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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.
Shift-left is an approach to software development and operations that emphasizes testing, monitoring, and automation earlier in the software development lifecycle. Moving inefficient code to cloud containers can be costly, as it may activate auto-scaling and increase your monthly bill.
Cloud environments have become ever more complex, with an increasingly interconnected set of services. To tame this complexity and deliver differentiated digital experiences, IT, development, security, and business teams need automated workflows throughout these cloud ecosystems.
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.
For executives, these directives present several challenges, including compliance complexity, resource allocation for continuous monitoring, and incident reporting. In dynamic and distributed cloud environments, the process of identifying incidents and understanding the material impact is beyond human ability to manage efficiently.
What developers want Developers want to own their code in a distributed, ephemeral, cloud, microservices-based environment. This ownership starts with understanding how their code behaves in all environments, resolving issues, and writing and optimizing code in a high-quality, secure, and timely manner.
Synthetic monitoring can help to confirm your applications are performing as intended and, in the event they’re not, help you quickly figure out what’s going on. Here’s a look at what synthetic monitoring is, how it’s different from real-user monitoring, and why it matters to your business.
That’s why cloud cost optimization is becoming a major priority regardless of where organizations are on their digital transformation journeys. In fact, Gartner’s 2023 forecast is for worldwide public cloud spending to reach nearly $600 billion. These costs also have an environmental impact. Utilization. Architecture.
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? GCF is part of the Google Cloud Platform. How Google Cloud Functions works.
Rising cloud complexity has made securing cloud-native and multicloud applications significantly more difficult. With the pace of digital transformation continuing to accelerate, organizations are realizing the growing imperative to have a robust application security monitoring process in place.
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?
However, with these benefits come complexities in terms of cloud management, Kubernetes observability, and automation, making it imperative for enterprises to address these intricacies to enhance reliability, performance, and resource usage. So many tools can result in data inconsistencies. So many tools can result in data inconsistencies.
Log monitoring, log analysis, and log analytics are more important than ever as organizations adopt more cloud-native technologies, containers, and microservices-based architectures. Driving this growth is the increasing adoption of hyperscale cloud providers (AWS, Azure, and GCP) and containerized microservices running on Kubernetes.
Cloud-native CI/CD pipelines and build processes often expose Kubernetes to attack vectors via internet-sourced container images. The Dynatrace Operator is responsible for the secure lifecycle of components necessary for Kubernetes cluster monitoring. Reference the container image in the DynaKube.
AWS Security Hub findings AWS Security Hub provides a great way of aggregating security findings, especially those related to cloud infrastructure. Findings from various stages of the Software Development Lifecycle (SDLC) are mixed in: code scans, build scans, and runtime. This increases the number of findings to prioritize.
Dynatrace enables our customers to monitor and optimize their cloud infrastructure and applications through the Dynatrace Software Intelligence Platform. For that reason, we started a simple load-test scenario where we flooded our event-based system with 100 cloud-events per minute. Dynatrace news. Can we fix it? Yes, we can!
As cloud environments become increasingly complex, legacy solutions can’t keep up with modern demands. As a result, companies run into the cloud complexity wall – also known as the cloud observability wall – as they struggle to manage modern applications and gain multicloud observability with outdated tools.
As a result, API monitoring has become a must for DevOps teams. So what is API monitoring? What is API Monitoring? API monitoring is the process of collecting and analyzing data about the performance of an API in order to identify problems that impact users. The need for API monitoring. Ways to monitor APIs.
As more organizations invest in a multicloud strategy, improving cloud operations and observability for increased resilience becomes critical to keep up with the accelerating pace of digital transformation. American Family turned to Dynatrace to help them monitor complex environments without the hassle. ski explains.
For IT teams seeking agility, cost savings, and a faster on-ramp to innovation, a cloud migration strategy is critical. Cloud migration enables IT teams to enlist public cloud infrastructure so an organization can innovate without getting bogged down in managing all aspects of IT infrastructure as it scales. Dynatrace news.
Real user monitoring can help you catch these issues before they impact the bottom line. What is real user monitoring? Real user monitoring (RUM) is a performance monitoring process that collects detailed data about a user’s interaction with an application. Real user monitoring collects data on a variety of metrics.
As organizations expand their cloud footprints, they are combining public, private, and on-premises infrastructures. But modern cloud infrastructure is large, complex, and dynamic — and over time, this cloud complexity can impede innovation. VA’s journey into the cloud.
Cloud-native technologies, including Kubernetes and OpenShift, help organizations accelerate innovation. Open source has also become a fundamental building block of the entire cloud-native stack. Why cloud-native applications, Kubernetes, and open source require a radically different approach to application security.
