It’s a wise idea to have a list of ways handy for how you can get the go-ahead at your company from those who matter the most to adopt more technology solutions. It’s your job as the lead in this area to sell them on it and make sure what you’re suggesting is genuinely going to help your business move forward in a positive direction.

Explain the Benefits

One tip to help your company adopt more technology solutions is to be forthcoming about all the benefits that will come from these upgrades. For instance, take time to study all you need to know about speeding up your content pages for mobile and understanding the advantages of working in the cloud. Come to meetings prepared to go over all the reasons why what you’re proposing is the best move at the time and worth the investment in the long run. Put together a list of the most appealing options in your opinion and present the benefits in a clear and concise manner or presentation. This is one of the most important steps because if people can’t see how these solutions are aiding them, then it’s going to be more difficult to get them to commit to your solutions and move forward. 

The transition to cloud-native applications and infrastructure is well underway: Over 60% of IT professionals mentioned that a majority of their applications are either built or run using hybrid cloud architectures. Infrastructure and operations (I&O) organizations will need vastly different skills, technologies, and processes over the next five years as they adopt a cloud-first posture. How do IT leaders find the right talent that can deploy and maintain dynamic, flexible and cost-effective digital services?

Armor, a leading cloud security solutions provider, announced today that it continues to expand its work with cloud-native solutions with the recent integration of Amazon Web Services (AWS) Security Hub with its Armor Anywhere service.

This move allows Armor to deliver deeper security insights and context to AWS customers by feeding vulnerability scan and malware detection information into the AWS Security Hub data repository. AWS Security Hub provides users with a comprehensive view of their high-priority security alerts and compliance status by aggregating, organizing, and prioritizing alerts, or findings, from multiple AWS services, such as Amazon GuardDuty, Amazon Inspector, and Amazon Macie as well as from AWS Partner Network (APN) security solutions. The findings are then visually summarized on integrated dashboards with actionable graphs and tables.

As a result of the integration, users of the Armor Anywhere service will now be able to receive alerts for high-priority vulnerability and malware information via the AWS Security Hub user interface. In addition, Armor’s threat prevention and response platform can analyze findings fed into AWS Security Hub by the customer’s other security solutions to further bolster their threat detection and overall security defenses.

Thundra, the newly launched observability company for serverless environments, today announced the release of Thundra Layers for AWS Lambda. The company also announced it has achieved Advanced Technology Partner status in the Amazon Web Services (AWS) Partner Network (APN).

A custom runtime implemented on top of the new AWS Runtime API feature, Thundra Layers reduces development and deployment time for software developers adding observability to their applications, even across multiple AWS Lambda functions and accounts.

With Thundra Layers for AWS Lambda-AWS’s "serverless" computing service-customers don’t need to download, install, and manually set up Thundra to achieve full serverless observability of AWS Lambda. Instead, they can simply select the Thundra Layer option within AWS Lambda, set a few configuration options, and immediately start monitoring their serverless applications. Customers can try Thundra free at console.thundra.io/sign-up.

Figure Eight, the essential Human-in-the-Loop Machine Learning (ML) platform, today announced that its production-quality ML algorithms and models will be available on Amazon Web Services (AWS) Marketplace for Machine Learning, which allows developers and data scientists to find and procure ML algorithms and models and deploy in Amazon SageMaker. The Figure Eight models will be deployed in Amazon SageMaker, a fully managed platform that enables developers and data scientists to quickly and easily build, train, and deploy ML models at any scale.

"We are excited to welcome Figure Eight as one of our launch ISVs for the new AWS Marketplace for Machine Learning," said Dave McCann, Vice President, AWS Marketplace Service Catalog and Migration Services, Amazon Web Services, Inc. "With the introduction of the AWS Marketplace for Machine Learning we are enhancing our customers’ ability to increase efficiency and productivity of their businesses with machine learning models, and making it easier for people to find models and algorithms right inside the Amazon SageMaker Console."

HubStor announced new cloud backup capabilities designed to give enterprise’s better control and protection of their information. First, HubStor unveiled continuous data protection capabilities, empowering organizations to capture file changes as they happen on network-based file systems and within virtual machines. HubStor also added version-control policies to its cloud data management platform, enabling organizations to reduce demand for cloud capacity by condensing the number of file versions held in storage as data ages.

