CloudBees, the enterprise DevOps leader powering the continuous economy, along with survey lead Sonatype, announced the results of the 6th annual DevSecOps Community Survey today. While DevOps practices are maturing rapidly, corporate application security initiatives are only gradually gaining traction, according to a survey released today by Sonatype, CloudBees, Carnegie Mellon’s Software Engineering Institute and several other partners. The 2019 DevSecOps Community Survey of 5,558 IT professionals also found that organizations with elite DevSecOps programs are outperforming others in terms of DevOps automation, open source controls, container controls, training and cybersecurity preparedness. The 6th annual DevSecOps Community Survey was led by Sonatype with CloudBees as a major sponsor.

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Google Cloud is looking at helping enterprise organisations avoid bill shock with the launch of a storage growth plan for Google Cloud Storage.

The launch came about after Google noted the ‘astonishing and unpredictable’ rate at which data is created in its storage offerings. This is evidently not for a handful of photos and videos; companies who sign up to Storage Growth Plan are expected to hand over $10,000 per month for 12 months of Cloud Storage usage.

At the end of the year customers can either commit to the next 12 months at the rate of their peak usage. If it is within 30% of their original commitment, the previous year’s overage is free.

“We’ve developed the Storage Growth Plan to help enterprise customers manage storage costs and meet the forecasting and predictability that is often asked of IT organisations,” wrote Geoffrey Noer, Google Cloud product manager and Darren Strange, product marketing in a blog post.  

“We heard from customers that data growth can be unpredictable, but costs can’t be. We’ve also heard that data can have unpredictable life cycles,” Noer and Strange added. “Consolidating storage into a centrally managed infrastructure resource can make life as a storage architect much easier. But the path to consolidation is fraught with complexity.”

This certainly makes sense. As this publication has frequently noted, different workloads suit different offerings. Some are so time- and resource-dependent that they can be used elsewhere at short notice; Google gives the example of a legacy image archive which could be reborn as an API training set. As ever Google wheeled out a customer already reaping the rewards; in this case pharmaceutical firm Recursion, whose biological image dataset is rapidly growing and is used to train neural networks.

The move can be seen as another way Google is trying to woo cloudy enterprise customers. In February CEO Thomas Kurian took his debut speaking platform, at a Goldman Sachs conference, to announce aggressive sales plans and give Google a stronger enterprise presence. Google Cloud acquired Alooma, an enterprise-focused data pipeline provider, later in the month.

Google Cloud also announced price drops to its cold yet low latency storage offering Coldline. The move comes after the company said Coldline in multi-regional locations was now geo-redundant, meaning data was protected from regional failure thanks to copies stored at least 100 miles away in a different region.

You can read the full blog post here.

Interested in hearing industry leaders discuss subjects like this and sharing their experiences and use-cases? Attend the Cyber Security & Cloud Expo World Series with upcoming events in Silicon Valley, London and Amsterdam to learn more.

Clare Hopping

Clare Hopping

Clare Hopping

Clare Hopping

Love it or loathe it (and I personally love it) the cloud is having a big impact on enterprise IT, but I don’t think I realised just how big until I got to see the results of a comprehensive survey looking at exactly what was going on in the enterprise cloud market.

Conducted on behalf of Nutanix by Vanson Bourne, a leading specialist in high tech research, this survey gathered some intriguing data from over 2,300 companies around the world. Not least the finding that over a third (36%) of enterprise workloads are up and running in the cloud already with the majority of those taking part expecting this figure to rise rapidly to over half of all workloads by 2020.

More than that, companies are increasingly looking to deploy apps across a blend of private and public clouds. Indeed, some 18% are already mixing clouds and that number is expected to more than double in the next two years to make this kind of hybrid cloud approach the most popular way of implementing IT by quite a wide margin.

Hybrid just makes sense

The reasons behind this move to a mix of clouds aren’t hard to fathom. In essence, companies are both switching on to the benefits of the public cloud – on-demand scalability, pay per use economics and so on – and, at the same time, becoming wise to the fact that not all clouds are the same. Indeed, putting all their application eggs in one basket might be counterproductive.

The age-old traps of vendor and platform lock-in, it seems, are still there waiting for the unwary and, as a result, many are now taking a much more application-centric approach to IT. As such, they are choosing the best home for each app they deploy – be that a public or private cloud – rather than standardising on just one and making their apps fit.

