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Of the 380 CIOs and CTOs who participated in the survey, 60% say their company’s IT modernization program is not yet ready for the future, according to the recently completed The State of IT Transformation Study conducted by the Managed Infrastructure Services unit of IBM’s Global Technology Services division. Nearly a quarter of CIOs and CTOs (24%) surveyed say their company is just starting its IT modernization journey or has yet to begin modernizing, with about a third surveyed saying they are still in the midst of transformation.

As a result, more than 95% of IT leaders surveyed said they are looking to adopt public, hybrid or private cloud strategies. Of those, many are moving at an aggressive pace — the study reveals that 53% of respondents are aggressively pursuing a public cloud strategy, 48% a hybrid cloud strategy and 45% a private cloud strategy.

“Our clients are looking to accelerate IT modernization by leveraging cloud models – both public and hybrid, data, AI, automation and other key technologies to help shape, scale and manage more effectively massive, complex, global architectures,” said Archana Vemulapalli, General Manager, IBM Infrastructure Services – Offerings and CTO. “In this rapidly changing digital business environment, organizations can bring in the right technology and the right partners to help aggregate, integrate, build and maintain a scalable digital business, while also enforcing effective governance.”

The pressures on IT infrastructures brought on by the COVID-19 pandemic have further accelerated the need for cloud infrastructure, professional skills development, and security upgrades, the survey found. More than 60% of technology leaders surveyed say they expect increased demand for cloud infrastructure to be permanent.

Even as IT leaders are feeling increased urgency to accelerate their organizations’ transformation, migrating to a multi-cloud environment can present significant challenges to organizations with legacy applications running large data pools.

What’s more, many surveyed technology leaders are not sure they have the right teams in place. A full 40% of survey respondents do not feel their teams have the right skills to fully meet their IT ambitions, and more than three in four surveyed say they will rely more on trusted partners that can provide managed infrastructure services.

Most CIOs and CTOs (67%) surveyed cite the need for increased infrastructure flexibility as driving the digital transformation, followed by the need for competitive advantage (61%), cost savings (58%), increasing globalization (54%) and meeting client demands (45%).

While the majority (60%) of CIOs and CTOs surveyed say their company’s IT modernization is not yet ready for the future, the study revealed significant differences in the U.S. and U.K. markets. For example, while approximately 56% of U.S. respondents say they are aggressively moving their IT infrastructure to hybrid cloud, only 38% of respondents in the U.K. describe their approach as aggressive. And while 56% of CIOs/CTOs surveyed in the U.S. say their IT infrastructures were completely prepared for the business changes brought on by COVID-19, only 23% of U.K. managers surveyed felt as prepared.

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“Students during the pandemic are struggling with digital access, engagement and a severe sense of isolation. Cybersecurity should be the least of their concerns, and yet, it’s concerning to find that nearly half of educational institutions show a lack of preparedness,” said Marcin Kleczynski, CEO of Malwarebytes. “It is essential that schools – and all organizations – stop viewing cybersecurity as an afterthought; protecting our students and their data online should be a top priority for educators.”

The report uncovered that cybersecurity preparation made a significant difference in a school’s ability to weather a cybersecurity event. For respondents who engaged in a variety of cybersecurity best practices before transitioning to a distance learning model, none suffered a cyberattack, and none cancelled a single day of distance learning because of a cyberattack.

18.2 percent of these more well-prepared respondents said “teachers or students have suffered a Zoom-bombing attack” compared to the 29.3 percent of all respondents.

In addition, the report revealed major inconsistencies in the perceived experiences between IT decision-makers and students. A remarkably low number of IT decision-makers said their schools suffered a cyberattack—just 2.7 percent—and yet, 46.2 percent of students said their schools suffered a cyberattack. This statistic of students experiencing a cyberattack is even more important as they look to enroll in universities or private schools because 61 percent of students reported that a cyberattack resulted in a significant or strong impact on their trust in their school.

