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In September, we announced the availability of the Dynatrace Software Intelligence Platform on Microsoft Azure as a SaaS solution and natively in the Azure portal. Today, we are excited to provide an update that Dynatrace SaaS on Azure is now generally available (GA) to the public through Dynatrace sales channels.
Azure Native Dynatrace Service allows easy access to new Dynatrace platform innovations Dynatrace has long offered deep integration into Azure and Azure Marketplace with its Azure Native Dynatrace Service, developed in collaboration with Microsoft. The following figure shows the benefits of Azure Native Dynatrace Service.
This extension provides fully app-centric Cassandra performance monitoring for Azure Managed Instance for Apache Cassandra. Azure Managed Instance for Apache Cassandra vs Azure Cosmos DB Cassandra API. Microsoft Azure offers multiple ways to manage Apache Cassandra databases.
More than 95% of Fortune 500 companies use Microsoft Azure. Azure provides a wide variety of cloud services with globally distributed applications. Running containers in the cloud is also a very popular use case for Azure. These challenges make Azure observability critical for building and monitoring cloud-native applications.
Azure Automation provides an extremely powerful set of tools for automating operations within enterprises on hybrid cloud. You can now simplify cloud operations with automated observability into the performance of your Azure cloud platform services in context with the performance of your applications. What is Azure Automation?
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.
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.
Dynatrace has partnered with the Microsoft Azure App Service team to seamlessly integrate enhanced observability with Linux App Service using the powerful Sidecar Pattern for containerized computing. It handles tasks like collecting metrics, tracing requests, and capturing logs independently. Decoupled integration.
Dynatrace has enhanced its partnership with Microsoft Azure, providing users a quick and easy path to purchasing, configuring, and managing Dynatrace directly inside the Microsoft Azure Portal. Dynatrace is excited to announce this enhancement is now in public preview for any Azure customer to evaluate. Dynatrace news.
Optimizing cloud services can prove quite challenging because logs, metrics, and traces are not always put together in context, and you don’t have access to the underlying hosts. This is done by Dynatrace automatically after you forward your Azure services logs. Use custom metrics based on logs for constant optimization.
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?
x runtime versions of Azure Functions running in an Azure App Service plan. This gives you deep visibility into your code running in Azure Functions, and, as a result, an understanding of its impact on overall application performance and user experience. Azure Functions in a nutshell. Optimize timing hotspots.
Versatile, feature-rich cloud computing environments such as AWS, Microsoft Azure, and GCP have been a game-changer. Cloud computing environments like AWS, Azure, and GCP offer a wide array of computing capabilities and capacity. It includes metrics, dashboards, alerts, events, logs, and cross-environment traces.
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.
In IT and cloud computing, observability is the ability to measure a system’s current state based on the data it generates, such as logs, metrics, and traces. If you’ve read about observability, you likely know that collecting the measurements of logs, metrics, and distributed traces are the three key pillars to achieving success.
Dynatrace collects a huge number of metrics for each OneAgent-monitored host in your environment. Depending on the types of technologies you’re running on individual hosts, the average number of metrics is about 500 per computational node. Running metric queries on a subset of entities for live monitoring and system overviews.
Hopefully, this blog will explain ‘why,’ and how Microsoft’s Azure Monitor is complementary to that of Dynatrace. Do I need more than Azure Monitor? Azure Monitor features. Application Insights – Collects performance metrics of the application code. Available as an agent installer).
The Carbon Impact app directly supports our customers sustainability efforts through granular real-time emissions reporting and analytics, translating host utilization metrics into their CO2 equivalent (CO2e). Youll be able to read more about our approach to cloud cost optimization in an upcoming blog post.
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.
x runtime versions of Azure Functions running in an Azure App Service plan. This gives you deep visibility into your code running in Azure Functions, and, as a result, an understanding of its impact on overall application performance and user experience. Azure Functions in a nutshell. Optimize timing hotspots.
With the advent and ingestion of thousands of custom metrics into Dynatrace, we’ve once again pushed the boundaries of automatic, AI-based root cause analysis with the introduction of auto-adaptive baselines as a foundational concept for Dynatrace topology-driven timeseries measurements. In many cases, metric behavior changes over time.
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. Whatever your use case, when log data reflects changes in your infrastructure or business metrics, you need to extract the metrics and monitor them.
With Azure Deployment Slots, a feature of the Azure App Service, you can create one or more slots that can host different versions of your app. You can now simplify cloud operations with automated observability into the performance of your Azure cloud platform services in context with the performance of your applications. .
As adoption rates for Azure continue to skyrocket, Dynatrace is developing a deeper integration with the Azure platform to provide even more value to organizations that run their businesses on Microsoft Azure or have Microsoft as a part of their multi-cloud strategy. More than just metrics. Dynatrace news.
