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DevOps and security teams managing today’s multicloud architectures and cloud-native applications are facing an avalanche of data. This enables proactive changes such as resource autoscaling, traffic shifting, or preventative rollbacks of bad code deployment ahead of time.
Medallion Architecture provides a framework for organizing data processing workflows into different zones, enabling optimized batch and stream processing. This article explores the concepts of Medallion Architecture and demonstrates how to implement batch and stream processing pipelines using Azure Databricks and Delta Lake.
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
As companies strive to innovate and deliver faster, modern software architecture 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.
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.
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?
As companies strive to innovate and deliver faster, modern software architecture 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.
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.
Dynatrace Delivers Software Intelligence as Code. With this announcement, Dynatrace delivers software intelligence as code, including broad and deep observability, application security, and advanced AIOps (or AI for operations) capabilities. Dynatrace Delivers Most Complete Observability for Multicloud Serverless Architectures.
This method of structuring, developing, and operating complex, multi-function software as a collection of smaller independent services is known as microservice architecture. ” it helps to understand the monolithic architectures that preceded them. Understanding monolithic architectures. Microservices benefits.
This method of structuring, developing, and operating complex, multi-function software as a collection of smaller independent services is known as microservice architecture. ” it helps to understand the monolithic architectures that preceded them. Understanding monolithic architectures. Microservices benefits.
AI-powered automation and deep, broad observability for serverless architectures. In addition to existing support for AWS Lambda , this support now covers Microsoft Azure Functions and Google Cloud Functions as well as managed Kubernetes environments, messaging queues, and cloud databases across all major cloud providers. Visit our?
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.
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.
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.
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.
You can read my blog supporting my session titled “ Performance as Code: Lets make it a Standard ” on the Neotys PAC blog. A single indicator is defined as a query against a data source such as a monitoring, testing, security or code quality tool. Bamboo, Azure DevOps, AWS CodePipeline …. Pitometer is a Node.js
Function as a service is a cloud computing model that runs code in small modular pieces, or microservices. 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.
According to Forrester Research, the COVID-19 pandemic fueled investment in “hyperscaler public clouds”—Amazon Web Services (AWS), Google Cloud Platform and Microsoft Azure. This approach—known as DevSecOps —places greater emphasis on developing secure application code in the cloud. Data confirms Aggarwal’s conclusions.
The fact is, Reliability and Resiliency must be rooted in the architecture of a distributed system. The email walked through how our Dynatrace self-monitoring notified users of the outage but automatically remediated the problem thanks to our platform’s architecture. Fact #4: Multi-node, multi-availability zone deployment architecture.
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.
Popular examples include AWS Lambda and Microsoft Azure Functions , but new providers are constantly emerging as this model becomes more mainstream. Code development also benefits from a serverless approach. Then, they can apply DevSecOps best practices to fully test new code and see what breaks without affecting current operations.
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….
As cloud-native, distributed architectures proliferate, the need for DevOps technologies and DevOps platform engineers has increased as well. DevOps teams are responsible for all phases of the software development lifecycle, from code commit to the deployment of products and services. Microsoft Azure. Atlassian Jira.
Especially in dynamic microservices architectures, distributed tracing is an essential component of efficient monitoring, application optimization, debugging, and troubleshooting. Microsoft has already introduced Trace Context support in some of their services, including.NET Azure Functions, API Management, and IoT Hub. Dynatrace news.
For those who aspire to become power users, the new in-app DQL editor (Dynatrace Query Language) translates manually selected filters into the DQL code executed in the backend. This architecture also means you’re not required to determine your log data use cases beforehand or while analyzing logs within the new Logs app.
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.
Automatically collect and evaluate business, service, and architectural indicator metrics to promote or roll back deployments. Since becoming General Availability in the fall of 2019 , GitHub Actions has helped teams automate continuous integration and continuous delivery (CI/CD) workflows for code builds, tests, and deployments.
You may be using serverless functions like AWS Lambda , Azure Functions , or Google Cloud Functions, or a container management service, such as Kubernetes. In contrast to modern software architecture, which uses distributed microservices, organizations historically structured their applications in a pattern known as “monolithic.”
A secure access management system for code repositories and pipeline configurations is necessary, as these are among the organization’s most valuable assets and must be protected from accidental access. Addressing vulnerabilities becomes challenging when dependencies in third-party libraries or solutions are unclear.
From of our learnings on how we integrated Dynatrace into our DevOps toolchain , we advise our customers to follow our best practices around integrating delivery tools with Dynatrace, enforcing Dynatrace-based quality gates, implementing monitoring as code or automate remediation based on Dynatrace problems. Monitoring Configuration as Code.
DevOps teams operating, maintaining, and troubleshooting Azure, AWS, GCP, or other cloud environments are provided with an app focused on their daily routines and tasks. This architecture also means you are not required to determine your log data use cases beforehand or while analyzing logs within the new logs app.
As a result, teams can focus on writing code and building features rather than dealing with infrastructure nuances. They shouldn’t worry about the platform; they should just start writing code.” Dynatrace has made the reference IDP architecture available on GitHub for anyone to use.
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.
To understand the root cause, the Dynatrace AI engine, Davis®, uses AI-driven PurePath technology to analyze the journey of an individual user request in the browser and trace all the way to the back end to see how it’s contributing to the problem, down to the line of code that was called. Next-level application performance insights.
In recent years, customer projects have moved towards complex cloud architectures, including dozens of microservices and different technology stacks which are challenging to develop, maintain, and optimize for resiliency. The white box load testing project setup. a Jenkinsfile. Next Steps: Collaboration on Keptn.
Billing Management For Your Next SaaS Idea Using Stripe And Azure Functions. Billing Management For Your Next SaaS Idea Using Stripe And Azure Functions. package to build an API layer comprising Azure Functions apps that can be executed by an HTTP trigger from a web, mobile, or desktop client. Creating Azure Functions.
But your infrastructure teams don’t see any issue on their AWS or Azure monitoring tools, your platform team doesn’t see anything too concerning in Kubernetes logging, and your apps team says there are green lights across the board. Kiosks, mobile apps, websites, and QR codes. Imagine you’re in a war room. So, what happens next?
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. As a result, teams are in dire need of end-to-end observability that can accommodate disparate formats and custom APIs with the context needed to take meaningful action.
And how can you verify this performance consistently across a multicloud environment that also uses Microsoft Azure and Google Cloud Platform frameworks? Using an interactive no/low code editor, you can create workflows or configure them as code.
After moving to Microsoft Azure for many of its production-stage applications, Park ‘N Fly’s IT teams experienced blind spots. “We IT automation speeds code development. To do so, organizations often succumb to a “hamster wheel” of having to release code more quickly to innovate effectively.
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.
Cloud application security practices enable organizations to follow secure coding practices, monitor and log activities for detection and response, comply with regulations, and develop incident response plans. It also entails secure development practices, security monitoring and logging, compliance and governance, and incident response.
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