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The need for application and DevOps modernization to deliver on business outcomes has never been greater. Organizations are increasingly embracing cloud- and AI-native strategies, requiring a more automated and intelligent approach to their observability and development practices. Dynatrace AutomationEngine. Dynatrace AppEngine.
DevOps and security teams managing today’s multicloud architectures and cloud-native applications are facing an avalanche of data. On average, organizations use 10 different tools to monitor applications, infrastructure, and user experiences across these environments.
While many companies now enlist public cloud services such as Amazon Web Services, Google Public Cloud, or Microsoft Azure to achieve their business goals, a majority also use hybrid cloudinfrastructure to accommodate traditional applications that can’t be easily migrated to public clouds.
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As enterprises embrace more distributed, multicloud and applications-led environments, DevOps teams face growing operational, technological, and regulatory complexity, along with rising cyberthreats and increasingly demanding stakeholders. But first, there are five things to consider before settling on a unified observability strategy.
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Infrastructure as code is a way to automate infrastructure provisioning and management. And it’s a crucial step toward achieving cloud automation on the path to NoOps. In this blog, I explore how Dynatrace has made cloud automation attainable—and repeatable—at scale by embracing the principles of infrastructure as code.
More technology, more complexity The benefits of cloud-native architecture for IT systems come with the complexity of maintaining real-time visibility into security compliance and risk posture. Configuration and Compliance , adding the configuration layer security to both applications and infrastructure and connecting it to compliance.
We can plausibly say the enterprise development market turned the tide on cloud-native development in 2020, as most net-new software and serious overhaul projects started moving toward microservices architectures, with Kubernetes as the preferred platform.
With the world’s increased reliance on digital services and the organizational pressure on IT teams to innovate faster, the need for DevOps monitoring tools has grown exponentially. But when and how does DevOps monitoring fit into the process? And how do DevOps monitoring tools help teams achieve DevOps efficiency?
In its report “ Innovation Insight for Observability ,” global research and advisory firm Gartner describes the advantages of observability for cloud monitoring as organizations navigate this shift. Observability defined. Where traditional monitoring falls flat. Then teams can leverage and interpret the observable data.
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As cloud-native, distributed architectures proliferate, the need for DevOps technologies and DevOps platform engineers has increased as well. DevOps engineer tools can help ease the pressure as environment complexity grows. ” What does a DevOps platform engineer do? Atlassian Jira. Selenium.
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That’s especially true of the DevOps teams who must drive digital-fueled sustainable growth. They’re unleashing the power of cloud-based analytics on large data sets to unlock the insights they and the business need to make smarter decisions. From a technical perspective, however, cloud-based analytics can be challenging.
Real-time streaming needs real-time analytics As enterprises move their workloads to cloud service providers like Amazon Web Services, the complexity of observing their workloads increases. As cloud complexity grows, it brings more volume, velocity, and variety of log data. Managing this change is difficult.
As organizations mature on their digital transformation journey, they begin to realize that automation – specifically, DevOps automation – is critical for rapid software delivery and reliable applications. Organizations can’t manage their cloud environments effectively with these traditional approaches.
You have set up a DevOps practice. As we look at today’s applications, microservices, and DevOps teams, we see leaders are tasked with supporting complex distributed applications using new technologies spread across systems in multiple locations. DevOps metrics to help you meet your DevOps goals. Dynatrace news.
Protecting IT infrastructure, applications, and data requires that you understand security weaknesses attackers can exploit. Cloudinfrastructure analysis ensures the secure configuration of cloudinfrastructure including virtual machines, containers, cloud-hosted databases, and serverless services.
In recent years, function-as-a-service (FaaS) platforms such as Google Cloud Functions (GCF) have gained popularity as an easy way to run code in a highly available, fault-tolerant serverless environment. What is Google Cloud Functions? Google Cloud Functions is a serverless compute service for creating and launching microservices.
