues. It also lacks a layer for data transformation and security.",{"id":153,"title":154,"subtitle":155,"description":96,"questions":156},119,"Orchestrate data pipelines","Task 1.3",[157],{"id":158,"subcategoryId":153,"content":159,"hint":160,"isPublic":9,"answers":161},31963,"You are a Data Engineer at a company that processes large volumes of data. As part of your data pipeline, you have a process that ingests data from various sources and transforms it before storing it into your data warehouse. You are using Amazon SQS to manage the ingestion of data by queuing messages that represent the data files to be processed. Due to the need for real-time processing, you must ensure that if any part of the system fails or encounters an issue, the appropriate team is immediately alerted so they can address the problem. Which service would you use to send these notifications, and how would you integrate it with Amazon SQS?","Think about a service that can send notifications and can integrate with message queues for real-time alerts.",[162,166,170,174],{"id":163,"questionId":158,"content":164,"hint":165,"isCorrect":117},144898,"Amazon CloudWatch Alarms; Create CloudWatch Alarms to monitor SQS and send notifications.","Amazon CloudWatch Alarms are used to monitor AWS metrics and can trigger actions based on those metrics. While CloudWatch can monitor SQS metrics, it requires integration with SNS to send notifications. CloudWatch Alarms alone do not send notifications on their own.",{"id":167,"questionId":158,"content":168,"hint":169,"isCorrect":9},144899,"Amazon SNS; Integrate Amazon SNS with Amazon SQS to send notifications when specific events occur in your data pipeline.","Amazon Simple Notification Service (SNS) is designed to send notifications. By integrating SNS with SQS, you can set up automations to send notifications to the appropriate team whenever a specific event occurs in your data pipeline (e.g., a message is added to a queue).",{"id":171,"questionId":158,"content":172,"hint":173,"isCorrect":117},144900,"Amazon Kinesis; Use Amazon Kinesis to monitor SQS and send notifications.","Amazon Kinesis is designed for real-time data processing and analytics, not for sending notifications. Though it can ingest and process data streams, it does not provide the native notification sending functionality needed for alerting teams.",{"id":175,"questionId":158,"content":176,"hint":177,"isCorrect":117},144901,"AWS Lambda; Use AWS Lambda functions to monitor SQS and send notifications.","AWS Lambda can be triggered by events in SQS and can execute code to process those events. However, Lambda is a compute service and does not natively send notifications. To send notifications, you would still need to integrate Lambda with Amazon SNS.",{"id":179,"title":180,"subtitle":181,"description":96,"questions":182},120,"Apply programming concepts","Task 1.4",[183],{"id":184,"subcategoryId":179,"content":185,"hint":186,"isPublic":9,"answers":187},32093,"You are a data engineer working for a media company that processes a large volume of user-uploaded video files. Your task is to create an AWS Lambda function that processes these video files as soon as they are uploaded to an Amazon S3 bucket. You need to ensure that the Lambda function has access to a temporary storage volume for buffering data during processing. Which of the following steps should you take to achieve this?","Consider how Lambda functions access both temporary storage, local storage, and data from Amazon S3.",[188,192,196,200],{"id":189,"questionId":184,"content":190,"hint":191,"isCorrect":117},145418,"Attach an EBS volume to the Lambda function and use it as temporary storage for processing files.","AWS Lambda does not support directly attaching EBS volumes to functions. Lambda functions can only use the \u002Ftmp directory for temporary storage.",{"id":193,"questionId":184,"content":194,"hint":195,"isCorrect":117},145419,"Mount an Amazon EFS file system to the Lambda function and use it for buffering the video files during processing.","While mounting an EFS file system to a Lambda function is possible, it is typically used for shared storage rather than temporary storage. For buffering purposes, the \u002Ftmp directory is more appropriate.",{"id":197,"questionId":184,"content":198,"hint":199,"isCorrect":117},145420,"Store the processed data back into Amazon S3 using an Object Lambda access point.","While Object Lambda access points can simplify accessing S3 objects, this does not address the need for temporary storage during processing. This option deals with storing or accessing data differently, not with temporary buffering.",{"id":201,"questionId":184,"content":202,"hint":203,"isCorrect":9},145421,"When defining the Lambda function, specify the amount of \u002Ftmp storage required and use the AWS SDK to read files from the S3 bucket into the \u002Ftmp directory.","Lambda functions have access to a \u002Ftmp directory which can be used as temporary storage. By specifying the amount of \u002Ftmp storage and using the AWS SDK to read files from S3, you can ensure the Lambda function has the necessary temporary storage.",{"id":205,"title":206,"subtitle":207,"description":208,"content":96,"coverImageUrl":14,"weight":209,"subcategories":210},30,"Data Store Management","Domain 2","Focused on selecting and managing AWS data stores, this domain addresses the lifecycle of data, including cataloging, schema design, and optimizing storage solutions for cost and performance.",26,[211,237,263,289],{"id":212,"title":213,"subtitle":214,"description":96,"questions":215},121,"Choose a data store","Task 2.1",[216],{"id":217,"subcategoryId":212,"content":218,"hint":219,"isPublic":9,"answers":220},32208,"You are a data engineer for a financial analytics firm, responsible for managing and analyzing large datasets. The firm’s transactional data is stored in an Amazon Aurora MySQL database. The analytical workload has increased significantly, and you need to speed up your data queries. You decide to store a subset of this data in Amazon Redshift for faster querying and reporting. What is the most efficient method to move and keep this data in sync while ensuring minimal impact on the Amazon Aurora database performance?","Consider methods that allow efficient data migration while maintaining performance and syncing between Amazon Aurora and Amazon Redshift.",[221,225,229,233],{"id":222,"questionId":217,"content":223,"hint":224,"isCorrect":117},145878,"Implement Amazon Redshift materialized views and manually refresh them periodically.","Materialized views improve query performance but require periodic manual refreshes, which may not capture real-time changes efficiently and could introduce additional overhead.",{"id":226,"questionId":217,"content":227,"hint":228,"isCorrect":117},145879,"Use Amazon Redshift Spectrum to query data directly from S3 with data exported from Aurora.","Amazon Redshift Spectrum is useful for querying large datasets in S3, but exporting Aurora data to S3 could introduce latency and complicate the setup process.",{"id":230,"questionId":217,"content":231,"hint":232,"isCorrect":117},145880,"Use AWS Data Pipeline to migrate the data from Amazon Aurora to Amazon Redshift.","Although AWS Data Pipeline can move data between services, it requires setting up complex ETL jobs and might not be the most efficient method for real-time or frequent data synchronization.",{"id":234,"questionId":217,"content":235,"hint":236,"isCorrect":9},145881,"Use Amazon Redshift federated queries to query the data directly from Amazon Aurora.","Amazon Redshift federated queries allow you to query data across operational and analytic databases without moving data, thereby maintaining performance and ensuring up-to-date data.",{"id":238,"title":239,"subtitle":240,"description":96,"questions":241},122,"Understand data cataloging systems","Task 2.2",[242],{"id":243,"subcategoryId":238,"content":244,"hint":245,"isPublic":9,"answers":246},32283,"You are an AWS Certified Data Engineer working for a retail company. Your task is to catalog data stored in Amazon S3 so that it can be queried and analyzed easily. You choose to use AWS Glue for this task. You want to create a new connection in AWS Glue to your Amazon S3 bucket named 'retail-sales-data'.\n\nWhat are the necessary steps you should follow to successfully create this connection and catalog the data?\n\nA. Create an AWS Glue Data Catalog, then configure a Crawler to scan the Amazon S3 bucket and store the metadata in the Data Catalog.\nB. Upload the data to Amazon S3, create an Amazon RDS database, and configure the AWS Glue Crawler to use the RDS instance.\nC. Use AWS Glue’s ETL (Extract, Transform, Load) feature to transform the data in Amazon S3 and move it to Amazon Redshift.