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Adopting AI to enhance efficiency and boost productivity is critical in a time of exploding data, cloud complexities, and disparate technologies. Dynatrace delivers AI-powered, data-driven insights and intelligent automation for cloud-native technologies including Azure.
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.
As organizations adopt more cloud-native technologies, the risk—and consequences—of cyberattacks are also increasing. Through this integration, Dynatrace enriches data collected by Microsoft Sentinel to provide organizations with enhanced data insights in context of their full technology stack.
Modern tech stacks such as Apache Spark, Azure Data Factory, Azure Databricks, and Azure Synapse Analytics offer powerful tools for building optimized data pipelines that can efficiently ingest and process data on the cloud.
To make this happen, enterprises are shifting an unprecedented volume of workloads onto cloud platforms such as Microsoft Azure. How Azure digital transformation helps There are three ways that Microsoft Azure can help organizations do more with less when it comes to organizations’ digital transformation journeys.
Indeed, around 85% of technology leaders believe their problems are compounded by the number of tools, platforms, dashboards, and applications they rely on to manage multicloud environments. Clearly, continuing to depend on siloed systems, disjointed monitoring tools, and manual analytics is no longer sustainable.
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 is explained in detail in our blog post, Unlock log analytics: Seamless insights without writing queries.
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….
To continue down the carbon reduction path, IT leaders must drive carbon optimization initiatives into the hands of IT operations teams, arming them with the tools needed to support analytics and optimization. By leveraging existing OneAgent instrumentation, customers can get started in minutes with no new instrumentation hurdles.
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.
This lack of visibility creates blind spots and makes it difficult to ensure the health of applications running on serverless technologies. 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.
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This lack of visibility creates blind spots and makes it difficult to ensure the health of applications running on serverless technologies. 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.
As adoption rates for Microsoft Azure continue to skyrocket, Dynatrace is developing a deeper integration with the platform to provide even more value to organizations that run their businesses on Azure or use it as a part of their multi-cloud strategy. Azure Batch. Azure DB for MariaDB. Azure DB for MySQL.
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Organizations need to ensure their solutions meet security and privacy requirements through certified high-performance filtering, masking, routing, and encryption technologies while remaining easy to configure and operate. This “data in context” feeds Davis® AI, the Dynatrace hypermodal AI , and enables schema-less and index-free analytics.
The latest State of Observability 2024 report shows that 86% of interviewed technology leaders see an explosion of data beyond humans’ ability to manage it. OpenPipeline also incorporates data contextualization technology, enriching data with metadata and linking it to other relevant data sources.
As companies accelerate digital transformation, they implement modern cloud technologies like serverless functions. According to Flexera , serverless functions are the number one technology evaluated by enterprises and one of the top five cloud technologies in use at enterprises. And serverless support is a core capability.
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.
Indeed, AI is revolutionizing our world, driving rapid innovation, and transforming how we engage with technology personally and professionally. To keep up, organizations are making significant investments to harness this technology and unlock new opportunities to thrive in the era of AI with Microsoft Azure and adjacent technologies.
Dynatrace, operated from Tokyo, addresses the data residency needs of the Japanese market Dynatrace operates its AI-powered unified platform for observability, security, and business analytics as a SaaS solution in 19 worldwide regions on three hyperscalers (AWS, Azure, and GCP). Data residency in Japan is a must.
Similarly, integrations for Azure and VMware are available to help you monitor your infrastructure both in the cloud and on-premises. Dynatrace provides two technologies for Digital Experience Monitoring (DEM): Synthetic Monitoring and Real User Monitoring (RUM). Further reading about Business Analytics : . Conclusion.
Generally, the storage technology categorizes data into landing, raw, and curated zones depending on its consumption readiness. The result is a framework that offers a single source of truth and enables companies to make the most of advanced analytics capabilities simultaneously. Support diverse analytics workloads.
Dynatrace now automatically discovers, instruments and maps various container technologies within Kubernetes, making the largest and most diverse containerized environments easier to deploy and manage. Florian Ortner, Dynatrace Chief Product Officer, joined Steve on stage to demonstrate how our enhanced support for Kubernetes.
