Both DevOps and NoOps are approaches designed to improve the efficiency and reliability of IT operations and software delivery. While they share some similarities in terms of automation and the goal of improving operational efficiency, they differ in their scope and implementation. DevOps focuses on collaboration between development and operations teams, while NoOps seeks to eliminate the need for traditional operations teams altogether by relying on fully automated systems.

This post will explore the key differences between DevOps and NoOps, discussing their major features, goals, and how they fit into modern IT and software development strategies.

1. Definition and Scope

DevOps:

• Collaboration between Dev and Ops:
  • DevOps is a cultural and technical approach that unifies development (Dev) and operations (Ops) teams. It emphasizes collaboration, communication, and shared responsibility to improve the software delivery pipeline.
• Automation and Continuous Integration:
  • DevOps practices focus on automating manual processes like code integration, testing, deployment, and monitoring. This automation accelerates software development, reduces errors, and ensures consistent application delivery.
• End-to-End Management:
  • DevOps covers the entire software lifecycle, from planning and development to deployment and monitoring in production. The goal is to ensure smooth and reliable software delivery by aligning teams across various stages.

NoOps:

• Automation of IT Operations:
  • NoOps is a concept that aims to automate the entire IT operations process, reducing or eliminating the need for manual intervention by operations teams. The idea is that the development and operations processes are fully automated using tools and cloud infrastructure.
• Zero Human Intervention:
  • In a NoOps environment, the need for traditional operations roles is minimized or eliminated entirely. Infrastructure management, scaling, deployment, and monitoring are handled automatically, often via cloud platforms with built-in automation features.
• Focus on Simplicity and Agility:
  • NoOps allows teams to focus purely on development and innovation without worrying about managing infrastructure. It is often associated with serverless computing, where the cloud provider manages all operational tasks.

2. Objectives and Goals

DevOps:

• Faster Software Delivery:
  • The primary goal of DevOps is to accelerate the software delivery process by fostering collaboration between developers and operations teams. This is achieved through automation, continuous integration, and regular software releases.
• Improved Collaboration:
  • DevOps seeks to break down silos between teams and encourage collaboration. By aligning development and operations goals, DevOps improves communication and reduces the friction typically seen in traditional software development processes.
• Continuous Improvement:
  • DevOps emphasizes continuous improvement through regular feedback loops. Automated testing, monitoring, and performance tracking allow for quick identification of issues and areas for optimization.

NoOps:

• Automation and Self-Healing Systems:
  • The main objective of NoOps is to automate all operational tasks to the point where no human intervention is required. This results in highly automated systems that can scale, deploy, and manage applications without dedicated operations teams.
• Minimized Operational Overhead:
  • By using NoOps practices, organizations aim to minimize the operational complexity traditionally associated with running IT systems. This reduces the need for skilled infrastructure teams and shifts focus toward more strategic business goals.
• Empowering Developers:
  • NoOps allows developers to manage everything from development to deployment without relying on operations teams. This enables faster iterations, quick experimentation, and more efficient development cycles.

3. Roles and Responsibilities

DevOps:

• Shared Responsibility:
  • In a DevOps environment, the responsibilities of both development and operations teams are shared. Development teams are responsible for writing code and ensuring quality, while operations teams manage infrastructure, deployment, and monitoring.
• Collaboration Across Teams:
  • The key role of DevOps is to improve the relationship between developers and operations teams. By having both teams involved in every step of the lifecycle, DevOps ensures a smooth transition between stages such as development, testing, deployment, and maintenance.
• Cross-Functional Teams:
  • DevOps promotes the creation of cross-functional teams that bring together development, operations, security, and other stakeholders to collaborate on software projects from start to finish.

NoOps:

• No Dedicated Operations Role:
  • In a NoOps environment, the traditional operations role is either eliminated or significantly reduced. There are no distinct operations teams, as IT operations are fully automated, and cloud services handle the infrastructure needs.
• Developer-Centric Model:
  • Developers take on more responsibility in a NoOps environment, as they manage infrastructure deployment, scaling, and monitoring through automated tools and cloud-based services. This shifts the operational burden away from separate IT teams.
• Reliance on Cloud Providers:
  • NoOps relies heavily on cloud services and platforms like AWS, Google Cloud, or Azure, which offer built-in automation and self-healing features that eliminate the need for dedicated operations professionals.

4. Tools and Automation

DevOps:

• CI/CD Tools:
  • DevOps relies on CI/CD tools like Jenkins, GitLab CI, Travis CI, and CircleCI to automate the processes of continuous integration and continuous delivery. These tools enable developers to continuously test, integrate, and deploy code.
• Infrastructure as Code (IaC):
  • DevOps incorporates IaC tools like Terraform, CloudFormation, and Ansible to automate infrastructure provisioning and configuration. This ensures consistency and scalability of environments.
• Monitoring and Logging:
  • DevOps teams use tools like Prometheus, Grafana, and ELK Stack to monitor applications and infrastructure. These tools provide visibility into the performance and health of systems, allowing for proactive troubleshooting.

NoOps:

• Cloud Automation Platforms:
  • NoOps relies on fully managed cloud platforms, such as AWS Lambda, Google Cloud Functions, and Azure Functions, to automatically handle infrastructure management, scaling, and provisioning.
• Serverless Computing:
  • NoOps embraces serverless architecture, where the cloud provider automatically manages resources, scaling, and deployment. Tools like AWS Lambda, Google Cloud Functions, and Azure Functions enable developers to deploy applications without managing servers.
• Self-Healing Infrastructure:
  • NoOps environments use self-healing infrastructure provided by cloud platforms, which automatically scale applications, detect issues, and resolve them without manual intervention.

5. Scalability and Complexity

DevOps:

• Scalability through Automation:
  • DevOps allows organizations to scale their applications and infrastructure by automating repetitive tasks and provisioning resources as needed. This helps to optimize both cost and performance.
• Handling Complex Systems:
  • DevOps handles complex environments, such as hybrid clouds or microservices architectures, by using containerization technologies like Docker and orchestration tools like Kubernetes to manage deployments and scaling.
• Dynamic and Flexible:
  • DevOps practices enable teams to rapidly adjust to changing requirements or workloads by automating scaling, provisioning, and deployment processes.

NoOps:

• Fully Managed and Scalable Systems:
  • NoOps environments leverage the scalability offered by cloud providers to automatically scale applications without requiring human intervention. This scalability is built into cloud services like AWS Elastic Beanstalk, Google Kubernetes Engine, and Azure App Services.
• Simplified Complexity:
  • NoOps eliminates the need for managing complex infrastructures. With cloud-native services, all the complexities of scaling, infrastructure management, and resource allocation are handled automatically by the cloud provider.
• Zero Manual Configuration:
  • In NoOps environments, there is minimal manual configuration required. The cloud provider takes care of infrastructure, scaling, and management, allowing developers to focus on application code.

6. Use Cases and Adoption

DevOps:

• Enterprise and Traditional Development:
  • DevOps is suitable for organizations with large, complex IT systems that require continuous development and integration of applications. It is widely adopted in industries such as finance, healthcare, and e-commerce.
• Custom Development and Infrastructure Management:
  • DevOps is beneficial for organizations that need customized solutions and have dedicated operations teams to manage infrastructure, security, and compliance.
• Legacy Systems Integration:
  • DevOps can be applied to existing legacy systems to automate processes and improve software delivery efficiency, even in environments with traditional IT infrastructure.

NoOps:

• Serverless and Cloud-Native Applications:
  • NoOps is best suited for organizations that are building cloud-native applications or working with serverless computing. It is particularly useful for startups and smaller teams that need to focus on rapid development without managing infrastructure.
• Cost-Effective Scaling:
  • NoOps environments are ideal for companies looking to reduce the operational overhead of infrastructure management. By relying on cloud providers, companies can scale their applications without the cost and complexity of maintaining dedicated infrastructure teams.
• Quick Deployment and Prototyping:
  • NoOps is ideal for rapidly prototyping new ideas and applications, as it reduces the complexity of infrastructure management and accelerates the time to market for new features.