Moreover, this fear of lock-in isn’t the only reason a growing number of companies to want to spread workloads across clouds. Many would also like to be able to move workloads between clouds for both technical and financial reasons, leading to app mobility being ranked well above cost and security concerns by those taking part in the Vanson Bourne survey.

Making hybrid work

Unfortunately we’re some way off being able to turn this desire for free movement of apps into a reality. Not least because, as already mentioned, not all clouds are the same, added to which another finding from the Vanson Bourne survey was a real scarcity of staff with the cloud skillsets needed to turn this aspiration into a reality. Plus, while technologies such as containers, microservices and APIs are helping to make apps a lot more portable, deployment, monitoring and management capabilities are lagging behind, further compounding the skills shortage.

To be clear, tools and technologies to fix this are being developed, but not as fast as many would like, plus those that are available tend to be proprietary with few able, as yet, to reach out beyond the boundaries of specific cloud platforms and products.

The end result is a real lack of visibility when apps are deployed across a hybrid mix of clouds. And when you add traditional on-premise infrastructure to the mix, it becomes even harder to see what’s going on with knock-on implications for, not just performance and availability, but security and compliance too.

Simply put, if you can’t see an app on every cloud it touches, you can’t hope to manage it or fix it when things go wrong. It also becomes much harder to guarantee compliance, availability becomes a major headache and, if you can’t see into different clouds, you certainly can’t automate processes between them.

Give us the tools

Something clearly needs to be done and there are some promising technologies and solutions being developed to deliver this much needed visibility across clouds. Here are just three capabilities that I’d like to see included:

• Expert analytical tools that understand the technical, financial and governance nuances of public clouds to empower IT teams to select the best home for their apps. Tools that can also tell managers what their investments are, where they are and how they’re performing against agreed metrics that can then orchestrate migration to a new cloud or product instance based on the needs of the business
• Cloud-based disaster recovery (DR) services to protect critical business applications and data. Identified by Gartner as one of the most “technologically tedious” requirements of IT, DR across clouds is even harder to deliver but, if done right, has the potential to solve a whole heap of availability issues
• Cross-cloud networking tools and technologies able to manage connectivity between applications across different vendor clouds, services and product instances, plus identify bottlenecks and potential vulnerabilities and initiate remedial action

Delivering these and other hybrid cloud management tools will be far from easy, and will require a lot more cooperation between cloud vendors and service providers than we’re seeing at present. However, with growing numbers of enterprise customers moving to hybrid, it’s very much in everyone’s best interests to work together. It’s time to join up the dots between clouds and deliver the visibility, technologies and tools needed to make it easier to exploit this exciting – and soon to be de facto – way of provisioning and managing enterprise IT.

Interested in hearing industry leaders discuss subjects like this and sharing their experiences and use-cases? Attend the Cyber Security & Cloud Expo World Series with upcoming events in Silicon Valley, London and Amsterdam to learn more.

Augmented analytics, continuous intelligence and explainable artificial intelligence (AI) are among the top trends in big data and analytics that have significant disruptive potential over the next three to five years, according to the latest worldwide market study by Gartner.

"The size, complexity, distributed nature of data, speed of action and the continuous intelligence required by digital business means that rigid and centralized architectures and tools break down,” said Donald Feinberg, vice president at Gartner. “The continued survival of any business will depend upon an agile, data-centric architecture that responds to the constant rate of change."

Gartner recommends that data and analytics leaders collaborate with senior business leaders about their critical business priorities and explore the ten top related trends.

Augmented analytics

Augmented analytics is the next wave of disruption in the data and analytics market. It uses machine learning (ML) and AI techniques to transform how analytics content is developed, consumed and shared.

By 2020, augmented analytics will be a dominant driver of new purchases of analytics and business intelligence (BI), as well as data science and ML platforms, and of embedded analytics. Data and analytics leaders should plan to adopt augmented analytics as platform capabilities mature.

Augmented data management

Augmented data management leverages ML capabilities and AI engines to make enterprise information management categories including data quality, metadata management, master data management, data integration as well as database management systems (DBMSs) self-configuring and self-tuning.

It is automating many of the manual tasks and allows less technically skilled users to be more autonomous using data. It also allows highly skilled technical resources to focus on higher value tasks.

Augmented data management converts metadata from being used for audit, lineage and reporting only, to powering dynamic systems. Metadata is changing from passive to active and is becoming the primary driver for all AI and ML.

