More and more companies are eager to move their operations to the cloud. Yet, there’s quite a bit of ambiguity on what moving to the cloud actually means. Is your business running in the cloud while you host your database on another platform or while you rely on a third-party service to handle your payments? That’s a good start for moving to the cloud, but there are many other aspects to consider when building a cloud native infrastructure.
In the wake of COVID-19, we saw a significant shift toward as-a-service offerings, something we haven’t seen in years. From conversations with CIOs over the past 12 months, we know they are looking for the flexibility, efficiencies and cost savings they get from the as-a-service model. This is especially important to them as they evolve their business models in a hybrid IT direction and become consumers of IT.
Google Cloud Platform is a complex suite of services that are aimed at satisfying client’s computing, storaging, and application operating needs. App Engine, Cloud SQL, Cloud Speech API, Deployment Manager ( just a share of ) are the proud services of a GCP. All of them are developed for optimizing business and making business-client relationships easy and comfortable for sealing the deals and conversions go high.
Fivetran Business Critical secures data traffic with AWS PrivateLink.
If you’ve ever gotten sticker shock after receiving a surprisingly large cloud bill, this might have been your reaction… I think we’ve all been there. While the cloud makes flexible scaling possible, it has also introduced many new services one can use, resulting in increased cloud costs. In this article, I’ll go over the eight ways you can reduce your Kubernetes cloud costs. I use Amazon Web Services (AWS) as an example, but the lessons can also apply to other cloud providers.
Earlier this year, Perforce hosted the Embedded DevOps Summit, exploring solutions to modern challenges in the planning, development, and testing stages of embedded software. As part of this event, Warren Savage, Visiting Researcher at the Applied Research Laboratory for Intelligence and Security (ARLIS) at the University of Maryland, presented Secure Collaboration in Cloud-Based Chip Design Environments.
During the process of turning data into insights, the most compelling data often comes with an added responsibility—the need to protect the people whose lives are caught up in that data. Plenty of data sets include sensitive information, and it’s the duty of every organization, down to each individual, to ensure that sensitive information is handled appropriately.
Over the last year, perhaps unsurprisingly, increasing numbers of companies have made the jump to the cloud. It’s become a necessary move for so many businesses. But, as I discussed with Joe DosSantos on the latest episode of Data Brilliant – the rewards are abundant, but the journey is not always straight forward.