DevOps vs NoOps

While DevOps and NoOps share a common goal of improving the software delivery process, they differ in their scope, approach, and execution. DevOps is a collaborative model that relies on automation and communication between development and operations teams to streamline the software lifecycle. In contrast, NoOps aims to eliminate the need for traditional operations teams by fully automating infrastructure and relying on cloud platforms to manage everything.

Organizations should choose between DevOps and NoOps based on their size, infrastructure complexity, and cloud adoption strategy. DevOps is ideal for large organizations with complex infrastructure needs, while NoOps is better suited for cloud-native and serverless environments where automation and scalability are key.

As I explained in my prior blog, Containers Practices Gap Assessment, containerizing software is valuable for DevOps.

Yet, as I work with clients on their DevOps journeys, I continue to encounter organizations that haven’t grasped the importance of using containers relative to bare metal, virtual machines (VMs) and serverless computing solutions. This article is intended to help organizations understand the difference and the advantages that containers offer for DevOps.

The workhorse of IT is the computer server on which software application stacks run. The server consists of an operating system, computing, memory, storage and network access capabilities; often referred to as a computer machine or just “machine.”

A bare metal machine is a dedicated server using dedicated hardware. Data centers have many bare metal servers that are racked and stacked in clusters, all interconnected through switches and routers. Human and automated users of a data center access the machines through access servers, high security firewalls and load balancers.

The virtual machine introduced an operating system simulation layer between the bare metal server’s operating system and the application, so one bare metal server can support more than one application stack with a variety of operating systems.

This provides a layer of abstraction that allows the servers in a data center to be software-configured and repurposed on demand. In this way, a virtual machine can be scaled horizontally, by configuring multiple parallel machines, or vertically, by configuring machines to allocate more power to a virtual machine.

One of the problems with virtual machines is that the virtual operating system simulation layer is quite “thick,” and the time required to load and configure each VM typically takes some time. In a DevOps environment, changes occur frequently. This load and configuration time is important, because failures that occur during the load and configuration can further delay the instantiation of the VM and the application.

The idempotent characteristic of modern configuration management tools such as Puppet, Chef, Ansible and SaltStack do help to reduce the chance for errors, but when configuration errors are detected, delays to reload and reconfigure the stacks take time. These delays constitute significant delays for each DevOps stage, and the accumulated time for the series of stages needed for a DevOps pipeline can be a significant bottleneck.

VMs are used in production IT environments because of the flexibility to support different configurations. However, the time to reload and configure VMs can be a bottleneck during release reconfigurations, and can delay mean-time-to-repair when failures occur.

Containers, such as those supported by Docker, have a very lightweight operating system simulation layer (the Docker ecosystem) that is tailored specifically to each application stack. Container systems such as Docker guarantee isolation between application stacks run over the same Docker layer.

Compared to VMs, the smaller “footprint” of containerized application stacks allows more application stacks to run on one bare metal machine or virtual machines, and they can be instantiated in seconds rather than minutes. These desirable characteristics make it easy to justify a migration from running an application stack on bare metal machines or VMs. Instead of time-consuming loading and configuring an application stack and OS layer for each machine, instantiation of a complete container image is loaded, and a small number of configuration variables are instantiated in seconds. This capability to quickly create and release containerized applications allows for the infrastructure to be immutable.

In thirty minutes, someone can go from having nothing on their machine to a full dev environment and the ability to commit and deploy. Containers are the fastest means to launch short-lived, purpose-built testing sandboxes as part of a continuous integration process.

Containers are the result of a build pipeline (artifacts-to-workload). Test tools and test artifacts should be kept in separate test containers. Containers include minimal runtime requirements of the application. An application and its dependencies bundled into a container is independent of the host version of the Linux kernel, platform distribution or deployment model.

Benefits of Containers
Benefits of containers include the following:

The small size of a container allows for quick deployment.
Containers are portable across machines.
Containers are easy to track and it is easy to compare versions.
More containers than virtual machines can run simultaneously on host machines.
The challenge with containers is to get your application stack working with Docker. Making containers for a specific application stack is a project easily justified by the ROI of reduced infrastructure costs and the benefits provided by immutable infrastructures such as fast mean-time-to-restore-service (MTTRS) during failure events.

Containerized infrastructure environments sit between the host server (whether it’s virtual or bare metal) and the application. This offers advantages compared to legacy or traditional infrastructure. Containerized applications start faster because you do not have to boot an entire server.

Containerized application deployments also are “denser,” because containers don’t require you to virtualize a complete operating system. Containerized applications are more scalable because of the ease of spinning up new containers.

Recommended Container Engineering Practices
Here are some recommended engineering practices for containerized infrastructure:

Containers are decoupled from infrastructure.
Container deployments declare resources needed (storage, compute, memory, network).
Place specialized hardware containers in their own cluster.
Use smaller clusters to reduce complexity between teams.
Serverless computing is a cloud computing execution model in which the cloud provider runs the server and dynamically manages the allocation of machine resources. Pricing is based on the actual resources consumed by an application, rather than on pre-purchased units of capacity. Serverless computing can simplify the process of deploying code into production. Scaling, capacity planning and maintenance operations may be hidden from the developer or operator. Serverless code can be used in conjunction with code deployed in traditional styles, such as microservices. Alternatively, applications can be written to be purely serverless and use no provisioned servers at all.

What This Means
This blog explained how containers compare to bare metal, virtual machines and serverless solutions. Those who are serious about DevOps would do well to learn about the advantages that containers offer as part of a DevOps solution. To learn more about containers, refer to my book Engineering DevOps.

Recently google Announcement New serverless Database Migration Service (DMS) In preview. This service supports migrating self-hosted MySQL databases on-premises or in the cloud, as well as managed databases from other clouds to Cloud SQL for MySQL.

New serverless services for database migration are aimed at enterprises migrating to Google Cloud Platform (GCP) managed database services Cloud SQL Or Google computing engine Seamlessly. In addition, according to a post on the announcement blog, customers using this service will benefit from:

Migration using DMS keeps data replication from the source database to the destination without any manual steps, minimizing downtime.
DMS uses the database’s native replication capabilities to maximize fidelity and reliability for a reliable and complete migration.
It’s serverless and secure because you don’t have to provision or manage migration-specific resources or monitor them to keep everything running smoothly.

In addition to Google, Microsoft Azure and AWS also offer database migration services. Azure for customers Azure managed SQL instance service. This allows customers to move their on-premises applications to the cloud with minimal application and database changes. AWS DMS It enables migration from Oracle to Oracle and heterogeneous migration between different database platforms such as Oracle to Amazon RDS for Oracle, MySQL to Amazon Aurora, MySQL to Amazon RDS for MySQL, and Microsoft SQL Server to Amazon RDS for SQL Server.

SAN FRANCISCO–(BUSINESS WIRE)–Vendia, a multi-party application development platform for sharing code and data in real time, has been recognized as a 2021 Gartner Cool Vendor in the “Cool Vendors in Cloud Computing” report by Arun Chandrasekaran, Sid Nag, and David Wright on May 13, 2021.

Business critical data is dispersed across both internal and external silos, making it challenging to control and share in real time. Vendia’s decentralized data platform enables the sharing and synchronizing of data or code across clouds, partners, and tech stacks with immutability and control. It is being used in production today to power multi-party distributed applications for track and trace of goods and services across complex supply chains, financial settlements and transactions, and real-time data analytics for AI/ML and IoT use cases. Vendia’s serverless implementation makes building distributed applications scalable, cost efficient, and developer friendly.

“Coming at a time when we are barely a year past our founding, this recognition by Gartner is an especially great honor,” said Tim Wagner, co-founder and CEO of Vendia. “Our mission is to simplify the challenges of building applications that span data silos and clouds by creating a single source of truth, while ensuring that each partner retains full control over its data. We’re delighted that Gartner recognizes the need for our offering in the market.”