DevOps and platform engineering are essential disciplines that provide immense value in the realm of cloud-native technology and software delivery. Observability of applications and infrastructure serves as a critical foundation for DevOps and platform engineering, offering a comprehensive view into system performance and behavior.
As a leader in cloudinfrastructure and platform services , the Google Cloud Platform is fast becoming an integral part of many enterprises’ cloud strategies. Simplified cloud complexity with fully automated observability of Google Cloud. Dynatrace news.
Today’s organizations face increasing pressure to keep their cloud-based applications performing and secure. Cloud application security remains challenging because organizations lack end-to-end visibility into cloud architecture. In many cases, organizations don’t discover vulnerabilities until after they have been exploited.
Cloud-native applications now dominate IT as DevOps teams respond to growing demands to deliver functionality faster and more securely. As DevOps teams are pivoting to cloud-native technologies, IT environments have become increasingly complex. Cloud-native is the preferred way of delivering applications.
Many organizations that have integrated their software development and operations into DevOps practices struggle with efficiency because they’re juggling disparate DevOps tools, or their tools aren’t meeting their needs. The status quo of the DevOps toolchain. How to approach transforming your DevOps processes.
The DevOps approach to developing software aims to speed applications into production by releasing small builds frequently as code evolves. As part of the continuous cycle of progressive delivery, DevOps teams are also adopting shift-left and shift-right principles to ensure software quality in these dynamic environments.
Most infrastructure and applications generate logs. In cloud-native environments, there can also be dozens of additional services and functions all generating data from user-driven events. This is critical to ensure high performance, security, and a positive user experience for cloud-native applications and services.
The DevOps approach to developing software aims to speed applications into production by releasing small builds frequently as code evolves. As part of the continuous cycle of progressive delivery, DevOps teams are also adopting shift-left and shift-right principles to ensure software quality in these dynamic environments.
Full-stack observability is fast becoming a must-have capability for organizations under pressure to deliver innovation in increasingly cloud-native environments. Endpoints include on-premises servers, Kubernetes infrastructure, cloud-hosted infrastructure and services, and open-source technologies. Dynatrace news.
Autonomous Cloud is not another lofty marketing term. Autonomous Cloud is what enables our globally distributed development teams at Dynatrace to deliver better software faster following our NoOps approach: Fully Autonomous and as a Self-Service! Three waves of DevOps leading to Autonomous Cloud. Dynatrace news.
Cloud application security is becoming more of a critical issue as cloud-based applications gain popularity. The cloud allows a modular approach to building applications, enabling development and operations teams to create and deploy feature-rich apps very quickly. What is cloud application security?
Software companies who have already been following and adopting DevOps and site reliability engineering (SRE) practices alongside their shared ancestry in agile concepts came out on top – especially if they adopted those practices across the whole organization and customer value stream. Automated release inventory and version comparison.
But as more organizations adopt cloud-native technologies and distribute workloads among multicloud environments, that goal seems harder to attain. In fact, a recent survey found that many cloud applications are vulnerable to outages , despite growing confidence in cloud platforms and services. What is always-on infrastructure?
Indeed, organizations view IT modernization and cloud computing as intertwined with their business strategy and COVID-19 recovery plans. As a result, reliance on cloud computing for infrastructure and application development has increased during the pandemic era. AWS re:Invent 2021: Modernizing for cloud-native environments.
The DevOps playbook has proven its value for many organizations by improving software development agility, efficiency, and speed. These methods improve the software development lifecycle (SDLC), but what if infrastructure deployment and management could also benefit? Dynatrace news. What is GitOps? How does GitOps work?
Cloud-native observability and artificial intelligence (AI) can help organizations do just that with improved analysis and targeted insight. Additionally, they discuss the need for cloud-native observability with GitOps that provides continuous operational insight across the Kubernetes value stream.
Cloud observability is fast becoming an imperative as more organizations adopt multicloud IT strategies. To adapt, many are turning to AIOps and other automation technologies to solve the complex issues that accompany cloud-native architecture. Multicloud complexity obscures cloud observability. Dynatrace news.
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