article thumbnail

DevOps monitoring tools: How to drive DevOps efficiency

Dynatrace

With the world’s increased reliance on digital services and the organizational pressure on IT teams to innovate faster, the need for DevOps monitoring tools has grown exponentially. But when and how does DevOps monitoring fit into the process? And how do DevOps monitoring tools help teams achieve DevOps efficiency?

DevOps 219
article thumbnail

Boost DevOps maturity with observability and a data lakehouse

Dynatrace

That’s especially true of the DevOps teams who must drive digital-fueled sustainable growth. All of these factors challenge DevOps maturity. Data scale and silos present challenges to DevOps maturity DevOps teams often run into problems trying to drive better data-driven decisions with observability and security data.

DevOps 183
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

Platform engineering: Empowering key Kubernetes use cases with Dynatrace

Dynatrace

Today, speed and DevOps automation are critical to innovating faster, and platform engineering has emerged as an answer to some of the most significant challenges DevOps teams are facing. But it is not only the number of clusters that matters, but also the storage underneath. Digital transformation continues surging forward.

article thumbnail

Google Improves Cloud Spanner: More Compute and Storage without Price Increase

InfoQ

times the storage per node than before” without a price change. Google recently announced various improvements to Cloud Spanner, its distributed, decoupled relational database service with a “50% increase in throughput and 2.5 By Steef-Jan Wiggers

Google 99
article thumbnail

What is predictive AI? How this data-driven technique gives foresight to IT teams

Dynatrace

Predictive AI empowers site reliability engineers (SREs) and DevOps engineers to detect anomalies and irregular patterns in their systems long before they escalate into critical incidents. Through predictive analytics, SREs and DevOps engineers can accurately forecast resource needs based on historical data. Continuous improvement.

article thumbnail

Why growing AI adoption requires an AI observability strategy

Dynatrace

AI requires more compute and storage. Training AI data is resource-intensive and costly, again, because of increased computational and storage requirements. FinOps, where finance meets DevOps, is a public cloud management philosophy that aims to control costs. AI performs frequent data transfers. What is AI observability?

Strategy 221
article thumbnail

What is log management? How to tame distributed cloud system complexities

Dynatrace

Log management is an organization’s rules and policies for managing and enabling the creation, transmission, analysis, storage, and other tasks related to IT systems’ and applications’ log data. It involves both the collection and storage of logs, as well as aggregation, analysis, and even the long-term storage and destruction of log data.

Systems 185