Indeed, a recent study by Valtix revealed that 95% of IT leaders declared to be making multi-cloud a priority in 2022, with a focus on security. However, only 54% stated to feel confident that they have the necessary tools and skills to achieve this goal. Most of them also think that their multi-cloud operations are underfunded.

Moreover, 67% of IT leaders feel that their own employees are underskilled regarding multi-cloud security. Most of them reported not knowing every application in their public cloud, or if host-based security is in place across their public cloud accounts.

Hence, with multi-cloud becoming more relevant in 2022, it is vital that organizations find the best solutions to implement multi-cloud security policy and visibility. To do so, businesses need to create a sustainable model for multi-cloud security, know their cloud environments, find ways to consolidate their cloud security, adopt a security strategy that is cloud-first, as well as make multi-cloud security an imperative in 2022.

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Indeed, the study showed that many IT leaders have chosen a new cloud provider in the last year as the cloud market is evolving. Hence, organisations are looking to invest in the right cloud strategy for their IT workloads.

Moreover, it was stated that security and technical requirements are the top drivers of cloud decision-making. 56% of respondents noted that security considerations had a significant impact on the final decision when choosing a provider.

It was reported that private cloud environments remain important to organizations wanted to make optimal workload-to-cloud placement decisions. Around 42% of respondents also declared pursuing a multi-cloud strategy.

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Indeed, it was reported that 89% of CISOs believe that microservices, containers, and Kubernetes have created application security blind spots while 97% of organizations stated not having real-time visibility into runtime vulnerabilities in containerized production environments.

Hence, the study showed that around 63% of CISOs think that DevOps and agile development have made it more complicated to identify and manage software vulnerabilities. 74% of CISOs also stated that traditional security controls, including vulnerability scanners, are not enough in today’s cloud-native world.

Therefore, the study revealed that manual vulnerability scans and impact assessments are no longer able to keep up with the pace of change. It was then highlighted that the only way for security to keep up with modern cloud-native application environments is to replace manual deployment, configuration, and management with automated approaches.

As we are leaning towards DevSecOps, it is vital that businesses have solutions that offer automatic, continuous, and real-time risk and impact analysis for every vulnerability, across both pre-production and production environments.

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Indeed, this deal will then allow Google to provide to the bank various services so as to enable digital transformation. Besides, developers of the bank will be able to follow a continuous integration and delivery (CI/CD) approach, which then will enable faster and easier building and maintaining of applications.

Commerzbank declared that it will benefit greatly from Google Cloud’s capabilities in infrastructure modernization, data analytics, and machine learning.

Moreover, Commerzbank also announced a ‘Strategy 2024’ approach, which will represent customer-centricity, digitalization, sustainability, and profitability, with a goal to run 85% of its decentralized applications in the cloud by that date.

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With all the options involved, multi-cloud can be reached via many different routes. What makes the difference today? Containers.

Containers and application design 

Software containers provide a way to package application elements as small and transferable elements. Rather than virtualisation – where virtual machines include operating systems and applications to run – containers are much smaller. They run on top of the Linux operating system and tap into the kernel, sharing resources across all container images and making the application containers themselves more efficient.

More importantly, the most popular container orchestration system, Kubernetes, has made it possible to move these container images between different providers and carry on running. Rather than being tied to internal data centre deployments, to specific data centre locations or to any single service provider, enterprises can migrate easily as and when suits them. For DevOps teams, container orchestration should make the move to container-based applications easier, even while the underlying infrastructure can become more complex.

According to Gartner, more than 75 percent of global organisations will be running containerised applications in production in 2022, compared with under 30 percent today. Container options like Kubernetes and Docker have grown rapidly in adoption – according to our research, around 30 percent of companies are running Docker on AWS in 2019, up from 18 percent in 2016 and 24 percent in 2017. Similarly, native Kubernetes deployments have grown from 8 percent in 2017 to 20 percent in 2019.

The reason for this is that containers represent a big change in how applications are deployed. Using containers, you can scale up and down in response to demand levels much faster than traditional IT infrastructures or virtualised environments allow. Using microservices design and API connections, you can also replace or extend these application components more easily than traditional application designs allow.

Theory vs practice

In theory, you can lift a set of containers from your internal data centre and run them to deliver a service in a public cloud, on a managed service, and bring that service back again too. Kubernetes should, therefore, help companies to adopt a hybrid cloud or multi-cloud strategy where the organisation has more control over its destiny. For the public cloud providers, the advent of Kubernetes should drive up more adoption of their services too. In practice, multi-cloud is still in its early stages – according to our research, currently, around nine percent of companies are running multiple clouds.

