Dynatrace transcends multi-cloud serverless for near-omniscient observability
As olde-age English colloquialisms go, the origins of the term ‘aye-oop’ are thought to possibly stem from ‘hey up’ or some other positively charged ovation, greeting or human civility.
As new age neologisms go, the term AIOps might sound remarkably similar to the above salutation still favoured by Yorkshirepersons the length and breadth of the Pennines, but of course it means the application of Artificial Intelligence (AI) to the operations (Ops) functions inside modern cloud-centric IT departments.
Why the aye-oop AIOps clarification?
Because software intelligence company Dynatrace has extended its platform’s observability prowess with what it calls ‘advanced AIOps capabilities’ to all major serverless architectures.
In addition to existing support for AWS Lambda, this includes Microsoft Azure Functions, Google Cloud Functions, as well as managed Kubernetes environments, messaging queues and cloud databases across all major cloud providers.
As a result, DevOps and site reliability engineering (SRE) teams can automatically analyze, troubleshoot and optimise serverless applications to drive innovation at scale.
Distributed application model
Dyntrace says its customers are clear i.e. the distributed application model [that typifies the constructs seen in modern cloud deployments]makes it hard to achieve end-to-end real-time visibility – and, as a direct consequence, it also makes it even harder to automate operations.
By extending its automatic observability to all serverless architectures, Dynatrace ensures applications are optimised, even in these complex, heterogeneous environments.
“While serverless architectures offer greater scalability and flexibility, they generate massive amounts of data and few answers about how to optimize the infrastructure and applications that run on them,” said Steve Tack, SVP of product management at Dynatrace.
Tack says that by providing full end-to-end observability across multi-cloud serverless offerings and enabling teams to automate operations with precise AI-powered insights, organizations can adopt modern approaches for the IT stack that they seek to build.
