Skip to main content

Dynatrace Supports AWS Compute Optimizer

Dynatrace announced its platform natively supports AWS Compute Optimizer, a service that uses customers’ utilization data to provide recommendations on provisioning Amazon Web Services (AWS) resources for improved resource utilization.

This support enables the Dynatrace platform to automatically capture and analyze all Amazon Elastic Compute Cloud (Amazon EC2) instances in customers’ AWS environments in near-real time and use Dynatrace causal AIOps and automation capabilities to continuously optimize Amazon EC2 consumption for cost, service reliability, and performance. This offering builds on the Dynatrace platform’s ability to automatically capture full-stack observability metrics, with continuous topology and dependency mapping, to power intelligent and automated cloud modernization at scale.

“Dynatrace is proud to work with AWS to help customers modernize and automate cloud operations,” said Bob Wambach, VP of Product Marketing at Dynatrace. “Extending our advanced observability, AIOps, and automation capabilities to power AWS Compute Optimizer enables our joint customers to prevent performance issues, avoid costly over-provisioning, and operate more efficiently so they can focus on what matters most – accelerating innovation and delivering exceptional digital experiences.”

“To achieve an elastic, well-architected cloud environment, organizations must be able to optimize their usage of cloud resources,” said Rick Ochs, Principal Product Manager of Optimizations at AWS. “With the Dynatrace platform’s support of AWS Compute Optimizer, we provide our customers with memory-aware rightsizing so they can increase operational efficiency and get the most out of AWS.”

Dynatrace’s service is generally available today.

The Latest

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...

Dynatrace Supports AWS Compute Optimizer

Dynatrace announced its platform natively supports AWS Compute Optimizer, a service that uses customers’ utilization data to provide recommendations on provisioning Amazon Web Services (AWS) resources for improved resource utilization.

This support enables the Dynatrace platform to automatically capture and analyze all Amazon Elastic Compute Cloud (Amazon EC2) instances in customers’ AWS environments in near-real time and use Dynatrace causal AIOps and automation capabilities to continuously optimize Amazon EC2 consumption for cost, service reliability, and performance. This offering builds on the Dynatrace platform’s ability to automatically capture full-stack observability metrics, with continuous topology and dependency mapping, to power intelligent and automated cloud modernization at scale.

“Dynatrace is proud to work with AWS to help customers modernize and automate cloud operations,” said Bob Wambach, VP of Product Marketing at Dynatrace. “Extending our advanced observability, AIOps, and automation capabilities to power AWS Compute Optimizer enables our joint customers to prevent performance issues, avoid costly over-provisioning, and operate more efficiently so they can focus on what matters most – accelerating innovation and delivering exceptional digital experiences.”

“To achieve an elastic, well-architected cloud environment, organizations must be able to optimize their usage of cloud resources,” said Rick Ochs, Principal Product Manager of Optimizations at AWS. “With the Dynatrace platform’s support of AWS Compute Optimizer, we provide our customers with memory-aware rightsizing so they can increase operational efficiency and get the most out of AWS.”

Dynatrace’s service is generally available today.

The Latest

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...