Sumo Logic this week announced it is making a security information event management (SIEM) platform available on the Amazon Web Services (AWS) cloud.

Jabari Norton, vice president of partners and alliances for Sumo Logic, said the Sumo Logic Cloud SIEM Powered by AWS extends the reach of the Sumo Logic Continuous Intelligence Platform for analyzing data into the realm of cybersecurity.

The Sumo Logic Continuous Intelligence Platform is already hosted on AWS. The challenge the company faced was extending the reach of that platform to create a SIEM that can collect data from multiple third-party data sources spanning everything from on-premises IT environments to software-as-a-service (SaaS) applications, said Norton. Those capabilities make it possible to now analyze security data using machine learning algorithms to detect threats and correlate security intelligence, noted Norton.

The Sumo Logic Cloud SIEM is also tightly integrated with AWS security services such as Amazon GuardDuty and AWS CloudTrail in addition to all the cloud services that AWS continuously updates, added Norton. While the relationship with AWS is not exclusive, Norton said Sumo Logic has no plans to host of a version of its SIEM on any other public cloud at this time.

In effect, Sumo Logic is now applying the same observability capabilities it provides to IT operations and DevOps teams to analyzing security data. In theory, that approach should make it easier for all those teams to collaborate around a platform that aggregates data from across the extended enterprise. That’s critical because while security teams are mainly tasked with discovering vulnerabilities they typically need to rely on DevOps and IT operations teams to remediate them.

In the meantime, the rate at which security platforms are shifting to the cloud continues to accelerate in the wake of the COVID-19 pandemic. Security teams that now need to work from anywhere are finding it simpler and more cost effective to employ cloud platforms to analyze security data. In many cases, the rise of cybersecurity AI will soon force the cloud migration issue. Few organizations have the infrastructure resources required to aggregate the volume of data that is required to train an AI model. The need for those AI models is becoming increasingly pressing because the rate at which cybersecurity attacks are being launched is increasing beyond the abilities of any cybersecurity team, on their own, to analyze.

Of course, there is no shortage of SIEM platforms available in the cloud. Sumo Logic is betting many organizations will simply extend their existing subscriptions to now include a SIEM service.

It may still be some time before the bulk of security platforms employed by any organization reside in the cloud. However, at this juncture, it’s now more a question of time. The less time understaffed cybersecurity teams spend managing infrastructure themselves, the more time they should have available to uncover threats. The issue, of course, is finding the time and resources to make transition in the middle of what is now often a daily cybersecurity firefight.

Red Hat this week reveals it has extended its alliance with Amazon Web Services (AWS) to include a managed Red Hat OpenShift service that the two companies will jointly provide.

Based on Kubernetes, the Red Hat OpenShift application development and deployment platform is at the core of the hybrid cloud computing strategy that Red Hat and its parent company, IBM, are betting will drive the next wave of enterprise computing.

Under the terms of the expanded alliance with AWS, the two companies are making available a managed Red Hat OpenShift Service on AWS (ROSA) that is more tightly integrated with the AWS Console.

That offering enables customers to subscribe to Red Hat OpenShift services, which will appear on the same bill IT organizations receive for the other AWS services they consume. There are no up-front investments required to use ROSA, and IT teams only pay for the container clusters and nodes they actually consume.

Sathish Balakrishnan, vice president of hosted platforms for Red Hat, says this managed service offering is similar to a managed service offering that Red Hat offers jointly with Microsoft. Demand for managed services has increased significantly because developers have accelerated the rate at which cloud-native applications are being built, even though Kubernetes management expertise among internal IT operations teams remains in short supply.

At the same time, many IT organizations are now looking to standardize on a single Kubernetes-based platform that provides a higher level of abstraction and spans multiple clouds and on-premises IT environments, including edge computing platforms. As IT environments become more distributed, the need to rely on an external IT services provider to manage it only increases, Balakrishnan says. A common layer of abstraction will also make it easier for IT organizations to shift workloads from one cloud provider to another as business and technology considerations warrant.

Ultimately, organizations of all sizes will soon have to decide the degree to which they want to manage IT infrastructure themselves. In theory, the more they rely on an external service provider, the more internal resources they should be able to devote to new application development and deployment. Of course, there’s never been a shortage of managed service providers (MSPs). The thing that is changing most is that IT vendors are now providing these managed services themselves. Each IT organization that decides to rely more on an external service provider will need to decide if it makes sense to rely on a service provided by a vendor – that is optimized for that single vendor – versus relying on a third-party MSP capable of aggregating multiple services.

In the meantime, the rate at which cloud-native applications are being deployed across an extended enterprise is only going to increase as the overall global economy continues to steadily improve. The major IT issue of the day, now, is determining how best to achieve that goal in an era when the global economy has never been more dependent on software.

VMware and Nvidia have expanded their alliance to make it easier for enterprises to run GPU-accelerated AI applications in existing data centre infrastructure.