\nD. Download the AWS Glue data plugin and configure it to connect to the Amazon S3 bucket directly from your local machine.\n","Think about the services and steps you need specifically for cataloging and not necessarily for transforming or moving data.",[247,251,255,259],{"id":248,"questionId":243,"content":249,"hint":250,"isCorrect":117},146178,"Use AWS Glue’s ETL (Extract, Transform, Load) feature to transform the data in Amazon S3 and move it to Amazon Redshift.","While AWS Glue ETL can transform data and move it to Amazon Redshift, the question asks about cataloging the data, not moving or transforming it.",{"id":252,"questionId":243,"content":253,"hint":254,"isCorrect":117},146179,"Download the AWS Glue data plugin and configure it to connect to the Amazon S3 bucket directly from your local machine.","AWS Glue is managed through the AWS Management Console, not through downloading a plugin for local use.",{"id":256,"questionId":243,"content":257,"hint":258,"isCorrect":117},146180,"Upload the data to Amazon S3, create an Amazon RDS database, and configure the AWS Glue Crawler to use the RDS instance.","This option involves creating an Amazon RDS database, which is not necessary for cataloging data inside an Amazon S3 bucket using AWS Glue.",{"id":260,"questionId":243,"content":261,"hint":262,"isCorrect":9},146181,"Create an AWS Glue Data Catalog, then configure a Crawler to scan the Amazon S3 bucket and store the metadata in the Data Catalog.","AWS Glue Data Catalog is a central repository to store structural and operational metadata for all your data assets. Configuring a Crawler will automatically scan your Amazon S3 bucket and store metadata in the Data Catalog.",{"id":264,"title":265,"subtitle":266,"description":96,"questions":267},123,"Manage the lifecycle of data","Task 2.3",[268],{"id":269,"subcategoryId":264,"content":270,"hint":271,"isPublic":9,"answers":272},32370,"Alex, a Data Engineer at a financial services company, has been tasked with optimizing the storage cost management of their AWS environment. The company uses Amazon S3 for storing large volumes of transaction logs and DynamoDB for storing metadata about these transactions. In order to comply with regulatory requirements, the transaction logs must be kept for a minimum period, but after that, they can be moved to cheaper storage or deleted. Alex implements S3 versioning to protect against accidental deletions or overwrites and uses DynamoDB Time to Live (TTL) to automatically delete entries after their retention period expires. To further optimize storage costs, Alex wants to automate the process of moving older S3 objects to cheaper storage classes and eventually delete them. What should Alex do to optimize the lifecycle of the data in S3?","Consider S3 lifecycle policies that help in transitioning objects between storage classes and expiring them when no longer needed.",[273,277,281,285],{"id":274,"questionId":269,"content":275,"hint":276,"isCorrect":117},146526,"Enable S3 Intelligent-Tiering for all objects.","While S3 Intelligent-Tiering can automatically move objects between frequent and infrequent access tiers, it does not support transitions to Glacier or automatic deletions, which might be needed for cost optimization in the long term.",{"id":278,"questionId":269,"content":279,"hint":280,"isCorrect":9},146527,"Implement Amazon S3 Object Lifecycle Policies to automatically transition objects between storage classes and expire them after a defined period.","Amazon S3 Object Lifecycle Policies help in automating the transition of objects to cheaper storage classes like Infrequent Access, Glacier, or Glacier Deep Archive, and can also delete them after a specified period, optimizing the storage cost.",{"id":282,"questionId":269,"content":283,"hint":284,"isCorrect":117},146528,"Use S3 versioning alone to manage the lifecycle of objects.","S3 versioning helps in protecting against accidental deletions, but it does not provide automated transitions or deletions based on object age or other criteria.",{"id":286,"questionId":269,"content":287,"hint":288,"isCorrect":117},146529,"Manually move objects between storage classes periodically.","Manually moving objects is error-prone and not a scalable solution for a large number of objects. It also requires continuous monitoring and manual intervention.",{"id":290,"title":291,"subtitle":292,"description":96,"questions":293},124,"Design data models and schema evolution","Task 2.4",[294],{"id":295,"subcategoryId":290,"content":296,"hint":297,"isPublic":9,"answers":298},32460,"As a data engineer, you've been tasked with setting up a data pipeline to process and transform large sets of data from various sources. The data needs to be analyzed and used to train machine learning models in Amazon SageMaker. To design your data models and manage schema evolution effectively, you must establish data lineage throughout the pipeline to ensure data quality and traceability. Which AWS service should you use to automate the extraction, transformation, and loading (ETL) of data while also providing built-in capabilities for tracking data lineage?","Consider an AWS service that is specifically designed for ETL processes and integrates with other AWS services to track changes and transformations in the data lifecycle.",[299,303,307,311],{"id":300,"questionId":295,"content":301,"hint":302,"isCorrect":9},146886,"AWS Glue","AWS Glue is a managed ETL service that automatically discovers and profiles your data, generates the code to transform it, and tracks the data lineage, making it well-suited for establishing data lineage in data pipelines.",{"id":304,"questionId":295,"content":305,"hint":306,"isCorrect":117},146887,"Amazon Kinesis","Amazon Kinesis is designed for real-time data processing but does not provide built-in ETL capabilities or data lineage tracking.",{"id":308,"questionId":295,"content":309,"hint":310,"isCorrect":117},146888,"Amazon Redshift","Amazon Redshift is a data warehousing service that stores and queries large datasets efficiently but does not provide ETL capabilities or data lineage tracking by itself.",{"id":312,"questionId":295,"content":313,"hint":314,"isCorrect":117},146889,"AWS Data Pipeline","AWS Data Pipeline is used for data-driven workflows and orchestration but does not offer built-in functionality for ETL processes and detailed data lineage tracking like AWS Glue.",{"id":316,"title":317,"subtitle":318,"description":319,"content":96,"coverImageUrl":14,"weight":320,"subcategories":321},31,"Data Operations and Support","Domain 3","Emphasizes the automation, monitoring, and support of data pipelines. It includes maintaining data quality, troubleshooting, and ensuring the seamless operation of data processes using AWS tools.",22,[322,348,374,400],{"id":323,"title":324,"subtitle":325,"description":96,"questions":326},125,"Automate data processing by using AWS services","Task 3.1",[327],{"id":328,"subcategoryId":323,"content":329,"hint":330,"isPublic":9,"answers":331},32587,"You are a data engineer at a company that collects large volumes of data from IoT devices. The data is streamed into an S3 bucket in near real-time. Your task is to automate the processing of this data using AWS services. The processing needs to be triggered at the arrival of new files in the S3 bucket, and you have decided to use AWS Batch for the processing jobs.\n\nWhich combination of AWS services can be used to automate this data processing workflow?","Consider how you can set up an event trigger for new files in S3 and how that trigger can initiate a batch processing job.",[332,336,340,344],{"id":333,"questionId":328,"content":334,"hint":335,"isCorrect":9},147394,"Use Amazon EventBridge to detect new files in the S3 bucket and trigger an AWS Batch job with the necessary processing configurations.","Amazon EventBridge can capture S3 events and invoke an AWS Batch job to process the new data, effectively automating the data processing workflow.",{"id":337,"questionId":328,"content":338,"hint":339,"isCorrect":117},147395,"Use AWS Step Functions to orchestrate a workflow that checks for new files in S3 and then invokes an AWS Batch job.","AWS Step Functions can orchestrate complex workflows, but it does not inherently detect new files in S3. EventBridge is more suited for event-based triggering on S3 file arrivals.",{"id":341,"questionId":328,"content":342,"hint":343,"isCorrect":117},147396,"Use Amazon SQS to detect new files in the S3 bucket and trigger an AWS Lambda function.","Amazon SQS can be used for queuing messages, but it is not intended for directly detecting new files in an S3 bucket. Additionally, AWS Lambda may not be suitable for long-running batch processing jobs involving large