This Gartner Cool Vendor in Cloud Computing report states “CIOs should assess these Cool Vendors that are disrupting the cloud market through robust multicloud implementation products.” The complete report can be accessed on Gartner, or read more about it on the Vendia blog.

Disclaimer

Gartner does not endorse any vendor, product or service depicted in our research publications, and does not advise technology users to select only those vendors with the highest ratings. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

Vendia

Vendia provides multi-cloud services that make it easy for organizations to share real time data and code across clouds, companies, and regions for data integration, financial settlement, ML training, transaction processing, supply chain solutions and more. Vendia was founded by Dr. Tim Wagner, formerly General Manager and creator of AWS Lambda at AWS, and Shruthi Rao, formerly Head of Business Development for Amazon Managed Blockchain at AWS. The company is based in San Francisco and has raised $20.6M in funding led by BMW i Ventures, Canvas Ventures, Neotribe Ventures, Sorenson Ventures, and other leading investors.

Cloud computing is quickly gaining ground in the business world and Microsoft Azure is taking the lead. About 84% of enterprises had a multi-cloud strategy in 2019. Gartner’s Top Strategic Trends for 2021 has established that organizations require a strong AI strategy to make sure that their projects don’t stall.

With cloud computing showing no signs of reducing in its application and Microsoft taking a strong lead, it is important to examine what Azure Cloud is and how it impacts businesses and what Microsoft would be doing with it in the future.

What is Microsoft Azure?
Azure Cloud is a cloud platform that provides both low-level cloud solutions and high-level infrastructure. The infrastructure makes it possible for companies to run their applications in a scalable, elastic, and redundant environment hosted in the cloud.

Signing up on the Azure Cloud platform gives you access to over 200 products and cloud services that are designed to offer new solutions to your business operations. It is designed to solve modern business challenges and help build a future that would be unimaginable without cloud computing.

With Microsoft Azure, you can build, run and manage applications across multiple clouds, on-premises, and at the edge with great tools of your liking.

Why Azure Cloud holds the future of cloud services?
Virtually everything in the digital world has a connection with the cloud in some way. As tech giants focus on developing new ways of organizing, processing, and presenting data, cloud computing is slowly becoming part and parcel of our everyday lives.

In the recent past, Microsoft Azure, Google Cloud, and Amazon Web Services have provided cloud computing and cloud storage services. Newer entrants such as Vultr and Linode have also made inroads into the space.

What do you think is the future of cloud computing? How will it affect future business strategies, and to what extent? Concepts such as decentralized cloud computing and serverless cloud may start trickling into your mind.

Infrastructure as a Service (IaaS)
Azure today is synonymous with Infrastructure as a Service. IaaS is the primary low-level public cloud service used to provide instant computing infrastructure. It is managed over the internet.

IaaS is unique because it is less expensive and is a simple way of managing physical servers and data center infrastructure. It offers essential storage, computing, and networking resources on demand.

With all the amazing computing benefits that come with it, adopting an IaaS solution for your organization helps reduce maintenance of on-premises data centers, gain real-time business insights and save money that would have been spent purchasing and maintaining hardware.

Organizations are keen on the scalability of their business operations, and more emphasis will be put on this in the future. IaaS solutions give businesses the flexibility to scale their IT resources up or down as their needs change. They also have a provision for you to quickly introduce new applications, further increasing the reliability of your infrastructure.

With IaaS, you will not incur the costs of buying and managing physical servers and data center infrastructure. Besides, you only have to pay for the resources you need since each one of them is offered separately.

Azure Data and Analytics
Azure data and analytics provide unified data governance that helps organizations do away with data challenges and shape their future.

Azure Cloud makes the future look bright by offering the general availability of Azure Synapse Analytics, a limitless analytics service that provides business insights with an emphasis on enterprise data warehousing, Big Data, and data integration.

Azure Synapse Analytics combines various capabilities, among them, machine learning, business intelligence, and data engineering. Simply put, Azure Synapse Analytics securely and seamlessly unifies your company’s data in one location.

You can get started with Azure’s machine learning features in this guide from Iteration Insights.

Data Security
No other player in the tech industry beats Azure Cloud in offering secure cloud computing. Microsoft leverages several years of being a productivity solution provider and being an enterprise operating system to provide top-shelf security to all the information hosted in their cloud products.

Microsoft Azure has put together several resources to ensure organizations’ on-site data centers are secure. They update their systems on a regular basis to make their systems immune to external threats.

Once you have purchased Azure Cloud services, you will gain access to all elements related to the security of your information. All their customers have access to the latest threat detection and prevention technologies.

There is a range of security solutions and architecture that come with Azure Cloud. They include Information Protection which enables organizations to classify and protect specific information, documents, and emails by applying labels to them, and Advanced Threat Protection and Threat Intelligence.

Azure Cloud threat monitoring agents generate real-time security alerts and threat intelligence reports which provide insights into the attackers, their motives, and their tactics.

Improved business sustainability and scalability
Many businesses will be expanding their operations in the future. If they want to do so without major hiccups, they should adopt Microsoft Azure Cloud technology which provides scalability to businesses.

Under normal circumstances, it is quite costly and time-consuming to expand a business and provide it with new infrastructure. Azure Cloud guarantees the availability of services throughout the year, thanks to its many data centers the world over. As if that is not enough, Microsoft is planning to add even more servers.

Azure Cloud boasts of having a physical infrastructure in every continent. This allows for replication in the case where an organization would like to expand beyond the borders of one continent.

Final thoughts
There is no doubt that Azure Cloud is a game-changer in cloud computing. The public cloud service, IaaS, for instance, is making cloud computing very easy while providing a simple way of managing physical servers and data center infrastructure. If you picture the future of cloud computing, you are probably thinking serverless cloud, enhanced data security, improved business analytics, and business scalability. Azure Cloud provides it all. It holds the future of cloud computing in its hands – or in the cloud – so to speak!

A few days ago, I had the privilege of attending a boardroom discussion of CISOs at the virtual Chicago CISO Summit on the topic of Rethinking Security and Governance in the Public Cloud. The boardroom discussions are great since they serve as an opportunity to benchmark various CISO topics, and to discover cloud security challenges enterprise organizations are facing.

It’s clear from our discussion that the ways in which we build technology value have changed drastically. Shifts from monolithic software to microservices, waterfall development to agile, IT to DevOps, and data centers to cloud form the foundation of the digital disruption revolution executives are leading. And, in the past 12 months, executives have ramped cloud faster than anyone ever expected.

With this rapid evolution, it is clear that enterprises must re-invent how they govern and secure in this “new world” where identities are the new perimeter. The old control points of IT, firewalls, and endpoints are simply outdated and ineffective in the new world of cloud development. Today, Cloud Service Providers, like AWS, Azure, and Google Cloud, look after the infrastructure and for enterprises, the new control points now center around identity, data, and the workload itself.

This transformation was top of mind in our session that was attended by twelve CISOs from public and private companies from a variety of industry verticals including Finance, Insurance, Retail, and more. In our group, all CISOs expressed some challenges with the complexity of the public cloud, rapid changes of the past twelve months, and blind spots in cloud security. For larger or more security-mature organizations, the complexities included a lack of integration between multiple departments including, DevOps, audit teams, security, and operations.

Takeaways From Our Boardroom
Identity is the New Perimeter
For many years, defense in depth was dominated by network controls. Traditional network security controls remain an essential component of public cloud security, but they aren’t sufficient. AWS, Azure, GCP, and others offer a rich service portfolio that exposes pubic HTTPS endpoints by default. IAM controls are the primary method of protection. However, not all of these services allow IP-based access control list (ACL) rules. Additionally, IP-based ACLs are coarse and inflexible controls for modern microservice-based cloud applications. The foundation of information security is in the public cloud focuses on identity-based security that controls access to cloud-based resources and data. Security professionals recognize that “identity is the new perimeter” for securing data in public clouds, and consequently, proper identity security is crucial to managing access-related errors. At Sonrai security we offer updated webinars to guide you on this journey of cloud security. Public cloud IAM models introduce many identity-to-data trust relationship configuration options that, although powerful, can come with risk. For example, poorly used access IAM controls leave significant attack vectors to sensitive data.