Leveraging cloud-native technologies like Kubernetes or Red Hat OpenShift in multicloud ecosystems across Amazon Web Services (AWS) , Microsoft Azure, and Google Cloud Platform (GCP) for faster digital transformation introduces a whole host of challenges. Dynatrace news. Connecting data siloes requires daunting integration endeavors.
How can you reduce the carbon footprint of your hybrid cloud? Evaluating these on three levels—data center, host, and application architecture (plus code)—is helpful. energy-efficient data centers—cloud providers—achieve values closer to 1.2. Is the solution to just move all workloads to the cloud? A PUE of 1.0
Cloud-native observability is a prerequisite for companies that need to meet these expectations. With PurePath ® distributed tracing and analysis technology at the code level, Dynatrace already provides the deepest possible insights into every transaction. Dynatrace news. Automatically connect logs and distributed traces at scale.
Organizations can now accelerate innovation and reduce the risk of failed software releases by incorporating on-demand synthetic monitoring as a metrics provider for automatic, continuous release-validation processes. Dynatrace combines Synthetic Monitoring with automatic release validation for continuous quality assurance across the SDLC.
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. Comparing log monitoring, log analytics, and log management.
These resources generate vast amounts of data in various locations, including containers, which can be virtual and ephemeral, thus more difficult to monitor. These challenges make AWS observability a key practice for building and monitoringcloud-native applications. AWS monitoring best practices. And why it matters.
Cloud observability can bring business value, said Rick McConnell, CEO at Dynatrace. Organizations have clearly experienced growth, agility, and innovation as they move to cloud computing architecture. But without effective cloud observability, they continue to experience challenges in their cloud environments.
More organizations than ever are undertaking cloud migration as digital transformation continues to gain momentum across every industry in every region. But what does it take to migrate your existing applications to the cloud? What is cloud migration? However, it can also mean migrating from one cloud to another.
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.
Cloud-native observability for Google’s fully managed GKE Autopilot clusters demands new methods of gathering metrics, traces, and logs for workloads, pods, and containers to enable better accessibility for operations teams. First, we create a small Kubernetes cluster in the Google Cloud Console. and GKE Autopilot 126.
More than 90% of enterprises now rely on a hybrid cloud infrastructure to deliver innovative digital services and capture new markets. That’s because cloud platforms offer flexibility and extensibility for an organization’s existing infrastructure. What is hybrid cloud architecture?
Welcome to another chapter in the ongoing series I started covering my journey into the world of cloud-native observability. I continued onwards with a few of the architectural challenges you might encounter when older monolithic applications and monitoring tools are still part of an organization's infrastructure landscape.
Cloud environments—including multicloud, hybrid, and cloud-native ecosystems—offer unmatched agility, scalability, and cost-effectiveness, though they also present new challenges and complexities that are impossible to manage manually. Another big advantage of automation-as-code is the scale at which automation is enabled.
Energy efficiency is a key reason why organizations are migrating workloads from energy-intensive on-premises environments to more efficient cloud platforms. But while moving workloads to the cloud brings overall carbon emissions down, the cloud computing carbon footprint itself is growing. Certainly, this is true for us.
As dynamic systems architectures increase in complexity and scale, IT teams face mounting pressure to track and respond to conditions and issues across their multi-cloud environments. Observability relies on telemetry derived from instrumentation that comes from the endpoints and services in your multi-cloud computing environments.
Many of our customers—the world’s largest enterprises—have embraced the Dynatrace SaaS approach to monitoring, which provides critical business insights powered by AI and automation for globally-distributed, heterogeneous IT landscapes. New self-monitoring environment provides out-of-the-box insights and custom alerting.
Dynatrace Cloud Native Full Stack injection for Kubernetes, now officially released, provides unparalleled flexibility and scale for onboarding teams to AI-powered observability. The foundation of this flexibility is the Dynatrace Operator ¹ and its new Cloud Native Full Stack injection deployment strategy. Dynatrace news.
Department of Veterans Affairs (VA) is packaging application code along with its libraries and dependencies within an executable software unit. The containers can run anywhere, whether a private data center, the public cloud or a developer’s own computing devices. VAPO is available in both Microsoft Azure and AWS.
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?
Built and maintained by Oracle, it provides an all-in-one solution for database modeling, query execution, user administration, and performance monitoring. Its built for users who want more than just basic queryingNavicat includes tools for data modeling, automation, team collaboration, and cloud integrations.
Key components of GitOps are declarative infrastructure as code, orchestration, and observability. Many observability solutions don’t support an “as code” approach. Because of these issues, developers often still lack control over the behavior of their monitoring platform. Dynatrace enables software intelligence as code.
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