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DevOps and security teams managing today’s multicloud architectures and cloud-native applications are facing an avalanche of data. However, the drive to innovate faster and transition to cloud-native application architectures generates more than just complexity — it’s creating significant new risk.
2020 cemented the reality that modern software development practices require rapid, scalable delivery in response to unpredictable conditions. Microservices are flexible, lightweight, modular software services of limited scope that fit together with other services to deliver full applications. Understanding monolithic architectures.
2020 cemented the reality that modern software development practices require rapid, scalable delivery in response to unpredictable conditions. Microservices are flexible, lightweight, modular software services of limited scope that fit together with other services to deliver full applications. Understanding monolithic architectures.
Azure observability and Azure data analytics are critical requirements amid the deluge of data in Azure cloud computing environments. Dynatrace recently announced the availability of its latest core innovations for customers running the Dynatrace® platform on Microsoft Azure, including Grail. Digital transformation 2.0
Dynatrace is proud to provide deep monitoring support for Azure Linux as a container host operating system (OS) platform for Azure Kubernetes Services (AKS) to enable customers to operate efficiently and innovate faster. What is Azure Linux? Why monitor Azure Linux container host for AKS? Resource utilization management.
As companies strive to innovate and deliver faster, modern softwarearchitecture is evolving at near the speed of light. x runtime versions of Azure Functions running in an Azure App Service plan. Azure Functions in a nutshell. Azure Functions is the serverless computing offering from Microsoft Azure.
Some time ago, we announced monitoring coverage for all Azure Monitor services , as well as the ability to purchase the Dynatrace Software Intelligence Platform through the Microsoft Azure Marketplace. Now, Dynatrace and Microsoft have further deepened their partnership by making Dynatrace for Azure generally available.
What is Azure Functions? Similar to AWS Lambda , Azure Functions is a serverless compute service by Microsoft that can run code in response to predetermined events or conditions (triggers), such as an order arriving on an IoT system, or a specific queue receiving a new message. The growth of Azure cloud computing.
As organizations adopt microservices architecture with cloud-native technologies such as Microsoft Azure , many quickly notice an increase in operational complexity. To guide organizations through their cloud migrations, Microsoft developed the Azure Well-Architected Framework. What is the Azure Well-Architected Framework?
Many organizations are taking a microservices approach to IT architecture. However, in some cases, an organization may be better suited to another architecture approach. Therefore, it’s critical to weigh the advantages of microservices against its potential issues, other architecture approaches, and your unique business needs.
As companies strive to innovate and deliver faster, modern softwarearchitecture is evolving at near the speed of light. x runtime versions of Azure Functions running in an Azure App Service plan. Azure Functions in a nutshell. Azure Functions is the serverless computing offering from Microsoft Azure.
For operations, development and security teams, the pressure to deliver better, more secure software faster has never been more critical for business value. Dynatrace Delivers Software Intelligence as Code. Dynatrace Delivers Most Complete Observability for Multicloud Serverless Architectures. Dynatrace news. Learn more!
Many software delivery teams share the same pain points as they’re asked to support cloud adoption and modernization initiatives. Automatically collect and evaluate business, service, and architectural indicator metrics to promote or roll back deployments. Key ingredients required to deliver better software faster.
To drive better outcomes using hybrid cloud architectures, it helps to understand their benefits—and how to orchestrate them seamlessly. What is hybrid cloud architecture? Hybrid cloud architecture is a computing environment that shares data and applications on a combination of public clouds and on-premises private clouds.
The devil is in the detail, though because of the sheer number, breadth, and volatility of technologies used in modern architectures and the immense volume, velocity, and variety of data they produce. The Dynatrace Software Intelligence Hub helps enterprises easily apply AI to all technologies and data sources and unlock automation at scale.
To take full advantage of the scalability, flexibility, and resilience of cloud platforms, organizations need to build or rearchitect applications around a cloud-native architecture. So, what is cloud-native architecture, exactly? What is cloud-native architecture? The principles of cloud-native architecture.
VMware commercialized the idea of virtual machines, and cloud providers embraced the same concept with services like Amazon EC2, Google Compute, and Azure virtual machines. Within this paradigm, it is possible to run entire architectures without touching a traditional virtual server, either locally or in the cloud.
Cloud providers then manage physical hardware, virtual machines, and web server software management. Cloud providers such as Google, Amazon Web Services, and Microsoft also followed suit with frameworks such as Google Cloud Functions , AWS Lambda , and Microsoft Azure Functions. FaaS vs. monolithic architectures.
Software reliability and resiliency don’t just happen by simply moving your software to a modern stack, or by moving your workloads to the cloud. The fact is, Reliability and Resiliency must be rooted in the architecture of a distributed system. Fact #4: Multi-node, multi-availability zone deployment architecture.
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. They are required to understand the full story of what happened in a system.
Validating Deployments still seems to be a semi-automated task for most software delivery teams. OpenSource project which is part of keptn and it provides a good solution to automate the validation of a software deployment based on a list of indicators resulting in an overall deployment score. Bamboo, Azure DevOps, AWS CodePipeline ….
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. Dynatrace news. As teams begin collecting and working with observability data, they are also realizing its benefits to the business, not just IT.