datasets.",{"id":345,"questionId":328,"content":346,"hint":347,"isCorrect":117},147397,"Use Amazon CloudWatch Events to monitor S3 for new files and then use AWS Glue to process the data.","Amazon CloudWatch Events (now part of EventBridge) can monitor S3, but AWS Glue is better suited for ETL processes rather than batch processing jobs where AWS Batch is more appropriate.",{"id":349,"title":350,"subtitle":351,"description":96,"questions":352},126,"Analyze data by using AWS services","Task 3.2",[353],{"id":354,"subcategoryId":349,"content":355,"hint":356,"isPublic":9,"answers":357},32671,"You are a data engineer at a retail company, and you are conducting an analysis of customer purchase data stored in Amazon S3. You decide to use AWS Glue to clean and catalogue the data and then explore it using Amazon Athena notebooks powered by Apache Spark. You want to aggregate customer purchase amounts per region and create visual insights on customer spending trends. Which of the following steps should you follow to achieve your goal efficiently?","Consider the functionalities of AWS Glue and Amazon Athena notebooks with Apache Spark for preparing and analyzing data stored in Amazon S3.",[358,362,366,370],{"id":359,"questionId":354,"content":360,"hint":361,"isCorrect":117},147730,"Upload the data to Amazon DynamoDB, use AWS Lambda for processing, and then analyze with Amazon CloudWatch.","Amazon DynamoDB and CloudWatch are not suitable for this type of analytical task. The scenario requires using AWS Glue and Athena notebooks with Spark, not DynamoDB or Lambda.",{"id":363,"questionId":354,"content":364,"hint":365,"isCorrect":117},147731,"Use AWS QuickSight for direct visualization from Amazon S3 data and bypass Athena and Glue.","QuickSight is used for data visualization, but it bypasses the steps involving AWS Glue for cataloging and the specified use of Athena notebooks with Apache Spark for analysis, which is a key part of the scenario.",{"id":367,"questionId":354,"content":368,"hint":369,"isCorrect":117},147732,"Run AWS Glue ETL jobs to process the data directly in Amazon RDS, and then use Amazon Redshift for visualization.","While AWS Glue can process data and you can visualize using Redshift, the scenario specifies using Athena notebooks with Spark for analysis. Redshift would not be the tool for this requirement.",{"id":371,"questionId":354,"content":372,"hint":373,"isCorrect":9},147733,"Use AWS Glue to create a Data Catalog and ETL jobs, then use Athena notebooks with Spark to write SQL queries for data analysis and visualization.","AWS Glue provides the necessary tools for transforming and cataloguing the data, and Athena notebooks with Spark offer the ability to write SQL queries and perform interactive data analysis with visualization capabilities.",{"id":375,"title":376,"subtitle":377,"description":96,"questions":378},127,"Maintain and monitor data pipelines","Task 3.3",[379],{"id":380,"subcategoryId":375,"content":381,"hint":382,"isPublic":9,"answers":383},32791,"You are a data engineer at a company that processes massive amounts of log data generated by various microservices. The log data is stored in Amazon OpenSearch Service for real-time analysis and monitoring. Recently, you have observed that the OpenSearch cluster is running slower because it is overwhelmed with the growing number of logs. You need a solution to maintain and monitor your data pipeline effectively ensuring better performance of the OpenSearch cluster. What should you do?","Consider options that help in managing data volume and improving retrieval times for log data in Amazon OpenSearch Service.",[384,388,392,396],{"id":385,"questionId":380,"content":386,"hint":387,"isCorrect":9},148210,"Set up automated index rotation using Index State Management (ISM) in Amazon OpenSearch Service to manage the size and performance of your indices.","Index State Management (ISM) allows you to define policies to automate the management of indices' lifecycle, which helps to keep the OpenSearch cluster performant by controlling the size and age of indices.",{"id":389,"questionId":380,"content":390,"hint":391,"isCorrect":117},148211,"Use Amazon Athena to query OpenSearch logs directly and reduce the query load on the OpenSearch cluster.","Amazon Athena is not designed to query data stored in OpenSearch Service directly. Athena is optimized for querying data stored in Amazon S3.",{"id":393,"questionId":380,"content":394,"hint":395,"isCorrect":117},148212,"Increase the size of the OpenSearch cluster by adding more nodes.","Adding more nodes will temporarily alleviate the issue, but it does not address the root cause, which is the need for better index management to handle log data effectively.",{"id":397,"questionId":380,"content":398,"hint":399,"isCorrect":117},148213,"Manually delete old indices from the OpenSearch cluster at the end of each month.","While this might work, it is not a scalable or efficient solution. Manual solutions are prone to human error and do not provide the automation needed for a large-scale operation.",{"id":401,"title":402,"subtitle":403,"description":96,"questions":404},128,"Ensure data quality","Task 3.4",[405],{"id":406,"subcategoryId":401,"content":407,"hint":408,"isPublic":9,"answers":409},32862,"During a routine audit in your data processing pipeline, you discovered inconsistencies in the data stored in your Amazon S3 buckets. You suspect that the data transformations performed by AWS Glue DataBrew might be the root cause of the inconsistencies. As a Data Engineer, you need to investigate and ensure data quality in your pipeline. Which of the following approaches would be the most effective to identify and rectify the data inconsistencies?","Think about how data profiling or validation can be applied to ensure data quality before and after transformations.",[410,414,418,422],{"id":411,"questionId":406,"content":412,"hint":413,"isCorrect":117},148494,"Use AWS CloudTrail to log and monitor S3 API calls to identify any suspicious activities.","AWS CloudTrail logs S3 API calls and can help identify unauthorized or unexpected access patterns, but it doesn't provide the capability to profile or validate the actual data content for inconsistencies.",{"id":415,"questionId":406,"content":416,"hint":417,"isCorrect":117},148495,"Use Amazon S3 Inventory to check the consistency of data stored in the S3 buckets.","Amazon S3 Inventory provides a flat-file list of the objects in an S3 bucket, but it does not provide insights into the data quality or consistency within the objects themselves.",{"id":419,"questionId":406,"content":420,"hint":421,"isCorrect":117},148496,"Enable versioning on the S3 bucket to track changes to the data and restore previous versions.","While enabling versioning can help track changes and restore previous versions of data objects, it does not directly address or identify inconsistencies within the data itself.",{"id":423,"questionId":406,"content":424,"hint":425,"isCorrect":9},148497,"Use AWS Glue DataBrew to create and run profiling jobs and data quality rules on the datasets stored in Amazon S3.","AWS Glue DataBrew allows you to create profiling jobs to analyze data and understand its structure, patterns, and anomalies. Additionally, it supports data quality rules that can be applied to detect and rectify inconsistencies.",{"id":427,"title":428,"subtitle":429,"description":430,"content":96,"coverImageUrl":14,"weight":431,"subcategories":432},32,"Data Security and Governance","Domain 4","Involves implementing security measures within AWS environments, including authentication, authorization, encryption, and compliance. It also covers ensuring data privacy and preparing logs for audits",18,[433,459,484,510,536],{"id":434,"title":435,"subtitle":436,"description":96,"questions":437},129,"Apply authentication mechanisms","Task 4.1",[438],{"id":439,"subcategoryId":434,"content":440,"hint":441,"isPublic":9,"answers":442},32951,"You are a data engineer at a financial services company and are responsible for setting up a secure data pipeline. You've been asked to grant access to a specific Amazon S3 bucket only to your analytics team so they can run queries for the quarterly financial reports. The team members should only have read access to the bucket. You already have an IAM group named 'AnalyticsTeam'. To ensure security, you decide to use AWS PrivateLink to keep the data transfer within the AWS network. What is the best way to achieve this?","Consider how IAM policies can be applied to IAM groups and specific services like S3. Also, think about the security benefits of AWS PrivateLink in keeping data within the AWS network.",[443,447,451,455],{"id":444,"questionId":439,"content":445,"hint":446,"isCorrect":117},148850,"Attach an admin IAM policy to the 