Entitlement Risk
Many CISOs in our group believe the highest identity risk lies with “entitlements,” not users or identities alone. The ability to delegate roles can become quite problematic in a public cloud because they are often a hidden risk. Management controls must be adapted to address concerns around privilege delegation to a service or function. Compute, containers, and serverless functions can assume a role that can be configured with permission to perform specific tasks and access certain data.

Granting an assumed role to a service can be your friend when your public cloud is architected correctly by a knowledgeable IT security and cloud team. It eliminates the unfortunate programming habit of storing service account credentials in configuration files or worse in the code. However, the delegation of a dominant role to a service must be fit for purpose with a focus on least privilege. Without this focus, you open your organization to risk.

Privacy Concerns
Our group’s CISOs are seeing privacy become a real hot button topic with board members with the advent of GDPR and similar regulations. They are beginning to see asks from the board to be educated on these topics and informed about the state of “privacy compliance” of the organization. Many of our group’s members see this has a huge challenge as many cannot effectively answer “where is my data?”, “who can access my data?” and “when has it been accessed?” They foresee many difficult discussions that will wrestle with questions like: “who and what exactly do we do with our customers’ data” while “not stopping the business” or increasing risk.

Cloud Complexity
Cloud complexities will continue to grow. The widespread adoption of cloud-native computing, micro-service-based architectures, containers, and serverless has led to an explosion in the number of ways that people and non-people identities can access sensitive data in public clouds. While this leads to incredible innovation, if ungoverned, it leads to a boatload of risk. Many CISOs must address the need for modern cloud-native organizations to find and prevent vulnerabilities tied to interrelationships between identity (people and non-people) and data.

Finding and eliminating complex identity and data access risks, in a way that aligns with how applications are developed today is a big challenge for security teams. Many CISOs struggle with operational workflow and remediation which prevent them from integrating seamlessly to eliminate risk in complex environments. Early cloud security systems have focused on simpler cloud network setups and sent too many alarms to the wrong teams. The CISO teams think that a new cloud security model needs to be heavily focused on identity and data.

Shift Left Needs Clarity
Some CISOs felt very strongly that this was their very frustrating) Achilles heel. There is still significant work to be done, particularly in the areas of including security in the CI/CD pipeline sooner. Although there is an industry-wide push to shift left, greater clarity is needed on how teams’ daily responsibilities are changing, because it impacts the entire organization’s security proficiency.

Conclusion
Building on the success of this boardroom session, we’re looking forward to ongoing, productive conversations that have focused on key data security issues including compliance, data governance, identities, and more. With this evolution underway, it is clear that leaders are reinventing how they govern and secure in this “new world” and we are here to help.

From rapidly transforming consumer behaviors to heavily affecting economies around the globe, the Covid-19 pandemic has created a plethora of challenges and continues to have a multi-sector impact on nations and citizens alike.

With the arrival of vaccinations, 2021 seems to bring a new ray of hope for economies worldwide but the fact remains: This year is going to witness the ‘survival of the fittest,’ implying that businesses that turn digital and adapt to the ‘new normal’ are likely to emerge out of the Covid-19 crisis in better position to succeed.

To begin with, cloud computing is arguably going to remain the staple of leading companies. To give a quick run-through, cloud spending grew by 37% in the first quarter of 2020 itself – ushering in a new era of digitization wherein companies look at cloud computing as the most robust way to tide themselves over during the Covid-19 challenge – at this time last year the world had just woken up to the viral effect of the novel Corona virus beyond China. Capitalizing upon the urgency to drive processes remotely and securely, cloud service providers had an unlikely successful year.
Even as total IT spending dropped by 8%, the cloud market grew substantially. Having worked on a number of cloud implementations, I pick the following three key trends in the post-Covid era.

Cost optimization was always a priority before the pandemic. However, disruptions afterward have further elevated its stature in the priority stack. Today, start-ups and enterprises are seeking intelligence to deploy flexible cost models, particularly those in pay-as-you-go services. As expected, the OpEx versus CapEx solutions debate has once again intensified.

In the pursuit of normalization, controlled costing is the first step. With OpEx, businesses can get the total of their costing parameters while achieving scalability with products & services. PwC, in its latest survey, found that 75% of finance decision-makers use OpEx cost modeling and are deferring CapEx for at least another year.

Cloud ecosystems assure total flexibility and scalability in developing and managing key enterprise processes. Using OpEx as a cost model and cloud as a deployment model, enterprises can:

Achieve faster installations, upgrades, and on-demand flexibility. Given the lesser time of approval in OpEx, businesses can leverage frequent product upgrades.
Cloud systems mean negligible maintenance hassles and site visiting. The OpEx model allows for seeking cloud hosting services that cover uninterrupted networking infrastructure and enterprise-grade security.
Entities, both government and private, are likely to upscale their infrastructure capacity in 2021. At the same time, they want to keep costs in control. Therefore, hybrid cloud systems backed by OpEx cost models will set the narrative for data storage and monitoring.

Rise of native clouds – containerization and serverless computing
In order to recover from the pandemic hangover, MSPs – Managed Service Providers, would want to enhance their Customer Experience (CX) quotient while keeping costs in check; exactly what native cloud computing delivers. Native cloud technologies through containerization empower digital transformation strategies for enterprises across the spectrum. Since Azure, AWS and Google Cloud have raised the green flags, at least 60% of service providers will offer containerization on public cloud platforms.

At their core, container management repositories perform workload transportation between multiple verticals such as on-premise, edge, and the cloud. Subsequently, platforms like Kubernetes, that lessen the complexity in container management, should gain explosive acceptance in 2021-22. In addition, serverless computing that was among the top five Platform-as-a-Service (PaaS) cloud services in 2020, is still likely to be a preferred paradigm for multi-cloud developments.

Edge computing gaining the edge
To put it simply, edge computing brings storage and processing closer to the geographic location of data consumption. Besides ensuring faster response times, it saves bandwidth (and infrastructure) while empowering the service providers to serve their customers locally.

There’s no doubt that Edge computing will grow stronger in 2021. Cloud service providers will experiment with new business models beyond humongous data centers and central control of public clouds. Nonetheless, it still seeks the innovation of computing in traditional clouds while enhancing business agility. Edge computing allows enterprises to improvise upon their real-time analytics and make smarter business decisions. Since predictive analysis in CRM and other ERP verticals is growing, edge computing will have a greater role in the process.

Per IDC research, by 2024 25% of organizations will look forward to using cases that integrate edge data with apps already hosted in the cloud. 2021 will also see a series of partnerships between traditional cloud and edge computing service providers. Also, telecom service providers will have a key role in driving these hybrid ecosystems.

Going forward, devices and applications closer to the consumer’s location will play an important role in the larger fabric of the Internet of Things (IoT) and hybrid cloud models.

Opportunity is in the eyes of the beholder
The cloud was already a dominating force. The pandemic only proved that most enterprise processes can be managed remotely if the right cloud implementation is backing them. Therefore, it is not incorrect to believe that cloud service providers are sitting on a gold mine of opportunity.

Datadog is planning to expand the scope of the security and observability services it provides following the acquisitions of Sqreen, an application security platform provider, and Timber Technologies, a provider of a tool, called Vector, for collecting and normalizing log data.

Ilan Rabinovitch, vice president of product and community for Datadog, said Vector makes it possible to collect, enrich and transform logs and other observability data from both on-premises and in-cloud environments in a way that makes it easier to route that data to wherever it is needed via a data pipeline.

Sqreen is a provider of a software-as-a-service (SaaS) platform that detects, blocks and responds to application-level attacks using runtime application self-protection (RASP) capabilities enabled by a web application firewall (WAF) embedded within an application.

Rabinovitch said as IT continues to evolve, it’s clear organizations are looking to embrace DevSecOps best practices in a way that will require security tools that can be embedded within an application, coupled with observability tools that provide more context about the overall IT environment. That context is especially critical, given the amount of data that needs to be analyzed to determine the potential scope of a security threat to an IT environment, Rabinovitch said.

