Dynatrace delivers low-code no-code AutomationEngine

Use cases

What kind of application use cases are we talking about here?

Working examples include automated remediation and progressive delivery to continuously evaluate software against specific measurable Service Level Objectives (SLOs).

Also here we can see use case suitability for the automated routing of vulnerabilities discovered by Dynatrace Application Security to the right staff, all within an environment that benefits from the ability to reduce false positives to ensure prompt action.

Automating provisioning

This technology also enables forecasting for future cloud infrastructure and compute resource requirements, as well as automating provisioning to help ensure an optimal customer experience.

“Cloud-native and multi-cloud technology adoption is accelerating, driving platform fragmentation and an explosion in observability and security data variety and volume. [To counter and channel this firehose] AI/ML and automation are increasingly useful in taming this complexity, enabling organisations to find the right answers and automate fixes,” said James Governor, co-founder of RedMonk.

The company says that the Dynatrace platform with AutomationEngine technology delivers answer-driven automation to operate clouds more efficiently and more securely deliver consistently better business results.

“The complexity, scale, and dynamism of modern clouds, with ever-increasing deployment frequency, requires extensive and intelligent automation to ensure flawless delivery,” said Bernd Greifeneder, founder and chief technical Officer at Dynatrace.

Formulating a feedback loop

Greifeneder says that combining precise causal-AI answers from observability, security and business data (all drawn from live production environments) with automation provides a feedback loop that makes the automation more intelligent and business-value-oriented.

“Now, teams can extend this answer-driven automation to nearly unlimited use cases, like managing seasonality, reacting to changing user experiences, disabling features for security or quality reasons, or enhancing software orchestration to reflect myriad external factors – from weather forecasts to energy consumption to supply chain delays and beyond,” added Greifeneder.

This is the ability to use intelligent automation for observability and security at scale. 

This is answer-driven automation with a feedback loop. Greifeneder calls it a sense-think-act process where an organisation might be tracking user experience issues in a progressive software application development roll-out and seeing that the project needs to stop and change or skew in some way.

The auto engine means that all automations are in one place. Users can start immediately without needing to build runtimes.

Real world uses

There are so many use case examples here says Dynatrace’s Greifeneder, speaking at the company’s Dynatrace Perform 2023 conference in Las Vegas this week, he explained some specific to the Computer Weekly Developer Network team.

Users could start with workflow automation to put KPIs and SLOs into Dynatrace and look at how much volume has been transacted through a company’s shopping cart (in a defined time period) and get alerts sent to managers (via email or Slack or so on) and so enable firms to change their business strategies.

For security automation, teams could use Dynatrace to scan through application logs to look for known vulnerabilities and scan for areas of concern in order to move towards remediation where and when needed.

The company insists that the Dynatrace AutomationEngine pushes the IT industry one step closer to a world where clouds run autonomously and software works perfectly.