While multi-cloud deployments are still in their initial stages there is a strong correlation between this and use of Kubernetes – while around 20 percent of AWS customers use Kubernetes, this goes up to 59 percent for those running AWS and Google Cloud Platform (GCP) and to 80 percent for those running AWS, GCP, and Azure together.

Theory, Meet Practice

 However, the move to containers can be more challenging in the longer term. The ability to run containers in the same way wherever the right infrastructure is located should provide more freedom to deal with availability and scalability concerns. What needs to be considered is how to wrap the right management approach around containers, so that the right decisions can be made consistently over time.

For DevOps teams, this means looking at observability – how to get the right data on details like each container instance through up to the whole application service. Observability comes from using application and infrastructure logs, metrics and tracing data together to build up the best possible picture of these new services.

Without data, it is difficult for developers building applications in containers to see problems. Similarly, it can be hard for infrastructure and operations teams to know that they are running applications in the most efficient way, or if they need to budget for additional capacity. From a practical perspective, gathering this data from each machine image or container is itself challenging, too.

While it is possible to orchestrate and manage containers at a massive scale, the observability side has not kept up. For companies with applications running across multiple data centre locations, or combinations of internal and external cloud services, this observability should be critical in order to control spend and budget allocation. However, it can easily be missed.

The specifics of containers

The first issue is that containers don’t produce data in the same way as virtual machines or more traditional physical servers. Each container can provide data on operations, but the information will stay within the container unless it is collected and centralised. For teams running applications across multiple locations, this process has to be considered from the start.

Containers also lose their data records when they shut down. For services that rely on flexibility and scaling up and down in response to demand levels, this can make it extremely difficult to track use patterns and application behaviour across different sites. Without this machine data, it becomes hard to run these multi-cloud applications over time.

Secondly, each of these images can be run anywhere. Rather than information automatically being gathered in one place, you either have to correlate data from multiple containers running across different instances or look at data specifically from the application itself. Neither of these approaches will be enough on its own to provide the right level of context for making decisions.

Getting a complete overview of these new applications – whether they are hosted internally, externally or as a mix of both – will be essential if you make the move to implement containers. Without this data, you run the risk of allocating resources in the wrong ways. By understanding the landscape developing around your applications, you can back the right approach for the future, rather than taking the wrong route. Regardless of who is viewed as winning the multi-cloud crown, it’s worth understanding how the race was won too.

Written by Mark Pidgeon, Vice President Technical Services at Sumo Logic. 

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New research reveals significant year-over-year growth in enterprise usage trends around multi-cloud adoption, open source technologies such as Kubernetes, and Amazon Web Services (AWS) cloud-native services adoption.

Sumo Logic’s The Continuous Intelligence Report: The State of Modern Applications and DevSecOps in the Cloud also revealed the increasing need for cloud-based security solutions such as cloud SIEM to help enterprises address today’s increasingly complex security landscape.

The report also summaries three major trends shaping today’s digital business:

• the rise of modern applications
• the rapid adoption of DevSecOps collaboration and processes
• the emergence of the Intelligence Economy from the tsunami of data.

Because of this shift, digital businesses now have real-time accountability understanding what is happening in their business the moment it happens, but the velocity, veracity and variety of their data makes it easy to fall behind.

The report states that this results in an intelligence gap, which impedes the real-time decision-making required for modern on-demand, customer experiences, but that the industry is recognizing that continuous intelligence as a strategy and capability is the best way to close this gap.

Stephen O’Grady, principal analyst with software development analyst firm, RedMonk, said: “Today’s enterprise technology landscape is more dynamic and fast moving than ever, and understanding what is changing and how quickly requires at-scale visibility into what businesses are embracing.

“The conclusions contained in Sumo Logic’s report, itself based on insights from thousands of customers, is broadly aligned with RedMonk’s projections for the industry moving forward, and thus offers value to executives and practitioners tasked with setting technical direction.”

Based on anonymized data from more than 2,000 customers and 100,000 users, this report takes that data to provide a unique analysis of mission-critical modern applications and cloud infrastructures running on AWS, Microsoft Azure and Google Cloud Platform (GCP).

Kalyan Ramanathan, vice president of product marketing for Sumo Logic, said: “Multi-cloud and open source technologies, specifically Kubernetes, are hand-in-hand dramatically reshaping the future of the modern application stack. For companies, the increased adoption of services to enable and secure a multi-cloud strategy are adding more complexity and noise, which current legacy analytics solutions can’t handle. To address this complexity, companies will need a continuous intelligence strategy that consolidates all of their data into a single pane of glass to close the intelligence gap.”

