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Redis® Monitoring Strategies for 2024

Scalegrid

Identifying key Redis® metrics such as latency, CPU usage, and memory metrics is crucial for effective Redis monitoring. To monitor Redis® instances effectively, collect Redis metrics focusing on cache hit ratio, memory allocated, and latency threshold.

Strategy 130
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Dynatrace supports SnapStart for Lambda as an AWS launch partner

Dynatrace

The new Amazon capability enables customers to improve the startup latency of their functions from several seconds to as low as sub-second (up to 10 times faster) at P99 (the 99th latency percentile). This can cause latency outliers and may lead to a poor end-user experience for latency-sensitive applications.

Lambda 214
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Benchmark (YCSB) numbers for Redis, MongoDB, Couchbase2, Yugabyte and BangDB

High Scalability

This is guest post by Sachin Sinha who is passionate about data, analytics and machine learning at scale. We note that for MongoDB update latency is really very low (low is better) compared to other dbs, however the read latency is on the higher side. Again Yugabyte latency is quite high. Author & founder of BangDB.

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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.

Cache 196
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Best practices and key metrics for improving mobile app performance

Dynatrace

By monitoring metrics such as error rates, response times, and network latency, developers can identify trends and potential issues, so they don’t become critical. Load time and network latency metrics. Minimizing the number of network requests that your app makes can improve performance by reducing latency and improving load times.

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What is a data lakehouse? Combining data lakes and warehouses for the best of both worlds

Dynatrace

The result is a framework that offers a single source of truth and enables companies to make the most of advanced analytics capabilities simultaneously. The performance of these queries needs to be at a level where they can support ad-hoc analytics use cases. Data lakehouses deliver the query response with minimal latency.

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Procella: unifying serving and analytical data at YouTube

The Morning Paper

Procella: unifying serving and analytical data at YouTube Chattopadhyay et al., Broadly, these can be categorized as: reporting and dashboarding, embedded statistics in pages, time-series monitoring, and ad-hoc analysis. Oh, and in additional to low latency, “ we require access to fresh data.” VLDB’19.