Dynatrace Provides Deeper Observability for AWS Services Working with AWS CloudWatch

Dynatrace will now support all AWS offerings that publish to Amazon CloudWatch.  Combining Amazon CloudWatch metrics with the data from Dynatrace will provide "more precise answers,” the company said.

Tags: AI, API, AWS, cloud, Dynatrace, hybrid, migration, observability,

Dynatrace is extending its Software Intelligence Platform to support all Amazon Web Services offerings that publish metrics to Amazon CloudWatch

 

CloudWatch is Amazon's fully managed service for monitoring cloud and hybrid apps and resources that use AWS.  Dynatrace's latest update will automatically identify and collect metrics from all 95 AWS services supported by Amazon CloudWatch. In turn, this enriches Dynatrace's AI-powered answers with rich sets of data from the latest services from AWS. 

 

[A full list of those AWS services supported by Dynatrace (now and coming soon) is available here.]

 

Combining Amazon CloudWatch metrics with the data already captured by Dynatrace will provide customers "with richer context and more precise answers for their dynamic AWS and hybrid-cloud environments," according to a statement from DynaTrace. 

 

Metrics from these and all services that publish metrics to AWS CloudWatch are automatically combined with the distributed tracing, log, user experience, and other observability data already processed by the Dynatrace platform. 

 

With AWS CloudWatch metrics automatically streamed to Dynatrace's AI-powered dashboards, which enhance CloudWatch data with displays of self-adjusting baselining, immediate anomaly detection, and precise root-cause determination. These resulting insights are prioritized by business impact across the customer's entire AWS and hybrid/multicloud environment. 

 

"Our customers are accelerating their digital transformation, and many are adopting AWS to help them on that journey," said Steve Tack, Dynatrace senior vice president for product management in a statement. 

 

Dynatrace's latest update builds on its ability to provide distributed tracing and code-level insights for applications and microservices running on AWS. The enhanced AWS integration allows Dynatrace to provide "rapid support as Amazon introduces new services for observability into any layer or service in their cloud stack," Tack added. 

 

AWS execs are also pleased with the new level of visibility Dynatrace’s updates deliver. 

 

"As organizations increasingly invest in cloud-native development using AWS, as well as microservices and Kubernetes architectures, complete visibility into these dynamic environments is critical," said Bob Wilkinson, AWS general manager of monitoring and observability services, said in a statement. "Organizations need the right capabilities to achieve that level of visibility, and Dynatrace can be a key part of the solution along with Amazon CloudWatch. I am excited the Dynatrace Software Intelligence Platform now supports any AWS service that publishes metrics to CloudWatch. This enables even greater automation and observability for customers as they migrate architectures to AWS."

 

Dynatrace Provides ‘Full Observability” of AWS Services that Work with CloudWatch

 

Details of Dynatrace’s enhancements that let users "achieve full observability of all AWS services" that share metrics with AWS CloudWatch were shared by technical product manager Michal Nalezinski in a blog post

With this announcement, those customers that rely heavily on AWS will have a complete, end-to-end picture of their cloud environment, combining workload insights with service metrics.

Dynatrace's ability to ingest metrics from all 95 AWS services will be available within the next 60 days. The latest batch of services covers databases, networks, machine learning and computing. Each service comes with zero-configuration, automatic instance detection, continuous data capture in context, and what's most important – thanks to our AI engine Davis – is each service provides answers, not just data.

Nalezinski also commented on Dynatrace's ability to provide what he called "out-of-the-box dashboard for each AWS service."

Dynatrace makes your life easier with preselected critical metrics of each service, so no additional configuration is required. However, for a specific use case, you can extend the list of monitored metrics that Dynatrace analyzes.

Additionally, Dynatrace creates predefined dashboard templates to visualize each service usage and performance.

He shared an example describing the impact of Dynatrace dashboards on Amazon Neptune graph database. 

 

"Dynatrace analyzes Amazon Neptune performance of resources (CPU, memory, network), requests and errors. With those insights, you can automatically see if the root cause of a problem lies within your graph database," Nalezinski said. 

 

At the core of Dynatrace is its purpose-built AI engine, Davis. It uses what Dynatrace calls "deterministic AI," rather than traditional machine learning. This approach, also used by NASA and the FAA, can deliver automatic fault-tree analysis, which uncovers "causation not correlation," according to Dynatrace. 

 

Davis is designed to process a wide range of data across mainframe, infrastructure, cloud platforms or CI/CD pipelines. Further, Davis uses high-fidelity metrics, traces, logs and real user data, all of which are mapped to a unified entity model. "The resulting root cause analysis is precise and reproducible step by step," the company added. 

 

This approach enables Davis to provide granularity and precision to automate the cloud via the following capabilities: 

Dependency detection - Real-time dependency detection and distributed tracing.

 

Topology visualization - Get a real-time map of your entire application stack across a hybrid cloud environment.

 

Anomaly detection - Dynatrace detects issues automatically and reliably – without the need for complex configuration or costly data scientists. 

 

Root cause analysis – Thanks to its "deterministic" features, it identifies actual root causes of issues with precision.

 

Business impact analysis - Determine the severity of an anomality in terms of impacts on real users and business KPIs.

 

AIOps - Automate operations and enable self-healing.

One long-time user of both AWS and Dynatrace is pleased with the latest update. 

 

"AWS and Dynatrace are core pillars in our cloud strategy, and play a key role in our digital transformation," said Chris Deane, a senior engineering manager at BT Consumer, in a statement. "These latest enhancements to the Dynatrace platform make it even easier to continually optimize our cloud environment and improve the outcomes of our digital transformation."




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