Other key findings from the report include:

• 50.7 percent of IT decision-makers said that no one (not students, staff or faculty) was required to enroll in cybersecurity training before the new school year began
• 46.7 percent of IT decision-makers said their schools developed “no additional requirements” for the students, faculty, or staff who connected to the school’s network (no cybersecurity training AND no antivirus tool installations)
• Nearly three quarters (70.7 percent) of schools deployed new software needed for distance learning, such as Zoom, Remind, and Google Classroom
• In preparing for the new school year, 30.7 percent of schools admitted to not being able to provide for all teachers, administrators, and staff members to work remotely, while 45.3 percent of schools could not provide all the devices needed for every student to attain an equal quality of education
• With distance learning in full swing, concerns remain with device shortages:
  • 28 percent of IT respondents said their schools are missing laptops, computers or tablets for teachers
  • 40 percent are missing those tools for parents and students
  • 38.7 percent worry that teachers or students are too quickly using up the data on school-provided WiFi hotspots

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When Amazon DevOps Guru identifies anomalous application behavior (e.g. increased latency, error rates, resource constraints, etc.) that could cause potential outages or service disruptions, it alerts developers with issue details (e.g. resources involved, issue timeline, related events, etc.) via Amazon Simple Notification Service (SNS) and partner integrations like Atlassian Opsgenie and PagerDuty to help them quickly understand the potential impact and likely causes of the issue with specific recommendations for remediation. Developers can use remediation suggestions from Amazon DevOps Guru to reduce time to resolution when issues arise and improve application availability and reliability with no manual setup or machine learning expertise required. There are no upfront costs or commitments with Amazon DevOps Guru, and customers pay only for the data Amazon DevOps Guru analyzes. To get started with Amazon DevOps Guru, visit https://aws.amazon.com/devops-guru

As more organizations move to cloud-based application deployment and microservice architectures to globally scale their businesses and operations without the limitations of on-premises deployments, applications have become increasingly distributed to meet customer needs, and developers need more automated practices to maintain application availability and reduce the time and effort spent detecting, debugging, and resolving operational issues. Application downtime events caused by faulty code or config changes, unbalanced container clusters, or resource exhaustion (e.g. CPU, memory, disk, etc.) inevitably lead to bad customer experiences and lost revenue. Companies invest considerable money and developer time to deploy multiple monitoring tools, often managed separately, and then have to develop and maintain custom alerts for common issues like spikes in load balancer errors or drops in application request rates. Setting thresholds to identify and alert when application resources are behaving abnormally is difficult to get right, involves manual setup, and requires thresholds that must be continually updated as application usage changes (e.g. an unusually large numbers of requests during holiday shopping season).

If a threshold is set too high, developers don’t see alarms until operational performance is severely impacted. When a threshold is set too low, developers get too many false positives, which ultimately get ignored. Even if developers get alerted to a potential operational issue, the process of identifying the root cause can still prove difficult. Using existing tools, developers often have difficulty triangulating the root cause of an operational issue from graphs and alarms, and even when they are able to find the root cause, they are often left without a means to fix it. Each troubleshooting attempt is a cold start where teams must spend hours or days to identify problems, and this leads to time consuming, tedious work that slows down the time to resolve an operational failure and can prolong application disruptions.

Amazon DevOps Guru’s machine learning models leverage over 20 years of operational expertise in building, scaling, and maintaining highly available applications for Amazon.com. This gives Amazon DevOps Guru the ability to automatically detect operational issues (e.g. missing or misconfigured alarms, early warning of resource exhaustion, config changes that could lead to outages, etc.), provide context on resources involved and related events, and recommend remediation actions – with no machine learning experience required. With just a few clicks in the Amazon DevOps Guru console, historical application and infrastructure metrics like latency, error rates, and request rates for all resources are automatically ingested and analyzed to establish normal operating bounds, and Amazon DevOps Guru then uses a pre-trained machine learning model to identify deviations from the established baseline.

When Amazon DevOps Guru analyzes system and application data to automatically detect anomalies, it also groups this data into operational insights that include anomalous metrics, visualizations of application behavior over time, and recommendations on actions for remediation. Amazon DevOps Guru also correlates and groups related application and infrastructure metrics (e.g. web application latency spikes, running out of disk space, bad code deployments, memory leaks etc.) to reduce redundant alarms and help focus users on high-severity issues. Customers can see configuration change histories and deployment events, along with system and user activity, to generate a prioritized list of likely causes for an operational issue in the Amazon DevOps Guru console.

