Dynatrace Announces New Integration with Azure Spring Cloud
September 02, 2021
Share this

Dynatrace, in partnership with Microsoft, announced a new integration that provides full application data transparency into applications deployed on Azure Spring Cloud.

Azure Spring Cloud makes it easy to deploy Spring Boot-based microservice applications to Azure with zero code changes. Azure Spring Cloud manages your application infrastructure so that you can focus on application code and business logic. While Azure Spring Cloud excels at removing much of the labor associated with managing containerized workloads, the challenge of monitoring and maintaining the performance and health of these applications, or of troubleshooting issues when they occur, can be daunting—especially as organizations deploy these applications at massive scale.

Dynatrace removes the complexity of dynamic microservice workloads by providing automatic and intelligent observability, without requiring any code changes. This all happens out-of-the-box with the Dynatrace OneAgent, which automatically discovers and maps all applications, microservices, and infrastructure as well as any dependencies in dynamic, hybrid, and multicloud environments, without configuration or scripting, and without having to know which apps or cloud platforms are running. This provides end-to-end visibility into the running of the application, saving time spent manually identifying any anomalies and allowing teams to get to the root cause of code-level issues quicker. This means full transparency into application data and more time to focus on developing feature-rich applications for your end-users.

The Azure Spring Cloud and Dynatrace integration brings freedom to application developers, allowing them to manage instances by abstracting the underlying infrastructure. With Dynatrace ingesting metrics for Azure Spring Cloud, teams can see metrics for each service instance, split metrics into multiple dimensions, and create custom charts they can pin to their dashboards. By automatically delivering metrics for each instance, the Dynatrace Platform enables developers to focus where their effort matters most, on innovation.

“At Microsoft, we are committed to helping our customers modernize their applications and innovate faster than ever before,” Julia Liuson, Corporate VP, Developer Division, Microsoft. “By integrating a software intelligence solution like Dynatrace with Azure Spring Cloud, we can enable our customers with easy implementation of end-to-end observability, including automatic and continuous root-cause analysis, for their Spring Boot applications.”

“The ability to scale is critical for today’s digital business, as organizations have made the shift to cloud-native workloads and microservices,” said Eric Horsman, Global Director of Strategic Alliances at Dynatrace. “While cloud-native technologies and microservices have tremendous advantages, dynamic environments bring complexity that makes it difficult to understand the relationships and dependencies across an organization’s hybrid, multicloud ecosystem. Through the Dynatrace integration with Azure Spring Cloud, we are enabling full visibility into Spring Boot applications, which means more time innovating and a better product for end-users.”

Share this

The Latest

September 22, 2021

The world's appetite for cloud services has increased but now, more than 18 months since the beginning of the pandemic, organizations are assessing their cloud spend and trying to better understand the IT investments that were made under pressure. This is a huge challenge in and of itself, with the added complexity of embracing hybrid work ...

September 21, 2021

After a year of unprecedented challenges and change, tech pros responding to this year’s survey, IT Pro Day 2021 survey: Bring IT On from SolarWinds, report a positive perception of their roles and say they look forward to what lies ahead ...

September 20, 2021

One of the key performance indicators for IT Ops is MTTR (Mean-Time-To-Resolution). MTTR essentially measures the length of your incident management lifecycle: from detection; through assignment, triage and investigation; to remediation and resolution. IT Ops teams strive to shorten their incident management lifecycle and lower their MTTR, to meet their SLAs and maintain healthy infrastructures and services. But that's often easier said than done, with incident triage being a key factor in that challenge ...

September 16, 2021

Achieve more with less. How many of you feel that pressure — or, even worse, hear those words — trickle down from leadership? The reality is that overworked and under-resourced IT departments will only lead to chronic errors, missed deadlines and service assurance failures. After all, we're only human. So what are overburdened IT departments to do? Reduce the human factor. In a word: automate ...

September 15, 2021

On average, data innovators release twice as many products and increase employee productivity at double the rate of organizations with less mature data strategies, according to the State of Data Innovation report from Splunk ...

September 14, 2021

While 90% of respondents believe observability is important and strategic to their business — and 94% believe it to be strategic to their role — just 26% noted mature observability practices within their business, according to the 2021 Observability Forecast ...

September 13, 2021

Let's explore a few of the most prominent app success indicators and how app engineers can shift their development strategy to better meet the needs of today's app users ...

September 09, 2021

Business enterprises aiming at digital transformation or IT companies developing new software applications face challenges in developing eye-catching, robust, fast-loading, mobile-friendly, content-rich, and user-friendly software. However, with increased pressure to reduce costs and save time, business enterprises often give a short shrift to performance testing services ...

September 08, 2021

DevOps, SRE and other operations teams use observability solutions with AIOps to ingest and normalize data to get visibility into tech stacks from a centralized system, reduce noise and understand the data's context for quicker mean time to recovery (MTTR). With AI using these processes to produce actionable insights, teams are free to spend more time innovating and providing superior service assurance. Let's explore AI's role in ingestion and normalization, and then dive into correlation and deduplication too ...

September 07, 2021

As we look into the future direction of observability, we are paying attention to the rise of artificial intelligence, machine learning, security, and more. I asked top industry experts — DevOps Institute Ambassadors — to offer their predictions for the future of observability. The following are 10 predictions ...