While technologies have enabled new productivity and efficiencies, customer expectations have grown exponentially, cyberthreat risks continue to mount, and the pace of business has sped up. It’s being recognized around the world as a transformative technology for delivering productivity gains. What is artificial intelligence?
Only Dynatrace provides a comprehensive and accessible log management and analytics experience, helping teams resolve issues faster without compromising on depth. Only Dynatrace Grail is schema-on-read and indexless, built with scaling in mind and built for exabyte scale, leveraging massively parallel processing.
If cloud-native technologies and containers are on your radar, you’ve likely encountered Docker and Kubernetes and might be wondering how they relate to each other. In a nutshell, they are complementary and, in part, overlapping technologies to create, manage, and operate containers. Dynatrace news. But first, some background.
That’s why, in part, major cloud providers such as Amazon Web Services, Microsoft Azure, and Google Cloud Platform are discussing cloud optimization. You have to get automation and analytical capabilities.” Throw in behavioral analytics, metadata, and real-user data. … We start with data types—logs, metrics, traces, routes.
It makes them available for a log analytics platform to gain automated, contextual, and actionable insights into the services and underlying platforms. You can filter logs based on their content, source, or process technology. Service ownership details In addition, Dynatrace offers powerful log analytics in the Dynatrace Log Viewer.
The move to SaaS and data residency in local markets Dynatrace operates its AI-powered unified platform for observability, security, and business analytics as a SaaS solution across the globe. Dynatrace is already supported in 17 local regions on three hyperscalers (AWS, Azure, and GCP).
And how can you verify this performance consistently across a multicloud environment that also uses Microsoft Azure and Google Cloud Platform frameworks? This is where unified observability and Dynatrace Automations can help by leveraging causal AI and analytics to drive intelligent automation across your multicloud ecosystem.
It requires specialized talent, a new technology stack to manage and deploy models, an ample budget for rising compute costs, and end-to-end security. Throughout business history, the advent of pivotal technologies has consistently led to disruptive shifts. Enterprises that fail to adapt to these innovations face extinction.
New analytics view for message queues. Select a specific queue or topic to display details about its connected producer and consumer services, as well as technology-specific metrics. Azure VMs that are monitoring candidates are now labeled “no OneAgent” on the Azure region and scale set pages. (APM-323431).
Container technology enables organizations to efficiently develop cloud-native applications or to modernize legacy applications to take advantage of cloud services. This clinic will walk you through Dynatrace’s log monitoring and analytics capabilities, with a specific focus on Kubernetes and cloud-native architectures.
When American Family Insurance took the multicloud plunge, they turned to Dynatrace to automate Amazon Web Services (AWS) event ingestion, instrument compute and serverless cloud technologies, and create a single workflow for unified event management. Step 2: Instrument compute and serverless cloud technologies. It only costs about $.01
We added monitoring and analytics for log streams from Kubernetes and multicloud platforms like AWS, GCP, and Azure, as well as the most widely used open-source log data frameworks. This also applies to logging use cases for certain technologies.
Build a custom pipeline observability solution With these challenges in mind, Omnilogy set out to simplify CI/CD analytics across different vendors, streamlining performance management for critical builds. Consequently, troubleshooting issues and ensuring seamless software deployment becomes increasingly tricky.
Enterprise data stores grow with the promise of analytics and the use of data to enable behavioral security solutions, cognitive analytics, and monitoring and supervision. Modern observability technologies have helped enterprises identify software vulnerabilities such as Log4Shell in their environments.
We can use cloud technologies such as Amazon Kinesis or Azure Stream Analytics for collecting, processing, and analyzing real-time, streaming data to get timely insights and react quickly to new information(e.g. Streaming Data Model. a new like, comment, etc.).
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Similar ly, integrations for Azure and VMware are available to help you monitor your infrastructure both in the cloud and on-premises. . Dynatrace provides two technologies for Digital Experience Monitoring (DEM): Synthetic Monitoring and Real User Monitoring (RUM). Further reading about Business Analytics : .
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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. Our solution to modernize this legacy approach is an approach we call white box testing.
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