Articles tagged with "AWS"

In cloud computing, security is a critical concern. While AWS provides backup solutions for many resources, custom configurations often require additional protection. Two key services, AWS Key Management Service (KMS) and AWS Secrets Manager, don’t offer direct backup options. However, they implement a deletion grace period— by default 30 days and this is the maximum — allowing for potential restoration.

Amazon OpenSearch Service is a powerful tool for search, log analytics, and RAG (Retrieval-Augmented Generation) systems. To ensure optimal performance and reliability, effective monitoring is crucial.

Amazon SageMaker offers a highly customizable platform for machine learning at scale. Job execution within Amazon SageMaker can take some time to set up, which can be inconvenient or even time consuming during development and debugging phases. Running training and processing jobs locally can greatly increase the speed of development and debugging before running them at scale on AWS.

In this blog post, I will demonstrate how to leverage Suricata with the AWS Gateway Load Balancer and Terraform to implement a highly available, scalable, and cost-effective IDS/IPS solution in AWS. This approach will enable you to monitor network traffic, detect threats, and block them before they reach your systems.

When developing applications, particularly in the realm of containerization, CI/CD workflows and pipelines play an important role in ensuring automated testing, security scanning, and seamless deployment. Leveraging a pipeline-based approach enables fast and secure shipping of new features by adhering to a standardized set of procedures and principles. Using the AWS cloud’s flexibility amplifies this process, facilitating even faster development cycles and dependable software delivery. In this blog post, I aim to demonstrate how you can leverage AWS CodePipeline and Amazon ECS alongside Terraform to implement an automated CI/CD pipeline. This pipeline efficiently handles the building, testing, and deployment of containerized applications, streamlining your development and delivery processes.

This guide empowers you to optimize OpenSearch for lightning-fast and accurate phone number searches. Frustration-free experiences are key for your customers, and by leveraging edge ngrams and custom analyzers, you can empower OpenSearch to efficiently handle even large datasets.

In today’s data-driven world, effective data management is crucial for organizations aiming to make well-informed, data-driven decisions. As the importance of data continues to grow, so does the significance of robust data management practices. This includes the processes of ingesting, storing, organizing, and maintaining the data generated and collected by an organization. Within the realm of data management, schema evolution stands out as one of the most critical aspects. Businesses evolve over time, leading to changes in data and, consequently, changes in corresponding schemas. Even though a schema may be initially defined for your data, evolving business requirements inevitably demand schema modifications. Yet, modifying data structures is no straightforward task, especially when dealing with distributed systems and teams. It’s essential that downstream consumers of the data can seamlessly adapt to new schemas. Coordinating these changes becomes a critical challenge to minimize downtime and prevent production issues. Neglecting robust data management and schema evolution strategies can result in service disruptions, breaking data pipelines, and incurring significant future costs. In the context of Apache Kafka, schema evolution is managed through a schema registry. As producers share data with consumers via Kafka, the schema is stored in this registry. The Schema Registry enhances the reliability, flexibility, and scalability of systems and applications by providing a standardized approach to manage and validate schemas used by both producers and consumers. This blog post will walk you through the steps of utilizing Amazon MSK in combination with AWS Glue Schema Registry and Terraform to build a cross-account streaming pipeline for Kafka, complete with built-in schema evolution. This approach provides a comprehensive solution to address your dynamic and evolving data requirements.

Der Amazon OpenSearch Service, der auf dem robusten OpenSearch-Framework basiert, zeichnet sich durch seine bemerkenswerte Geschwindigkeit und Effizienz in Such- und Analysefunktionen aus. Trotz seiner Stärken sind die Standardkonfigurationen des Dienstes möglicherweise nicht vollständig darauf ausgelegt, die spezifischen sprachlichen Herausforderungen bestimmter Sprachen zu bewältigen.