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Conducting log analysis with an observability platform and full data context

Dynatrace

With more automated approaches to log monitoring and log analysis, however, organizations can gain visibility into their applications and infrastructure efficiently and with greater precision—even as cloud environments grow. They enable IT teams to identify and address the precise cause of application and infrastructure issues.

Analytics 246
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Unlock the Power of DevSecOps with Newly Released Kubernetes Experience for Platform Engineering

Dynatrace

Platform engineering is on the rise. According to leading analyst firm Gartner, “80% of software engineering organizations will establish platform teams as internal providers of reusable services, components, and tools for application delivery…” by 2026. Automation, automation, automation.

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AWS observability: AWS monitoring best practices for resiliency

Dynatrace

Because of its matrix of cloud services across multiple environments, AWS and other multicloud environments can be more difficult to manage and monitor compared with traditional on-premises infrastructure. EC2 is Amazon’s Infrastructure-as-a-service (IaaS) compute platform designed to handle any workload at scale. Amazon EC2.

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How platform engineering and IDP observability can accelerate developer velocity

Dynatrace

Platform engineering creates and manages a shared infrastructure and set of tools, such as internal developer platforms (IDPs) , to enable software developers to build, deploy, and operate applications more efficiently. “It makes them more productive.

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Data Engineers of Netflix?—?Interview with Pallavi Phadnis

The Netflix TechBlog

Interview with Pallavi Phadnis This post is part of our “ Data Engineers of Netflix ” series, where our very own data engineers talk about their journeys to Data Engineering @ Netflix. Pallavi Phadnis is a Senior Software Engineer at Netflix. Pallavi, what’s your journey to data engineering at Netflix?

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Automating Success: Building a better developer experience with platform engineering

Dynatrace

Check out the following use cases to learn how to drive innovation from development to production efficiently and securely with platform engineering observability. According to Deinhammer, once software is released into production, it’s usually deployed at a large scale—often in complex multicloud or hybrid setups.

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Designing Instagram

High Scalability

FUN FACT : In this talk , Rodrigo Schmidt, director of engineering at Instagram talks about the different challenges they have faced in scaling the data infrastructure at Instagram. The streaming data store makes the system extensible to support other use-cases (e.g. media search index, locations search index, and so forth) in future.

Design 334