Microsoft’s Load Balancer for AKS
Microsoft has introduced its Azure Load Balancer with the ability to work with applications in the Azure Kubernetes Service. The load balancer can be used both internally and externally. If internal, the load balancer makes a Kubernetes service only accessible to applications running in the same virtual network as the AKS cluster. External load balancers receive one or more public IPs for ingress to make a Kubernetes service accessible externally using public IPs.
The load balancer will be available in two SKUs: basic and standard. Basic is the default used to create a load balancer on AKS, while Standard provides additional features and functionality such as larger back-end pool size and Availability Zones.
While the addition of these load balancers may appear to be an excellent move for Azure, it’s one that only catches them up to other major cloud providers. AWS has two load balancers that support Kubernetes called the Network Load Balancer and the Classic Load Balancer, Google Cloud has the HTTP Load Balancer and the TCP/UDP Load Balancers, and Alibaba has the Alibaba Cloud Server Load Balancer.
VPC Traffic Mirroring for AWS
Amazon has added a new feature made to capture and inspect network traffic, called VPC Traffic Mirroring. AWS introduced VPC Traffic Mirroring to counter the problem customers faced keeping an eye out for unusual traffic patterns or content that could signify a network intrusion, compromised instance, or another anomaly.
AWS wants customers to think of VPC Traffic Mirroring as a “virtual fiber tap” that gives direct access to the network packets flowing through their VPC. Users can choose to capture all of their traffic or use filters to capture specific packets that are of particular interest. They also have the option to limit the number of bytes captured per packet.
VPC Traffic Mirroring also has the ability to be used in a multi-account AWS environment, mirroring traffic from any EC2 instance that is powered by the AWS Nitro System. Again, other cloud providers already have similar features, such as the Azure Network Watcher, Google Cloud’s VPC Flow Logs, and Alibaba Flow Logs.
Oracle Partners with Chainlink
On June 25th at the CloudEXPO conference in Santa Clara, California, Fernando Ribeiro, senior manager with Oracle for startups, and Pablo Freitas, an engineer with Oracle’s Customer Innovation Labs, announced that the company would be partnering with Chainlink. Ribeiro says the collaboration has been in the works for months. Their collaboration follows news from earlier this month that Google Cloud was also partnering with Chainlink.
Together, the companies will set out to help startups use Chainlink’s decentralized oracle technology to monetize APIs via smart contracts on the Oracle Blockchain Platform, Oracle’s “business ready” distributed ledger. Ribeiro stated, “We are going to co-develop chainlinks with 50 qualified start ups to prepare them to sell their data to Oracle’s 430,000 customers in 175 countries on the Oracle Blockchain Platform.”
Ribeiro stated that the startups they choose will be announced at Oracle’s developer conference, Oracle Code One, in September. News has increased buying pressure, causing LINK token prices to rise. They rose to $2.41 just before Oracle’s presentation and settled around $2.17.
In other blockchain news, AWS has launched GXChain June 21st. Developers using the company’s services can deploy the service in one click and launch through the image service on the AWS App Store. AWS says GXChain is committed to building a trusted data internet of value.
The company also said that the Trusted Computing Protocol, or TCP developed by GXChain’s core team will do several things. It will provide breakthrough solutions for enterprise and individual data computing in the era of big data, solve the contradiction between data business efficiency and personal privacy, and fully release the potential of data’s value. AWS claims this launch is just the beginning of their efforts in Blockchain.
Google Cloud Announces Deep Learning Containers
Google Cloud announced that the beta of their Deep Learning Containers are now available. Deep Learning Containers are designed to provide consistent environment for testing and deploying applications across GCP products and services like Cloud AI Platform Notebooks and Google Kubernetes Engine. This makes it easier to scale deep learning applications in the cloud or shift app across on-prem and cloud.
The introduction of these containers will help users better manage the capability and complexities of an ever software stack when working on machine learning projects, which can at times be frustrating and time consuming. Google Cloud states that their Deep Learning Containers are prepackaged, performance optimized, and compatibility tested. Other major cloud providers have already dipped their toes in the deep learning containers “pool”, such as AWS’ DL Containers and NVIDIA GPU Cloud (NGC) packaged deep learning containers run in Alibaba Cloud.
That’s a wrap for this week’s Liftr Cloud Look Ahead. Has your business made major strides using cloud? We want to hear from you! Email us at email@example.com.
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