Through to the end of 2022, data management manual tasks will be reduced by 45 percent through the addition of ML and automated service-level management.

Continuous intelligence

By 2022, more than half of major new business systems will incorporate continuous intelligence that uses real-time context data to improve decisions.

Continuous intelligence is a design pattern in which real-time analytics are integrated within a business operation, processing current and historical data to prescribe actions in response to events. It provides decision automation or decision support.

Continuous intelligence leverages multiple technologies such as augmented analytics, event stream processing, optimization, business rule management and ML.

Explainable AI

AI models are increasingly deployed to augment and replace human decision making. However, in some scenarios, businesses must justify how these models arrive at their decisions. To build trust with users and stakeholders, application leaders must make these models more interpretable and explainable.

Unfortunately, most of these advanced AI models are complex black boxes that are not able to explain why they reached a specific recommendation or a decision. Explainable AI in data science and ML platforms, for example, auto-generates an explanation of models in terms of accuracy, attributes, model statistics and features in natural language.

Graph analytics

Graph analytics is a set of analytic techniques that allow for the exploration of relationships between entities of interest such as organizations, people and transactions.

The application of graph processing and graph DBMSs will grow at 100 percent annually through 2022 to continuously accelerate data preparation and enable more complex and adaptive data science.

Graph data stores can efficiently model, explore and query data with complex interrelationships across data silos, but the need for specialized skills has limited their adoption to date.

Graph analytics will grow in the next few years due to the need to ask complex questions across complex data, which is not always practical or even possible at scale using SQL queries.

Data fabric

Data fabric enables frictionless access and sharing of data in a distributed data environment. It enables a single and consistent data management framework, which allows seamless data access and processing by design across otherwise siloed storage.

Through 2022, bespoke data fabric designs will be deployed primarily as a static infrastructure, forcing organizations into a new wave of cost to completely re-design for more dynamic data mesh approaches.

NLP conversational analytics

By 2020, 50 percent of analytical queries will be generated via search, natural language processing (NLP) or voice, or will be automatically generated. The need to analyze complex combinations of data and to make analytics accessible to everyone in the organization will drive broader adoption, allowing analytics tools to be as easy as a search interface or a conversation with a virtual assistant.

Commercial AI and ML

Gartner predicts that by 2022, 75 percent of new end-user solutions leveraging AI and ML techniques will be built with commercial solutions rather than open source platforms.

Commercial vendors have now built connectors into the Open Source ecosystem and they provide the enterprise features necessary to scale and democratize AI and ML, such as project & model management, reuse, transparency, data lineage, and platform cohesiveness and integration that Open Source technologies lack.

Blockchain

The core value proposition of blockchain and distributed ledger technologies is providing decentralized trust across a network of untrusted participants. The potential ramifications for analytics use cases are significant, especially those leveraging participant relationships and interactions.

It will be several years before four or five major blockchain technologies become dominant. Until then, technology end users will be forced to integrate with the blockchain technologies and standards dictated by their dominant customers or networks. This includes integration with your existing data and analytics infrastructure.

The costs of integration may outweigh any potential benefit. Blockchains are a data source, not a database, and will not replace existing data management technologies.

Persistent memory servers

New persistent-memory technologies will help reduce costs and complexity of adopting in-memory computing (IMC)-enabled architectures. Persistent memory represents a new memory tier between DRAM and NAND flash memory that can provide cost-effective mass memory for high-performance workloads.

It has the potential to improve application performance, availability, boot times, clustering methods and security practices while keeping costs under control. It will also help organizations reduce the complexity of their application and data architectures by decreasing the need for data duplication.

Interested in hearing industry leaders discuss subjects like this and sharing their experiences and use-cases? Attend the Cyber Security & Cloud Expo World Series with upcoming events in Silicon Valley, London and Amsterdam to learn more.

Enterprises are continuing to accelerate the migration of workloads to public cloud service providers – such as AWS, Azure, Oracle and Google – often as part of an overall digital transformation and cloud-first IT strategy. According to LogicMonitor, more than 80 percent of enterprise workloads will be in the cloud by 2020. Businesses need a multi-cloud solution that provides them with an integrated environment to migrate workloads between multiple public clouds, or between private and public clouds.

In addition, enterprises require multi-cloud solutions that can be custom-tuned for specific applications, as well as provide the ability to port workloads from one public cloud to another for additional flexibility and resiliency – this is where SD-WAN comes into play.