In this blog post, we will discuss some of these challenges and how to overcome them. These functions are executed by a serverless platform or provider (such as AWS Lambda, Azure Functions or Google Cloud Functions) that manages the underlying infrastructure, scaling and billing. What are serverless applications?
In this blog, I want to dig a bit into a core capability of Keptn which is used across all use cases: SLI/SLO-based Evaluations for Quality Gates as well as Auto-Remediation. While an SLI is just a metric, an SLO just a threshold you expect your SLI to be in and SLA is just the business contract on top of an SLO.
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. Collecting data requires massive and ongoing configuration efforts.
Ingest data remotely through cloud integrations covering Amazon CloudWatch, Azure Monitor, Azure Liftr, and Google Cloud™ Kubernetes with GKE™ AutoPilot cluster. The capabilities highlighted in this blog post will be available in Dynatrace SaaS environments in the coming weeks.
Here is the first batch of 15 public locations for HTTP monitoring: Chicago (Azure) ?, Virginia (Azure), N. California (AWS), San Jose (Azure), Texas (Azure), Ohio (AWS), Toronto (Azure) ?, London (AWS), London (Azure), Frankfurt (AWS) ?, Hong Kong (Azure), Tokyo (Azure), Sao Paulo (AWS).
You can create custom log metrics for smarter and faster troubleshooting, and you will be able to understand log data in the context of your full stack, including real user impacts. The default values cover a large range of different cluster sizes; you can modify them according to your needs, based on the ActiveGate self-monitoring metrics.
Davis AI contextually aligns all relevant data points—such as logs, traces, and metrics—enabling teams to act quickly and accurately while still providing power users with the flexibility and depth they desire and need. This is explained in detail in our blog post, Unlock log analytics: Seamless insights without writing queries.
This guest blog is authored by Raphael Pionke , DevOps Engineer at T-Systems MMS. I, Andreas Grabner, helped to bring the blog to life! It automatically sends JMeter metrics to the Dynatrace cluster via the Metrics Ingest API. Dynatrace news. In this example, the application has reached its limit near the 90 percent load.
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. You’ll benefit from serverless computing when: Authenticating users (for example, Okta , Azure Active Directory ).
With this announcement: Davis now automatically ingests additional Kubernetes events and metrics, including state changes, workload changes and critical events across clusters, containers and runtimes. Ability to create custom metrics and events from log data, extending Dynatrace observability to any application, script or process.
To make this possible, the application code should be instrumented with telemetry data for deep insights, including: Metrics to find out how the behavior of a system has changed over time. And because Dynatrace can consume CloudWatch metrics, almost all your AWS usage information is available to you within Dynatrace.
Custom data buckets for faster queries, increased control, and custom retention periods The first layer in the Grail data model consists of buckets and tables (and views for entities, which is outside this blog post’s scope). Tables are a physical data model, essentially the type of observability data that you can store.
Symptoms : No data is provided for affected metrics on dashboards, alerts, and custom device pages populated by the affected extension metrics. Select a specific queue or topic to display details about its connected producer and consumer services, as well as technology-specific metrics. Extension logs display errors.
Metrics are an essential functionality provided by the Dynatrace Software Intelligence Platform. Dynatrace OneAgent and ActiveGate extensions provide you with a multitude of metrics. We also empower you with the ability to ingest your own custom metrics and leverage those metrics using a variety of Dynatrace features.
As a full stack monitoring platform, Dynatrace collects a huge number of metrics for each OneAgent monitored host in your environment. Depending on the types of technologies you’re running on your individual hosts, the average number of metrics is about 500 per computational node. New metric identifiers and structure.
And how can you verify this performance consistently across a multicloud environment that also uses Microsoft Azure and Google Cloud Platform frameworks? The Dynatrace platform approach to managing your cloud initiatives provides insights and answers to not just see what could go wrong but what could go right.
This helps you transform faster by taming modern cloud complexity with observability, automation, and intelligence in a single platform delivering multicloud observability that’s more than metrics, logs, and traces. appeared first on Dynatrace blog. The post What’s the hype with hyperscale?
Azure supporting services (Synapse Analytics). Apache Spark pool metrics are replaced with new ones. See Available metrics. Improved `builtin:apps.web.actionCount.summary` metric. (APM-339840). File descriptors metric now correctly aggregates PIDs on host’s process list and process details page. (APM-341616).
Five available hybrid cloud platforms from the top public cloud providers include the following: Azure Stack : Consumers can access different Azure cloud services from their own data center and build applications for Azure cloud. Accordingly, these platforms provide a unified, consistent DevOps and IT experience.
Cloud Foundry and Azure buttons on Deploy Dynatrace page now open pages in new tabs. The calculated service metrics limit message is now improved to be more specific. On CPU usage chart for Windows host, System and User metrics are no longer interchanged. APM-247271). Autonomous Cloud. APM-248520). APM-246341). APM-245699).
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