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Why applying chaos engineering to data-intensive applications matters

Dynatrace

Stream processing One approach to such a challenging scenario is stream processing, a computing paradigm and software architectural style for data-intensive software systems that emerged to cope with requirements for near real-time processing of massive amounts of data.

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Dynatrace Managed turnkey Premium High Availability for globally distributed data centers (Early Adopter)

Dynatrace

Dynatrace Managed is intrinsically highly available as it stores three copies of all events, user sessions, and metrics across its cluster nodes. The network latency between cluster nodes should be around 10 ms or less. Turnkey high availability across globally distributed data centers. Dynatrace news.

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Crucial Redis Monitoring Metrics You Must Watch

Scalegrid

Key Takeaways Critical performance indicators such as latency, CPU usage, memory utilization, hit rate, and number of connected clients/slaves/evictions must be monitored to maintain Redis’s high throughput and low latency capabilities. It can achieve impressive performance, handling up to 50 million operations per second.

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The Three Cs: Concatenate, Compress, Cache

CSS Wizardry

In this post, I’m going to break these processes down into each of: ? What is the availability, configurability, and efficacy of each? Plotted on the same horizontal axis of 1.6s, the waterfalls speak for themselves: 201ms of cumulative latency; 109ms of cumulative download. Read the complete test methodology. It gets worse.

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Dynatrace accelerates business transformation with new AI observability solution

Dynatrace

The RAG process begins by summarizing and converting user prompts into queries that are sent to a search platform that uses semantic similarities to find relevant data in vector databases, semantic caches, or other online data sources. RAG augments user prompts with relevant data retrieved from outside the LLM.

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Data Reprocessing Pipeline in Asset Management Platform @Netflix

The Netflix TechBlog

Hence we built the data pipeline that can be used to extract the existing assets metadata and process it specifically to each new use case. This feature support required a significant update in the data table design (which includes new tables and updating existing table columns). N, first N rows are fetched from the table.

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Redis vs Memcached in 2024

Scalegrid

Redis Data Types and Structures The design of Redis’s data structures emphasizes versatility. Redis can be configured to optimally utilize both RDB and AOF persistence methods optimally, achieving a balance between speed and data safety while minimizing the impact on response times due to its child process handling for disk writes.

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