Category: Learning Levels

Large organizations processing huge volumes of data usually store it in Amazon Simple Storage Service (Amazon S3) and query the data to make data-driven business decisions using distributed analytics engines such as Amazon Athena. If you simply run queries without considering the optimal data layout on Amazon S3, it results in a high volume of […]

Using Amazon OpenSearch Service’s vector database capabilities, you can implement semantic search, Retrieval Augmented Generation (RAG) with LLMs, recommendation engines, and search in rich media. Learn how.

Amazon Redshift is a fast, petabyte-scale cloud data warehouse that makes it simple and cost-effective to analyze all of your data using standard SQL. Tens of thousands of customers today rely on Amazon Redshift to analyze exabytes of data and run complex analytical queries, making it the most widely used cloud data warehouse. You can […]

Amazon DynamoDB is a fully managed NoSQL service that delivers single-digit millisecond performance at any scale. It’s used by thousands of customers for mission-critical workloads. Typical use cases for DynamoDB are an ecommerce application handling a high volume of transactions, or a gaming application that needs to maintain scorecards for players and games. In traditional […]

February 9, 2024: Amazon Kinesis Data Firehose has been renamed to Amazon Data Firehose. Read the AWS What’s New post to learn more. It’s common to store the logs generated by customer’s applications and services in various tools. These logs are important for compliance, audits, troubleshooting, security incident responses, meeting security policies, and many other […]

Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon Simple Storage Service (Amazon S3) and data sources residing in AWS, on-premises, or other cloud systems using SQL or Python. Athena is built on open-source Trino and Presto engines, and Apache Spark frameworks, with no provisioning or configuration effort […]

With Amazon Managed Streaming for Apache Kafka (Amazon MSK), you can build and run applications that use Apache Kafka to process streaming data. To process streaming data, organizations either use multiple Kafka clusters based on their application groupings, usage scenarios, compliance requirements, and other factors, or a dedicated Kafka cluster for the entire organization. It […]

Kafka quotas are integral to multi-tenant Kafka clusters. They prevent Kafka cluster performance from being negatively affected by poorly behaved applications overconsuming cluster resources. Furthermore, they enable the central streaming data platform to be operated as a multi-tenant platform and used by downstream and upstream applications across multiple business lines. Kafka supports two types of quotas: […]

With the recent introduction of Amazon Security Lake, it has never been simpler to access all your security-related data in one place. Whether it’s findings from AWS Security Hub, DNS query data from Amazon Route 53, network events such as VPC Flow Logs, or third-party integrations provided by partners such as Barracuda Email Protection, Cisco […]

In today’s world, customers manage vast amounts of data in their Amazon Simple Storage Service (Amazon S3) data lakes, which requires convoluted data pipelines to continuously understand the changes in the data layout and make them available to consuming systems. AWS Glue crawlers provide a straightforward way to catalog data in the AWS Glue Data […]