According to Forrester Research, the COVID-19 pandemic fueled investment in “hyperscaler public clouds”—Amazon Web Services (AWS), Google Cloud Platform and Microsoft Azure. The session will cover how Dynatrace can help you deliver better software faster as you build applications based on AWS Lambda or microservices architecture.
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.
As cloud-native, distributed architectures proliferate, the need for DevOps technologies and DevOps platform engineers has increased as well. They are similar to site reliability engineers (SREs) who focus on creating scalable, highly reliable software systems. Open source software containerization platform. Microsoft Azure.
Example 1: Architecture boundaries. First, they took a big step back and looked at their end-to-end architecture (Figure 2). SLO dashboard defined by architectural boundary. Another customer is from a multinational software corporation that develops enterprise software to manage business operations and customer relations.
As modern agile software development relies heavily on automated CI/CD pipelines to swiftly build and deploy releases multiple times daily, these pipelines must be reliable and high-performing. Consequently, troubleshooting issues and ensuring seamless software deployment becomes increasingly tricky. Normalization of data on ingest.
The study analyzes factual Kubernetes production data from thousands of organizations worldwide that are using the Dynatrace Software Intelligence Platform to keep their Kubernetes clusters secure, healthy, and high performing. Open-source software drives a vibrant Kubernetes ecosystem. Java, Go, and Node.js
Popular examples include AWS Lambda and Microsoft Azure Functions , but new providers are constantly emerging as this model becomes more mainstream. Serverless architecture makes it possible to host code anywhere, rather than relying on an origin server. Architectural complexity. Reduced latency. Optimizes resources.
Digital workers are now demanding IT support to be more proactive,” is a quote from last year’s Gartner Survey Understandably, a higher number of log sources and exponentially more log lines would overwhelm any DevOps, SRE, or Software Developer working with traditional log monitoring solutions.
The rapidly evolving digital landscape is one important factor in the acceleration of such transformations – microservices architectures, service mesh, Kubernetes, Functions as a Service (FaaS), and other technologies now enable teams to innovate much faster. New cloud-native technologies make observability more important than ever….
You may be using serverless functions like AWS Lambda , Azure Functions , or Google Cloud Functions, or a container management service, such as Kubernetes. Many customers try to use traditional tools to monitor and observe modern software stacks, but they struggle to deal with the dynamic and changing nature of cloud environments.
Incorporating cloud application security practices is an effective way for organizations to avoid application security risks, ensure a smoothly running software development lifecycle (SDLC), and establish an overall strong security posture. However, open source software is often a vector for security vulnerabilities.
That’s why, in part, major cloud providers such as Amazon Web Services, Microsoft Azure, and Google Cloud Platform are discussing cloud optimization. Traditional cloud monitoring methods can no longer scale to meet organizations’ demands, as multicloud architectures continue to expand. But it is also about process automation.
Hyperconverged infrastructure (HCI) is an IT architecture that combines servers, storage, and networking functions into a unified, software-centric platform to streamline resource management. HCI deployment resources are combined under software-defined platforms, allowing teams to manage these resources from a single interface.
And how can you verify this performance consistently across a multicloud environment that also uses Microsoft Azure and Google Cloud Platform frameworks? This process enables you to continuously evaluate software against predefined quality criteria and service level objectives (SLOs) in pre-production environments.
Consider Log4Shell, a software vulnerability in Apache Log4j 2 , a popular Java library. Log4j is a ubiquitous software code in various consumer-facing products and services. Modern observability technologies have helped enterprises identify software vulnerabilities such as Log4Shell in their environments.
Platform engineering creates and manages a shared infrastructure and set of tools, such as internal developer platforms (IDPs) , to enable software developers to build, deploy, and operate applications more efficiently. Dynatrace has made the reference IDP architecture available on GitHub for anyone to use.
Organizations have clearly experienced growth, agility, and innovation as they move to cloud computing architecture. As a result, many IT teams have turned to cloud observability platforms to reduce blind spots in their cloud architecture, to resolve problems rapidly, and to deliver better customer experience. Cloud modernization.
Data is proliferating in separate silos from containers and Kubernetes to open source APIs and software to serverless compute services, such as AWS and Azure. Modern IT organizations are generating more data from more tools and technologies than ever.
Park ‘N Fly has created a series of software-based services to enhance customer experience while patrons park. But Park ‘N Fly’s services require software intelligence at every layer of the IT stack. After moving to Microsoft Azure for many of its production-stage applications, Park ‘N Fly’s IT teams experienced blind spots. “We
While data lakes and data warehousing architectures are commonly used modes for storing and analyzing data, a data lakehouse is an efficient third way to store and analyze data that unifies the two architectures while preserving the benefits of both. This is simply not possible with conventional architectures. Data management.
Our engineering and delivery teams at Dynatrace have invested a lot of time building automation into the Dynatrace Software Intelligence Platform. Keptn can integrate with other monitoring and observability platforms thanks to our event-driven architecture. Keptn can be extended with new use cases through event-driven architecture.
The various presenters in this session aligned platform engineering use cases with the software development lifecycle. Standards are set by the platform engineers and ensured throughout all stages of the software development lifecycle. According to Gardner, teams gradually deliver software to user groups with progressive delivery.
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