HubStor’s continuous data protection supports monitoring of certain file system directories in order to detect new files and dynamically capture them into HubStor, either as a backup with a very short recovery point objective (RPO) or as a WORM archive for compliance.

There are various methods to monitor for changes on a file system. HubStor’s current approach is agentless. HubStor may add support for other methods based on demand.

Starting with the agentless approach is the simplest because it avoids adding new software. When configuring a file system target in HubStor, enabling CDP is a simple checkbox option. By default, HubStor detects and captures any changes within 30 seconds. This change detection time can be adjusted as needed.

The flexibility of HubStor supports some file connectors having CDP enabled while perhaps others do not, allowing various workloads to be handled differently.

Trifacta, Inc., the global leader in data preparation, today announced the addition of a serverless data preparation service on Amazon Web Services, Inc. (AWS). Based on Amazon Elastic MapReduce (Amazon EMR), the fully managed service allows organizations to quickly deploy Trifacta while eliminating the need for customers to manage their own AWS infrastructure. The serverless architecture was designed to allow customers to dynamically scale computing capacity to match the shifting requirements of different workloads, which, in turn, can increase efficiency and lower operational costs.

Trifacta’s customer portfolio is growing rapidly, with over 4X growth in the number of customers deploying Trifacta on AWS in the last year, such as Deutsche Börse and Munich Re. Trifacta has been working with AWS since 2013. Trifacta products Wrangler Pro and Wrangler Enterprise are available on AWS Marketplace and AWS GovCloud (US) to support government agencies, in addition to Trifacta managed deployments on AWS. The addition of a serverless data preparation service on AWS allows Trifacta to best meet enterprises’ evolving data needs in the cloud.

E8 Storage has officially launched into the APAC region by partnering with AI cloud service provider, Clustar Technology. E8 Storage continues to grow its global partner base and expand its international presence in high performance computing with its shared NVMe storage platform for customers who need high performance and low latency for data intensive applications.

Zivan Ori, co-founder and CEO of E8 Storage elaborated, "Clustar Technology is delivering an innovative and successful service in the industry with its AI cloud platform, and the partnership with E8 Storage cements our continued international expansion. By working with Clustar Technology, we are enabled to offer a unique proposition by delivering industry leading performance for organizations that are on their AI journey."

Cloud Academy, the leading digital skills development platform for enterprises, today released its November 2018 Data Report revealing trends and shifts in the cloud computing industry. The data is collected from Cloud Academy’s publicly available benchmarking tools Cloud Roster and Cloud Catalog. Among the report’s key findings:

Amazon Web Services, Inc. (AWS) announced 13 new machine learning capabilities and services, across all layers in the machine learning stack, to help put machine learning in the hands of even more developers. AWS introduced new Amazon SageMaker features making it easier for developers to build, train, and deploy machine learning models – including low cost, automatic data labeling and reinforcement learning (RL). AWS revealed new services, framework enhancements, and a custom chip to speed up machine learning training and inference, while reducing cost. AWS announced new artificial intelligence (AI) services that can extract text from virtually any document, read medical information, and provide customized personalization, recommendations, and forecasts using the same technology used by Amazon.com. And, last but certainly not least, AWS will help developers get rolling with machine learning with AWS DeepRacer, a new 1/18^th scale autonomous model race car for developers, driven by reinforcement learning.

These announcements continue the drum beat of machine learning innovation from AWS, which has launched more than 200 significant machine learning capabilities in the past 12 months. Customers using these new services and capabilities include Adobe, BMW, Cathay Pacific, Dow Jones, Expedia, Formula 1, GE Healthcare, HERE, Intuit, Johnson & Johnson, Kia Motors, Lionbridge, Major League Baseball, NASA JPL, Politico.eu, Ryanair, Shell, Tinder, United Nations, Vonage, the World Bank, and Zillow. To learn more about AWS’s new machine learning services, visit: https://aws.amazon.com/machine-learning.

"We want to help all of our customers embrace machine learning, no matter their size, budget, experience, or skill level," said Swami Sivasubramanian, Vice President, Amazon Machine Learning. "Today’s announcements remove significant barriers to the successful adoption of machine learning, by reducing the cost of machine learning training and inference, introducing new SageMaker capabilities that make it easier for developers to build, train, and deploy machine learning models in the cloud and at the edge, and delivering new AI services based on our years of experience at Amazon."