'AnalyticsTeam' group and enable AWS Direct Connect.","An admin IAM policy grants too many permissions, violating the principle of least privilege. AWS Direct Connect is not necessary for keeping data within the AWS network; AWS PrivateLink would be more appropriate here.",{"id":448,"questionId":439,"content":449,"hint":450,"isCorrect":117},148851,"Attach a read-only IAM policy to each individual user and configure an S3 VPC endpoint using AWS Direct Connect.","While it follows the least privilege principle, it is less efficient than attaching the policy to the group. AWS Direct Connect is not the right service for keeping data within the AWS network; AWS PrivateLink should be used.",{"id":452,"questionId":439,"content":453,"hint":454,"isCorrect":117},148852,"Add each user to the 'AnalyticsTeam' group but don't attach any additional policies. Configure an S3 VPC endpoint using AWS PrivateLink.","Simply adding users to the group without attaching any policies does not grant any permissions. Additional IAM policies are necessary to manage access rights.",{"id":456,"questionId":439,"content":457,"hint":458,"isCorrect":9},148853,"Attach a read-only IAM policy to the 'AnalyticsTeam' group and configure an S3 VPC endpoint using AWS PrivateLink.","This solution uses IAM policies to define the necessary read permissions and employs AWS PrivateLink to secure the data transfer by keeping it within the AWS network.",{"id":83,"title":460,"subtitle":461,"description":96,"questions":462},"Apply authorization mechanisms","Task 4.2",[463],{"id":464,"subcategoryId":83,"content":465,"hint":466,"isPublic":9,"answers":467},33031,"You are a data engineer at a company that uses Amazon Redshift, Amazon EMR, and Amazon S3 for big data analytics. To enhance your data security and governance, you are considering using AWS Lake Formation for managing data access permissions. A specific requirement is to ensure that the data engineers can run jobs on Amazon EMR clusters and have restricted access to only specific datasets stored in Amazon S3. How should you configure Lake Formation to meet this requirement?","Think about how Lake Formation integrates with access permissions and policies for both Amazon EMR and Amazon S3 datasets.",[468,472,476,480],{"id":469,"questionId":464,"content":470,"hint":471,"isCorrect":117},149170,"Use AWS Glue Data Catalog to manage permissions and then configure EMR to read from the Glue Data Catalog.","While AWS Glue Data Catalog helps with schema management, it does not provide sufficient permission management. Lake Formation is specifically designed for fine-grained access control.",{"id":473,"questionId":464,"content":474,"hint":475,"isCorrect":117},149171,"Configure bucket policies in Amazon S3 to restrict access to specific datasets and use these policies in EMR.","Bucket policies are less fine-grained compared to Lake Formation permissions and don't integrate well with EMRFS. This approach fails to leverage the full set of permission controls available through Lake Formation.",{"id":477,"questionId":464,"content":478,"hint":479,"isCorrect":9},149172,"Create Lake Formation permissions to grant the data engineers SELECT access to specific datasets and configure EMRFS to use Lake Formation.","Lake Formation permissions provide a fine-grained access control to datasets in Amazon S3, and EMRFS can leverage these permissions to access data securely on an EMR cluster.",{"id":481,"questionId":464,"content":482,"hint":483,"isCorrect":117},149173,"Create IAM policies granting S3 read access and configure Amazon EMR to use these policies.","IAM policies alone do not provide the fine-grained access control that Lake Formation offers. This approach does not leverage Lake Formation capabilities for managing data access permissions.",{"id":485,"title":486,"subtitle":487,"description":96,"questions":488},131,"Ensure data encryption and masking","Task 4.3",[489],{"id":490,"subcategoryId":485,"content":491,"hint":492,"isPublic":9,"answers":493},33112,"Acme Corp is migrating its data pipeline to AWS and wants to ensure that all data is encrypted in transit to comply with regulatory requirements. They have a stringent security policy that mandates the use of IAM policies to enforce encryption settings on all data transfers. As the lead Data Engineer, you need to configure IAM policies to ensure all S3 buckets can only be accessed via HTTPS. Which of the following IAM policy statements would best meet these requirements?","You'll need to focus on policies that explicitly define the conditions under which the S3 resources can be accessed, particularly regarding secure transport mechanisms.",[494,498,502,506],{"id":495,"questionId":490,"content":496,"hint":497,"isCorrect":117},149494,"{ \"Version\": \"2012-10-17\", \"Statement\": [ { \"Effect\": \"Allow\", \"Action\": \"s3:*\", \"Resource\": \"arn:aws:s3:::example-bucket\u002F*\", \"Condition\": { \"Bool\": { \"aws:SecureTransport\": \"false\" } } } ] }","This policy allows S3 actions without secure transport, which fails to meet the requirement of encryption in transit. Allowing with a `false` condition compromises security.",{"id":499,"questionId":490,"content":500,"hint":501,"isCorrect":9},149495,"{ \"Version\": \"2012-10-17\", \"Statement\": [ { \"Effect\": \"Deny\", \"Action\": \"s3:*\", \"Resource\": \"arn:aws:s3:::example-bucket\u002F*\", \"Condition\": { \"Bool\": { \"aws:SecureTransport\": \"false\" } } } ] }","This policy correctly denies any S3 action that does not use secure transport (HTTPS), thereby enforcing encryption in transit.",{"id":503,"questionId":490,"content":504,"hint":505,"isCorrect":117},149496,"{ \"Version\": \"2012-10-17\", \"Statement\": [ { \"Effect\": \"Deny\", \"Action\": \"s3:*\", \"Resource\": \"arn:aws:s3:::example-bucket\u002F*\", \"Condition\": { \"Bool\": { \"aws:SecureTransport\": \"true\" } } } ] }","This policy inadvertently denies any S3 action that uses secure transport, which is the opposite of the goal. The `true` condition should not trigger a deny.",{"id":507,"questionId":490,"content":508,"hint":509,"isCorrect":117},149497,"{ \"Version\": \"2012-10-17\", \"Statement\": [ { \"Effect\": \"Deny\", \"Action\": \"*\", \"Resource\": \"*\", \"Condition\": { \"Bool\": { \"aws:SecureTransport\": \"false\" } } } ] }","While this policy denies all actions without secure transport, it's overly broad and can unintentionally affect other AWS services beyond the S3 bucket. Specificity to S3 resources is required.",{"id":511,"title":512,"subtitle":513,"description":96,"questions":514},132,"Prepare logs for audit","Task 4.4",[515],{"id":516,"subcategoryId":511,"content":517,"hint":518,"isPublic":9,"answers":519},33192,"John is a data engineer responsible for managing log data generated by an Amazon EMR cluster running various data processing workloads. The cluster generates a high volume of log data that needs to be securely stored and retrieved for audit purposes. John also needs to ensure that only specific team members have access to these logs and that all access is properly logged for further auditing. He has decided to use Amazon S3 as the storage solution for the logs and needs to make sure that the security policies are set correctly using AWS Identity and Access Management (IAM). Which combination of IAM policies and AWS services should John implement to achieve the above requirements?","Think about the secure storage of logs, the principle of least privilege for access control, and comprehensive logging to track access patterns.",[520,524,528,532],{"id":521,"questionId":516,"content":522,"hint":523,"isCorrect":117},149814,"Store the logs on an EC2 instance with open access to everyone and use IAM roles to manage access.","This is insecure because storing logs on an EC2 instance with open access violates security best practices. It fails to control access strictly and is less reliable for long-term storage.",{"id":525,"questionId":516,"content":526,"hint":527,"isCorrect":9},149815,"Create an S3 bucket with server-side encryption enabled, implement IAM policies that grant read\u002Fwrite access only to specific team members, and enable AWS CloudTrail logging for S3 bucket access.","This approach ensures that logs are securely stored with encryption, access is restricted to specific individuals, and all access attempts are logged for auditing purposes.",{"id":529,"questionId":516,"content":530,"hint":531,"isCorrect":117},149816,"Use an S3 bucket with no encryption and grant public read-only access while using AWS CloudWatch for monitoring.","Not using encryption for sensitive log data is a security vulnerability. Granting public read-only access could lead to data breaches. While CloudWatch can monitor metrics, it does not log access activities for