The Datadog platform is already widely employed to monitor cloud computing environments. There is an industry wide effort to take monitoring to the next level by enabling observability, which applies analytics to provide more context. Surfacing that context, however, requires the ability to normalize data across a pipeline using Vector, Rabinovitch said.

Of course, the Vector tools are equally applicable to DevOps workflows that have yet to incorporate security technologies. The goal, now, is to make it easier for IT teams, made up of developers, IT operations teams and security specialists, to collaborate by breaking down the various data silos created by IT and security management tools.

It’s too early to tell what impact the rise of DevSecOps will have on roles within IT organizations. Most organizations will continue to employ a range of specialists that will be able to work more closely with IT generalists, Rabinovitch said. Managing IT is becoming the equivalent of a barn raising, in that it requires members of a community with different skills to come together for a certain amount of time to accomplish a specific task, Rabinovitch added.

It’s also not clear whether IT organizations view observability as a distinct capability separate from monitoring, or whether they will simply view observability as the next logical extension of existing tools. At the core of that issue is debate over whether observability platforms need to be acquired separately, as part of an effort to replace existing monitoring tools, or whether those tools will evolve over time to provide observability capabilities.

Regardless of the path forward, it’s apparent the increased complexity of modern IT environments – made up of microservices, containers and serverless computing frameworks – is about to force that issue.

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.”

Google has recently announced that Google Cloud Workflows, the service to orchestrate Google Cloud and HTTP-based API services with serverless workflows, is now generally available. Workflows Connectors are now in public preview.

Google Cloud Workflows requires no infrastructure management and scales on demand, including scaling down to zero if no requests are processed, It can be used to develop complex serverless applications, building on workflows that connect series of serverless tasks together in a predetermined order and work with other managed services like Google Cloud’s APIs, Cloud Functions or Cloud Run.

Among the features of the new service, an error handling with configurable retry policies, a reliable workflow execution targeted to enterprise and line-of-business applications and the ability to pass information between steps using JSON parsing and expression-based variable manipulations. Workflows publishes connectors to make it easier to access other Google Cloud APIs within a workflow.

Among the use cases that can benefit from workflows, inventory management processes, e-commerce transactions and other services that require an orchestration layer. Filip Knapik, product manager at GCP, wrote an article before the GA that covers examples for Workflows such as processing files uploaded to a storage bucket, tagging the files based on the extension. He explains:
GCP is not the only cloud provider offering managed workflows. Microsoft has Azure Logic Apps and Amazon introduced AWS Step Function over four years ago. Tim Bray, formerly VP/distinguished engineer at AWS, wrote a detailed comparison between the AWS and GCP services. But regardless of which features they offer and the maturity of the different services, he concludes that choosing the workflow service is a platform choice:

Google Cloud Workflows has a pay-per-use pricing model based on the number of steps and the number of external HTTP calls, with the first 5000 steps and 2000 HTTP calls free every month.

IAM governance is a priority for DevOps and security teams in the public cloud. Accounts, access, permissions, and privileges have become popular targets in recent cybersecurity attacks on the cloud. A well-established IAM governance policy will significantly reduce the risks of data breaches on the cloud from unauthorized access.

While cloud service providers may offer effective baseline security policies that safeguard users from malicious activities, enterprises may face compromised security when implementing a multi-cloud strategy. However, multi-cloud adoption may seem inevitable for some enterprises as they scale their operations.

DevOps teams can help companies achieve safer data management through a comprehensive IAM strategy that works across multiple cloud platforms. While IAM strategies may differ among enterprises, general guidelines can help cloud users achieve the Principle of Least Privilege and stay there.

Regardless of the complexity of your operations, the aim of our best practice recommendations is to make whatever you are doing work out better, faster, and more efficiently with fewer problems and mistakes. Here are just a few best practices to be aware of when working in the cloud.

Due Diligence of Administrator Credentials
Administrator credentials should strictly belong to administrator accounts. Enterprises should consistently monitor the usage of administrator accounts to eliminate the risks of anomalies. For the best practices, enterprises should restrict administrator accounts to necessary functions and discourage daily usage.

It is vital for enterprises to protect the powerful set of permissions linked to administrator credentials. Cloud users should consider additional security measures, such as implementing separate account logins and enforcing encryption, which minimizes the risks of malicious infiltration.

Categorize User Management
Systematic user management will help enterprises optimize account and access controls. DevOps can achieve this by sorting users into groups and roles according to their linked permissions. Through grouped categorization, system administrations can effectively manage similar permissions, roles, and privileges without tediously sorting through individual accounts.

However, it is best practice to have complete visibility into all permissions, roles, and privileges for all users and identities. Without this visibility, a user may receive more access than needed leaving your organization open to unnecessary risks.

MFA Activation
MFA (multifactor) authentication provides critical accounts with added security that discourages cyberthreats by complicating the hacking process. Fundamental access controls, including Role-Based Access Control (RBAC) and Multifactored Authorizations (MFAs), can prevent intrusions by both types of criminals. These controls verify the identity of valid users, then monitor their usage to ensure it remains within the security parameters mandated by their work. As a general security best practice activate MFA for all of your accounts.

Access keys provide long-lived access to your environment programmatically as opposed to logging in via the Console using a good old user/password combo. As a general best practice, temporary credentials should be used whenever and wherever possible, not long-lived access. This can be achieved by using IAM roles.

Enforce Password Hygiene
Enterprises should ensure that users maintain proper password hygiene, which eliminates weak authentications (recommended on top of standard MFA implementations). The NIST SP 800-63-3 Policy provides a comprehensive list of password guidelines for optimized digital data security. Some key suggestions include skipping character composition rules (which burden malicious parties) and only changing passwords in the event of compromised account login.

Rotate Access Tokens
Users should regularly rotate access tokens to minimize the risk of compromised credentials. The process involves creating new tokens, switching applications that use the new token, and deleting the old token. Like passwords, regularly changing an API token will limit the damage a leaked or misplaced API token can cause.

Centralize IAM
By providing centralized management of all identities (whether it’s users, groups, services, and/or roles), your organization gains the visibility needed for proper oversight. Centralized IAM makes it easier to enforce policies governing identity and access. This is because an effective centralized approach ensures that privileges are issued in accordance with the policies and controls within your organization’s governance framework. As a result, you can align privileges with your business requirements.

Enforce Least Privilege
The Principle of Least Privilege ensures that users receive the minimum permissions required to fulfill their roles. Through least privilege, DevOps can significantly reduce the blast radius in the event of a data breach by restricting threats to the specific permissions linked to an account.

Ultimately, as best practice only give individual users or specific pieces of compute the exact amount of privileges they need to get their job done.

Discover and Inventory All Identities
You can’t protect or manage accounts, identities, roles, or assets that you don’t know about. Unfortunately, with so many scripts and so much automation layered all over the DevOps toolchain, it can be tremendously difficult to discover and inventory all of your identities. Some identities are embedded in runtimes or hard-coded into compiled executables making visibility a challenge, but it must be done. Organizations need to get clear visibility into exactly what tools are executing the automation and what the privileges are assigned to them.

Manage Shared Secrets and Hard-Coded Passwords
Unfortunately, even when teams are meticulous about rooting hard-coded passwords out of their finished applications, they often leave them within the IT infrastructure that helps support the development of that software for the sake of expedience. The same goes for account sharing, which is a frequent mistake organizations make to just get the automation working and keep it working with stability. The problem is, this makes it difficult for traceability or auditability of activity within the affected environment.

Best practices for shared secrets are to continuously monitor identifies and manage risks associated with critical systems and data on an ongoing basis. By doing so, all potential access paths to your data, serverless functions, containers, VMs, and users are uncovered and categorized by privilege.

With continuous monitoring, organizations gain an additional layer of oversight over their existing cloud security frameworks and optimize the effectiveness of internal controls. It also maintains a documented record of change control and validation, which improves ongoing compliance and reduces auditing workloads. Also, an organization can gain increased visibility into the changes in their environment: Who made the changes? When did the changes occur? What information was accessed?

