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Accelerate your cloud journey with Dynatrace observability for AWS S3 logs

Dynatrace

Many AWS services and third party solutions use AWS S3 for log storage. We hear from our customers how important it is to have a centralized, quick, and powerful access point to analyze these logs; hence we’re making it easier to ingest AWS S3 logs and leverage Dynatrace Log Management and Analytics powered by Grail.

AWS 204
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AWS observability: AWS monitoring best practices for resiliency

Dynatrace

With EC2, Amazon manages the basic compute, storage, networking infrastructure and virtualization layer, and leaves the rest for you to manage: OS, middleware, runtime environment, data, and applications. AWS Lambda. Through auto-instrumentation, Dynatrace provides seamless end-to-end distributed tracing for AWS Lambda functions.

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OpenTelemetry observability and Dynatrace deliver actionable answers at scale

Dynatrace

The collector processes the data and exports it to a predetermined monitoring, tracing, or logging back end, such as Dynatrace, for analysis. Challenges of adopting OpenTelemetry The first challenge is that OpenTelemetry only gathers and processes data—it has no back end, no storage, and no analytics.

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Dynatrace SaaS release notes version 1.233

Dynatrace

Azure supporting services (Synapse Analytics). WeThe Detected processes page has been clarified. RUM linking timeouts adjusted in transaction storage. (APM-341299). Time aggregation corrected for `GC time` chart on process group instance page. (APM-343594). Masking v1. Masking v2. See Available metrics. APM-341631).

Lambda 185
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Carving an AWS certification path

Dynatrace

AWS Certified Data Analytics – Specialty: Highly knowledgeable data analytics pros who have already worked with AWS for some time should consider getting this certification. Data analytics. If your company is pursuing AWS certification for a team, AWS Certification Exam Vouchers make the process easier. Machine learning.

AWS 215
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In-Stream Big Data Processing

Highly Scalable

The shortcomings and drawbacks of batch-oriented data processing were widely recognized by the Big Data community quite a long time ago. It became clear that real-time query processing and in-stream processing is the immediate need in many practical applications. Fault-tolerance. Interoperability with Hadoop.

Big Data 154
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Evolution of Netflix Conductor:

The Netflix TechBlog

Many of the Netflix Content and Studio Engineering services rely on Conductor for efficient processing of their business flows. External Payload Storage External payload storage was implemented to prevent the usage of Conductor as a data persistence system and to reduce the pressure on its backend datastore.

Lambda 189