audit.",{"id":533,"questionId":516,"content":534,"hint":535,"isCorrect":117},149817,"Create an Amazon RDS database to store the log data and restrict access using database user accounts.","Amazon RDS is not optimized for storing and querying high volumes of log data efficiently. Additionally, it would require more complex maintenance and doesn't directly integrate IAM policies for fine-grained access control and audit logging as seamlessly as S3 with CloudTrail.",{"id":537,"title":538,"subtitle":539,"description":96,"questions":540},133,"Understand data privacy and governance","Task 4.5",[541],{"id":542,"subcategoryId":537,"content":543,"hint":544,"isPublic":9,"answers":545},33248,"You have recently joined a company as a data engineer. The company has a strict policy for data governance and data privacy. As part of the policy, all configuration changes within the AWS account need to be monitored and recorded meticulously. The company uses AWS Config for this purpose. Recently, several configuration changes were made to various AWS resources, and you need to verify if these changes comply with the company's policies. Which service or feature can you use to view the chronological order of configuration changes along with their details?","Think about the AWS service designed to track changes to configurations across your AWS resources.",[546,550,554,558],{"id":547,"questionId":542,"content":548,"hint":549,"isCorrect":117},150038,"AWS CloudTrail","AWS CloudTrail logs API calls and user activities but is not specifically designed for tracking configuration changes in detail. It primarily focuses on audit trails for API activity.",{"id":551,"questionId":542,"content":552,"hint":553,"isCorrect":117},150039,"Amazon CloudWatch","Amazon CloudWatch is used for monitoring and logging performance metrics, but it does not provide a detailed chronological view of configuration changes.",{"id":555,"questionId":542,"content":556,"hint":557,"isCorrect":117},150040,"AWS Trusted Advisor","AWS Trusted Advisor provides optimization recommendations for AWS resources, but it is not meant for viewing the historical configuration changes in chronological order.",{"id":559,"questionId":542,"content":560,"hint":561,"isCorrect":9},150041,"AWS Config Timeline","AWS Config Timeline allows you to view the historical changes and configuration details of supported AWS resources in chronological order, which is essential for verifying compliance with data governance policies.",[563,568,573,577,582,587,593,598,604,609,615,621,627,633,638,643,648,653,659,665,671,677,683,689,695,700,706,712,718,723,728,734,740,746,752,758,763,768,773,778,782,787,792,797,802,808,814,820,826,832,838,844,850,856,862,868,874,880,886,892,898,904,910,916,922,927,933,939,945,951],{"id":33,"title":564,"description":565,"slug":566,"coverImageUrl":567},"Amazon Athena","Amazon Athena is a query service for analyzing data in Amazon S3 using SQL, allowing direct data analysis in S3 without loading it into databases or warehouses.","amazon-athena","\u002Fimages\u002Fprovider-services\u002Famazon-athena\u002Fcovers\u002FArch_Amazon-Athena_64.png",{"id":52,"title":569,"description":570,"slug":571,"coverImageUrl":572},"Amazon EMR","Amazon EMR is a managed AWS service for large-scale data processing with frameworks like Hadoop and Spark, offering petabyte-scale analytics on a scalable infrastructure at a lower cost than owning Hadoop clusters.","amazon-emr","\u002Fimages\u002Fprovider-services\u002Famazon-emr\u002Fcovers\u002FArch_Amazon-EMR_64.png",{"id":43,"title":301,"description":574,"slug":575,"coverImageUrl":576},"Amazon Glue is a fully managed extract, transform, and load (ETL) service that simplifies data preparation and loading for analytics for both customers and users.","aws-glue","\u002Fimages\u002Fprovider-services\u002Faws-glue\u002Fcovers\u002FArch_AWS-Glue_64.png",{"id":24,"title":578,"description":579,"slug":580,"coverImageUrl":581},"AWS Lake Formation","AWS Lake Formation is a service by Amazon Web Services that simplifies the process of building, securing, and managing data lakes by automating much of the manual and time-consuming tasks involved, such as data ingestion, cleaning, cataloging, and securing.","aws-lake-formation","\u002Fimages\u002Fprovider-services\u002Faws-lake-formation\u002Fcovers\u002FArch_AWS-Lake-Formation_64.png",{"id":5,"title":583,"description":584,"slug":585,"coverImageUrl":586},"Amazon Managed Streaming for Apache Kafka","Amazon Managed Streaming for Apache Kafka (Amazon MSK) is a fully managed service that enables you to build and run applications that use Apache Kafka to process streaming data without having to manage the Kafka infrastructure.","amazon-managed-streaming-for-apache-kafka","\u002Fimages\u002Fprovider-services\u002Famazon-managed-streaming-for-apache-kafka\u002Fcovers\u002FArch_Amazon-Managed-Streaming-for-Apache-Kafka_64.png",{"id":588,"title":589,"description":590,"slug":591,"coverImageUrl":592},11,"Amazon OpenSearch Service","Amazon OpenSearch Service is a scalable and fully managed search and analytics service powered by the open source Elasticsearch and OpenSearch engines, designed for real-time application monitoring, log analytics, and search functionality.","amazon-opensearch-service","\u002Fimages\u002Fprovider-services\u002Famazon-opensearch-service\u002Fcovers\u002FArch_Amazon-OpenSearch-Service_64.png",{"id":594,"title":309,"description":595,"slug":596,"coverImageUrl":597},12,"Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud from Amazon Web Services (AWS), designed for large scale data set storage and analysis.","amazon-redshift","\u002Fimages\u002Fprovider-services\u002Famazon-redshift\u002Fcovers\u002FArch_Amazon-Redshift_64.png",{"id":599,"title":600,"description":601,"slug":602,"coverImageUrl":603},13,"Amazon QuickSight","Amazon QuickSight is a fast, cloud-powered business intelligence service that makes it easy to deliver insights to everyone in your organization by providing interactive visualizations, dashboards, and ML-powered insights.","amazon-quicksight","\u002Fimages\u002Fprovider-services\u002Famazon-quicksight\u002Fcovers\u002FArch_Amazon-QuickSight_64.png",{"id":431,"title":605,"description":606,"slug":607,"coverImageUrl":608},"Amazon AppFlow","Amazon AppFlow is a fully managed integration service that enables users to securely transfer data between Software as a Service (SaaS) applications like Salesforce, ServiceNow, and AWS services, and Amazon S3, facilitating automated workflows and data synchronization.","amazon-appflow","\u002Fimages\u002Fprovider-services\u002Famazon-appflow\u002Fcovers\u002FArch_Amazon-AppFlow_64.png",{"id":610,"title":611,"description":612,"slug":613,"coverImageUrl":614},21,"Amazon EventBridge","Amazon EventBridge is a serverless event bus service provided by AWS that enables applications to communicate with each other using events, facilitating the building of event-driven architectures.","amazon-eventbridge","\u002Fimages\u002Fprovider-services\u002Famazon-eventbridge\u002Fcovers\u002FArch_Amazon-EventBridge_64.png",{"id":616,"title":617,"description":618,"slug":619,"coverImageUrl":620},23,"Amazon Simple Notification Service (Amazon SNS)","Amazon Simple Notification Service (Amazon SNS) is a fully managed messaging service for both application-to-application (A2A) and application-to-person (A2P) communication, enabling the delivery of messages or notifications to subscribers or other applications.","amazon-simple-notification-service-(amazon-sns)","\u002Fimages\u002Fprovider-services\u002Famazon-simple-notification-service-(amazon-sns)\u002Fcovers\u002FArch_Amazon-Simple-Notification-Service_64.png",{"id":622,"title":623,"description":624,"slug":625,"coverImageUrl":626},24,"Amazon Simple Queue Service (Amazon SQS)","Amazon Simple Queue Service (Amazon SQS) is a scalable, fully managed message queuing service that enables the decoupling and scaling of microservices, distributed systems, and serverless applications.","amazon-simple-queue-service-(amazon-sqs)","\u002Fimages\u002Fprovider-services\u002Famazon-simple-queue-service-(amazon-sqs)\u002Fcovers\u002FArch_Amazon-Simple-Queue-Service_64.png",{"id":628,"title":629,"description":630,"slug":631,"coverImageUrl":632},25,"AWS Step Functions","AWS Step Functions is a cloud service from Amazon Web Services that enables developers to coordinate multiple AWS services into serverless workflows, allowing the creation and execution of complex business processes and applications through visual workflows.","aws-step-functions","\u002Fimages\u002Fprovider-services\u002Faws-step-functions\u002Fcovers\u002FArch_AWS-Step-Functions_64.png",{"id":209,"title":634,"description":635,"slug":636,"coverImageUrl":637},"AWS Budgets","AWS Budgets is a service provided