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Tag: DevOps

Multi-Database Shops Now the Norm, Redgate Says

The number of organizations adopting multiple databases went up by 17 percentage points over the past three years, increasing the complexity of data management and testing organizations’ capability to acquire the requi Read more…

Tristan Handy’s Audacious Vision of the Future of Data Engineering

Tristan Handy is a lot of things: co-creator of dbt, founder and CEO of dbt Labs, and self-described “startup person.” But besides leading dbt Labs to a $4 billion valuation, he is one more thing: An audacious dreame Read more…

How to Manage Cloud Costs in a Dynamic Economy With FinOps

Sponsored Content by Informatica

Even amid economic uncertainty, investing in the cloud has not slowed down. In fact, according to a recent survey of business and technology leaders, 85% plan on increasing their cloud spend over the previous year.[1] Th Read more…

Why LLMOps Is (Probably) Real

The jury is still out whether MLOps will survive as a discipline independent of DevOps. There are some who believe MLOps is real, and others who don’t. But what about LLMOps? There are indicators that practitioners nee Read more…

How DataOps Strengthens Business Resilience and Agility

Agility is critical for any business looking to grow and remain relevant in today’s complicated industry landscape. Being able to quickly respond and reliably deliver actionable insights is vital for businesses — esp Read more…

AI for DevOps: Cutting Cost, Reducing Risk, Speeding Delivery

Organizations collectively spend billions every month on DevOps processes, yet bad code still makes it into production, causing downtime, additional time/money, and reputational harm. With so much at stake, it would seem Read more…

CI/CD Pipeline: 7 Advantages To A Continuous Integration Approach to Data Pipelines

Sponsored Content by Informatica

When it comes to modern software development, it’s not surprising that companies have a need for speed. But if you develop software too quickly, it can mean sacrificing quality, security and compliance. DevOps and con Read more…

Short-Staffed IT Teams Need Unified Observability to Turn Insights into Action

The world has changed around IT teams. The basic formula may be the same—ensure the performance, accessibility and security of their organizations’ systems, services and applications. But the environment surrounding Read more…

DataRobot Introduces Expanded AI Cloud Capabilities and Tools

At its AIX 2022 conference this week, DataRobot announced new products and enhancements for its AI Cloud platform for data scientists, business users, MLOps, and DevOps. DataRobot says its AI Cloud can centralize the Read more…

Birds Aren’t Real. And Neither Is MLOps

Are birds real? A group of 20-somethings tried to convince us they weren’t in the past few years, to varying degrees of success. And now a University of Washington professor wants us to believe that MLOps isn’t real, Read more…

How Intelligent Observability Unleashes Innovation

Companies are constantly on the hook to push the frontiers of innovation. Just look at what happens when businesses blunder modernization: Nokia rested on its hardware laurels without improving its cell phone software, X Read more…

Leaky Pipelines and the Business Case for Data DevOps

As enterprises embrace digital transformation and migrate critical infrastructure and applications to the cloud as a key component of those efforts, what can be called “data clouds” have started to take shape. Built Read more…

ML Needs Separate Dev and Ops Teams, Datatron Says

In the machine learning world, the folks developing models often are the same folks who are tasked with running the models in production. And they often use the same end-to-end ML software stacks. But emerging best pract Read more…

AI Continues DevOps Expansion

AI gives us the potential to look through the clutter and pick out pieces of data that really matter. It’s no wonder, then, that AI is increasingly being used to target complex IT tasks, including DevOps. For instan Read more…

In Search of Data Observability

The concept of “observability” is well understood as it pertains to DevOps and site reliability engineering (SRE). But what does it mean in the context of data? According to Barr Moses, the CEO of data observability Read more…

AI-Enabled DevOps: Reimagining Enterprise Application Development

Today, advances in artificial intelligence (AI) and machine learning (ML) have opened up significant application possibilities, from sensor-driven weather prediction to driverless cars to intelligent chatbots. Developmen Read more…

AI Governance Rises to the Top of the Stack

Artificial intelligence (AI) is running amok, or so that’s the general perception these days. AI governance is important because the stakes are so high for getting AI right and consequences so dire if we screw it up. Read more…

Virtualization Startup Varada Streamlines Data Ops

Varada, a data virtualization startup targeting big data query acceleration, announced a $12 million funding round this week as it ramps up its “zero data-ops” platform designed to prioritize analytics workloads via Read more…

A ‘Breakout Year’ for ModelOps, Forrester Says

The rapid maturation of machine learning operations (ModelOps) tools is leading to a “breakout year” for ModelOps, Forrester says in a recent report. The ML lifecycle is a potential nightmare for many organization Read more…

Google Joins the MLOps Crusade

Machine learning developers face an expanded set of management issues beyond merely getting the code right, including the testing and validation of data used in ML models while handling an additional set of infrastructur Read more…

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