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This article is the first in a multi-part series sharing a breadth of Analytics Engineering work at Netflix, recently presented as part of our annual internal Analytics Engineering conference. Subsequent posts will detail examples of exciting analytic engineering domain applications and aspects of the technical craft.
The rapid evolution of cloud technology continues to shape how businesses operate and compete. AWS’ recent recognition of Dynatrace as the 2024 AWS EMEA Technology Partner of the Year highlights the joint commitment to accelerate customer cloud transformation.
Leverage AI for proactive protection: AI and contextual analytics are game changers, automating the detection, prevention, and response to threats in real time. UMELT are kept cost-effectively in a massive parallel processing data lakehouse, enabling contextual analytics at petabyte scale, fast.
Dynatrace integrates application performance monitoring (APM), infrastructure monitoring, and real-user monitoring (RUM) into a single platform, with its Foundation & Discovery mode offering a cost-effective, unified view of the entire infrastructure, including non-critical applications previously monitored using legacy APM tools.
Metadata enrichment improves collaboration and increases analytic value. The Dynatrace® platform continues to increase the value of your data — broadening and simplifying real-time access, enriching context, and delivering insightful, AI-augmented analytics. Our Business Analytics solution is a prominent beneficiary of this commitment.
On average, organizations use 10 different tools to monitor applications, infrastructure, and user experiences across these environments. 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.
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. Modernizing your technology stack will improve efficiency and save the organization money over time.
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.
We’re proud to announce that Ally Financial has presented Dynatrace with its Ally Technology Velocity with Quality award. This is the second time Ally Financial has presented its Ally Technology Partner Awards. Ally Financial is the home of the nation’s largest all-digital bank and is an industry-leading auto financing business.
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. This is partly due to the complexity of instrumenting and analyzing emissions across diverse cloud and on-premises infrastructures.
For instance, in a Kubernetes environment, if an application fails, logs in context not only highlight the error alongside corresponding log entries but also provide correlated logs from surrounding services and infrastructure components. Advanced analytics are not limited to use-case-specific apps.
Log monitoring, log analysis, and log analytics are more important than ever as organizations adopt more cloud-native technologies, containers, and microservices-based architectures. What is log analytics? Log analytics is the process of evaluating and interpreting log data so teams can quickly detect and resolve issues.
Leveraging business analytics tools helps ensure their experience is zero-friction–a critical facet of business success. How do business analytics tools work? Business analytics begins with choosing the business KPIs or tracking goals needed for a specific use case, then determining where you can capture the supporting metrics.
With 99% of organizations using multicloud environments , effectively monitoring cloud operations with AI-driven analytics and automation is critical. IT operations analytics (ITOA) with artificial intelligence (AI) capabilities supports faster cloud deployment of digital products and services and trusted business insights.
Infrastructure complexity is costing enterprises money. AIOps offers an alternative to traditional infrastructure monitoring and management with end-to-end visibility and observability into IT stacks. As 69% of CIOs surveyed said, it’s time for a “radically different approach” to infrastructure monitoring.
The Dynatrace platform automatically captures and maps metrics, logs, traces, events, user experience data, and security signals into a single datastore, performing contextual analytics through a “power of three AI”—combining causal, predictive, and generative AI.
” [1] As modern enterprises adopt cloud technologies over time, they often end up with a heterogeneous mix of fragmented security products managed by siloed teams, resulting in complexity, a broadened attack surface, and a plethora of unanswered security questions. Key takeaways: How do CSPM, KSPM, and CNAPP compare?
Log management and analytics is an essential part of any organization’s infrastructure, and it’s no secret the industry has suffered from a shortage of innovation for several years. Current analytics tools are fragmented and lack context for meaningful analysis. Effective analytics with the Dynatrace Query Language.
Infrastructure monitoring is the process of collecting critical data about your IT environment, including information about availability, performance and resource efficiency. Many organizations respond by adding a proliferation of infrastructure monitoring tools, which in many cases, just adds to the noise. Dynatrace news.
However, cloud infrastructure has become increasingly complex. Further, the delivery infrastructure that makes this happen has also become complex. IT pros want a data and analytics solution that doesn’t require tradeoffs between speed, scale, and cost. The next frontier: Data and analytics-centric software intelligence.
The latest Dynatrace report, “ The state of observability 2024: Overcoming complexity through AI-driven analytics and automation ,” explores these challenges and highlights how IT, business, and security teams can overcome them with a mature AI, analytics, and automation strategy.
We’ve introduced brand-new analytics capabilities by building on top of existing features for messaging systems. Now, with technology-specific views, DevOps teams can see messaging system-related anomalies, which significantly simplifies troubleshooting efforts. Easily troubleshoot anomalies with technology-specific views.
The complexity of such deployments has accelerated with the adoption of emerging, open-source technologies that generate telemetry data, which is exploding in terms of volume, speed, and cardinality. Dynatrace extends its unique topology-based analytics and AIOps approach.