End-to-End Visibility
Visibility is key to security, this is why it’s important to know the effective permissions for all Identities (human and non-human) in your organization. You can get true visibility into data and access trust relationships by graphing, classifying, and mapping identities. With end-to-end visibility, organizations will detect misconfigurations and changes — and respond effectively.

DevOps practices allow for incremental implementation so enterprises do not need to make required changes and updates from the beginning. Following the above-mentioned DevOps best practices, your organization can ensure to develop and deliver robust software solutions that help companies to achieve their business object effectively without additional security risks..

Sonrai Dig has been developed to help organizations improve security, ensure compliance and increase operational efficiencies for their AWS, Azure, GCP and other cloud platforms. Core to the platform is the ability to gain a centralized and consistent view into cloud identity and data relationships, activity, and data movement across cloud accounts, cloud providers, and 3rd party data stores. Read our blog to learn more about our solution.

Amazon Web Services recently announced the general availability of AWS Glue DataBrew, a new visual data preparation tool that enables users to prepare data without writing code. While AWS Glue provides both code-based and visual interfaces, data analysts and scientists now gain an easier way to clean and transform data. AWS Glue DataBrew is a service that allows data exploration and experimentation directly from AWS data lakes, data warehouses, and databases. It also touts more than 250 pre-built transformations for data prep automation.

AWS Glue DataBrew is a visual data preparation tool for AWS Glue that allows data analysts and data scientists to clean and transform data with an interactive, point-and-click visual interface, without writing any code. The solution lets users access and visually explore any data across their organization directly from their Amazon Simple Storage Service (S3) data lake, Amazon Redshift data warehouse, and Amazon Aurora and Amazon Relational Database Service (RDS) databases. DataBrew recommends data cleaning and normalization steps as well.

For complex tasks like converting words to a common base or root word, AWS Glue DataBrew provides transformations that use advanced machine learning techniques like Natural Language Processing and apply them automatically to future incoming data. The tool publishes prepared data to Amazon S3, which makes it simple for customers to immediately use it in analytics and machine learning. DataBrew is serverless and fully managed so users never need to configure, provision, or manage any compute resources.

In a media statement, AWS VP of Database and Analytics Raju Gulabani said: “Customers love the scalability and flexibility of code-based data preparation services like AWS Glue, but they could also benefit from allowing business users, data analysts, and data scientists to visually explore and experiment with data independently, without writing code. AWS Glue DataBrew features an easy-to-use visual interface that helps data analysts and data scientists of all technical levels understand, combine, clean, and transform data.”

The rise of COVID-19 defined 2020 for nearly every industry. Cloud computing is no exception, though growth in the sector continued this year. Gartner estimates that $257.9 billion will be spent on public cloud services in 2020, up 6.3% from 2019. IDC reports that almost half of IT spending is cloud-based, “reaching 60% of all IT infrastructure and 60% to 70% of all software, services and technology spending in 2020.” These projections came in mid-2020, which proves that cloud adoption and spending were not greatly impacted by the pandemic.

You can make the argument that cloud computing itself is the trend of 2020. Blockchain, quantum computing, machine learning and AI all deservedly earn a lot of headlines in the tech press. But at a more basic level, cloud computing is changing the way we do business. Whether it is the way they store their data, improvements to agility and go-to-market for faster release of new products and services, or how they develop and operate services remotely in today’s “locked-down world,” cloud computing is benefitting all businesses in every sector.

In short, cloud computing had a strong year in 2020 despite COVID-19 and appears to have a very bright future. Several key trends, perhaps overshadowed by the pandemic, helped define a dynamic year for the sector. These include the following:

Continued Dominance of ‘The Big Four’ – All of the big four cloud providers—AWS, Azure, Google Cloud and Alibaba Cloud—reported strong growth and collectively grew 40% in Q320. Together they still account for 63% of the entire cloud sector.
Rise of Managed Services – The global cloud managed services market, in particular, is growing rapidly and is expected to reach $116 billion by 2026, growing from $62.4 billion in 2020, according to a study conducted by Markets and Markets.
Serverless and Containers – There used to be some talk about serverless and containers replacing the use of traditional virtual machines (VM). But I mostly see customers realizing that VM infrastructure is not going to disappear anytime soon, though container use certainly rose over the last 12 months.
Automation – The push toward greater automation continued in 2020. I noticed users accepting greater automation in their infrastructure environments, and there was simply more demand for it across the board. This is great news as one of the major advantages of a DevOps approach is automating away the manual tasks that bog down critical projects.
Growth in home use – This may seem an obvious one, but with the COVID-19 pandemic leading companies across the globe to new “work from home” policies, virtual desk infrastructure (VDI) usage exploded.
Security – Especially with a remote workforce, cloud security faced new challenges this year. One example of this playing out is in Snowflake’s massive IPO.
Other trends of note this year included the continued growth of hybrid and multi-cloud and desktop as a service (DaaS). So, while COVID-19 truly defined 2020 for most people, the cloud sector was busy with the trends discussed above. It will certainly be interesting to see how these trends play out in the year ahead. Whatever new trends arise, it seems likely that cloud computing will continue to transform the way we all do business.

CloudKnox Security extended support for serverless functions on Amazon Web Services (AWS), Azure, and Google Cloud Platform (GCP). The enhancement adds serverless functions to a substantial list of permissions management capabilities, including users, bots, service accounts, access keys, and other resources.

The company also announced an integration with ServiceNow, the next step of many towards realizing CloudKnox’s next gen cloud security and permissions management vision.

Together, the support for serverless functions and ServiceNow integration underscore CloudKnox’s market lead with the most comprehensive support offering in the cloud infrastructure entitlement management (CIEM) segment.

With this extension, CloudKnox customers gain remediation for multi-cloud serverless functions, allowing security and infrastructure teams to generate a right-sized permissions policy based on activity of roles associated with the serverless function.

In a recent assessment within CloudKnox’s customer base, the company discovered that by categorizing serverless function as non-human identities, the ratio of human to non-human identities jumped from 1 in 5 to 1 in 10.

Given the industry shift from cloud native architecture to microservices, this ratio is expected to continue growing and has led to a need for a holistic permissions management platform. As such, it is critical that organizations take proactive control over managing resources and identities permissions.

“The ephemeral nature of serverless functions leads people to believe that over provisioning for serverless functions is harmless. But the reality is that serverless functions are full-fledged machine—non-human—identities, meaning they can access your infrastructure in the same way a human user can,” said Raj Mallempati, Chief Operating Officer, CloudKnox.

“If a serverless function is over-permissioned, it can cause the same costly damage—either accidentally or maliciously—to an enterprise’s infrastructure that a human user can. As with all identities, serverless functions must be monitored and right-sized when necessary.”

To manage the exponential increase in identities, many companies use information technology service management (ITSM) tools for permissions management and security incident tracking. By integrating with ITSM tools, such as ServiceNow, CloudKnox makes permission automation and permissions on demand possible.

Rather than granting always-on “standing permissions,” organizations can enable access to permissions and resources that are needed for specific tasks for a predefined time, at which point the permissions are rescinded automatically. Plus, by prioritizing such integrations, CloudKnox can fit into any customer’s existing technology ecosystem—no matter the tools they have deployed.

“We’re working with our customers and partners to mitigate the risk of permissions abuse by eliminating the permissions or entitlements gap, thereby preventing unauthorized access to sensitive data,” said Mallempati.

“We take pride in assisting our clients with the monumental challenge of securing their hybrid and multi-cloud infrastructures by identifying their Cloud Permissions Gap risk and successfully implementing the principle of least privilege (PoLP) and Zero Trust access to address it.”

As CloudKnox continues to maintain their industry-leading market position, the company will be introducing more product features in the coming months, including support for container workloads on Kubernetes.