To help customers resolve issues quickly, Amazon DevOps Guru provides intelligent recommendations with remediation steps and integrates with AWS Systems Manager for runbook and collaboration tooling, giving customers the ability to more effectively maintain applications and manage infrastructure for their deployments. Together with Amazon CodeGuru – a developer tool powered by machine learning that provides intelligent recommendations for improving code quality and identifying an application’s most expensive lines of code – Amazon DevOps Guru provides customers the automated benefits of machine learning for their operational data so that developers can more easily improve application availability and reliability.

“Customers have asked us to continue adding services around areas where we can apply our own expertise on how to improve application availability and learn from the years of operational experience that we have acquired running Amazon.com,” said Swami Sivasubramanian, Vice President, Amazon Machine Learning, Amazon Web Services, Inc. “With Amazon DevOps Guru, we have taken our experience and built specialized machine learning models that help customers detect, troubleshoot, and prevent operational issues while providing intelligent recommendations when issues do arise. This enables teams to immediately benefit from operational best practices Amazon has learned from running Amazon.com, saving customers the time and effort that would otherwise be spent configuring and managing multiple monitoring systems.”

With a few clicks in the AWS Management Console, customers can enable Amazon DevOps Guru to begin analyzing account and application activity within minutes to provide operational insights. Amazon DevOps Guru gives customers a single-console experience to visualize their operational data by summarizing relevant data across multiple sources (e.g. AWS CloudTrail, Amazon CloudWatch, AWS Config, AWS CloudFormation, AWS X-Ray) and reduces the need to switch between multiple tools. Customers can also view correlated operational events and contextual data for operational insights within the Amazon DevOps Guru console and receive alerts via Amazon SNS. Additionally, Amazon DevOps Guru supports API endpoints through the AWS SDK, making it easy for partners and customers to integrate Amazon DevOps Guru into their existing solutions for ticketing, paging, and automatic notification of engineers for high-severity issues. PagerDuty and Atlassian are among the partners that have integrated Amazon DevOps Guru into their operations monitoring and incident management platforms, and customers who use their solutions can now benefit from operational insights provided by Amazon DevOps Guru. Amazon DevOps Guru is available in preview today in US East (N. Virginia), US East (Ohio), and US West (Oregon), Asia Pacific (Singapore), and Europe (Ireland) with availability in additional regions in the coming months.

Teams at more than 170,000 companies rely on Atlassian products to make teamwork easier, and help them organize, discuss, and complete their work. “Atlassian is proud to partner with AWS on the launch of Amazon DevOps Guru and help empower teams to deploy code and operate services with confidence,” said Emel Dogrusoz, Head of Product, Opsgenie. “With our new Opsgenie and Jira Service Management integration, the right teams can be immediately notified the instant Amazon DevOps Guru predicts a potential issue, or determines an incident has occurred. Amazon DevOps Guru provides a new dimension of insight, and Atlassian ensures the fastest response.”

“PagerDuty was built to drive the move to a DevOps culture by automating the entire incident response lifecycle with resolution,” said Jonathan Rende, SVP of Product at PagerDuty. “We’re excited to continue this commitment to DevOps with our latest integration with Amazon DevOps Guru. Leveraging Amazon’s decades of operational excellence and Amazon DevOps Guru’s machine learning capabilities, PagerDuty provides even more real-time signal-to-action capabilities to our joint customers. Through PagerDuty’s ingestion of Amazon DevOps Guru’s Amazon SNS, AWS customers can take real-time action on operational issues before they become customer-impacting outages.”

Thomson Reuters is one of the world’s most trusted providers of answers, helping professionals make confident decisions and run better businesses. “Customer experience is vital to us. Dealing with multiple sources of alerts for availability, performance, and change requests can be a challenge when trying to prevent and mitigate incidents impacting our customers,” said Steve Thoennes, Director of Infrastructure Hosting Portfolio at Thomson Reuters. “We are excited to use Amazon DevOps Guru and leverage its machine learning insights to provide clear paths for action, allowing us to mitigate issues quickly and avoid customer impacting events. The integration with PagerDuty is a bonus, as we can have recommendations delivered to the right people timely and efficiently.”