We introduced Dynatrace’s Digital Business Analytics in part one , as a way for our customers to tie business metrics to application performance and user experience, delivering unified insights into how these metrics influence business milestones and KPIs. Only with Dynatrace Digital Busines Analytics.
Infrastructure and operations teams must maintain infrastructure health for IT environments. With the Infrastructure & Operations app ITOps teams can quickly track down performance issues at their source, in the problematic infrastructure entities, by following items indicated in red.
The methodology and algorithms were designed by Dynatrace with guidance from the Sustainable Digital Infrastructure Alliance (SDIA), expanding on formulas from the open source project Cloud Carbon Footprint. Some use cases benefit from dashboards or ad-hoc analytics, complementing the insights from Carbon Impact.
The technology race never stops. Sure, cloud infrastructure requires comprehensive performance visibility, as Dynatrace provides , but the services that leverage cloud infrastructures also require close attention. Extend infrastructure observability to WSO2 API Manager. Dynatrace news. Read on to see how it works.
Azure observability and Azure data analytics are critical requirements amid the deluge of data in Azure cloud computing environments. As digital transformation accelerates and more organizations are migrating workloads to Azure and other cloud environments, they need observability and data analytics capabilities that can keep pace.
But as more organizations adopt cloud-native technologies and distribute workloads among multicloud environments, that goal seems harder to attain. For organizations running their own on-premises infrastructure, these costs can be prohibitive. What is always-on infrastructure?
Building on its advanced analytics capabilities for Prometheus data , Dynatrace now enables you to create extensions based on Prometheus metrics. This allows teams to extend the intelligent observability Dynatrace provides to all technologies that provide Prometheus exporters. documentation.
Technology and business leaders express increasing interest in integrating business data into their IT observability strategies, citing the value of effective collaboration between business and IT. Metric extraction is a convenient way to create your business metrics, delivering fast, flexible, and cost-effective analytics.
HANA maintains all the business and analytics data that your business runs on. Dynatrace ActiveGate extensions allow you to integrate Dynatrace monitoring with any remote technology that exposes an interface. And that’s exactly what Dynatrace provides for key SAP technologies, now including SAP HANA DB. Dynatrace news.
Not only are cyberattacks increasing, but they’re also becoming more sophisticated, with tools such as WormGPT putting generative AI technology in the hands of attackers. In this blog post, we’ll use Dynatrace Security Analytics to go threat hunting, bringing together logs, traces, metrics, and, crucially, threat alerts.
In his keynote address on the first day of Perform 2023 in Las Vegas, Dynatrace Chief Technology Officer Bernd Greifeneder and his colleagues discussed how organizations struggle with this problem and how Dynatrace is meeting the moment. Grail combines the big-data storage of a data warehouse with the analytical flexibility of a data lake.
Kafka is optimized for high-throughput event streaming , excelling in real-time analytics and large-scale data ingestion. Its architecture supports stream transformations, joins, and filtering, making it a powerful tool for real-time analytics. Apache Kafka, designed for distributed event streaming, maintains low latency at scale.
already address SNMP, WMI, SQL databases, and Prometheus technologies, serving the monitoring needs of hundreds of Dynatrace customers. are technologically very different, Python and JMX extensions designed for Extension Framework 1.0 Extensions can monitor virtually any type of technology in your environment. Extensions 2.0
But there are other related components and processes (for example, cloud provider infrastructure) that can cause problems in applications running on Kubernetes. Dynatrace AWS monitoring gives you an overview of the resources that are used in your AWS infrastructure along with their historical usage. Monitoring your i nfrastructure.
Native support for syslog messages extends our infrastructure log support to all Linux/Unix systems and network devices. Customers can also proactively address issues using Davis AI’s predictive analytics capabilities by analyzing network log content, such as retries or anomalies in performance response times.
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 organizations grapple with mounting cloud complexity, IT teams know they must identify and respond to evolving issues across the entire technology stack—from mainframes to multicloud environments. Endpoints include on-premises servers, Kubernetes infrastructure, cloud-hosted infrastructure and services, and open-source technologies.
According to recent Dynatrace data, 59% of CIOs say the increasing complexity of their technology stack could soon overload their teams without a more automated approach to IT operations. In what follows, we explore some key cloud observability trends in 2023, such as workflow automation and exploratory analytics.
Optimize the IT infrastructure supporting risk management processes and controls for maximum performance and resilience. Managing these risks involves using a range of technology solutions, from in-house, do-it-yourself solutions to third-party, software-as-a-service (SaaS) solutions.
Challenges The cloud network infrastructure that Netflix utilizes today consists of AWS services such as VPC, DirectConnect, VPC Peering, Transit Gateways, NAT Gateways, etc and Netflix owned devices. These metrics are visualized using Lumen , a self-service dashboarding infrastructure.
In fact, according to technology intelligence analyst firm HG Insights , OpenTelemetry is the Cloud Native Computing Foundation’s second most active project after Kubernetes and is used by more than 1,600 organizations worldwide, with customer adoption growing at a compound annual growth rate of 59%.
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