The Cloud Permissions Management Platform was recently named among CRN’s Top 10 Hottest Cloud Startups of 2020 and offers a free Cloud Identity Risk Assessment to help enterprises understand their cloud identity and resource risk profile.

Trend Micro announced the world’s first cloud-native, fully serverless file storage security tool for organizations building applications in the cloud. Trend Micro Cloud One – File Storage Security is designed to mitigate threats across the cloud environment and support strict compliance requirements.

The explosion of cloud-based file and object storage presents a new attack vector for threat actors to target with malicious files. Cloud One – File Storage Security provides automated anti-malware scanning to keep information safe and ease compliance needs.

“Global organizations are increasingly looking to public cloud providers to drive IT agility, cost savings and business growth. But while the provider deals with security of the cloud, the customer is responsible for everything inside their cloud environment,” said Mark Nunnikhoven, vice president of cloud research for Trend Micro.

“This is a highly scalable, automated scanning tool that’s fast to deploy with no added infrastructure, allowing organizations to confidently store cloud files and data associated with their cloud applications.”

Backed by Trend Micro’s 30+ years of cybersecurity experience and industry leading threat intelligence, the tool blocks known bad files, and looks for hidden or changing malware variants.

The scanner itself is a lightweight, cloud-native serverless function that’s designed for minimal operational overhead. This architecture enables fast, seamless deployment and flexible integration with organizations’ existing custom workflows for added value.

The tool supports various compliance requirements that call for anti-malware scanning of cloud files while maintaining data sovereignty.

Trend Micro Cloud One – File Storage Security is available now for AWS S3, with support for Microsoft Azure Blob storage and Google Cloud Storage coming soon.

Using Trend Micro’s Cloud One platform, teams can implement a range of security services and compliance checks without hindering agile cloud development and deployment. This single cloud-native security seamlessly complements and integrates with existing AWS, Microsoft Azure, VMware, and Google Cloud toolsets.

SEATTLE–(BUSINESS WIRE)–Today, Amazon Web Services, Inc. (AWS), company (NASDAQ: AMZN), announced that Nationwide, a Fortune 100 insurance and financial services provider, is expanding its relationship with AWS and has selected AWS as its preferred cloud provider. As part of its company-wide digital transformation, Nationwide is moving key, business critical workloads to AWS, including more than 850 business and customer-facing applications, such as Claims, Personal and Commercial Insurance Policy Systems, and their flagship website Nationwide.com. Leveraging the breadth and depth of AWS’s advanced services, including analytics, database, machine learning, security, and serverless technologies, Nationwide is delivering deeper insights to its independent agents, financial professionals, and customer service associates to provide more personalized recommendations and customer service to their millions of customers.

Nationwide’s rapid move to the cloud is accelerated by AWS Enterprise Next, a program that pairs AWS experts with customer teams to create a long-term plan and key milestones to drive a company’s ongoing digital transformation. Through this 15-month engagement program, AWS experts and partners are working with Nationwide to create an on-site, cross-functional team to modernize Nationwide’s applications, IT environment, and operating practices. AWS Enterprise Next has already helped Nationwide build more than 60 applications in the cloud, including its Nationwide Small Business Advisory platform, an online experience that uses machine learning services like Amazon Textract (a machine learning service that automatically extracts text and data from scanned documents) to pull data from scanned forms and documents to automate the underwriting process for small business owners. In addition, the platform uses AWS’s machine learning-driven personalization service, Amazon Personalize, to tailor personalized insurance policy recommendations to small business customers in minutes. This is rapidly speeding up the time to get new policies into the hands of customers, providing greater assurance to small businesses, where insurance coverage is vital.

Leveraging AWS gives Nationwide the ability to introduce new resources like enhanced mobile applications and self-service financial planning, to customers much faster, getting these new ideas into the hands of customers in days, as opposed to the months it took previously. AWS analytics is also helping to reveal new insights related to application usage patterns, business trends, and customer preferences, allowing Nationwide to empower independent agents and financial professionals to make better, more personalized recommendations to customers based on the financial and insurance resources available. Going forward, Nationwide will also use Amazon SageMaker, AWS’s service for easily building, training, and deploying machine learning models quickly at scale, to help its data scientists enhance their performance in areas such as marketing analytics and risk assessment to accelerate the company’s life insurance policy processing.

“Our customers’ needs and expectations of how their insurance partner supports them are evolving rapidly and AWS has given us the agility that we need to quickly innovate and provide new services, while delivering the security, reliability, and performance that customers have come to expect from us for more than 90 years,” said Jim Fowler, CTO at Nationwide. “AWS has helped us move to the cloud quicker than we ever imagined possible, and their unmatched portfolio of services is transforming our business. AWS gives us the ability to reach new digital audiences who can access and consume our services through a variety of channels, and empowers our associates with next-generation tools and insights to enhance our customer service.”

“Combining Nationwide’s financial expertise with AWS’s proven performance and unmatched portfolio of services is enabling them to deliver powerful new financial tools to help them stay ahead competitively and remain a leader in serving customers,” said Greg Pearson, Vice President, Worldwide Commercial Sales at AWS. “Leveraging AWS, Nationwide can innovate and deploy new solutions while they are streamlining their business operations and processes on the backend. By building and running their most strategic platforms on AWS, Nationwide is positioning itself as a leading choice for life insurance and financial services for years to come.”

Amazon Web Services

For 14 years, Amazon Web Services has been the world’s most comprehensive and broadly adopted cloud platform. AWS offers over 175 fully featured services for compute, storage, databases, networking, analytics, robotics, machine learning and artificial intelligence (AI), Internet of Things (IoT), mobile, security, hybrid, virtual and augmented reality (VR and AR), media, and application development, deployment, and management from 77 Availability Zones (AZs) within 24 geographic regions, with announced plans for 18 more Availability Zones and six more AWS Regions in Australia, India, Indonesia, Japan, Spain, and Switzerland. Millions of customers—including the fastest-growing startups, largest enterprises, and leading government agencies—trust AWS to power their infrastructure, become more agile, and lower costs. To learn more about AWS, visit aws.amazon.com.

Amazon

Amazon is guided by four principles: customer obsession rather than competitor focus, passion for invention, commitment to operational excellence, and long-term thinking. Customer reviews, 1-Click shopping, personalized recommendations, Prime, Fulfillment by Amazon, AWS, Kindle Direct Publishing, Kindle, Fire tablets, Fire TV, Amazon Echo, and Alexa are some of the products and services pioneered by Amazon. For more information, visit www.amazon.com/about and follow @AmazonNews.

Nationwide

Nationwide, a Fortune 100 company based in Columbus, Ohio, is one of the largest and strongest diversified insurance and financial services organizations in the United States. Nationwide is rated A+ by both A.M. Best and Standard & Poor’s. An industry leader in driving customer-focused innovation, Nationwide provides a full range of insurance and financial services products including auto, business, homeowners, farm and life insurance; public and private sector retirement plans, annuities and mutual funds; excess & surplus, specialty and surety; pet, motorcycle and boat insurance

With increasing move to cloud infrastructures, we have seen rapid growth of cloud-native applications. These applications are a collection of small, faster, and integrated services. By creating and operating cloud-native applications, businesses bring new ideas to market faster and respond instantly to customer demands. These applications typically empower enterprises to build and run scalable applications in modern, dynamic cloud environments such as public, private, and hybrid clouds. Serverless architectures, containers, Kubernetes, and others are some cloud-native applications. Though these are designed to deliver enhanced business value, they also introduce a set of cybersecurity risks.

Businesses substantially move to cloud computing in order to boost the scalability and availability of applications. This can be achieved through self-service and on-demand provisioning of resources, in addition to the application life cycle automation from development to production. Cloud-native applications embrace the runtime and services provided by the cloud platform to create resilient, agile, and scalable solutions.

Securing Cloud-Native Applications
Securing cloud-native infrastructure requires a profound understanding to detect where the security needs. Considering security professionals’ responsibilities that rely on the services they are consuming is also imperative to implement security measures to apps. According to Gartner, 99% of cloud security failures will be the customer’s fault through 2026. To close this security gap, CIOs will need to deploy and enforce policies on cloud ownership, responsibility and risk acceptance.

