We needed a solution that could scale and process millions of transactions, by effectively using high memory and CPU configurations to perform complex queries quickly
We used a graph database, Amazon Elastic Kubernetes Service (EKS), and Amazon Neptune, to search for suspicious financial chains across large amounts of transactional data in minutes.
In this post, we share how ENGIE created a CI/CD pipeline for an Amazon MWAA project template using an AWS CodeCommit repository and plugged it into AWS CodePipeline to build, test, and package the code and custom plugins.
This post demonstrates how we automated our engine wash analytics process to handle the complexity of ingesting data from multiple data sources and how we selected the right programming paradigm to reduce the overall time of the analytics job.
The modern data platform ingests delta changes from all source data feeds once per night. The orchestration and transformations of the data is undertaken by dbt. dbt enables data analysts and engineers to write data transformation queries in a modular manner without having to maintain the run order manually.
You can also use the Amazon Redshift query monitoring rules (QMR) feature to set metrics-based performance boundaries for workload management (WLM) queues, and specify what action to take when a query goes beyond those boundaries.
This architecture uses Azure Relay Hybrid Connections to connect from Azure to edge resources or devices that are protected by firewalls
In this blog, we will describe some Azure network security services that help organizations to address Zero Trust, focusing on the third principle—assume breach.
To ensure transactions are completed securely and to prevent fraud, the architecture provides voice authentication using Amazon Connect Voice ID and a visual portal to submit payments.
When architecting a solution to tackle operational efficiency challenges with IoT, consider the devices’ impact on environmental sustainability.
AWS IoT Greengrass is an IoT open-source edge runtime and cloud service that helps you build, deploy, and manage device software.
The key metric tested was message throughput in transactions per second (TPS) consumed, processed, and produced for each component.
At IoT Analytics, our market analyses rely on the findings from our analyst team but also on the input from experts and advisors. We gathered our advisor’s opinions on the most important IoT technology trends to watch in 2022:
APIOps places the Azure API Management infrastructure under version control to achieve these goals. Rather than making changes directly in API Management, most operations happen through code changes that can be reviewed and audited. This approach supports the security principle of least-privilege access.
APIOps not only enforces policies within API Management, but also helps support security by providing feedback for proposed policy changes.
Code comes from a single location and deploys to multiple targets in development, test, and production environments in your local datacenter, private clouds, or the public cloud.
AppSec teams may need to coordinate with security and ops teams from cloud service providers (CSPs) to ensure proper coverage and to adapt cloud-specific best practices.