Turning to a multi-cloud strategy with SD-WAN

In this new multi-cloud era, businesses are often faced with an entirely new set of questions and challenges, which can be daunting and confusing. For example, how do businesses use the internet to connect users securely and directly to cloud applications? How do they ensure the performance for every business-critical app? How do they keep pace with WAN changes without going device-by-device? How do they deploy new applications quickly to thousands of sites, across multiple clouds? How do they see everything and always know which WAN issues to focus on? How do they reduce human error in an ever-changing environment? How do they make sure their WAN always keeps pace with the business? And how do they protect their business when cloud is open and connected?

To counter these complexities, organisations are turning to service providers to deploy and manage SD-WAN, a virtual network architecture that enables enterprises to secure private and public cloud connectivity between branch offices and larger corporate data centres, for any cloud application, using any transport.

SD-WAN enables cloud connect solutions that are well suited for extending an SD-WAN between multiple clouds and data centres, as well as delivering high-performance connectivity for all software as a service (SaaS) and infrastructure as a service (IaaS) applications, from any on-net or off-net location. It’s easier and more efficient to route traffic from branches and to establish local internet breakout for trusted SaaS applications.

Flexible policies, defined in a single cloud management console determine the best path every time, utilising any underlying transport, whether it’s internet, MPLS or LTE.

Benefits of a multi-cloud strategy with SD-WAN

A multi-cloud strategy provides enterprises with custom networking solutions for cloud environments that suit different business needs, as well as cloud diversity using the best available network services. Moreover, it enables efficient cloud-to-cloud inter-connectivity, supporting workload migration, backups, DCI and load balancing functions. By turning to a best-in-class SD-WAN, enterprises realise a range of business benefits, including:

• Consistent deployment branch to cloud: Seamless support for cloud deployments enables enterprises to extend the reach of their SD-WAN deployments into virtual private cloud environments to deliver the highest quality SaaS and IaaS applications
• Strengthened last mile broadband for cloud connectivity: Advanced SD-WANs ensure quality of service over broadband to provide fast and reliable connections to the cloud provider’s internet peering point. For hosted voice or business-critical SaaS services, enterprises can backhaul that traffic to cloud-hosted SD-WAN for handoff to the cloud provider’s backbone and out to the internet, delivering peak quality for select traffic
• Cloud flexibility: With a business-first SD-WAN platform, enterprises in the early stages of formalising public cloud strategies can confidently migrate on premise IT resources to any combination of leading public cloud platforms, knowing their cloud-hosted instances will be fully supported
• Multi-cloud flexibility: Enterprises now have choice in public cloud platforms, making it easier to initiate multi-cloud deployments and distribute resources across multiple cloud providers, deploying the best, or most economical, services from any combination of cloud providers. With an advanced SD-WAN, enterprises can accelerate data access, dramatically reduce the amount of data transferred and optimise application performance between cloud instances

SD-WAN: Win-win technology

With SD-WAN, enterprises can realise the full benefits of a multi-cloud strategy, while, at the same time, service providers can capitalise on its simple management and speedy deployment.

Service providers can easily enable application performance-boosting capabilities for cloud-to-cloud communications within the SD-WAN network infrastructure, without installing any new software or deploying any additional virtual network functions (VNFs). Moreover, SD-WANs enable tiered managed services that allow service providers to offer full-mesh connectivity with secure, high-performance links between all clouds. It also assures low latency connectivity and creates new monetisation opportunities through differentiated services that accelerate the “cloudification” of applications, using both public or private cloud services from online and offline locations.

As SD-WAN adoption accelerates, businesses can capitalise on the cost-effectiveness, integrated connectivity advantages and flexibility that multi-cloud environment provides. At the same time, managed service providers can further leverage SD-WAN to offer flexible, high-performance multi-cloud diversity, while reducing the stress and complexity of enterprise migration.

Interested in hearing industry leaders discuss subjects like this and sharing their experiences and use-cases? Attend the Cyber Security & Cloud Expo World Series with upcoming events in Silicon Valley, London and Amsterdam to learn more.

Enterprises are continuing to accelerate the migration of workloads to public cloud service providers – such as AWS, Azure, Oracle and Google – often as part of an overall digital transformation and cloud-first IT strategy. According to LogicMonitor, more than 80 percent of enterprise workloads will be in the cloud by 2020. Businesses need a multi-cloud solution that provides them with an integrated environment to migrate workloads between multiple public clouds, or between private and public clouds.