by Amazon Web Services that enables users to set custom budget limits for their AWS costs and usage, allowing for alerts and actions based on specified thresholds.","aws-budgets","\u002Fimages\u002Fprovider-services\u002Faws-budgets\u002Fcovers\u002FArch_AWS-Budgets_64.png",{"id":205,"title":639,"description":640,"slug":641,"coverImageUrl":642},"AWS Cost Explorer","AWS Cost Explorer is a web service that allows users to visualize, understand, and manage their Amazon Web Services (AWS) costs and usage over time through detailed reports and analytics.","aws-cost-explorer","\u002Fimages\u002Fprovider-services\u002Faws-cost-explorer\u002Fcovers\u002FArch_AWS-Cost-Explorer_64.png",{"id":427,"title":644,"description":645,"slug":646,"coverImageUrl":647},"AWS Batch","AWS Batch is a cloud service offered by Amazon Web Services that enables developers and scientists to easily and efficiently run hundreds to thousands of batch computing jobs on the AWS Cloud, automatically managing the provisioning of the compute resources and scaling them up or down as needed to optimize for performance and cost.","aws-batch","\u002Fimages\u002Fprovider-services\u002Faws-batch\u002Fcovers\u002FArch_AWS-Batch_64.png",{"id":97,"title":649,"description":650,"slug":651,"coverImageUrl":652},"Amazon EC2","Amazon EC2 (Elastic Compute Cloud) is a web service that provides resizable compute capacity in the cloud, allowing users to run and manage virtual servers.","amazon-ec2","\u002Fimages\u002Fprovider-services\u002Famazon-ec2\u002Fcovers\u002FArch_Amazon-EC2_64.png",{"id":654,"title":655,"description":656,"slug":657,"coverImageUrl":658},48,"Amazon Elastic Container Registry (Amazon ECR)","Amazon Elastic Container Registry (Amazon ECR) is a fully managed Docker container registry that makes it easy for developers to store, manage, and deploy Docker container images.","amazon-elastic-container-registry-(amazon-ecr)","\u002Fimages\u002Fprovider-services\u002Famazon-elastic-container-registry-(amazon-ecr)\u002Fcovers\u002FArch_Amazon-Elastic-Container-Registry_64.png",{"id":660,"title":661,"description":662,"slug":663,"coverImageUrl":664},54,"Amazon Elastic Container Service (Amazon ECS)","Amazon Elastic Container Service (Amazon ECS) is a fully managed container orchestration service that allows you to run and scale containerized applications on AWS.","amazon-elastic-container-service-(amazon-ecs)","\u002Fimages\u002Fprovider-services\u002Famazon-elastic-container-service-(amazon-ecs)\u002Fcovers\u002FArch_Amazon-Elastic-Container-Service_64.png",{"id":666,"title":667,"description":668,"slug":669,"coverImageUrl":670},55,"Amazon Elastic Kubernetes Service (Amazon EKS)","Amazon Elastic Kubernetes Service (Amazon EKS) is a managed service that makes it easy to deploy, manage, and scale containerized applications using Kubernetes on AWS.","amazon-elastic-kubernetes-service-(amazon-eks)","\u002Fimages\u002Fprovider-services\u002Famazon-elastic-kubernetes-service-(amazon-eks)\u002Fcovers\u002FArch_Amazon-Elastic-Kubernetes-Service_64.png",{"id":672,"title":673,"description":674,"slug":675,"coverImageUrl":676},59,"Amazon DocumentDB (with MongoDB compatibility)","Amazon DocumentDB (with MongoDB compatibility) is a fully managed, scalable, and highly available document database service designed to be compatible with MongoDB workloads, allowing you to use MongoDB tools and drivers for managing and querying your data.","amazon-documentdb-(with-mongodb-compatibility)","\u002Fimages\u002Fprovider-services\u002Famazon-documentdb-(with-mongodb-compatibility)\u002Fcovers\u002FArch_Amazon-DocumentDB_64.png",{"id":678,"title":679,"description":680,"slug":681,"coverImageUrl":682},60,"Amazon DynamoDB","Amazon DynamoDB is a fully managed NoSQL database service provided by Amazon Web Services (AWS) that offers fast and predictable performance with seamless scalability for applications that need consistent, single-digit millisecond latency at any scale.","amazon-dynamodb","\u002Fimages\u002Fprovider-services\u002Famazon-dynamodb\u002Fcovers\u002FArch_Amazon-DynamoDB_64.png",{"id":684,"title":685,"description":686,"slug":687,"coverImageUrl":688},62,"Amazon Keyspaces (for Apache Cassandra)","Amazon Keyspaces (for Apache Cassandra) is a scalable, highly available, and managed Apache Cassandra-compatible database service offered by Amazon Web Services for running Cassandra workloads on AWS without needing to manage the underlying infrastructure.","amazon-keyspaces-(for-apache-cassandra)","\u002Fimages\u002Fprovider-services\u002Famazon-keyspaces-(for-apache-cassandra)\u002Fcovers\u002FArch_Amazon-Keyspaces_64.png",{"id":690,"title":691,"description":692,"slug":693,"coverImageUrl":694},63,"Amazon Neptune","Amazon Neptune is a fast, reliable, and fully managed graph database service that makes it easy to build and run applications that work with highly connected datasets.","amazon-neptune","\u002Fimages\u002Fprovider-services\u002Famazon-neptune\u002Fcovers\u002FArch_Amazon-Neptune_64.png",{"id":81,"title":696,"description":697,"slug":698,"coverImageUrl":699},"Amazon RDS","Amazon RDS (Relational Database Service) is a managed service provided by Amazon Web Services (AWS) that makes it easier to set up, operate, and scale a relational database in the cloud by handling routine database tasks such as provisioning, patching, backup, recovery, and scaling.","amazon-rds","\u002Fimages\u002Fprovider-services\u002Famazon-rds\u002Fcovers\u002FArch_Amazon-RDS_64.png",{"id":701,"title":702,"description":703,"slug":704,"coverImageUrl":705},73,"Amazon API Gateway","Amazon API Gateway is a fully managed service that makes it easy for developers to create, publish, maintain, monitor, and secure APIs at any scale, providing a way to facilitate communication between software applications through web services.","amazon-api-gateway","\u002Fimages\u002Fprovider-services\u002Famazon-api-gateway\u002Fcovers\u002FArch_Amazon-API-Gateway_64.png",{"id":707,"title":708,"description":709,"slug":710,"coverImageUrl":711},83,"Amazon SageMaker","Amazon SageMaker is a fully managed service that provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly.","amazon-sagemaker","\u002Fimages\u002Fprovider-services\u002Famazon-sagemaker\u002Fcovers\u002FArch_Amazon-SageMaker_64.png",{"id":713,"title":714,"description":715,"slug":716,"coverImageUrl":717},92,"AWS CloudFormation","AWS CloudFormation is a service that enables users to model, provision, and manage AWS and third-party application resources in a safe, repeatable, and efficient manner using templates.","aws-cloudformation","\u002Fimages\u002Fprovider-services\u002Faws-cloudformation\u002Fcovers\u002FArch_AWS-CloudFormation_64.png",{"id":719,"title":548,"description":720,"slug":721,"coverImageUrl":722},93,"AWS CloudTrail is a service that provides a comprehensive log of user activity and API usage across the AWS infrastructure, enabling security monitoring, compliance auditing, and operational troubleshooting.","aws-cloudtrail","\u002Fimages\u002Fprovider-services\u002Faws-cloudtrail\u002Fcovers\u002FArch_AWS-CloudTrail_64.png",{"id":724,"title":552,"description":725,"slug":726,"coverImageUrl":727},95,"Amazon CloudWatch is a monitoring and observability service offered by Amazon Web Services (AWS) that provides data and actionable insights to monitor applications, respond to system-wide performance changes, optimize resource utilization, and get a unified view of operational health.","amazon-cloudwatch","\u002Fimages\u002Fprovider-services\u002Famazon-cloudwatch\u002Fcovers\u002FArch_Amazon-CloudWatch_64.png",{"id":729,"title":730,"description":731,"slug":732,"coverImageUrl":733},96,"AWS Command Line Interface (AWS CLI)","The AWS Command Line Interface (AWS CLI) is a unified tool that allows you to manage and automate AWS services directly from the terminal or command prompt.","aws-command-line-interface-(aws-cli)","\u002Fimages\u002Fprovider-services\u002Faws-command-line-interface-(aws-cli)\u002Fcovers\u002FArch_AWS-Command-Line-Interface_64.png",{"id":735,"title":736,"description":737,"slug":738,"coverImageUrl":739},98,"AWS Config","AWS Config is a service that enables you to assess, audit, and evaluate the configurations of your AWS resources, providing a detailed view of their compliance with the configurations specified by your internal guidelines and regulatory standards.","aws-config","\u002Fimages\u002Fprovider-services\u002Faws-config\u002Fcovers\u002FArch_AWS-Config_64.png",{"id":741,"title":742,"description":743,"slug":744,"coverImageUrl":745},102,"Amazon Managed Grafana","Amazon Managed Grafana is a fully managed service by AWS that provides scalable, secure, and easily deployable visualizations for real-time analytics, operational dashboards, and monitoring