Key findings from this year’s report include:

• multi-cloud is growing faster than any other modern infrastructure category
• enterprise adoption and deployments of multi-cloud grew 50% year-over-year.
• Kubernetes is highly prevalent in multi-cloud environments

As customers adopt multi-cloud, Kubernetes adoption significantly rises. Enterprises are betting on Kubernetes to drive their multi-cloud strategies:

• 20% of customers in AWS-only environment use Kubernetes
• 23% of customers on AWS and Azure use Kubernetes
• 59% of customers on AWS and GCP use Kubernetes
• more than 80% of customers on all three clouds use Kubernetes.

Open source has disrupted the modern application stack:

• 4 of the 6 tiers that make up the modern application stack have been disrupted by open source
• open source solutions for containers, orchestration, infrastructure and application services are leading this transformation.

Enterprises only use 15 out of 150+ available AWS cloud-native services:

• adoption of individual IaaS services suggest enterprises are trying to avoid vendor lock-in.
• basic compute, storage, database and network services services make up top 10 adopted services in AWS
• the top AWS cloud-native services used: EC2, RDS, IAM, STS, CloudFormation.

Serverless adoption has reached a tipping point:

• serverless architectures continue to grow at a rapid pace as a cost-effective option to speed cloud and DevOps deployment automation.
• AWS Lambda adoption grew to 36% in 2019, up 12% from 2017
• 1-in-3 enterprises are using serverless in production
• AWS Lambda is also being used in several non-production use cases and has become one of the top 10 AWS services by adoption.

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The report provides a rich analysis of mission-critical modern applications and cloud infrastructures running on Amazon Web Services (AWS), Microsoft Azure and Google Cloud Platform (GCP).

Multi-cloud technologies

It found that Azure adoption grew from 10%  (2017) to 15% (2018); adoption of multi-cloud technologies grew from 6% (2017) to 9% (2018) and that the percentage of exclusively on-premises workloads has decreased dramatically from 26% (2017) to 16% (2018).

“For the past two years, Sumo Logic has delivered the first and only industry report that quantitatively defines the state of the modern application stack,” said Kalyan Ramanathan, VP of product marketing, Sumo Logic, in a press release.

Tools & processes

“Working with our customers, we continue to see rapid advances in tools and processes used by various enterprise personas to build, run and secure modern applications, and we’re now extending our analysis to DevSecOps, an innovative trend for developing, securing and operating modern applications that are growing rapidly in adoption amongst our customers.”

The report also found that AWS Docker adoption has grown from 24% (2017) to 28% (2018), and nearly 30% adopted AWS Lambda when in production compared to 23% in 2017.

Written by Leah Alger

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Taking advantage of being one of Microsoft’s ExpressRoute partners, and leveraging its low latency cloud connection services such as Multi-Cloud Connect and Software-Defined Exchange Service, it has “achieved fast and secure connections to Azure”.

Microsoft’s Gold Cloud Platform status has now been awarded to the following NTT groups worldwide:

• NTT Communications
• NTT Com Manages Services SAU
• NTT America
• NTT Europe
• NTT Com Asia (Hong Kong)
• NTT Singapore
• NTT Com ICT Solutions (Australia)
• As well as two Asian based subsidiaries; Emerio and Netmagic.

Damian Skendrovic, NTT CEO, said: “Gold status is an important recognition of our competency in the cloud arena.

“With Microsoft Cloud Platform Competency, we are helping enterprises to manage their hybrid cloud infrastructures, delivering on SaaS and PaaS solutions available in the Azure and Azure Stack marketplace that will enable our customers to optimise on performance and reach their business goals.”

Written from press release by Leah Alger

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The company showcased TrueSight Cloud Cost Control and SecOps Policy Service at today’s BMC Exchange event in New York, which manages cost, compliances and next-generation performance monitoring through artificial intelligence and machine learning.

The complexity is created by multi-cloud, enabling speed and innovation, and amplifying the traditional challenges and pressures placed on IT and the business: visibility, cost, security, performance, automation, and migration.

BMC introduced two solutions today that address amplified challenges:

• TrueSight Cloud Cost Control is a cost management solution that analyses current and future costs and utilisation of multi-cloud infrastructure services, providing insight and control over capital and operating expenditures. With a single view of on-premises and public cloud infrastructure spend, organisations can track and analyse infrastructure costs and utilisation, identify overspending, and forecast future costs.
• SecOps Policy Service embeds compliance and security testing into the software development lifecycle, empowering developers to perform critical checks without stalling innovation. The cloud-based solution provides continuous verification, analytics, and governance to ensure compliance is protected, reducing risk when creating multi-cloud applications.

Bill Berutti, president for enterprise solutions at BMC, said: “Businesses are in the midst of dramatic transformation from the data centre to the cloud and beyond.

“Enterprises are poised to spend roughly US$1.1trillion in digital transformation technologies. This investment creates unprecedented opportunities for companies to develop new services, enhance employee productivity and efficiency, improve real-time decision-making, and develop new and innovative user experiences.”

Written from press release by Leah Alger

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