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Financial services IT leaders can boost customer lifetime value with DevSecOps-driven innovation

Dynatrace

Customer lifetime value (CLV) has long been established as the key metric financial services firms use to gauge their profitability and competitive position in the market. The growing demand for rapid innovation is worsened by the ongoing skills shortages. This puts sensitive customer and transactional information at risk.

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A guide to event-driven SRE-inspired DevOps

Dynatrace

This is a mouthful of buzzwords” is how I started my recent presentations at the Online Kubernetes Meetup as well as the DevOps Fusion 2020 Online Conference when explaining the three big challenges we are trying to solve with Keptn – our CNCF Open Source project: Automate build validation through SLI/SLO-based Quality Gates. Dynatrace news.

DevOps 245
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Scale DevOps and SRE with open source Keptn

Dynatrace

When it comes to site reliability engineering (SRE) initiatives adopting DevOps practices, developers and operations teams frequently find themselves at odds with one another. The goal is to accelerate innovation by eliminating the need for custom automation scripts and point-to-point tool integrations. Dynatrace news.

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What is observability? Not just logs, metrics and traces

Dynatrace

As a result, IT operations, DevOps , and SRE teams are all looking for greater observability into these increasingly diverse and complex computing environments. In IT and cloud computing, observability is the ability to measure a system’s current state based on the data it generates, such as logs, metrics, and traces.

Metrics 363
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Closed-loop remediation: Why unified observability is an essential auto-remediation best practice

Dynatrace

Closed loop” refers to the continuous feedback loop in which the system takes actions — based on monitoring and analysis — and verifies the results to ensure complete problem remediation. Stage 2: Remediate Root cause analysis : The observability platform should be able to pinpoint the incident’s root cause.

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Data lakehouse innovations advance the three pillars of observability for more collaborative analytics

Dynatrace

The short answer: The three pillars of observability—logs, metrics, and traces—converging on a data lakehouse. You’re getting all the architectural benefits of Grail—the petabytes, the cardinality—with this implementation,” including the three pillars of observability: logs, metrics, and traces in context.

Analytics 182
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Automate CI/CD pipelines with Dynatrace: Part 4, Validation stage

Dynatrace

SRG is a potent tool that automates the analysis of release impacts, ensuring validation of service availability, performance, and capacity objectives throughout the application ecosystem by examining the effect of advanced test suites executed earlier in the testing phase.

DevOps 200