across various data sources.","amazon-managed-grafana","\u002Fimages\u002Fprovider-services\u002Famazon-managed-grafana\u002Fcovers\u002FArch_Amazon-Managed-Grafana_64.png",{"id":747,"title":748,"description":749,"slug":750,"coverImageUrl":751},112,"AWS Systems Manager","AWS Systems Manager is a management service that provides visibility and control over your AWS resources, enabling you to automate operational tasks, gather system inventory, apply OS patches, automate the creation of Amazon Machine Images, and configure your operating systems and applications.","aws-systems-manager","\u002Fimages\u002Fprovider-services\u002Faws-systems-manager\u002Fcovers\u002FArch_AWS-Systems-Manager_64.png",{"id":753,"title":754,"description":755,"slug":756,"coverImageUrl":757},114,"AWS Well-Architected Tool","The AWS Well-Architected Tool is a cloud service provided by Amazon Web Services that offers a set of questions across five pillars: operational excellence, security, reliability, performance efficiency, and cost optimizations to help users review the state of their workloads and compare them against AWS architectural best practices.","aws-well-architected-tool","\u002Fimages\u002Fprovider-services\u002Faws-well-architected-tool\u002Fcovers\u002FArch_AWS-Well-Architected-Tool_64.png",{"id":153,"title":759,"description":760,"slug":761,"coverImageUrl":762},"AWS Application Discovery Service","AWS Application Discovery Service is a cloud-based service designed to help enterprise customers streamline migration planning by automatically identifying and cataloging applications and dependencies running in on-premises data centers.","aws-application-discovery-service","\u002Fimages\u002Fprovider-services\u002Faws-application-discovery-service\u002Fcovers\u002FArch_AWS-Application-Discovery-Service_64.png",{"id":212,"title":764,"description":765,"slug":766,"coverImageUrl":767},"AWS Application Migration Service","AWS Application Migration Service is a service that simplifies the process of migrating applications to AWS, enabling organizations to move applications without making changes to them, at scale and with minimal downtime.","aws-application-migration-service","\u002Fimages\u002Fprovider-services\u002Faws-application-migration-service\u002Fcovers\u002FArch_AWS-Application-Migration-Service_64.png",{"id":238,"title":769,"description":770,"slug":771,"coverImageUrl":772},"AWS Database Migration Service (AWS DMS)","AWS Database Migration Service (AWS DMS) is a cloud service that simplifies the migration of relational databases, data warehouses, NoSQL databases, and other types of data stores to AWS, between on-premises instances, or between different AWS services, with minimal downtime.","aws-database-migration-service-(aws-dms)","\u002Fimages\u002Fprovider-services\u002Faws-database-migration-service-(aws-dms)\u002Fcovers\u002FArch_AWS-DataSync_64.png",{"id":264,"title":774,"description":775,"slug":776,"coverImageUrl":777},"AWS DataSync","AWS DataSync is a data transfer service that facilitates the migration, replication, and synchronization of data between on-premises storage systems, AWS Storage services, and edge storage devices quickly and securely.","aws-datasync","\u002Fimages\u002Fprovider-services\u002Faws-datasync\u002Fcovers\u002FArch_AWS-DataSync_64.png",{"id":323,"title":779,"description":780,"slug":781,"coverImageUrl":14},"AWS Snow Family","The AWS Snow Family is a collection of physical devices and services designed by Amazon Web Services to facilitate data migration and edge computing tasks by transferring large volumes of data into and out of the AWS cloud securely and efficiently, without relying solely on internet connectivity.","aws-snow-family",{"id":349,"title":783,"description":784,"slug":785,"coverImageUrl":786},"AWS Transfer Family","AWS Transfer Family is a fully managed service by Amazon Web Services that facilitates the secure transfer of files over protocols like SFTP, FTPS, and FTP directly into and out of Amazon S3 or Amazon EFS.","aws-transfer-family","\u002Fimages\u002Fprovider-services\u002Faws-transfer-family\u002Fcovers\u002FArch_AWS-Transfer-Family_64.png",{"id":401,"title":788,"description":789,"slug":790,"coverImageUrl":791},"Amazon CloudFront","Amazon CloudFront is a fast content delivery network (CDN) service that securely delivers data, videos, applications, and APIs to customers globally with low latency, high transfer speeds, all within a developer-friendly environment.","amazon-cloudfront","\u002Fimages\u002Fprovider-services\u002Famazon-cloudfront\u002Fcovers\u002FArch_Amazon-CloudFront_64.png",{"id":511,"title":793,"description":794,"slug":795,"coverImageUrl":796},"AWS PrivateLink","AWS PrivateLink is a networking service that allows AWS customers to securely access services across the Amazon Web Services (AWS) network in a private manner, without using public IPs or requiring the traffic to traverse the public internet.","aws-privatelink","\u002Fimages\u002Fprovider-services\u002Faws-privatelink\u002Fcovers\u002FArch_AWS-PrivateLink_64.png",{"id":537,"title":798,"description":799,"slug":800,"coverImageUrl":801},"Amazon Route 53","Amazon Route 53 is a scalable cloud Domain Name System (DNS) web service designed to give developers and businesses a reliable way to route end users to Internet applications by translating names like www.example.com into the numeric IP addresses like 192.0.2.1 that computers use to connect to each other.","amazon-route-53","\u002Fimages\u002Fprovider-services\u002Famazon-route-53\u002Fcovers\u002FArch_Amazon-Route-53_64.png",{"id":803,"title":804,"description":805,"slug":806,"coverImageUrl":807},136,"Amazon VPC","Amazon VPC (Virtual Private Cloud) is a service that allows users to launch AWS resources in a logically isolated virtual network that they can define and control, including IP address ranges, subnets, route tables, and gateways.","amazon-vpc","\u002Fimages\u002Fprovider-services\u002Famazon-vpc\u002Fcovers\u002FVirtual-private-cloud-VPC_32.png",{"id":809,"title":810,"description":811,"slug":812,"coverImageUrl":813},148,"AWS IAM Identity Center (AWS Single Sign-On)","AWS IAM Identity Center (formerly AWS Single Sign-On) is a cloud service that enables secure and unified authentication for users to access AWS accounts and business applications with a single set of credentials.","aws-iam-identity-center-(aws-single-sign-on)","\u002Fimages\u002Fprovider-services\u002Faws-iam-identity-center-(aws-single-sign-on)\u002Fcovers\u002FArch_AWS-IAM-Identity-Center_64.png",{"id":815,"title":816,"description":817,"slug":818,"coverImageUrl":819},149,"AWS Identity and Access Management (IAM)","AWS Identity and Access Management (IAM) is a cloud service that helps securely control access to AWS resources by allowing you to create and manage AWS users and groups, and use permissions to allow and deny their access to AWS resources.","aws-identity-and-access-management-(iam)","\u002Fimages\u002Fprovider-services\u002Faws-identity-and-access-management-(iam)\u002Fcovers\u002FArch_AWS-Identity-and-Access-Management_64.png",{"id":821,"title":822,"description":823,"slug":824,"coverImageUrl":825},152,"Amazon Macie","Amazon Macie is a fully managed data security and data privacy service that uses machine learning and pattern matching to discover and protect sensitive data in AWS.","amazon-macie","\u002Fimages\u002Fprovider-services\u002Famazon-macie\u002Fcovers\u002FArch_Amazon-Macie_64.png",{"id":827,"title":828,"description":829,"slug":830,"coverImageUrl":831},155,"AWS Secrets Manager","AWS Secrets Manager is a service provided by Amazon Web Services that enables users to securely store, manage, and retrieve sensitive information such as API keys, passwords, and database credentials.","aws-secrets-manager","\u002Fimages\u002Fprovider-services\u002Faws-secrets-manager\u002Fcovers\u002FArch_AWS-Secrets-Manager_64.png",{"id":833,"title":834,"description":835,"slug":836,"coverImageUrl":837},157,"AWS Shield","AWS Shield is a managed Distributed Denial of Service (DDoS) protection service that safeguards applications running on AWS against DDoS attacks.","aws-shield","\u002Fimages\u002Fprovider-services\u002Faws-shield\u002Fcovers\u002FArch_AWS-Shield_64.png",{"id":839,"title":840,"description":841,"slug":842,"coverImageUrl":843},158,"AWS WAF","AWS WAF (Web Application Firewall) is a web application firewall service that helps protect web applications and APIs from common web exploits and bots that may affect availability, compromise security, or consume excessive resources.","aws-waf","\u002Fimages\u002Fprovider-services\u002Faws-waf\u002Fcovers\u002FArch_AWS-WAF_64.png",{"id":845,"title":846,"description":847,"slug":848,"coverImageUrl":849},168,"AWS Lambda","AWS Lambda is a serverless