Articles tagged with "level-400"

When setting up a microservice architecture, each individual service is often owned and managed by a different team. To achieve a higher level of resource isolation, and allow for more granular security and cost management, each service team usually deploys its resources into a dedicated AWS account. While this type of distributed approach offers many benefits in terms of productivity, scalability, and resiliency, it introduces another layer of complexity in regard to AWS cross-account communication and microservice consumption. In this blog post, I would like to show you how you can leverage AWS services like Amazon API Gateway, Lambda, DynamoDB, and VPC Endpoints in combination with Terraform to build a fully-managed and serverless cross-account microservice architecture.

When setting up IPSec VPN connections between different companies, the connecting parties often require the tunnel to use public IP addresses as the encryption domain. Especially when establishing a connection to telecommunication partners, the usage of public addresses is often mandatory and ensures that there are no overlapping addresses across other connections. In this blog post, I would like to show you how you can leverage tools like pfSense and VNS3 in combination with Terraform to build a Site-to-Site IPSec VPN connection between AWS and on-premises networks with a public encryption domain.

When deciding which Infrastructure as Code tool to use for deploying resources in AWS, Terraform is often a favored choice and should therefore be a staple in every DevOps Engineer’s toolbox. While Terraform can increase your team’s performance quite significantly even when used locally, embedding your Terraform workflow in a CI/CD pipeline can boost your organization’s efficiency and deployment reliability even more. By adding automated validation tests, linting as well as security and compliance checks you additionally ensure that your infrastructure adheres to your company’s standards and guidelines. In this blog post, I would like to show you how you can leverage the AWS Code Services CodeCommit, CodeBuild, and CodePipeline in combination with Terraform to build a fully-managed CI/CD pipeline for Terraform.

Amazon OpenSearch Service is a fully-managed solution for interactive log analytics, real-time application monitoring, website search, observability, and more. With a vast customer base, Amazon OpenSearch Service manages hundreds of thousands of clusters and processes trillions of requests monthly. The service provides seamless access for users through SAML-based federation for OpenSearch Dashboards, enabling single sign-on (SSO) on Amazon OpenSearch Service domains using existing identity providers (IdPs) like OneLogin. SAML simplifies the login process by allowing users to access multiple platforms with a single username and password, providing a safer and more convenient online experience. This guide will walk you through integrating OneLogin with OpenSearch Dashboards for a seamless SSO experience, leveraging Amazon OpenSearch Service’s capabilities.

When discussing high performant real-time event streaming, Apache Kafka is a tool that immediately comes to mind. Optimized for ingesting and transforming real-time streaming data in a reliable and scalable manner, a great number of companies today rely on Apache Kafka to power their mission-critical applications and data analytics pipelines. In this blog series, I would like to show you how you can leverage Amazon MSK and Terraform to set up a fully managed, cross-account Apache Kafka streaming pipeline on AWS. In this first part, we will set up the MSK Kafka cluster and producers. The second part will show you how you can set up distributed Kafka clients in different AWS accounts and communicate with the MSK cluster via AWS VPC Endpoints.

When discussing high performant real-time event streaming, Apache Kafka is a tool that immediately comes to mind. Optimized for ingesting and transforming real-time streaming data in a reliable and scalable manner, a great number of companies today rely on Apache Kafka to power their mission-critical applications and data analytics pipelines. In this blog series, I would like to show you how you can leverage Amazon MSK and Terraform to set up a fully managed, cross-account Apache Kafka streaming pipeline on AWS. In the first part, we already set up the MSK Kafka cluster and producers. The second part will show you how you can set up distributed Kafka clients in different AWS accounts and communicate with the MSK cluster via AWS VPC Endpoints.

When setting up a Jenkins build server on a physical machine, right-sizing can become a challenging task. Long idle times followed by high, irregular loads make it hard to predict the necessary hardware requirements. One solution to this problem is the deployment of a containerized Controller/Agent-based Jenkins setup and to offload workloads to dedicated, transient agents. This is the first post of a three-post series. In this series, I would like to show you how you can leverage AWS Fargate and Terraform to deploy a serverless as well as fault-tolerant, highly available, and scalable Jenkins Controller/Agent deployment pipeline.

When setting up a Jenkins build server on a physical machine, right-sizing can become a challenging task. Long idle times followed by high, irregular loads make it hard to predict the necessary hardware requirements. One solution to this problem is the deployment of a containerized Controller/Agent-based Jenkins setup and to offload workloads to dedicated, transient agents. This is the second post of a three-post series. In this series, I would like to show you how you can leverage AWS Fargate and Terraform to deploy a serverless as well as fault-tolerant, highly available, and scalable Jenkins Controller/Agent deployment pipeline.