cloud professional services

Jan 9, 2022 7:13:13 PM by Danny Lev-ran

The Latest Updates from AWS re:Invent: Cloudride’s Insight

AWS, AWS re:Invent

In our last blog post reporting from AWS re:Invent, we covered The Most Prominent Innovation and Tech Developments in the Field of Backup & Storage.This week we’re all about Networking, Content Delivery and Next Generation Compute. So let’s get down to business with the most important highlights for 2022:

Virtual Private Cloud (VPC) IP Address Manager (IPAM)

Amazon Virtual Private Cloud (VPC) IP Address Manager (IPAM) is a simple and secure way to connect applications running in a VPC to resources outside of the VPC. This new feature, in addition to existing connectivity options such as VPN connections and AWS Direct Connect, helps customers extend their existing network infrastructure into the AWS cloud. In addition, VPC with PrivateLink makes it easier for customers to manage their expanding IP address needs by introducing Amazon Virtual Private Cloud (VPC) IP Address Manager (IPAM).

You can use IPAM to discover and monitor the IP addresses in your VPCs and manage address space across multiple VPCs. IP addresses can include static IP addresses and Amazon Elastic IP addresses (EIPs). You can use IPAM to find unused addresses in your VPCs so that you can consolidate IP addresses. IPAM provides visibility into an organization's IP usage, allowing administrators to see IP address utilization across their AWS environment and control and automation tools that allow them to manage IP address requests.

The feature is part of Amazon's larger effort to make it easier for companies of all sizes to move workloads into the cloud. IPAM uses native VPC functionality to provide subnet-level visibility into each customer's entire public IPv4 address space. Customers simply create a VPC and then add their subnets, and IPAM automatically provisions IP addresses for each subnet, without any further configuration required by the customer.

Kinesis Data Streams On-Demand

Tectonic shifts are happening in cloud computing: with serverless computing on the rise and SaaS applications becoming increasingly dependent on streaming data, AWS's new Kinesis Data Streams service is designed to help companies capture and analyze this data.

Kinesis Data Streams enables you to build and run real-time data applications by using a serverless approach. That means you can have a data stream up and running in minutes without having to provision or manage any infrastructure. The service scales automatically and runs your code when events occur. It also handles the operational details of running your code, like monitoring for failures, managing upgrades, and applying security patches.

Amazon Kinesis Data Streams enables you to capture a high volume of data in real-time, process the data for custom analytics, and store the data for batch-oriented analytics. Amazon Kinesis Data Streams can stream data for various use cases, from microservices to operational analytics and Data Lake storage, among other scenarios. You can build and host your own applications to process and store data or use the AWS SDKs to build custom applications in Java, .Net, PHP, Python, or Node.js.


New Amazon EC2 C7g instances, powered by Graviton 3, are designed to deliver the performance and cost savings that allow you to run more of your workloads on AWS while also providing lower latency, higher IOPS, and higher memory bandwidth than previous generations of EC2 compute instances.

The new C7g instances include eight Graviton3 CPU cores, each with 128 KB of L2 cache and SSE4.1 support for improved floating-point performance. Each core is independently multithreaded and can run simultaneous threads at 2.5 GHz.

Custom-designed AWS Graviton3 processors provide greater compute density and power efficiency than general-purpose processors. They allow for more CPU cores per rack unit, more RAM per instance, and higher I/O bandwidth per instance than in previous generations of EC2 compute instances.

Tests have shown that with a mixed workload of MySQL and Memcached technologies, EC2 C7g instances can achieve up to a 75% reduction in latency for applications with increased throughput and reduced tail latencies.


AWS Karpenter; a new open-source Kubernetes cluster autoscaling project

AWS Karpenter is a new open source project that makes setting up and manages Kubernetes clusters across multiple AWS regions. Karpenter can be used to provision and manage AWS EC2 instances to autoscaling in response to traffic. It uses Amazon CloudWatch Events as an input to trigger scaling operations on Kubernetes clusters running on AWS.

If you're in the process of migrating to a containerized platform, or you're looking for a way to help your developers build and deploy applications faster, Karpenter might be an interesting project to check out.

The cluster management system allows users to allocate resources across a set of Kubernetes cluster instances. The key benefit of the cluster manager is it allows users to scale the number of nodes in the cluster dynamically according to traffic patterns. This results in lower running costs and higher throughput during peak periods.

Users can easily specify their application requirements, select the best infrastructure and software configuration, receive a deployment plan, and have their cluster ready in minutes.

As a Certified AWS partner, we expect AWS to be previewing even more new technology and innovation on an ongoing basis. If you are interested in AWS services, be sure to give the book a free call here for white-glove consultation on migration, cost, and performance optimization.



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