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In fact, according to a Dynatrace global survey of 1,300 CIOs , 99% of enterprises utilize a multicloud environment and seven cloudmonitoring solutions on average. What is cloudmonitoring? So, how does cloudmonitoring work? Cloudmonitoring types and how they work. Database monitoring.
The rapid evolution of cloud technology continues to shape how businesses operate and compete. This year’s AWS re:Invent will showcase a suite of new AWS and Dynatrace integrations designed to enhance cloud performance, security, and automation.
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Dynatrace has announced that it has successfully achieved the Google Cloud Ready – Cloud SQL designation for Cloud SQL, Google Cloud’s fully-managed, relational database service for MySQL, PostgreSQL, and SQL Server.
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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.
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Real-time streaming needs real-time analytics As enterprises move their workloads to cloud service providers like Amazon Web Services, the complexity of observing their workloads increases. As cloud complexity grows, it brings more volume, velocity, and variety of log data. Managing this change is difficult.
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This trend is prompting advances in both observability and monitoring. But exactly what are the differences between observability vs. monitoring? Monitoring and observability provide a two-pronged approach. To get a better understanding of observability vs monitoring, we’ll explore the differences between the two.
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Advanced processing on your observability platform unlocks the full value of log data. Dynatrace now includes powerful log-processing capabilities for all types of log data. Log data is processed on ingest, whether coming from a fleet of OneAgents deployed across your enterprise hosts or generic API ingest from cloud services.
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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.
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. Synthetic monitors can be created with our innovative web recorder or through MONACO , our Monitoring-As-Code approach.
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The containers can run anywhere, whether a private data center, the public cloud or a developer’s own computing devices. Dynatrace container monitoring supports customers as they collect metrics, traces, logs, and other observability-enabled data to improve the health and performance of containerized applications.
Cloud observability is fast becoming an imperative as more organizations adopt multicloud IT strategies. To adapt, many are turning to AIOps and other automation technologies to solve the complex issues that accompany cloud-native architecture. Multicloud complexity obscures cloud observability. Dynatrace news.
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Future blogs will provide deeper dives into each service, sharing insights and lessons learned from this process. The Netflix video processing pipeline went live with the launch of our streaming service in 2007. The Netflix video processing pipeline went live with the launch of our streaming service in 2007.
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If you use Windows, you will want to monitor Windows Events. A recent contribution of a distribution of the OpenTelemetry (OTel) Collector makes it much easier to monitor Windows Events with OpenTel. We will be shipping Windows Event logs to a popular backend: Google Cloud Ops. You can find out more on the GitHub page here.
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Logs complement metrics and enable automation Cloud practitioners agree that observability, security, and automation go hand in hand. The increasing complexity of cloud service architectures requires a rock-solid understanding of the activity, health status, and security of cloud services.
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