Dynatrace

DECEMBER 5, 2022

Organizations are increasingly adopting DevOps to stay competitive, innovate faster, and meet customer needs. By helping teams release new software more frequently, DevOps practices are an essential component of digital transformation. Thankfully, DevOps orchestration has evolved to address these problems.

DevOps 203

DevOps Virtualization Innovation Best Practices 203

Dynatrace

APRIL 18, 2022

When it comes to site reliability engineering (SRE) initiatives adopting DevOps practices, developers and operations teams frequently find themselves at odds with one another. Too many SLOs create complexity for DevOps. With many pipelines to maintain, DevOps teams need automated orchestration. Dynatrace news.

Open Source 181

Open Source DevOps Cloud Metrics 181

Dynatrace

FEBRUARY 4, 2021

What is site reliability engineering? Site reliability engineering (SRE) is the practice of applying software engineering principles to operations and infrastructure processes to help organizations create highly reliable and scalable software systems. Dynatrace news. Solving for SR.

Engineering 250

Engineering DevOps Government Latency 250

Dynatrace

JANUARY 23, 2024

‘Composite’ AI, platform engineering, AI data analysis through custom apps This focus on data reliability and data quality also highlights the need for organizations to bring a “ composite AI ” approach to IT operations, security, and DevOps. The platform engineer role: A game-changer or just hype? Enter causal AI.

Performance 179

Performance DevOps Innovation Artificial Intelligence 179

Dynatrace

FEBRUARY 4, 2021

Site reliability engineering (SRE) is the practice of applying software engineering principles to operations and infrastructure processes to help organizations create highly reliable and scalable software systems. Organizations can then integrate these skilled engineers at key points in the DevOps life cycle.

Engineering 170

Engineering DevOps Government Latency 170

Dynatrace

MARCH 3, 2020

For software engineering teams, this demand means not only delivering new features faster but ensuring quality, performance, and scalability too. One way to apply improvements is transforming the way application performance engineering and testing is done. Industry apps explosion. 1 Performance-as-a-self-service at Pay P al .

Performance 237

Performance Education Innovation Software Architecture 237

The Morning Paper

FEBRUARY 18, 2020

Many of the software engineering discipline and controls need to be brought over into an ML context. Flock treats ML models as software artefacts derived from data. Typical applications of (EG)ML are built by smaller, less experienced teams, yet they have more stringent demands. What do these notebooks use instead?

Government 95

Government Software Engineering Storage Database 95