The virtualisation giant announced the expanded alliance with Nvidia Tuesday, saying that the GPU maker has exclusively certified VMware’s vSphere 7 Update 2 to support the new Nvidia AI Enterprise offering, a software suite of enterprise-grade AI tools and frameworks that enables Nvidia GPU-accelerated applications to run in virtual machines and containers.

VMware’s vSphere 7 Update 2 is also introducing support for Nvidia’s A100 Tensor Core GPU and its multi-instance GPU feature, which will allow data centre operators to split up individual A100s into as many as seven distinct instances for use by multiple users.

Nvidia said it developed Nvidia AI Enterprise alongside VMware as part of a first-of-its-kind industry collaboration that will allow enterprises to move AI applications from bare-metal servers to virtualized environments with very little performance impact. The suite includes solutions that support a broad range of industries, from health care and manufacturing to financial services.

Justin Boitano, vice president and general manager of Enterprise and Edge Computing at Nvidia, told CRN USA that the vSphere exclusivity agreement means that the Nvidia AI Enterprise offering is not available on any other virtualization platform. He declined to say when the exclusivity agreement would expire.

“We’re working together to make this as easy to consume as possible for enterprises that want to go on this journey of using AI to improve efficiency,” he said in a briefing with journalists last week.

The new software certification work means that Nvidia AI Enterprise is primed to run on servers from Dell Technologies, Hewlett Packard Enterprise, Supermicro and other server makers that has been certified through the GPU maker’s recently launched Nvidia-Certified Systems program.

Lee Caswell, vice president of marketing of VMware’s cloud platform business unit, said the new collaboration around Nvidia AI Enterprise “is going to be incredibly powerful in reducing both real and perceived risk” when it comes to running AI applications in data centres.

“We’re doing the work behind the scenes to reduce the real risk through certification, integration, testing, and then perceived risk is how we come to market together to show that our companies are both ready to support the joint solution,” he said.

Boitano said Nvidia AI Enterprise can significantly reduce the amount of work required for companies to deploy AI applications into production environments. For instance, he said, Nvidia’s Transfer Learning Toolkit, which is available in the suite, can reduce the amount of time it takes for a company to build an AI model from 80 weeks to eight weeks.

“We’re taking this cloud-native deployment to heart in trying to make sure everything’s containerized and can be orchestrated in cloud native ways going forward to make setup and deployment easy,” he said, adding that support for Nvidia Enterprise AI will eventually come to vSphere Tanzu for running AI applications in containers from the virtualization platform.

Nvidia AI Enterprise is now available as a perpetual license at US$3,595 per CPU socket, and enterprise business standard support for the software suite is US$899 a year per license

Next-generation database developer MongoDB and Google Cloud are extending the strategic alliance they launched two years ago with a new partnership deal under which the MongoDB Atlas cloud database will be integrated with a slew of Google Cloud services.

The move is expected to provide systems integrators, ISVs and other solution provider partners of the two companies with new opportunities in cloud application development and cloud data migration.

Google Cloud and MongoDB have undertaken the joint engineering task of integrating MongoDB Atlas with a number of Google applications and services that run on the Google Cloud Platform including BigQuery data warehouse, Pub/Sub publish and subscribe messaging, Dataflow data processing, Dataproc managed Hadoop and Spark, TensorFlow machine learning, Cloud Run serverless computing, Cloud Functions serverless execution, App Engine platform-as-a-service, and the Google Kubernetes Engine container environment.

The new pre-built integrations and reference architectures being developed by MongoDB and Google Cloud will make it easier for an ISV partner or an in-house developer to build applications that tie into both MongoDB Atlas and all those Google Cloud services, said Alan Chhabra, MongoDB senior vice president of worldwide partners.

“A developer, who is the person who uses MongoDB the most, potentially can now get a full-stack architecture to develop applications centered around MongoDB Atlas and Google Cloud services,” said Chhabra in an interview with CRN.

The joint development initiative “really solidifies the amount of pre-built integration work between the two companies’ platforms,” said Chhabra.

In February 2020 Google bought Cornerstone Technology and its tools for migrating mainframe workloads to the cloud. Those mainframe modernization tools now support MongoDB Atlas, the companies said Thursday, making it easier to convert legacy Cobol code on mainframes into Java-based applications that can run on MongoDB.

Those capabilities will assist global and regional systems integration partners that MongoDB and Google Cloud work with for projects to modernize legacy mainframe applications and move them to Google Cloud, said Chhabra.

Shortly after taking the job of Google Cloud CEO, Thomas Kurian said the company would work more closely with developers of open-source software. In 2019 MongoDB took Google Cloud up on that promise, striking a go-to-market partnership through which MongoDB Atlas was offered through the Google Cloud Platform Marketplace.

And in 2020 MongoDB Atlas became a fully managed service directly integrated with the Google Console, providing integrated billing and support for the companies’ joint customers.