computing service provided by Amazon Web Services that allows developers to run code in response to events without provisioning or managing servers.","aws-lambda","\u002Fimages\u002Fprovider-services\u002Faws-lambda\u002Fcovers\u002FArch_AWS-Lambda_64.png",{"id":851,"title":852,"description":853,"slug":854,"coverImageUrl":855},169,"AWS Backup","AWS Backup is a fully managed backup service that makes it easy to centralize and automate the backup of data across AWS services in the cloud and on-premises.","aws-backup","\u002Fimages\u002Fprovider-services\u002Faws-backup\u002Fcovers\u002FArch_AWS-Backup_64.png",{"id":857,"title":858,"description":859,"slug":860,"coverImageUrl":861},170,"Amazon Elastic Block Store (Amazon EBS)","Amazon Elastic Block Store (Amazon EBS) is a high-performance block storage service designed for use with Amazon Elastic Compute Cloud (EC2) for both throughput and transaction-intensive workloads at any scale.","amazon-elastic-block-store-(amazon-ebs)","\u002Fimages\u002Fprovider-services\u002Famazon-elastic-block-store-(amazon-ebs)\u002Fcovers\u002FArch_Amazon-Elastic-Block-Store_64.png",{"id":863,"title":864,"description":865,"slug":866,"coverImageUrl":867},171,"Amazon Elastic File System (Amazon EFS)","Amazon Elastic File System (Amazon EFS) is a cloud-based file storage service offered by Amazon Web Services (AWS) that provides a simple, scalable, elastic file system for use with AWS Cloud services and on-premise resources.","amazon-elastic-file-system-(amazon-efs)","\u002Fimages\u002Fprovider-services\u002Famazon-elastic-file-system-(amazon-efs)\u002Fcovers\u002FArch_Amazon-EFS_64.png",{"id":869,"title":870,"description":871,"slug":872,"coverImageUrl":873},173,"Amazon S3","Amazon S3 (Simple Storage Service) is a scalable cloud storage service offered by Amazon Web Services (AWS) that allows users to store and retrieve any amount of data from anywhere on the web.","amazon-s3","\u002Fimages\u002Fprovider-services\u002Famazon-s3\u002Fcovers\u002FArch_Amazon-Simple-Storage-Service_64.png",{"id":875,"title":876,"description":877,"slug":878,"coverImageUrl":879},174,"Amazon S3 Glacier","Amazon S3 Glacier is a secure, low-cost cloud storage service provided by Amazon Web Services (AWS) designed for data archiving and long-term backup, offering highly durable storage with retrieval times ranging from minutes to hours.","amazon-s3-glacier","\u002Fimages\u002Fprovider-services\u002Famazon-s3-glacier\u002Fcovers\u002FArch_Amazon-Simple-Storage-Service-Glacier_64.png",{"id":881,"title":882,"description":883,"slug":884,"coverImageUrl":885},179,"Amazon Managed Workflows for Apache Airflow (Amazon MWAA)","Amazon Managed Workflows for Apache Airflow (Amazon MWAA) is a cloud service that orchestrates complex data workflows, allowing users to manage, execute, and scale Apache Airflow environments on the AWS cloud without managing the underlying infrastructure.","amazon-managed-workflows-for-apache-airflow-(amazon-mwaa)","\u002Fimages\u002Fprovider-services\u002Famazon-managed-workflows-for-apache-airflow-(amazon-mwaa)\u002Fcovers\u002FArch_Amazon-Managed-Workflows-for-Apache-Airflow_64.png",{"id":887,"title":888,"description":889,"slug":890,"coverImageUrl":891},184,"AWS Cloud9","AWS Cloud9 is a cloud-based integrated development environment (IDE) that provides a platform for writing, running, and debugging code with just a browser, offering a seamless experience for developing serverless applications, allowing collaboration in real-time among developers.","aws-cloud9","\u002Fimages\u002Fprovider-services\u002Faws-cloud9\u002Fcovers\u002FArch_AWS-Cloud9_64.png",{"id":893,"title":894,"description":895,"slug":896,"coverImageUrl":897},185,"AWS Cloud Development Kit (AWS CDK)","The AWS Cloud Development Kit (AWS CDK) is an open-source software development framework designed to model and provision cloud application resources using familiar programming languages.","aws-cloud-development-kit-(aws-cdk)","\u002Fimages\u002Fprovider-services\u002Faws-cloud-development-kit-(aws-cdk)\u002Fcovers\u002FArch_AWS-Cloud-Development-Kit_64.png",{"id":899,"title":900,"description":901,"slug":902,"coverImageUrl":903},189,"AWS CodeBuild","AWS CodeBuild is a fully managed build service that compiles source code, runs tests, and produces software packages ready to deploy, without the need for provisioning, managing, or scaling your own build servers.","aws-codebuild","\u002Fimages\u002Fprovider-services\u002Faws-codebuild\u002Fcovers\u002FArch_AWS-CodeBuild_64.png",{"id":905,"title":906,"description":907,"slug":908,"coverImageUrl":909},190,"AWS CodeCommit","AWS CodeCommit is a secure, highly scalable, managed source control service hosted by Amazon Web Services that makes it easy for teams to collaboratively manage and store their code repositories in the cloud.","aws-codecommit","\u002Fimages\u002Fprovider-services\u002Faws-codecommit\u002Fcovers\u002FArch_AWS-CodeCommit_64.png",{"id":911,"title":912,"description":913,"slug":914,"coverImageUrl":915},191,"AWS CodeDeploy","AWS CodeDeploy is a fully managed deployment service that automates software deployments to a variety of compute services such as Amazon EC2, AWS Fargate, AWS Lambda, and your on-premises servers.","aws-codedeploy","\u002Fimages\u002Fprovider-services\u002Faws-codedeploy\u002Fcovers\u002FArch_AWS-CodeDeploy_64.png",{"id":917,"title":918,"description":919,"slug":920,"coverImageUrl":921},246,"Amazon MemoryDB for Redis","Amazon MemoryDB for Redis is a fully managed, in-memory database service that provides a highly available, scalable, and compatible layer for Redis, designed to deliver ultra-fast performance for data-intensive applications.","amazon-memorydb-for-redis","\u002Fimages\u002Fprovider-services\u002Famazon-memorydb-for-redis\u002Fcovers\u002FArch_Amazon-MemoryDB-for-Redis_64.png",{"id":923,"title":924,"description":925,"slug":926,"coverImageUrl":14},268,"AWS Schema Conversion Tool (AWS SCT)","The AWS Schema Conversion Tool (AWS SCT) is a software application that facilitates the migration of database schemas and certain business logic from one database engine to another, by automatically converting the source database schema and a majority of the custom code to a format compatible with the target database.","aws-schema-conversion-tool-(aws-sct)",{"id":928,"title":929,"description":930,"slug":931,"coverImageUrl":932},274,"Amazon Kinesis Data Firehose","Amazon Kinesis Data Firehose is a fully managed service designed to load streaming data in real time into data lakes, data stores, and analytics services such as Amazon S3, Amazon Redshift, Amazon Elasticsearch Service, and Splunk.","amazon-kinesis-data-firehose","\u002Fimages\u002Fprovider-services\u002Famazon-kinesis-data-firehose\u002Fcovers\u002FArch_Amazon-Kinesis-Data-Firehose_64.png",{"id":934,"title":935,"description":936,"slug":937,"coverImageUrl":938},275,"Amazon Kinesis Data Streams","Amazon Kinesis Data Streams is a scalable and durable real-time data streaming service that enables developers to continuously capture gigabytes of data per second from hundreds of thousands of sources such as website clickstreams, database event streams, financial transactions, social media feeds, IT logs, and location-tracking events.","amazon-kinesis-data-streams","\u002Fimages\u002Fprovider-services\u002Famazon-kinesis-data-streams\u002Fcovers\u002FArch_Amazon-Kinesis-Data-Streams_64.png",{"id":940,"title":941,"description":942,"slug":943,"coverImageUrl":944},279,"AWS CodePipeline","AWS CodePipeline is a continuous integration and continuous delivery (CI\u002FCD) service for fast and reliable application and infrastructure updates.","aws-codepipeline","\u002Fimages\u002Fprovider-services\u002Faws-codepipeline\u002Fcovers\u002FArch_AWS-CodePipeline_64.png",{"id":946,"title":947,"description":948,"slug":949,"coverImageUrl":950},288,"Amazon Managed Service for Apache Flink","Amazon Managed Service for Apache Flink is a fully managed service that allows you to build and run applications that use Apache Flink - an open-source framework and engine for processing big data streams - without the need for infrastructure management.","amazon-managed-service-for-apache-flink","\u002Fimages\u002Fprovider-services\u002Famazon-managed-service-for-apache-flink\u002Fcovers\u002FArch_Amazon-Managed-Service-for-Apache-Flink_64.png",{"id":952,"title":953,"description":954,"slug":955,"coverImageUrl":14},289,"AWS Serverless Application Model (AWS SAM)","AWS Serverless Application Model (AWS SAM) is a framework for building serverless applications that simplifies the process of defining, deploying, and managing serverless infrastructure on AWS using familiar infrastructure as code techniques.","aws-serverless-application-model-(aws-sam)",[],1790430979443]