In addition, enterprises require multi-cloud solutions that can be custom-tuned for specific applications, as well as provide the ability to port workloads from one public cloud to another for additional flexibility and resiliency – this is where SD-WAN comes into play.

Turning to a multi-cloud strategy with SD-WAN

In this new multi-cloud era, businesses are often faced with an entirely new set of questions and challenges, which can be daunting and confusing. For example, how do businesses use the internet to connect users securely and directly to cloud applications? How do they ensure the performance for every business-critical app? How do they keep pace with WAN changes without going device-by-device? How do they deploy new applications quickly to thousands of sites, across multiple clouds? How do they see everything and always know which WAN issues to focus on? How do they reduce human error in an ever-changing environment? How do they make sure their WAN always keeps pace with the business? And how do they protect their business when cloud is open and connected?

To counter these complexities, organisations are turning to service providers to deploy and manage SD-WAN, a virtual network architecture that enables enterprises to secure private and public cloud connectivity between branch offices and larger corporate data centres, for any cloud application, using any transport.

SD-WAN enables cloud connect solutions that are well suited for extending an SD-WAN between multiple clouds and data centres, as well as delivering high-performance connectivity for all software as a service (SaaS) and infrastructure as a service (IaaS) applications, from any on-net or off-net location. It’s easier and more efficient to route traffic from branches and to establish local internet breakout for trusted SaaS applications.

Flexible policies, defined in a single cloud management console determine the best path every time, utilising any underlying transport, whether it’s internet, MPLS or LTE.

Benefits of a multi-cloud strategy with SD-WAN

A multi-cloud strategy provides enterprises with custom networking solutions for cloud environments that suit different business needs, as well as cloud diversity using the best available network services. Moreover, it enables efficient cloud-to-cloud inter-connectivity, supporting workload migration, backups, DCI and load balancing functions. By turning to a best-in-class SD-WAN, enterprises realise a range of business benefits, including:

• Consistent deployment branch to cloud: Seamless support for cloud deployments enables enterprises to extend the reach of their SD-WAN deployments into virtual private cloud environments to deliver the highest quality SaaS and IaaS applications
• Strengthened last mile broadband for cloud connectivity: Advanced SD-WANs ensure quality of service over broadband to provide fast and reliable connections to the cloud provider’s internet peering point. For hosted voice or business-critical SaaS services, enterprises can backhaul that traffic to cloud-hosted SD-WAN for handoff to the cloud provider’s backbone and out to the internet, delivering peak quality for select traffic
• Cloud flexibility: With a business-first SD-WAN platform, enterprises in the early stages of formalising public cloud strategies can confidently migrate on premise IT resources to any combination of leading public cloud platforms, knowing their cloud-hosted instances will be fully supported
• Multi-cloud flexibility: Enterprises now have choice in public cloud platforms, making it easier to initiate multi-cloud deployments and distribute resources across multiple cloud providers, deploying the best, or most economical, services from any combination of cloud providers. With an advanced SD-WAN, enterprises can accelerate data access, dramatically reduce the amount of data transferred and optimise application performance between cloud instances

SD-WAN: Win-win technology

With SD-WAN, enterprises can realise the full benefits of a multi-cloud strategy, while, at the same time, service providers can capitalise on its simple management and speedy deployment.

Service providers can easily enable application performance-boosting capabilities for cloud-to-cloud communications within the SD-WAN network infrastructure, without installing any new software or deploying any additional virtual network functions (VNFs). Moreover, SD-WANs enable tiered managed services that allow service providers to offer full-mesh connectivity with secure, high-performance links between all clouds. It also assures low latency connectivity and creates new monetisation opportunities through differentiated services that accelerate the “cloudification” of applications, using both public or private cloud services from online and offline locations.

As SD-WAN adoption accelerates, businesses can capitalise on the cost-effectiveness, integrated connectivity advantages and flexibility that multi-cloud environment provides. At the same time, managed service providers can further leverage SD-WAN to offer flexible, high-performance multi-cloud diversity, while reducing the stress and complexity of enterprise migration.

Interested in hearing industry leaders discuss subjects like this and sharing their experiences and use-cases? Attend the Cyber Security & Cloud Expo World Series with upcoming events in Silicon Valley, London and Amsterdam to learn more.