This week Chhabra said that in the last year MongoDB and Google Cloud have seen a 300 percent year-over-year increase in joint customer wins, particularly in such vertical industries as financial services and retail.

Altogether the database vendor has some 22,600 customers.

MongoDB runs on all three of the hyper-scale cloud platforms, including Amazon Web Services and Microsoft Azure. (AWS offers Amazon DocumentDB, its own database software that some observers see as competing with MongoDB.)

In 2019 MongoDB allied with Alibaba to bring its cloud database service to China.

“We are delighted to expand our partnership with MongoDB to deliver Atlas at global scale on Google Cloud and help businesses leverage data in their digital transformations,” said Kevin Ichhpurani, corporate vice president, global ecosystem at Google Cloud, in a statement. “This announcement builds on our shared commitment to helping businesses build a foundation for data-driven transformation. We are excited to build on significant customer successes with MongoDB on Google Cloud.”

In June 2019, Microsoft and Oracle announced what they described as an industry-first multicloud collaboration. The partnership enables customers to interconnect the two companies’ cloud platforms and simplify management of IT environments and individual applications that span both clouds. Following the announcement, demand from joint Oracle and Microsoft customers for multicloud solutions drove the two vendors to accelerate regional expansion.

The first expansion of that alliance connects Microsoft Azure and Oracle Cloud Infrastructure (OCI) in London, opening the partnership’s capabilities to a second continent and one of the busiest Oracle Cloud regions in the world.

Why Cloud Proximity Matters

The initial phase of the alliance connected Oracle Cloud Infrastructure’s Ashburn, Virginia region with Microsoft Azure’s US East region, also located in Virginia. The decision to start with geographically co-located regions was deliberate: physical proximity between cloud data centres reduces network latency, which in turn enables faster data transfer, tighter application integration across clouds, and support for a broader range of latency-sensitive workloads.

The same principle applies to the London expansion. By placing the interconnect between OCI London and Azure UK South in the same metropolitan area, the two vendors deliver the low-latency cross-cloud connectivity that enterprise workloads require. Without geographic proximity, the overhead of traversing public internet routes would make many multicloud architectures impractical for production use.

What the Alliance Delivers in the UK

London is described by Oracle as one of its most active cloud regions, hosting a broad mix of workloads ranging from mission-critical systems of record to cloud-native greenfield deployments. The interconnect between Azure and OCI in London includes the following capabilities:

• Preconfigured, dedicated interconnection: A private, high-bandwidth link between the two clouds without traffic traversing the public internet.
• Common identity management: Integrated identity and access controls that allow administrators to manage authentication and authorisation across both platforms from a single pane.
• Unified support: Joint support capabilities from both Oracle and Microsoft to reduce the operational friction of running workloads across two cloud providers.
• Cross-cloud service access: Azure customers can deploy Oracle databases and Oracle applications as managed cloud services and connect them to Azure-hosted workloads running the Microsoft stack. Equally, OCI customers can consume Azure services alongside Oracle services without redesigning their architecture.

The result is that joint customers can select the optimal cloud environment for each component of their workload inventory — Oracle for databases and enterprise applications, Azure for Microsoft-stack services and integrations — without incurring the complexity or performance penalties that previously made cross-cloud architectures difficult to operate.

Restoring On-Premises Coexistence in the Cloud Era

Mixed Oracle and Microsoft technology stacks have long been common in enterprise data centres. On-premises, these stacks could coexist naturally: servers running each vendor’s software sat on the same network, making information exchange straightforward. The shift to cloud disrupted this model. Each vendor’s cloud was a separate, isolated environment, and moving data or integrating applications between them required workarounds that added latency, cost, and operational complexity.

The Oracle–Microsoft multicloud alliance directly addresses this gap. Key architectural enablers include:

• Decoupled application architectures: Services on one cloud can call services on the other without tight coupling, preserving independent scalability and release cadences.
• Common management frameworks: Shared control planes reduce the operational overhead of managing resources across two cloud accounts and two billing models.
• Private network interconnection: Dedicated links replace ad-hoc internet tunnels, making cross-cloud network performance predictable and auditable.

For enterprises with long-standing investments in both Oracle and Microsoft software, this interconnect restores the freedom they had in their own data centres: the ability to run each part of a workload on the platform best suited to it, with reliable, low-latency connectivity between the two.

Looking Ahead

The London expansion was announced in August 2019 as the first step beyond the original US East / Ashburn pairing. At the time, both vendors indicated that additional regions were planned, though specific timelines and locations were not committed to in the announcement. For the latest information on available interconnect regions and supported services, consult the official Oracle Cloud and Microsoft Azure documentation directly.

Future Product Disclaimer (Oracle): The preceding information is intended to outline Oracle’s general product direction. It is intended for information purposes only and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied on in making purchasing decisions. The development, release, timing, and pricing of any features or functionality described for Oracle’s products may change and remains at the sole discretion of Oracle Corporation.