SmugMug facilitates the sale of digital and print media for amateur and professional photographers. “My team follows an ops-for-life motto, and we are always on the lookout for ways to automate our manual activities,” said Andrew Shieh, Operations Director at SmugMug. “With Amazon DevOps Guru, we hope to realize that goal and let AIOps take over many of our day-to-day tasks and make our workday composed of a single George-Jetson-style Easy Button, so my team can focus on IT innovation. We are now not only meeting the needs of the business but able to exceed them since we have more time to focus on what matters most – delivering value for our organization and our customers.”

NextRoll helps marketplaces and marketing platforms grow revenue by empowering them to build and enhance their marketing solutions. “We run thousands of Amazon Elastic Compute Cloud (Amazon EC2) instances, and we are looking for ways to reduce my team’s time spent on resolving operational issues,” said Valentino Volonghi, CTO at NextRoll. “We are excited to use Amazon DevOps Guru and leverage its machine learning-powered insights to help us identify, correlate, and remediate operational issues with recommendations. This will help my team save hours and reduce our mean time to recovery.”

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This revolutionary new approach instruments an extremely lightweight snippet of Qualys code into the container image, enabling policy-driven monitoring, detection and blocking of container behavior at runtime. This capability eliminates the need for cumbersome management of sidecar and privileged containers by security solutions that are difficult to manage and administer on host nodes and don’t work in container-as-a-service environments. Qualys Runtime Container Security, once instrumented in the image, will work within each container irrespective of where the container is instantiated and does not need any additional administration containers. This new solution addresses, in real time, container security use cases like critical file-access monitoring and blocking, network micro-segmentation, vulnerability and exploit mitigation, and virtual patching.

“At Zoom, we continue to enhance our comprehensive security program that addresses prevention, detection and response capabilities across all types of workloads,” said Randolph Barr, Head of Security Operations at Zoom. “Enforcing security best practices, mitigating attacks and monitoring are key use cases for container runtime security. Qualys Container Runtime Security will be key to further extending our detection and response capabilities to containerized workloads running on any container infrastructure.”

Now security teams can implement a comprehensive container security program with a single solution that includes vulnerability management, and detection and response across the build-ship-run container pipeline. With Qualys Container Runtime Security, customers can:

• Perform comprehensive, policy-driven monitoring and blocking of container runtime behavior including file access, network communications and process behaviors
• Create granular custom behavioral policies, use policies from the built-in policy library or automatically generate policies based on learned container behaviors
• Instrument container images in the CI/CD build pipeline with an innovative “follow the image” instrumentation approach which allows for standardized, guaranteed container runtime security across all types of container environments like Docker, Kubernetes, AWS Elastic Kubernetes Service, AWS Elastic Container Service, Azure Kubernetes Service, and Google Kubernetes Engine, as well as including container-as-a-service environments like Azure Container Instances, AWS Fargate and Google CloudRun.

“The growth of Kubernetes comes at a time when it is adept at solving many pertinent problems in IT and software development today. However, new tools are needed to secure containers, as container-based application development is a completely different approach to software,” said Frank Dickson, program vice president, Security Products at IDC. “Kubernetes can be managed as immutable infrastructure; however, the reality is that container configurations can drift during runtime. The Qualys approach empowers security to follow the container image with built-in instrumentation, enabling visibility and behavior enforcement for running containers. The solution also facilitates a ‘follow the container’ approach, providing DevOps and application teams future-proof development protection as applications migrate to more mature container and managed container environments such as Docker, Kubernetes, AWS Fargate and others.”

“Detection and Response in a single application across the container DevOps pipeline is key to effectively secure the containerized applications, as the high-velocity DevOps container pipeline can be exploited by malicious actors at runtime,” said Philippe Courtot, chairman and CEO of Qualys. “Therefore, we must build security into cloud workloads and extend protection into running containers. Qualys brings defense capabilities to our Container Security solution with the addition of policy-driven behavior detection and response capabilities to protect running containers on-premises, in private clouds or in container-as-a-service public clouds.”

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