So, what is essential to securing cloud-native applications?

High Fidelity Visibility and Context
Visibility is the most crucial aspect of cloud applications’ cybersecurity. A lack of centralized administration and visibility can lead to the chances of undetected misconfigurations, as well as the inability to quantify risks. Security alerts that lack context and generally require human intervention can also result in delays in mitigation and alert fatigue.

Continuous Security
As enterprises leverage cloud-native technologies, such as Kubernetes, across their clouds, the complexity and distributed nature of these platforms significantly require businesses to plan strategies not only for DevOps, but also for security. Addressing vulnerabilities and threats in the cloud-native development model and infrastructure requires continuous security across the software development lifecycle. It also requires a shared security responsibility and ownership, along with shared processes and tools. This will enable organizations to keep cloud-native deployments in general, and infrastructure, applications and data specifically, safe and cybersecurity-proof.

Security of Server Workloads
Cloud workload security is particularly challenging and as workloads pass among multiple vendors and hosts so the responsibility for securing the workload must be shared. Many companies still use traditional enterprise security solutions to endpoints security, network segmentation, and perimeter protection. However, in a cloud-native environment, businesses cannot rely on these traditional security solutions. Server workloads these days are more vulnerable to cyberattacks than ever before. According to VMware, micro-segmentation and bare-metal hypervisor are two main ways to protect workloads with cloud workload protection platform.

In one of the most significant commitments to the cloud by a major media company to date, ViacomCBS announced an agreement that makes Amazon Web Services the preferred cloud provider for its global broadcast media operations. As part of the strategic agreement, ViacomCBS will migrate operations for its entire broadcast footprint, which spans 425 linear television channels and 40 global data and media centers, to the AWS cloud – one of the first such large-scale transformations in the media and entertainment industry.

According to the two companies, the migration will enable ViacomCBS to drive greater efficiencies and cost savings, simplify access to content for its licensing partners, and reliably deliver new viewing experiences to consumers by broadcasting and streaming content on any device.

“We are expanding our strategic relationship with AWS to support our industry-leading technology and operations transformation,” says Phil Wiser, Executive Vice President and Chief Technology Officer at ViacomCBS. “With AWS, we will be able to automate and streamline our processes for content production, licensing, and distribution to consumer streaming services and innovate faster to deliver improved customer experiences. We are thinking and acting aggressively to build on the major disruptions that ViacomCBS is bringing to the market with our leading global content and services. AWS’s deep portfolio of services will help us unleash the power of content in new and interesting ways that benefit our advertisers, licensing partners, and streaming services.”

ViacomCBS will leverage AWS’s infrastructure cloud capabilities, including serverless, containers, databases, media services, analytics, and machine learning, to build a cloud-based broadcast and media supply chain operating model. This new cloud-based hub will help the broadcaster spin up new channels faster, dynamically assemble live content to optimize delivery over any distribution channel, add image and video analysis to applications, and automate workflows.

ViacomCBS plans to use AWS Elemental media services as well as AWS machine learning technologies, including Amazon Rekognition (AWS’s service that adds intelligent image and video analysis to applications) and Amazon SageMaker (AWS’s service for building, training, and deploying machine learning models), to quickly scale video processing resources, automate workflows, and predict audience preferences. These capabilities will aid ViacomCBS in producing and streaming dynamic content and enabling efficient national and local news distribution on CBSN, CBS News’s 24/7 digital streaming service.

“We are excited to deepen our relationship with ViacomCBS to redefine video delivery of media and entertainment content for global audiences across any platform,” says Greg Pearson, Vice President, Worldwide Commercial Sales at Amazon Web Services. “Moving its broadcast media operations to AWS gives ViacomCBS the agility to lower costs, take advantage of new distribution models, and drive efficiency and innovation across its entire global media operations. Using AWS’s proven operational experience and unparalleled portfolio of services, ViacomCBS can create and deliver new video content experiences with the utmost reliability and reach audiences no matter what platform they use.”

Aviatrix announced that it will be showcasing how enterprise customers are benefiting from its most recent achievement of AWS Outposts Ready designation and support for AWS Gateway Load Balancer (GWLB) as well as its multi-cloud transit capabilities for AWS Lambda serverless computing.

“Aviatrix provides the right business-critical cloud networking platform tools that enable us to do what we need to do for our hybrid environment. There’s so much flexibility; whether it’s network segmentation, integrating a newly acquired company, or evolving our enterprise to a multi-cloud infrastructure. These things would be very hard to achieve without using Aviatrix,” emphasized Luis Castillo, Sr. Manager, Architecture Information Technology at NI (formerly known as National Instruments).

“With all its challenges, 2020 has been a great year for cloud providers, enterprises accelerating their move to the cloud and for our company. Aviatrix is yet again proud to be an AWS Partner participating in AWS re:Invent 2020, and to support the launch of their most recent cloud innovations, including being an AWS Outposts Service Ready Partner and supporting the recently announced AWS Gateway Load Balancer service.

“Aviatrix is dedicated to helping customers achieve their business and technology goals by delivering solutions that offer the simplicity and automation that enterprises expect from cloud, while also supporting their cloud network requirements for operational visibility, advanced networking and security control, and multi-cloud readiness,” said Steve Mullaney, CEO of Aviatrix.

Delivering new advanced network capabilities for AWS Outpost customers
Aviatrix has now extended its cloud network platform to operate on AWS Outposts infrastructure within customer data centers. Advanced networking capabilities include the ability for customers to route traffic within the AWS Outposts infrastructure and between the AWS Outposts infrastructure and the customer’s legacy data center, without having to flow back to the AWS Region.

As an AWS Outposts Service Ready Partner, Aviatrix product has been fully tested and validated on AWS Outposts, and is (generally) available immediately and is fully supported for customer deployments.

“Customers are looking for ways to easily manage, monitor and control the network architecture connecting their enterprise cloud infrastructure with their employees and customers,” said Joshua Burgin, General Manager, AWS Outposts, Amazon Web Services, Inc.

“With Aviatrix cloud network platform now available to customers on AWS Outposts, customers can easily define and deploy a network architecture that spans their AWS Outposts, the AWS Region, and their broader enterprise network architecture for a truly consistent hybrid experience.”

Simplifying security service insertion and chaining for Amazon VPCs
Deploying next generation firewalls in the cloud is increasingly required by organizations to meet security best practices. The Aviatrix cloud network platform Firewall Network Service (FireNet) now offers support for the new AWS Gateway Load Balancer (GWLB) and AWS Gateway Load Balancer Endpoint (GWLBE) to scale and manage appliances that support GENEVE encapsulation.

Aviatrix Transit/FireNet Gateways either directly or in-line with GWLB, provide a high-performance connection to virtual appliances, eliminate the need for Source Network Address Translation (SNAT) and allow customers to add or remove appliances for scaling or in response to health checks, without impacting existing sessions.

The Aviatrix Controller automates attachment of GWLB, and their associated GWLBE, and all connected appliances to an Aviatrix Transit/FireNet Gateway. Aviatrix supports the GWLB native APIs to simplify the orchestration and automation of security services insertion into customer’s cloud network and brings the operational visibility and control enterprises require.

Multi-cloud transit networking capabilities for AWS Lambda serverless computing
AWS Lambda Serverless computing architecture offers application development teams a powerful solution to achieve shorter time-to-market and decreased operational costs, however, network operations are often still a bottleneck.

Aviatrix now delivers the full capabilities of its cloud network platform to the application development team. Simply attaching an AWS Lambda function to an Amazon VPC with an Aviatrix spoke gateway allows that function to take advantage of the Aviatrix multi-cloud transit infrastructure, delivering connectivity to applications, data and other serverless functions that may reside in on-premise data centers or other clouds.

The Aviatrix solution also enforces all the security policies and delivers all the visibility operations teams need to support corporate and regulatory policies, with the visibility to rapidly help applications teams solve connectivity issues that arise.